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THE ROLE OF PRIVATE PARTNERSHIP IN HOUSING FINANCE MAINTENANCE IN NIGERIA

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THE ROLE OF PRIVATE PARTNERSHIP IN HOUSING FINANCE MAINTENANCE IN NIGERIA

CHAPTER ONE

INTRODUCTION

1.1 Introduction

By 2030, it is anticipated that about 3 billion people or roughly 40 per cent of the world’s population, will lack proper housing. In the developing economies, housing supply is being limited by poor governance systems and human resource deficiencies, as well as by institutions and regulations which are either obsolete, lacking in capacity, or poorly informed (UN-Habitat, 2015). The scale of the housing crisis facing Nigeria is unprecedented. Each year, Nigeria builds about 600,000 fewer homes than are needed, adding to the current dearth of 23 million that has been growing for decades. This shortfall has been accrued because of years of undersupply. In an effort to increase affordable housing delivery in Nigeria, this research suggests that the use of public private partnership (PPP) as a tool, if applied effectively, could increase private sector investment and fuel development initiatives. A key motivation is the opportunity for cash strapped government to tap into new private financing sources to meet the costs of delivering adequate housing.

Policy debates on housing are still very much dominated by how the nation can best support the low-middle income housing market (Sa-Aadu, 1984). The complex nature of the term affordable housing is reflected by the fact that affordability is both a function of housing demand and supply factors (Bieri, 2012). A supply side housing program typically sidesteps the private housing market while a demand side program relies on the discipline of the market to promote society’s affordable housing goals for the needy. The Nigerian government has been engaging in demand side approaches (such as Refinancing Mortgage Company and Federal Mortgage Bank) for years to promote home ownership without major significant success. This research however examines a supply-side strategy to attack the affordable housing problems faced by emerging Nigerian middle class. This involves giving a variety of assistance to those people and businesses involved in the delivery side of the housing sector (Berry, 2002).

The central focus of this thesis is therefore the creation of an effective public private partnership for the provision of affordable housing in Nigeria. The intent of this chapter is to set out the nature and scope of the thesis as well as to outline its structure. The rationale for affordable housing delivery, which is the motivation for the thesis, is presented in this chapter, as is the case for public private partnership (and the beneficiaries – emerging middle class Nigerians). Key concepts are elucidated, albeit briefly, in this chapter but dealt with more elaborately in the rest of the thesis. The aim of the research and the concomitant research questions are also the subject of this chapter. The significance of the research is also presented in the chapter and finally, a brief summary of the following chapters of the thesis is given.

1.2 Rationale for Affordable Housing Delivery

Housing has been identified as one of the world’s prevalent problems. The international community recognises that increasing affordable housing is one of the major development challenges of the twenty-first century (Kothari, 2005, Kissick et al., 2006, Walley, 2010). From slum residents in the developing countries to middle-income households in expensive global capitals in developed countries, hundreds of millions of people struggle to find decent housing that they can afford without severe financial stress which has social as well as economic consequences (Woetzel et al., 2014). Globally, around 1.6 billion people live in substandard housing and 100 million are homeless (Kothari, 2005). Every week more than a million people are born in or move to cities in low-income countries, driving up the need for new and better housing (Kissick et al., 2006). Estimates of total new housing need in Africa have been set at around 4 million units per year with over 60 per cent of the demand required to accommodate urban residents and this is likely to increase to 5 million per year (Walley, 2010). This translates into nearly 14,000 homes per day in order to accommodate the expected urban population growth.

Inadequate affordable housing, particularly in developing countries like Nigeria, is a constraint on economic growth and a persistent challenge for governments. Nigerian governments have historically struggled with the challenge of housing its citizens and providing housing at a reasonable cost for low and middle-income people. For years, Nigeria has underprovided affordable housing. In Nigeria, total current housing production is at about 100,000 units per year, for a country of nearly 170 million. Nigeria needs about 720,000 additional units each year, with the federal government estimating that there is a deficit of 23million homes in Nigeria (FGN, 2013). For some of the major urban centres (such as Lagos, Abuja, Ibadan and Kano), housing demand is growing at about 20 per cent per annum (Okonjo-Iweala, 2014). In 2010, it was reported that 85 percent of the urban population lives in rented accommodation, spending more than 40 percent of their income on rent (Kokularupan, 2010). It is also noteworthy that 90 per cent of houses in Nigeria are self-built; this may be due to a general lack of affordability and also the difficulty in obtaining mortgage financing (FinMarkTrust, 2010, CAHF, 2012).

While the dire shortage of affordable housing has been recognised internationally as a deep and pervasive problem, strategies to address this do not seem to have been thoroughly examined (UN-Habitat, 2005). Some of the policies, institutions and regulations which the Nigerian government has put in place since independence in 1960 have been hindered by frequent changes of government and this has tended to disrupt policies and programmes before they have had a chance to take hold (FinMarkTrust, 2010). Although these initiatives may have had some impact, they have not been sufficient or effective enough to deliver housing for all Nigerians. Financing affordable housing is important if the world is to secure environmentally sustainability, economic prosperity, cultural diversity and social equality (UN-Habitat, 2005). In addressing these challenges, there is need for new organisational arrangements and commitments across sectors (government and private sector) (Brinkerhoff and Brinkerhoff, 2011). With these new combinations of desired resources, it is expected that overall effectiveness in the pursuit of the objective of affordable housing delivery might be enhanced.

History has shown that, nations that fail to house their people have risked urban unrest: poor-quality housing outputs contributed to rioting in Rome in 75 BC, Paris in 1848, several US cities in 1967, and Morocco in 2003 (Ernst and Young, 2013). Affordable housing has always been part of the Nigeria housing policy statements. ‘A good home for every citizen’ has been part of the national social contracts (NHP, 2012) but that is a promise governments could not keep. For decades, however, governments have been falling behind: the systems in place, cannot keep up with growing and diversifying economies and the long-predicted boom in urban population. With increasing population pressures, urbanisation and other developmental trends, the government’s ability to address the affordable housing needs adequately through traditional means has been severally constrained. To continue with the current system would be to condemn a majority of the populace to homelessness, or at best unsuitable housing. In most developed economies, the housing sector is seen as an important sector for stimulating economic growth. Many housing-related activities contribute directly to achieving broader socioeconomic development goals (Kissicks et al, 2006).

Housing is also a key driver shaping the social sustainability of societies, a vehicle for social inclusion. In fact, social scientists (Karn and Wolman, 1992) have observed that one key way to evaluate a nation’s housing system delivery is whether, and how much, it contributes to social stability. Therefore, the citizens’ sense of social cohesion is often directly connected to the delivery of sufficient housing they could afford. Housing is what creates and defines nations. A growing body of research shows that access to good quality affordable housing supports not only the nation’s households, but also has positive nationwide benefits related to economic competitiveness, health, education and public well-being (MAH, 2011). In addition, clean, warm housing is an essential factor in the prevention and care of the diseases of poverty like HIV/AIDS, tuberculosis, diarrhoea, and malaria (World Bank, 1993, Reeves, 2005). Thus, there is need for innovation by both the public and private sectors, to work together to deliver the housing the country needs and the citizens can afford. As such, affordable housing is essential to the continued success, growth and competitiveness of Nigerian state.

Although Nigeria has 84 primary mortgage banks (PMBs) and 20 commercial banks, most Nigerians usually, depend on private savings to pay for their homes. The size of the mortgage market has grown from N54billion (US$342 million) in 2006, to about N224billion (US$1.42 billion) in 2011 yet, this still accounted for only roughly 0.5% of GDP. For commercial banks, mortgage loans accounted for less than 1 per cent of their total assets. Nigeria’s Federal Mortgage Bank (FMBN) manages a National Housing Fund financed mostly by contributions from public sector workers. But results from this fund have been disappointing: as at August 2012, only about 12,000 mortgages had been provided for a total of 3.8 million eligible contributors (World Bank, 2013). This has contributed to the dearth of affordable housing in Nigeria. Various (of the 36 and the Federal Capital Territory) state governments also have housing development agencies, but these institutions have had very limited impact. Moreover, a number of administrative and bureaucratic, operational and financial capacity problems are hindering the development of the mortgage industry and the housing sector. These problems are well known and well documented but what needed is a plan to tackle the challenges.

Housing is expensive to provide in Nigeria. The construction cost for a simple threebedroom house in Nigeria is about N8million (or US$50,000); compared to US$36,000 in South Africa and US$26,000 in India (Okonjo-Iweala, 2014). The costs are high for three reasons: high costs of building materials, high costs of skilled labour, and the costs of associated public infrastructure such as sewers, roads, etc. About 75 percent of households in Nigeria’s urban areas live in dwellings constructed with concrete. Cement prices in Nigeria are about 30-40 percent higher compared to neighbouring countries or to the world market prices due to epileptic power supply ((Ibem, 2011, Okonjo-Iweala, 2014). Nigeria therefore needs to explore the greater use of local inputs and alternative building materials, which are cheaper, of good quality, and environmentally friendly.

Affordable housing is usually viewed as non-market housing provided to those whose needs are not met by the market (DCLG, 2006). Housing is however expensive to provide and people whose incomes are low are likely to find it difficult to procure adequate housing through normal market mechanisms (Satsangi et al., 2001). This suggests that, there is a gap between the need for housing and the capacity to provide the desired housing type, resulting in an effective demand crisis for affordable housing in the country (FinMarkTrust, 2010). Walley (2010) conducted research into various options to provide housing in Nigeria for different income levels. The research found that none of the studied areas was delivering solutions for the needs of low-middle income households. The study recommended commissioning a detailed study on a framework for Housing Public Private Partnership Schemes, and advocated a more coordinated and inclusive housing policy. In line with previous studies, the research identified inadequate access to finance, slow bureaucratic processes, and the high cost of land and building materials as major factors negatively affecting housing provision in Nigeria.

The key issue here is that there is still a shortage of affordable housing in Nigeria and the performance of both public and private sectors in affordable housing delivery has been inadequate. The widening gap of effective demand over affordable housing is not arising because governments do not care; rather, it is proof that government’s existing frameworks are not adequate. It is time for government to make innovative changes in the delivery models and, in particular, to shift into a more outsourced, public private partnership oriented approach on both the supply side (new homes) and the demand side (financing products).

It is more apparent that the scale of housing problem in Nigeria and the finance requires to address the problem exceed what governments are prepared to commit. As stated earlier, governments and private sectors are not delivering enough homes and some of the available ones are often for high income earners. As a result, relying solely on government programs for the provision of housing is now unsustainable. Other options need exploring. Since governments are ill-equipped to deal with the problem, they must explore new ways to ensure that limited public resources are used in the most efficient way. One initiative proposed as a possible solution to address the provision of affordable housing is public private partnerships. The remainder of this thesis focuses on this initiative.

“While the dire shortage of affordable housing has been recognised internationally as a deep and pervasive problem, strategies to address this have not been thoroughly addressed” (UN-Habitat, 2005). Providing affordable housing for citizens is a perennial challenge for nations around the world (Woetzel et al., 2014) The problem of affordable housing is particularly severe in Nigeria, where a variety of housing initiatives have been tried and found wanting. The most recent involves Public Private Partnerships (PPP). PPPs are contractual relationships between partners in different sectors. Nigeria has recently experienced political transition, and the government plans to pursue private sector participation to accelerate access to housing to drive economic growth. This comes in the context of growing financial constraints. Good example is the drop in the price of oil over the past year has severely limited government revenue, since oil accounts for 70 per cent of the government’s income (Goussard, 2015). Growing resource constraints have increased the need for, and willingness of, organisations to work together (Alter and Hage., 1993, Christianson et al., 1995). However, evidence on whether PPP provides truly “win-win” solutions, (succeeding where both governments and markets have failed), is far from clear (Biermann et al., 2007). Given their diverse nature and ranging focuses, more needs to be done to analyse the effect of PPP project, especially in the provision of affordable housing in Nigeria.

The need for affordable housing investment continues to grow in virtually all countries; governments are recognising the value in establishing partnerships with the private sector to increase the provision of affordable housing projects (Austin, 2008). There is consensus among policy makers that to achieve solutions to the affordable housing crisis at scale, major support and involvement by the private sector is necessary (Davis, 2006). At their best, private funds ease budget constraints (Sanusi, 2012), for example, in the USA; budgetary constraint was the driving force, which prompted community based non-profit housing developers to forge creative alliances with various parties to finance affordable housing (Pomeroy et al., 1998, Davis, 2006). The same was true in the UK (Webb and Pulle, 2002, Boussabaine, 2007), Canada (Moskalyk, 2008) and Australia (Susilawati, 2009).

The private sector cannot however produce housing that is affordable to low-middle income households without some form of subsidy (Pomeroy et al., 1998, Suchman and Sowell, 1997). Even for the construction of modest housing units, the break-even rents are higher than what is considered to be affordable for many low-income households (Moskalyk, 2008). Similarly, the withdrawal of government funding has shown that housing authorities lack sufficient funding and resources to produce low-cost housing on their own. Therefore, based on the public sector lack of sufficient funding and current market conditions, it appears that affordable housing provision will require a partnership between public and private sectors. This observation is echoed in research literature and the trend toward Public Private Partnerships has been noted in the UK, Canada, Australia and the United States (NAO, 2010, Pomeroy et al., 1998, Berry et al., 2006).

With the failure of the most recent attempt at national housing reform and the growing financial pressures, the public and private sectors are looking more often to these types of partnerships to respond to housing needs (NHP, 2012). Despite the positive rhetoric surrounding their perceived role, however, whether or not partnerships will prove a model of effective delivery for affordable housing in a new world of complex interdependence required a systematic examination. The argument that PPP effectively address global challenges is still rather a normative idea than a methodologically sound and theoretically grounded empirical fact (Homkes, 2011). Initial researches suggest that partnerships have indeed led to substantial gains and contributed to addressing these pressing global problems (Caines, 2005, Buse and Tanaka, 2011). The cumulative positive impact of this is perhaps neither established nor properly tested (Biermann et al., 2007). Therefore, more needs to be done to systematically study the impact of these unique collaborative partnerships.

PPP could only be successful if the right enabling environment is created including political stability, enforcement of a legal framework, and increased transparency and openness to foreign investment coupled with an institution that has strong corporate governance and is shielded from undue political interference. However, the capacity to appraise and implement PPP projects is still relatively limited, resulting in incomplete project preparation, inadequate financial models and business plans, and a general lack of experience in developing high quality concession contracts and most particularly monitoring their operational success. Nigeria needs to do more to address these weaknesses (Sanusi, 2012). In Nigeria, according to (Okonjo-Iweala, 2011), every project takes at least twice as much time to complete because of regulatory failures, lack of consensus and in the end the projects are the most costly compared to other neighbouring countries. The private sector has been shown to be more willing to enter into partnership where regulatory framework is clear and in a structured environment. This is needed in Nigeria to facilitate the development of effective PPP.

While there are many positive aspects to the emergence of PPP, there remain many uncertainties and some causes for concern (Teiseman and Klijn, 2002). Research is needed to learn more about what makes a partnership effective and in particular what organisational forms and management arrangements represent best practice for governance and what factors contribute to partnership effectiveness on the ground. Recent research says harnessing the potential and minimising the risks of partnership failures relies on the systematic identification of potential pitfalls associated with PPP and the use of these findings to develop appropriate guidelines, procedures and safeguards (Hayford, 2013).

Public private partnership has long been advocated and analysed as a potential organisational solution to pressing societal problems that call for the comparative advantages of government, business, and civil society (Brinkerhoff and Brinkerhoff, 2011). Addressing these challenges, taking advantage of the opportunities they provide, and mitigating threats calls for new organisational measures and unwavering commitment across sectors (public and private). Broadbent et al (2003) note: ‘partnerships are no panacea, for they bring their own technical, organisation and political challenges’. However, if the government cannot deliver the affordable housing needed by the Nigerian public with the available resources, there may have to be a review of the functions undertaken by the government.

Nigeria has experienced mixed success in the development and execution of PPP projects, and has recently taken concerted action to improve aspects of the operating environment or to boost institutional capacity. The country has undergone significant regulatory reform, with the ratification of new PPP acts, while at the same time developing institutional frameworks from the ground up. Although the country has had some experience in engaging private-sector parties in the development of power facilities with relative success. However, regulatory frameworks and institutional arrangements are not yet robust. There is however, a good level of political will towards deploying PPP as a means of boosting much needed affordable housing investment (Ohiani, 2014). Despite weak regulatory frameworks and underdeveloped institutions, the attractiveness of the country’s investment proposition is critical, as is the imperative to get the rules and the institutions right. Prospects for Nigeria are bright, given the increasing attractiveness of its business environment and the growth of increasingly sophisticated domestic financial facilities (AFDB et al., 2012).

Affordable housing is an overlooked opportunity for developers, investors, and financial institutions. To replace today’s substandard housing and build additional units needed by 2025 would require an investment of $9 to $11 trillion for construction; with land, the total cost could be $16 trillion. Of this, $1 trillion to $3 trillion may be required from public funding (Woetzel, et al, 2014). These findings indicate that new approaches are needed since attempts to date to provide affordable housing have yielded inadequate results. The governments need to think more broadly and creatively about a solution to satisfy the need for affordable housing that can accommodate citizens of all income groups and their changing requirements that might connect them to employment and society. To turn these aspirations into reality, governments will need efficiently functioning delivery mechanisms.

Affordable housing cannot be fully effective without an efficient delivery mechanism to manage and fund affordable housing initiatives. The affordable housing delivery mechanism is how the government turns its goals, aspirations, and policies into action. To ensure this is achievable, policy makers need to collaborate with the private sector, choose the housing delivery model(s) that fits the local context, identify all possible sources of funding, and establish rules for governance, including deciding how affordable housing benefits will be allocated and in doing this manage the performance of housing-related regulatory processes (Woetzel, et al, 2014). In this arrangement, the public sector is an active partner with the private sector, rather than a passive, regulatory actor. Public private partnerships could be an influential scheme for providing affordable housing by leveraging the best of both the public and private sectors, wherein the government enlists a private sector partner to deliver affordable housing under agreed-upon conditions.

Overall, this public private partnership shows that there is a strong economic case for expanding the private sector involvement in affordable housing delivery in Nigeria. New provision may require increased investment in public private partnerships, but they could be capable of delivering important improvements in the affordability and efficiency of affordable housing delivery, and improving the Nigerian housing system’s capacity to cope with the impact of the housing deficit.

Why Emerging Middle Class is Important

The focus of this research is to examine how PPP could be effectively used to deliver affordable housing for emerging middle class Nigerians. Many recent studies have focused on housing for low-income earners (Wapwera, Parsa and Egbu, 2011; Abdullahi and Abd Aziz, 2011; CAHF, 2012; Ibem, 2011 and Adedeji and Olotuah, 2012); however, there is little research on affordable housing provision for middle class in Nigeria (Okpoechi, 2014). Mabogunje (2011) and Awotona (1990) observed that, this middle-income group (which forms the bulk of the working population) suffers from the shortage of housing stock in Nigeria; translating their aspirations into effective demand is challenging. Nigeria’s middle class has emerged along with expansion of the private sector industries like banking, telecommunications and services, centred in urban areas. A study carried out by Africa Development Bank, estimated that Nigeria’s middle class accounted for about 23% of the Nigerian population (39.9m) (Ncube et al., 2011) (See Figure 1 – Page 12). According to Hever (2007), an equitable society is one in which the middle class is large and the upper and lower classes are small. All over the world, the existence and sustenance of the middle class are perceived as very important factors in measuring the extent of economic well-being of a country’s working population (Li, 2006). For many years, it was apparent that high rate of poverty and income inequality have threatened the Nigerian middle class with extinction (NBS, 2007). In order to sustain and improve the middle class in Nigeria, Nigeria Bureau of Statistics suggested that Nigeria need to boost its homeownership program for middle class. This invariably, might reduce social inequality in Nigeria (NBS, 2007).

Many of the emerging middle class in sub-Saharan Africa are not “income-secure”. They are at the risk of slipping back into poverty in the event of some exogenous shocks (Ncube et al., 2011). Where the secure middle class is small, it is also likely to be more economically dependent on government, either directly in the case of civil servants or indirectly in the case of employees of government-owned companies and other enterprises heavily dependent on government subsidies and political largesse (Birdsall, 2007). Both federal and State governments in the country are grappling with how to address the need for more housing that is affordable for their civil servants. With little or no subsidies available, huge construction costs have made private developers focus on building luxury rentals, not low-middle class housing.

Housing has become severely unaffordable for much of the Nigerian middle class in urban areas, and particularly for new working families (Ibem, 2011); this is negatively affecting their standard of living. Without an effective and coherent policy promoting affordable housing and a strong commitment by various levels of government to promote and strengthen a middle class in Nigeria, the prospects of a vibrant, stable, and affluent middle class may be less than encouraging. The failure to establish a strong middle class in Nigeria may also negatively impact economic growth, the goal of a more consumptionbased domestic economy, and the hope of building a harmonious and civil society in Nigeria. Sound policies encouraging the growth of the middle class are necessary to ensure sustainable development in any country (Li, 2010). This is particularly important for a populous country like Nigeria.

The middle class is widely acknowledged to be Africa’s future, the group that is crucial to the continent’s economic and political development. Recent estimates put the size of the middle class in the region in the neighbourhood of 300 to 500 million people, representing the population that is between Africa’s vast poor and the continent’s few elite (Ncube et al., 2011). It is also argued that Africa’s middle class is strongest in countries that have robust and growing private sectors (Ramachandran et al. 2009). Africa’s middle class is not only crucial for economic growth but is also essential for the growth of democracy (Mahajan, 2009). Whilst the affordable housing problem for low-income group is huge, but the current trends are that the problem is now spreading to middle-income households, families earning between $6,000 and $7,000 per year (Ncube et al., 2011 and Robertson et al., 2011). These middle-income families have less money to spend on other goods and services and that creates huge losses across the economy. Some middle-class households choose to move out of major cities in search of more affordable housing, depriving the state of young, skilled workers who represent the backbone of the workforce and the state’s future (Lutz, 2015).

One advantage of delivering affordable housing for emerging middle class is to create housing opportunities near centres of job growth. Thus, this could promote balanced urban growth that strengthens existing cities (Katz et al. 2003). Affordable housing can offer development opportunities for the housing sector, and it can be a stabilising factor for economic development. It can also facilitate urban development and regeneration, contribute to ecologically sound standards in new construction and refurbishment, stabilise migration flows and reduce social tensions (United Nation, 2010). Additionally, projections by the African Development Bank in 2011 suggest that by 2030, countries like Nigeria, Ethiopia and South Africa, are expected to provide the largest number of middle income in Africa (Juma, 2011). It thus becomes important that for there to be a continued rise in the middle class in Nigeria, policies that bolster the incomes of those already in the middle class would have to be introduced. Housing is one such policy, as it has the capacity to accelerate the reduction of poverty, and improve the living conditions of the people.

Statement of the problem

Affordable housing has become a great concern for both developed and developing countries. To date, there is still no commonly agreed upon definition of ‘affordable housing’, and there are still major gaps in the knowledge on how various countries such as, Nigeria can effectively tackle its growing housing challenge and what more can be done to increase provision (Walley, 2010; Woetzel et al., 2014; CAHF, 2015). The primary reason for affordable housing is to ensure equity in accessing housing, which is generally regarded as a basic human need (UN-Habitat, 2008). Government involvement is inevitable due to the failure of market housing to adequately meet housing needs. The quality of housing provision plays a decisive role in the economy of a nation and health status of its citizens. Many health problems are either directly or indirectly related to housing because of inappropriate construction materials, the equipment installed, the size or design of the individual dwellings and the quality of the internal environment (Butler-Jones, 2009).

Evidence has shown that those who have the least resources at their disposal suffer the worst housing conditions (Krieger and Higgins, 2002; Bonnefoy, 2007). Dealing with poverty will thus remain a most important element in any housing policy, either through specific housing programmes, or through specific economic policies. Looking at available knowledge on housing strategies, The World Bank observed that: “While the dire shortage of affordable housing has been recognised internationally as a deep and pervasive problem, strategies to address this have not been thoroughly addressed” (UN-Habitat, 2005). The World Bank strongly believes that more research on housing strategies will bring about better solutions for local, regional, and national policy-making.

Similarly, the Report of the Presidential Committee on Urban Development and Housing opined that “the strategies and programmes of successive governments did not satisfy the quests of the average Nigerian for housing mainly due to lack of adequate resources and political will” (NHP, 2012). Walley (2010) conducted research into various options to provide housing in Nigeria for different income levels. The research found that none of the studied areas were delivering solutions for the needs of low-middle income households.

The study recommended a detailed study on a framework for PPP housing schemes, and advocated a more coordinated and inclusive housing policy. However, this shows there is an urgent need for a renewed commitment; redirection of focus and private sector participation if achieving an adequate affordable housing objective is to be achieved.

The several housing policies and programmes previously developed in Nigeria, though well intended, have made little impact. The small achievements made to meet the needs of the low-middle income groups have usually been taken over by higher-income groups (Adedeji and Olotuah, 2012). Ogunshakin and Olayiwola (1992) traced the causal roots of the failure of affordable housing policy in Nigeria to the flaws in the institutional mechanisms of decision making and implementation processes. On provision of housing through PPP in Nigeria, Oyebanji, Akintoye and Liyanage (2011) also revealed that poor structure and lack of well-defined policy guidelines have been the underlying issues in Nigerian housing sector (Oyebanji et al., 2011).

The effort toward closing the affordable housing gap will not be possible if the Nigerian government do not have effective ways to follow through with affordable housing initiatives. Housing is very important, and requires innovative approaches. It is clearly necessary to approach housing in a cross-sectional and multidisciplinary way. The literature search has identified the role the private sector could play in reducing the supplydemand gap of affordable housing through productivity and expertise. The best housing strategy will fail to accomplish its goals if it is not effectively implemented. In order to encourage sustainable affordable housing delivery, policy makers need to create a supportive environment, which could play an important role in attracting investments into PPP for affordable housing delivery. A conducive environment is a critical factor in determining the efficiency and effectiveness of PPP because it not only affects the process, but also influence the interactions, decisions and outcomes of any PPP projects.

In summary, the existing literature on the use of PPP for the provision of affordable housing in Nigeria have identified the causal roots of failure as flaws in the institutional mechanisms of decision making and implementation processes (Ogunshakin and Olayiwola, 1992). They have revealed that poor structure and lack of well-defined policy guidelines have been the underlying issues (Oyebanji, Akintoye and Liyanage, 2011). There is, however, a gap in knowledge in the reasons for these flaws, for the poor structure and the lack of well-defined guidelines. This means that the problem situation is not well understood let alone the knowledge of the problems and constraints that exist within it. The knowledge gap therefore is the understanding of the problem situation, which the research aims to achieve.

Once this knowledge gap is filled, it would enable the development of a more robust and comprehensive framework for implementation of PPP projects which would help to foster confidence and thereby encourage investors to get involved.

Research Objectives

1. To identify the mechanisms for affordable housing delivery?

2. To identify the issues, problems and constraints that hinder the performance and success of using Public Private Partnership for affordable housing delivery in Nigeria?

3. To know how Public Private Partnership increase the provision of affordable housing in Nigeria?

Research Questions

The following research questions are raised for this study:

1. What are the factors that facilitate the establishment, performance and success of Public Private Partnership as a mechanism for affordable housing delivery?

2. What are the issues, problems and constraints that hinder the performance and success of using Public Private Partnership for affordable housing delivery in Nigeria?

3. How could Public Private Partnership increase the provision of affordable housing in Nigeria?

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THE CONTRIBUTION OF URBANIZATION TO SLUM DEVELOPMENT IN NIGERIA

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THE CONTRIBUTION OF URBANIZATION TO SLUM DEVELOPMENT IN NIGERIA

CHAPTER ONE

INTRODUCTION

Background of the study

Accordingly, the major questions which this project seeks to answer are: How has urbanization encouraged and accelerated the tempo of slum formation? Is slum formation a determinant of insecurity of land tenure? How has slum development deepened the incidence of poverty and enhanced insecurity of land tenure in the selected areas?

This project is based on the concept of political ecology. According to Bryant and Bailey (1997), political ecology is the study of the “politi- cised environment”. It is a multi-disciplinary investigation that uses the methods of the social sciences to understand the human processes that result in the initial destruction and re-creation of material environ- ments. Bryant and Wilson (1998) therefore define political ecology as “the political economy of human-environment interactions”.

As a conceptual framework, political ecology argues that the out- come in environmental change is determined by the relative power of agents with conflicting agendas. The agents reflect the scale of analysis. Dietz (1999) identifies two main modes in Third World political ecol- ogy. First, in the eco-imperialist mode, the interests of the first world result in the creation of environmental regimes, under the framework of ecological modernization and often under the label of sustainable development. He identifies eco-populism as the second major mode of thought and action. All of these have effects on the way in which the environment is used, who uses it, when and with what effects. These

necessarily entail analyses concerning those situated on the margins of society and the environment and how to ensure environmental sustain- ability.

For example, Jusilla et al. (1999) found that while the process of marginalization has been an object of inquiry in the last 25 years, there is as yet no operational definition of the term. The concept of margin- ality, which can be applied to people and environments, illuminates restrictions in the options available to marginal people in terms of the management of sensitive environments (Blaikie, 1985). The fact that marginal people are condemned to earn a living in marginal environ- ments, whether rural or urban, is perhaps the essential truth of political ecology. With the exception of those who deliberately marginalize themselves through criminality, marginal people are unlikely to have access to the resources that are required to overcome the restrictions imposed by marginal environments and thus enable them to live be- yond the limits of subsistence. Marginality is thus reinforced and re- produced and environmental sustainability becomes still be more difficult to achieve.

The goal of environmental sustainability is to minimize environ- mental degradation, i.e. the damage to the biosphere as a whole that results from human activity. Environmental degradation occurs when: natural resources (such as trees, habitat, earth, water and air) are con- sumed faster than nature can replenish them, when pollution results in irreparable damage to the environment, or when human beings destroy or damage ecosystems in the process of development. An unsustain- able situation occurs when the natural capital (the sum total of nature’s resources) is used up faster than it can be replenished. Sustainability requires that human activity, at a minimum, only uses nature’s re- sources at a rate at which they can be replenished naturally.

Statement of the problem

There may have been previous researches in this subject. This work gives further explanations and analysis in the contribution of urbanization to slum development in Nigeria

Objectives of the study
To understand the contribution of urbanization to slum development in Nigeria
To understand the relationship between the contribution of urbanization and slum development in Nigeria

Research questions
What is the the contribution of urbanization to slum development in Nigeria
What is the relationship between relationship between the contribution of urbanization and slum development in Nigeria

Research hypothesis

H0: There is no relationship between the contribution of urbanization and slum development in Nigeria

H1: There is a relationship between the contribution of urbanization and slum development in Nigeria

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LAND USE EFFECT ON URBAN STREAM

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LAND USE EFFECT ON URBAN STREAM

CHAPTER ONE

INTRODUCTION

1.1 Background of the study

Profound and far-reaching impacts of humans on the environment are mediated through land use changes which destroy, degrade, and fragment habitat, and constitute the primary cause of losses in biodiversity worldwide (Sala et al., 2000; Chapin et al., 2001). Human impacts on landscapes often diminish the capabilities for ecosystems to provide essential services for people, including clean air and water and natural products (Foley et al., 2005). Land use changes have had a large effect on terrestrial and aquatic environments in mediterranean climate regions (medregions), that is the Mediterranean Basin, CaliforniaBaja California, southwestern Australia, southwestern South Africa, and central Chile, because of their long history with human activity, rapid urban and agricultural development, and large climatic and topographic variation (Underwood et al., 2009; Sirami et al., 2010). Because med-regions contain many endemic species, human impacts on these regions have a disproportionate effect on global biodiversity and make mediterranean ecosystems (med-ecosystems) among the ‘‘most imperiled’’ in the world (Myers et al., 2000; Horwitz et al., 2008; Underwood et al., 2009). Although considerable research has been conducted on the effects of land use change on terrestrial environments in med-regions, studies of land use impacts on aquatic habitats are more limited. Because water is seasonally scarce in med-regions, many rivers and streams have been dammed or diverted to provide water supplies for human activities (Gasith & Resh, 1999). Given the critical importance of water quality and quantity in med-regions and concerns about the impacts of human environmental alterations on aquatic systems and species, there is a need for more data and knowledge to guide management and policy decisions balancing human and environmental needs for sustainable water resources. Research in other temperate regions of the world has shown that land use changes denude native vegetation, increase runoff and erosion, alter stream geomorphology and substrata characteristics, modify flow regimes, and enhance the transport of nutrients, sediment, and contaminants from catchments to receiving waters, all with numerous implications for the stream and river biota (Paul & Meyer, 2001; Allan, 2004; Walsh et al., 2005; Johnson & Horst, 2010). Human land use impacts on med-ecosystems are predicted to be heightened by climate change which will result in warmer, drier, and more variable weather (Klausmeyer & Shaw, 2009).

The growth of the wildland–urban interface in many med-regions has increased the intensity and frequency of wildfires and promoted the introduction of exotic species (Verkaik et al., 2012). Land use changes and fires have similar short-term effects on the physical, chemical, and biological characteristics of streams, but with fires constituting a pulsed perturbation, with rapid ecosystem recovery (Verkaik et al., 2012), and land use changes constituting a press perturbation with sustained, long-term impacts on ecosystems. Frequent clearance, burning, or intense grazing of med-vegetation, however, can produce a vegetation type conversion from forest or shrubland to degraded scrub or grassland (Keeley, 2002; Van de Wouw et al., 2011), with persistent effects on both terrestrial and aquatic ecosystems. Other human effects on med-rivers include straightening and building levees along river channels, decoupling rivers from their floodplains and destroying riparian vegetation as floodplains are converted to grazing, farming, industrial, or urban uses. For example, riparian vegetation cover in the middle section of the River Ebro declined from 40% in the 1950s to 4.5% today (Ollero, 2007). Although land use changes have diminished riparian vegetation in many med-ecosystems, canopy cover by riparian vegetation can be as high or higher in human-altered basins as in undeveloped basins because of the protection or restoration of riparian bufferstrips, planting of ornamental trees, and increased return flows of irrigation or sewage water in some catchments. In addition, the construction of dams on rivers reduces floods in downstream areas, which may allow the encroachment of riparian vegetation; however, the net effects of dams on downstream riparian vegetation depend on the effects of dams on seasonal river flows (i.e., increased vs. decreased dry season flows).

Statement of the problem

There may have been previous researches in this subject. This work gives further explanations and analysis in land use effect on urban stream

Objectives of the study

1.To understand the impact of land use on urban stream

To understand the relationship between land use and urban stream.

Research questions
What is the impact of land use on urban stream
What is the relationship between land use and urban stream.

Research hypothesis

H0: There is no relationship between land use and urban stream.

H1: There is a relationship between land use and urban stream.

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ASSESSMENT OF COMMUNITY PARTICIPATION IN URBAN ENVIRONMENTAL MANAGEMENT

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ASSESSMENT OF COMMUNITY PARTICIPATION IN URBAN ENVIRONMENTAL MANAGEMENT

CHAPTER ONE

INTRODUCTION

1.1 Background of the study

Environmental management involves the management of all components of the bio-physical environment, both living (biotic) and non-living (abiotic). This is due to the interconnectedness and network of relationships amongst all living species and their habitats. It also involves the relationships of various human facets, such as the social, cultural and economic environment with the bio-physical environment.

Over the last decade, management on usage of natural resources in a sustainable manner has become one of the priorities of government, policy makers and environmentalists etc. Due to unbridled industrial growth in last century huge impacts both positive as well negative has been realized, of which one major negative one is on the environment. The increasing focus placed on the environment globally, through multilateral norms, agreements and conventions, has shifted the responsibility from the governments (particularly the national governments) as a ‘provider’ to a more consensus-based approach, where all stakeholders have a role to play, bringing to the table different resources during the different processes of environmental management.

Of particular significance has been the participation and role of the ‘community’ the primary stakeholder in these processes has become an important component of all environmental programmes and projects, both in terms of decision-making processes, and of creating an enabling environment for the community to have a say over aspects that affect their lives. In general in all development programmes of government local level participation has occupied an important position in project implementation. Otherwise also participation or decentralized governance is one of the cornerstones of Indian democracy and has equal benefits for policy makers, public servants and civil society. To highlight few:

• Participation helps government to make more appropriate decisions based on the local needs of people

• The more informed people are, or the more participation ,the better they understand about government’s strategy, budget and resource limitations .

The local needs are varying in various communities and thus creating a partnership between community and government helps in addressing the development needs and service delivery.

The present paper tries to look into the role of local community with specific focus on women in managing environmental programmes through sustainable use of natural resources and of disposing and keeping the generated wastes judiciously. It will look into the intersection between community participation, and environmental management, the dynamics of interrelationships of local community with the policy makers and environment. This will help in providing significant opportunities and challenges for sustainable development at the local level. The paper would also supplement few case studies from rural area where local community specifically women have helped in environmental management.

Key Issues in Community Participation which helps in Environmental Management Community Participation (CP) is a process which involves people to participate in planning, implementing and managing their local environment. It is actually a readiness on the part of both local governments and the community to accept equal responsibilities and activities in managing their surroundings. It also means a commitment to bring to the table resources, skills and knowledge for this purpose, and a respect for the capabilities and capacities of all partners. It means that the value of each group’s contribution is seen, appreciated and used. It is an inclusive form of development in which the community’s representatives as “partners” in decision-making, makes for successful community participation.

Statement of the problem

There may have been previous researches in this subject. This work gives further explanations and analysis in assessment of community participation in urban environmental management

Objectives of the study

1. To understand the impact of community participation in urban environmental management

2.To understand the relationship between community participation and urban environmental management

Research questions
What is the impact of community participation in urban environmental management
What is the relationship between community participation and urban environmental management

Research hypothesis

H0: There is no relationship between community participation and urban environmental management

H1: There is a relationship between relationship between community participation and urban environmental management

HOW TO RECEIVE PROJECT MATERIAL(S)

After paying the appropriate amount (#5,000) into our bank Account below, send the following information to

08068231953 or 08168759420

(1) Your project topics

(2) Email Address

(3) Payment Name

(4) Teller Number

We will send your material(s) after we receive bank alert

BANK ACCOUNTS

Account Name: AMUTAH DANIEL CHUKWUDI

Account Number: 0046579864

Bank: GTBank.

Account Name: AMUTAH DANIEL CHUKWUDI

Account Number: 3139283609

Bank: FIRST BANK

FOR MORE INFORMATION, CALL:

08068231953 or 08168759420

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ANALYSIS OF PRESENT TRAFFIC CONDITION WITHIN

admin — Sat, 24 Sep 2022 13:20:15 +0000

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ANALYSIS OF PRESENT TRAFFIC CONDITION WITHIN

ABSTRACT

Traffic congestion is a common feature on highways in many cities of the world, including Akure , Nigeria. Previous studies have shown that several mathematical traffic flow models developed to analyse congestion cannot be easily generalised or adapted to varying situations. In addition, validation errors of some models are as high as 60.0 %. In pursuit of the objective of minimising traffic congestion in parts of the Akure , headway simulation models were developed for the analysis of flow on some selected highways characterised by heavy traffic.

Traffic survey was conducted on three purposively selected heavily-trafficked highways in the Akure . Headway modelling approach incorporating the prevailing roadway, traffic and control conditions was developed. Field data were captured on the three roads with a camcorder between 7.00 a.m. and 6.00 p.m. for a period of six months as specified in the Highway Capacity Manual. Comparison of the modelling result and field headway data were carried out using Kolmogorov-Smirnov (KS) test (p = 0.05). A traffic flow simulator was developed to simulate the different congestion scenarios by varying the minimum and maximum headways. Capacity analysis and validation of the results were carried out using ANOVA methods.

Average vehicular flow of 715 ± 3, 970 ± 5 and 1118 ± 9 vph per lane on Total Garden-Agodi Gate, J Allen-Oke Bola and Odo Ona-Apata roads respectively. Eighteen hyperbolic headway scenarios were produced and the highest coefficient of correlation (R²= 0.92) was recorded at 90 percentile while 0.18, 0.36, 0.50, 0.71, 0.82, and 0.79 were obtained at 1, 10, 30, 50, 70, and 100 percentiles respectively. There was no significant difference between theoretical and field data using KolmogorovSmirnov (KS) test (p < 0.05). Also, a total number of 171 congestion scenarios were generated using the traffic flow simulator. Traffic flow varied between 204 and 2376 pcu per lane while headways varied between 1 and 18 seconds. The capacity analysis produced approximated maximum flow rates of 1850, 2865 and 2881 pcu in the two directions of travel for Total Garden-Agodi Gate, J Allen-Oke Bola and Odo OnaApata roads respectively. The capacity of Total Garden-Agodi Gate was within the recommended maximum value of 2800 pcu in the two directions of travel for highways. The results for J Allen-Oke Bola and Odo Ona-Apata roads showed that an additional lane will be required in each direction of travel. The validation of the models on the dualised J Allen-Oke Bola road showed that congestion can be reduced by about 55.0 %. A maximum validation error of 35.0 % was obtained.

The traffic flow simulator developed successfully simulated the traffic situations on the selected highways. The analysis of the flow yielded results that could ameliorate traffic congestion on the selected highways in the Akure .

Keywords: Traffic flow, Highways, Headway simulation models, Traffic congestion, Capacity analysis.

Word Count: 469

TABLE OF CONTENTS

Page

Certification ii

Dedication iii

Acknowledgements iv

Abstract vi

Table of Contents viii List of Figures xi List of Plates xiii

List of Tables xiv

Notation xv

Chapter 1 INTRODUCTION 1

1.1 Background 1

1.2 Research Problem 4

1.3 Study Area 5

1.4 Aim and Objectives 5

1.5 Justification 10

Chapter 2 LITERATURE REVIEW

2.1 Traffic Flow 11

2.1.1 Traffic flow parameters 11

2.1.2 Measurement of Traffic Flow 12

2.1.3 Traffic Flow Regimes 12

2.2 Traffic congestion 13

2.2.1 Causes of traffic congestion 13

2.2.2 Negative Impacts of traffic congestion 13

2.2.3 Congestion reduction strategies 14

2.2.4 Analysis of congested flow 16

2.3 Traffic flow modelling 17

2.3.1 Types of models 17

2.3.2 Criteria for model selection 18

2.3.3 Traffic simulation 21

2.3.4 Traffic simulation models 21

Page

2.3.5 Classification of traffic simulation models 22

2.3.6 Traffic simulation model building 24

2.3.7 Vehicle generation algorithm 25

2.4 Headway Distribution Models 26

2.4.1 Headway distribution models for free flow 27

2.4.2 Headway distribution models for constrained flow 28

2.4.3 Parameter estimation and calibration of headway models 29

2.5 Highway Capacity 32

2.5.1 Factors affecting capacity 32

2.5.2 Need for highway capacity analysis 34

2.5.3 Capacity analysis methods 35

2.5.3.1 The Highway Capacity Manual method 35

2.5.3.2 The British Standard Approach 36

2.5.3.3 Statistical method 38

2.5.3.4 Dynamic highway capacity estimation method 38

2.5.3.5 Safety-based capacity analysis 38

2.5.4 Level of Service 38

2.5.5 Acceptable degrees of congestion 40

2.5.6 Design hourly volume 41

2.5.7 Capacity of highways 41

2.5.8 Capacity analysis of highways 42

Chapter 3 METHODOLOGY 44

3.1 Traffic Survey 44

3.2 Traffic Data collection 44

3.2.1 Headway data capturing and extraction 45

3.3 Headway Modelling Process 45

3.3.1 Theoretical headway generation algorithm 45

3.3.2 Hyperbolic headway distribution models 47

3.4 Traffic Flow Simulator (TRAFLOS) 48

3.4.1 TRAFLOS algorithm 48

3.5 Experimental Design of Congestion Scenarios 50

3.6 Practical Capacity of Selected Roads 52 Page

3.6.1 Determination of adjustment factors 52

3.7 Statistical Analysis 53

Chapter 4 RESULTS AND DISCUSSIONS 55

4.1 Traffic Survey Results 55

4.1.1 General summary 55

4.1.2 Average traffic flow 57

4.1.3 Field headways 58

4.2 Headway Modelling Output 61

4.2.1 Vehicular interaction 61

4.2.2 Comparison of theoretical and field headways 67

4.3 Traffic Flow Analysis 68

4.3.1 Simulated traffic flows 68

4.3.2 Congestion factors 72

4.3.3 Capacity adjustment 75

4.3.4 Capacity analysis for different congestion scenarios 75

4.3.5 Results of the analysis of variance test 82

4.3.6 Validation of models for J Allen Oke-Bola road 83

4.3.7 Validation errors 84

Chapter 5 CONCLUSION AND RECOMMENDATION 85

5.1 Conclusions 85

5.2 Recommendation 85

REFERENCES 86 APPENDICES 96

Appendix A1: SONY camcorder operating guide 97

Appendix A2: Extracted field headway data set 105

Appendix B: Headway modelling output 112

Appendix C: Kolmogorov-Smirnov test 135

Appendix D: Traffic flow simulator output 150

Appendix E: One-way ANOVA test 192

LIST OF FIGURES

Page

Fig. 1.1: Nigeria’s road network 6

Fig. 1.2: Akure metropolitan area’s road network 7

Fig. 1.3: Network of some principal roads in Akure 8

Fig. 2.1: Model usage flow chart 19

Fig. 3.1: Theoretical headway generation algorithm flowchart 46

Fig. 3.2: Traffic flow simulator flowchart 49

Fig. 4.1: Distribution of field headways for flows between 700 to 1200vph 60

Fig. 4.2: Cumulative headway distribution for flows between 700 to 1200vph 66

Fig. 4.3: Distribution of simulated flows with minimum headway of 1 second 71

Fig. 4.4: Congestion factors for simulated flows 74

Fig. B2.1: Hyperbolic model at 1 percentile vehicular interaction 117 Fig. B2.2: Hyperbolic model at 2 percentile vehicular interaction 118

Fig. B2.3: Hyperbolic model at 3 percentile vehicular interaction 119

Fig. B2.4: Hyperbolic model at 4 percentile vehicular interaction 120

Fig. B2.5: Hyperbolic model at 5 percentile vehicular interaction 121

Fig. B2.6: Hyperbolic model at 10 percentile vehicular interaction 122

Fig. B2.7: Hyperbolic model at 20 percentile vehicular interaction 123

Fig. B2.8: Hyperbolic model at 30 percentile vehicular interaction 124

Fig. B2.9: Hyperbolic model at 40 percentile vehicular interaction 125

Fig. B2.10: Hyperbolic model at 50 percentile vehicular interaction 126

Fig. B2.11: Hyperbolic model at 60 percentile vehicular interaction 127

Fig. B2.12: Hyperbolic model at 70 percentile vehicular interaction 128

Fig. B2.13: Hyperbolic model at 80 percentile vehicular interaction 129

Fig. B2.14: Hyperbolic model at 90 percentile vehicular interaction 129 Fig. B2.15: Hyperbolic model at 95 percentile vehicular interaction 130

Fig. B2.16: Hyperbolic model at 98 percentile vehicular interaction 131

Fig. B2.17: Hyperbolic model at 99 percentile vehicular interaction 132

Fig. B2.18: Hyperbolic model at 100 percentile vehicular interaction 133 Page

Fig. C1.1: Comparison of field and simulated headways for flow rate of 700 vph 145

Fig. C1.2: Comparison of field and simulated headways for flow rate of 800 vph 146

Fig. C1.3: Comparison of field and simulated headways for flow rate of 900 vph 147

Fig. C1.4: Comparison of field and simulated headways for flow rate of 1000 vph 148 Fig. C1.5: Comparison of field and simulated headways for flow rate of 1100 vph 149

LIST OF PLATES

Page

Plate 1.1: Traffic stream on Obafemi Awolowo road (before dualisation) 9

Plate 1.2: Traffic stream on Odo Ona-Apata road 9

Plate 3.1: Sony HDR-HC3 Camcorder 54

Plate 3.2: Traffic Flow Simulator screen 55 LIST OF TABLES

		Page
Table 2.1: Overview of traffic flow models		20
Table 2.2: Comparison of headway distribution models		30
Table 2.3: Recommended design flows for two-way urban roads		37
Table 2.4: Level of service characteristics		39
Table 2.5: Guide for selection of design levels of service		41
Table 2.6: Maximum service volumes under ideal conditions		43
Table 3.1: Congestion scenarios design template		51
Table 4.1: Summary of preliminary traffic study		56
Table 4.2: Average traffic flow on selected roads		57
Table 4.3: Minimum and maximum values of headway		58
Table 4.4: Percentage composition of field headway per flow regime		59
Table 4.5: Hyperbolic headway simulation models		62
Table 4.6: Hyperbolic model adjustment factors Table 4.7: Cumulative headway distribution spreadsheet		63
for flows between 700 to 1200 vph		64
Table 4.8: Kolmogorov-Smirnov test result		67
Table 4.9: Simulated traffic volume for different congestion scenarios		69
Table 4.10: Computed flow rates for different congestion scenarios		70
Table 4.11: Computed congestion factors for different congestion scenarios	73
Table 4.12: Congestion factors and equivalent level of service	74
Table 4.13: Capacity adjustment factors	75
Table 4.14: Capacity analysis of Total Garden-Agodi Gate road for k_c=1	76
Table 4.15: Capacity analysis of J Allen-Oke Bola road for k_c=1	77
Table 4.16: Capacity analysis of Odo Ona-Apata road for k_c=1 Table 4.17: Simulated capacities at different congestion levels	78
for Total Garden-Agodi Gate road Table 4.18: Simulated capacities at different congestion levels	79
for J Allen-Oke Bola road Table 4.19: Simulated capacities at different congestion levels	80
for Odo Ona-Apata road	81
Table 4.20: ANOVA test result for field and simulated capacities	82
Table 4.21: Capacity adjustment factors for dualised J Allen-Oke Bola road	83
Table 4.22: Capacity analysis of dualised J Allen-Oke Bola Road	84

NOTATION

A = cumulative headway adjustment factor

C = basic capacity

C_p = practical capacity

e_i = lower boundary limit of headways in G_i d_i = upper boundary limit of headways in G_i f (x) = probability density function of x

f_i = adjustment factor G_i = headway group i

h = headway

h₁ = minimum headway h₂ = maximum headway H = cumulative headway k = traffic density k_c= congestion factor

k_i= headway group composition factor i q = flow (vehicles arrival rate)

R_n = random number

R² = coefficient of correlation T = total time/total headway v = mean (average) speed

V = traffic volume

V_R= number of vehicles released per simulation run

Chapter 1

INTRODUCTION

1.1 Background

The highway network is an important component of the transportation system. In Nigeria, it is the principal means of transportation facilitating the socioeconomic activities of the people. Highways (single carriageway) formed the main component of this system at the local, state and federal levels. Efficient and effective flow of traffic is desirable for the highway system to operate optimally at designed capacity and for favourable level of service.

Traffic flow represents the interaction between vehicles, drivers and infrastructure. Traffic flow can be either free or constrained (Helbing, 2001; and Nagatani, 2002). In free flow conditions, drivers can choose their own speed or constrained to car-following system. Kerner (2004) classified the congestion regime into two distinct phases: synchronized flow and wide moving jams. In synchronized flow, the speeds of the vehicles are low and vary quite a lot between vehicles, but the traffic flow remains close to free flow. In wide moving jams, vehicle speeds are more equal and lower, and time delays can be quite large. Traffic congestion is a road condition characterised by speeds slower than free flow speeds, resulting in longer travel times and increased queuing (Aworemi et al., 2009; Hook 1995). It occurs when traffic demand is greater than the capacity of a road (Lee et al., 2008). Traffic jam is extreme traffic congestion where vehicles are fully stopped for periods of time (Abul-Magd, 2007).

Traffic congestion is considered one of the main urban transportation problems, particularly in developing countries where vehicle ownership is growing geometrically without corresponding sustainable land use patterns and transportation schemes (Tugbobo, 2009). Traffic congestion leads to increased travel time, air pollution and fuel consumption. Providing additional lanes to existing highways and building new ones have been the traditional response to congestion (FHW 2005). However, the data collection effort for this exercise is great. Consequently, transportation engineers and researchers are increasingly developing simulation models to analyse traffic flows on highways.

Capacity expansion is one of the strategies usually adopted in both developed and developing countries to mitigate traffic congestion. Expanded highways improve traffic flow and reduce congestion. Capacity is the maximum number of vehicles that can pass a given point on a roadway or in a designated lane during one hour without the traffic density being so great as to cause unreasonable delay, hazard, or restriction to the drivers’ freedom to manoeuvre under the prevailing roadway and traffic conditions (TRB, 2000). Major attention has been given to capacity analysis methodology, because capacity estimates have a central role in the estimation of other highway performance measures (Luttinen, 2004). False estimation pollutes other reasonable traffic studies. Errors caused by inaccurate or wrong estimation of highway capacity can easily affect the results of other studies (Hwang et al., 2005).

Zang (2010) developed an improved highway capacity model that is feasible and can reflect the actual traffic flow characteristics; Yao et al. (2009) developed optimisation procedure that produced good estimates of the roadway capacity and other traffic stream parameters. Tanyel et al. (2005) showed that further studies should be made to develop a more reliable capacity and performance models for Turkey. Chang and Kim (2000) presented a quantitative method for highway capacity determination by evaluating alternative approaches in developing capacity from the statistical distribution of observed headways of traffic flow in Korea. Approximated headway distribution models of free-flowing traffic on Ohio Freeways was developed by Zwahlen et al. (2007) to simulate queue buildup and delay times under congested traffic conditions.

Traffic flow is a complex phenomenon and quite difficult to completely understand. Over the last fifty years, several modelling methods have been developed for vehicular traffic flow and categorised based on applicability, generability and accuracy (Hoogendoorn and Bovy, 2001). Lu (1990) also emphasised the importance of the accuracy of models for traffic flow simulation. Brockfield et al. (2004) reported that the most difficult stage in the development and use of traffic flow models is the calibration and validation stage. Validation errors of some models are as high as 60 %. The difficulty is due to lack of suitable methods for adapting the models to empirical data.

Headway modelling is useful in the analysis of flow in a traffic stream (Chandra & Kumar, 2001). Highway capacity is usually determined by the minimum acceptable mean headway (Zhang et al., 2007 and Arasan and Koshy, 2003).

Headway is defined as the time between successive vehicles as they pass a point on a lane (Banks, 2003; Kyte & Teplay, 1999; Owolabi and Adebisi, 1996). It is usually measured in seconds. Headway measurement can be performed manually with a stopwatch and automatically with any presence-type detector or with video image processors (Salter, 1990). Headways are affected by such factors as traffic volume, ratio of large sized vehicles, road structure, daytime or night-time, and weather (Daisuke et al., 1999).

Several studies have been carried out using headway modelling to analyse and solve specific traffic problems on highways (Akintayo and Agbede, 2009); Onibere et al. (1987); and Ovuworie (1980). Hoogendoorn (2005) presented a new approach to estimating the distribution of free speeds using a composite time headway distribution model. Haight et al. (1961) proposed a new statistical method for describing headway distribution of cars by classifying them as random, regular (equally spaced) or intermediate. Hossain and Iqbal (1999) found that in the flow range of 200-640 vph the exponential and log-normal distributions can best describe the headway pattern on two-lane, two-way highways. Owolabi and Adebisi (1993) found the composite exponential model to be a sound descriptor of observed headways along Zaria-Sokoto Road, Nigeria for flows ranging from 170 vph to 750 vph irrespective of whether or not motorcycles were in the traffic stream. Dawson and Chimini (1968) developed a generalised type headway model for single lane traffic flows on two-lane, single carriageways. Bham and Ancha (2006) proposed two shifted continuous distribution models, the lognormal and gamma models for preferred time headway and time headway of drivers in steady state car-following. Yuichi and Shizuma (1989) presented a practical method for estimating the headway distribution based on the experimentally observed data of the number of vehicles passing in a certain time interval theoretically as a general case of gamma-type headway distribution model.

Parameters of headway distribution models are usually estimated from the field data. The field data must be reliable and the parameters must be properly estimated before the models can be applied. Hagring (2000) highlighted three techniques usually employed in headway parameters estimation: the method of moments, the maximum-likelihood method and the least-squares method. As highlighted earlier, several researchers have used these techniques to develop simple mathematical models based on Poisson and Erlang distributions to estimate headway parameters for flows at low levels. Complex mathematical headway distribution models such as Lognormal, Pearson Type III and Hyperlang have been employed in parameter estimation of moderate and high traffic flow levels. However, for cases in which the random traffic-based Poisson does not hold or other mathematical headway distributions require great field measurements or do not fit the real-world data closely, researchers are increasingly developing simulation models to analyse and solve complex flow problems in engineering (Agbede, 1995; Kosonen, 1999). Brockfield et al. (2007) reported that simulation models are becoming increasingly important tools in modelling transportation systems. Metcalfe (1997) explained that simulation techniques are useful in complex situations for which appropriate formulae are not known although they are far less convenient than mathematical models. It is also important to apply appropriate and reasonable initial and boundary conditions to the simulation models to ensure reliability of output results (Agbede and Adegbola, 2003)

Lee et al. (2008) developed a simulation tool using stand-alone application which adopts object-oriented approach and JAVA as the main application programming interface (API) to forecast traffic congestion level. Zwahlen et al. (2007) suggested that it would be advantageous to convert hourly traffic counts into corresponding cumulative headway using the least-squares method. They employed this method to generate hyperbolic fit models to approximate headway distributions of free-flowing traffic on Ohio Freeways for work zone traffic simulations.

1.2 Research Problem

In spite of the global economic recess, vehicle ownership is continuing to increase in cities of the world including Nigeria. The consequences of this in Akure , where there is no corresponding sustainable land use patterns and transportation schemes is traffic congestion. Dynamic traffic data capturing and analysis systems are necessary to assist the civil engineers on the improvement schemes to ameliorate the problem. However, the challenges and cost of these systems are enormous for Ondo State and the eleven Local Government Areas constituting the Akure .

Previous studies have shown that several mathematical traffic flow models developed to analyse congestion cannot be easily generalised or adapted to varying roadway, traffic and control conditions. In addition, validation errors of some models are as high as 60.0 %. In pursuit of the objective of minimising traffic congestion in parts of the Akure , headway simulation models were developed for the analysis of flow on some selected highways characterised by heavy traffic.

1.3 Study Area

Nigeria is connected by a network of roads as shown in Fig. 1.1. The two-lane roads form its major component particularly in Ondo State. Akure is the capital of Ondo State, one of the thirty-six states in Nigeria. The metropolitan area of Akure is approximately on Latitudes 7^o 15’and 7^o 30′ North of the Equator; and Longitudes 3^o 45′ and 4^o 00′ East of the Greenwich Meridian (Ayeni, 2002).

The road network connecting the eleven Local Government Areas in the metropolis (Fig. 1.2) is vast and central to the socioeconomic activities of the people. A network of the roads studied (Total Garden-Agodi Gate, J Allen-Oke Bola and Odo Ona-Apata) and some other principal roads in the metropolis are shown in Fig. 1.3.

Two of the roads studied, J Allen-Oke Bola and Odo Ona-Apata are sections of Obafemi Awolowo (formerly Lagos By-pass) and Akure -Abeokuta roads respectively. These roads are under the jurisdiction of the federal government. The Odo Ona-Apata road serves as a link to the Nigerian National Petroleum Corporation

(NNPC) depot in Akure . The road also connects Akure to Abeokuta, the Ogun State capital.

The J Allen-Oke Bola is a link road to the Central Business District (CBD) of the metropolis (Dugbe and environs). The third road, Total Garden-Agodi Gate is under the purview of the Ondo State government. It links some areas in the metropolis with the University Teaching Hospital (UCH) and the Ondo State Secretariat. Traffic streams on J Allen-Oke Bola and Odo Ona-Apata roads are shown in Plates 1.1 and 1.2 respectively.

1.4 Aim and Objectives

The aim of this study is to formulate a rational procedure for minimising highway traffic congestion using germane traffic parameters such as headway and flow.

The objectives of this study are as follows:

To determine the parameters that contribute to congestion of purposively selected roads in Akure .
To develop models for representing and replicating the parameters.
To evolve mechanisms for traffic flow enhancement and congestion reduction on the roads under study.

Fig. 1.1. Nigeria’s road network

Source: GEOATLAS (2011)

Fig. 1.2. Akure metropolitan area’s road network

Source: Ayeni (2002)

Fig. 1.3. Network of some principal roads in Akure

Source: Tele Atlas Africa (2007)

Total Garden-Agodi Gate road

J Allen-Oke Bola road

Odo Ona-Apata road

Plate 1.1. Traffic stream on J Allen-Oke Bola road

(14 January, 2009; before dualisation of the road)

Plate 1.2. Traffic stream on Odo Ona-Apata road

(23 April, 2009; 10:12 a.m.)

1.5 Justification

Traffic congestion is a common feature on highways in many cities of the world including Akure , Nigeria. Previous studies have shown that several mathematical traffic flow models developed to analyse congestion cannot be easily generalised or adapted to varying situations. In addition, validation errors of some models are as high as 60.0 %. There is therefore a need to formulate a rational procedure for minimising highway traffic congestion using germane traffic parameters such as headway and flow. The mechanisms should be able to enhance traffic flow and reduce congestion on the highways under study in Akure , Nigeria. The system should also be replicable and adaptable for efficient and effective management of other highways in many cities of the world.

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THE CONTRIBUTION OF URBANIZATION TO SLUM DEVELOPMENT IN NIGERIA

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THE CONTRIBUTION OF URBANIZATION TO SLUM DEVELOPMENT IN NIGERIA

CHAPTER ONE

INTRODUCTION

Background of the study

necessarily entail analyses concerning those situated on the margins of society and the environment and how to ensure environmental sustain- ability.

Statement of the problem

There may have been previous researches in this subject. This work gives further explanations and analysis in the contribution of urbanization to slum development in Nigeria

Objectives of the study
To understand the contribution of urbanization to slum development in Nigeria
To understand the relationship between the contribution of urbanization and slum development in Nigeria

Research questions
What is the the contribution of urbanization to slum development in Nigeria
What is the relationship between relationship between the contribution of urbanization and slum development in Nigeria

Research hypothesis

H0: There is no relationship between the contribution of urbanization and slum development in Nigeria

H1: There is a relationship between the contribution of urbanization and slum development in Nigeria

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IMPACT OF URBAN ENCROACHMENT ON WETLANDS IN PORTHARCOURT METROPOLIS

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IMPACT OF URBAN ENCROACHMENT ON WETLANDS IN PORTHARCOURT METROPOLIS

CHAPTER ONE

INTRODUCTION

1.1 Background to the Study

Wetlands are defined as areas of marsh, fen, peat land or water, whether natural or artificial, permanent or temporary, with water that is static or flowing, fresh, brackish or salt, including areas of marine water the depth of which at low tide does not exceed six meters (RCS,

2007). In addition, they „may incorporate riparian and coastal zones adjacent to the wetlands, and islands or bodies of marine water deeper than six meters at low tide lying within the wetland (RCS, 2007). Wetland therefore is “an ecosystem that arises when inundation by water produces soils dominated by anaerobic processes, which in turn, forces the biota, particularly rooted plants, to adapt to flooding” (Keddy, 2010). Wetland ecosystems are among the most important in the world, providing a diverse range of ecosystem services vital to human well-being (Barbier et al., 1997; RCS, 2007). They gave rise to the first modern global nature- conservation convention (Matthews, 1993) and remain the only single group of ecosystems with their own International Convention (Turner et al. 2000; Ramsar, 2010).

Globally, wetlands are estimated to cover 5–10% of the earth‟s terrestrial surface (Mitsch and Gosselink, 2007; RCS, 2007), some 1,280 million hectares, although, it is believed that this is an underestimate (MEA 2005). Some estimates put the global loss of wetlands at about 50% (Barbier, 1994; Rijsberman and Silva, 2006; ICSU et al., 2008). However, this is speculative, being based on extrapolation of wetland loss during the twentieth century of some types of wetland in the areas that have been best documented including North America, Europe, Australia and New Zealand (MEA, 2005). Primarily, the factor that distinguishes wetlands from other land forms or other water bodies is the characteristic vegetation that is adapted to its unique soil conditions: wetland ecosystems consist primarily of hydro soil, which supports aquatic plants (Butlers et al, 2010; Ramsar, 2011). The water found in wetlands can be salt water, fresh water, or brackish (Ramsar, 2011). Main wetland types include swamps, marshes, bog and fens (Keddy, 2011). Wetlands can be considered the most biologically diverse of all ecosystems, serving as a home to a wide range of plant and animal life (Ramsar, 2011). Wetlands occur naturally on every continent except Antarctica (USEPA, 2011). They can also be constructed artificially as a water management tool, which may play a role in the developing field of water-sensitive urban design. The largest wetlands in the world include the Amazon River basin and the west Siberian plain (Fraser and Keddy, 2005). The Niger delta is a wetland of about 76,000sq km and has the largest mangrove forest in Africa (11,134 sq km) and the third largest in the world (Spalding et al, 1997).

Wetland ecosystems are part of our natural wealth. At a world wide scale, they provide us with services worth trillions of US dollars every year-entirely free of charge-making a vital contribution to human health and well-being. With the global population set to increase to nine billion by 2050, increasing pressure on water resources and the threats posed by climate change, the need to maximize these benefits has never been greater or more urgent (Ramsar, 2011). Numerous factors contributed to the degradation of natural wetlands in Nigeria especially in the Niger Delta region. The most important among them were land demand by a large population, a lack of understanding of wetland values, a misguided policy, a lack of environmental laws and regulations, and water diversion needed because of rapid economic growth (Ohimain et al., 2002).

Urban development in wetland ecosystems for agriculture, human settlement and industrial development is one of the biggest threats to wetland conservation and management. Management of urban development in wetland ecosystem aims to conserve major services and restore natural resources while meeting the socio-economic, political and cultural needs of current and future generation (Brussard et al., 1998; and Szaro et al., 1999). Urbanization which is the conversion of land into uses associated with growing population and economy has been recognized as having a world – wide trend. More than 50% of the world‟s population currently resides in urban settlements. The shift to urban living is expected to continue at the rates of 1.6% per annum at a global scale. The highest urbanization rates were expected in developing and least developed countries (UN-Habitat, 2010) while 95% of the net increase in global population would be in cities of the developing world (Zhang et al., 2008) of which Port Harcourt is one. As part of this trend, the coastal zones are known to be home to nearly 75% of the global population (Asangwe, 2006).

Urbanization is a major cause of loss of coastal wetlands. Urbanization impacts wetlands in numerous direct and indirect ways. For example, construction reportedly impacts wetlands by causing direct habitat loss, suspended solids additions, hydrologic changes and altered water quality. Indirect impacts include changes in hydrology and sedimentations which substantially alter wetlands. It also exerts significant influences on the structure and function of coastal wetlands, mainly through modifying the hydrological and sedimentation regimes, and the dynamics of nutrients and chemical pollutants (Adedeji et al., 2010). Natural coastal wetlands are characterized by a hydrological regime comprising concentrated flow to estuarine and coastal areas during flood events, and diffused discharge into groundwater and waterways during the non- flood periods.

There has been a renewed focus on the study of urban systems in the last few years, as urbanization remains a major development challenge exerting awesome pressure on social, economic and environmental sustainability (Pickett et al., 2001). Cohen (2004) is of the view that in developing countries, urbanization is associated with natural population growth, rural– urban migration, convergence in rural and urban lifestyles, and the economic and political processes associated with globalization. Though urban areas currently account for about 3% of the Earth‟s surface, the ecological footprint associated with urban expansion has important environmental consequences especially on wetland ecosystems. According to Ehrenfeld and Schneider (1991), wetlands commonly occur in human-dominated landscapes such as agricultural and urban regions. Studies have shown that negative effect on wetland species and ecosystem functioning can be expected in such areas due to human activities (Ehrenfeld, and Schneider, 1991; Morris, 1991).

In the past, wetlands have been regarded as “wasteland”, which harbor disease vectors (Kenyan Wetland Forum, 2013). This has led to large scale drainage and conversion for alternative uses without regard to ecological and socio-economic values. Wetland ecosystem is among the most productive ecosystems due to their functions and attributes (Kenyan, wetland Forum, 2013). Humankind benefits from a multitude of resources and processes that are supplied by wetland ecosystem. Collectively, these benefits are known as “ecosystem services and include products like clean drinking water and processes such as the decomposition of wastes. Scientists and environmentalists have discussed ecosystem services for decades; these services were popularized and their definitions formalized by the UNITED NATION 2005 MILLENNIUM ECOSYTEM ASSESSMENT (M.A.), a four-year intensive study involving more than 1,300 Scientists World- Wide (M.A., 2005). They group ecosystem services into four broad categories. The Millennium Ecosystem Assessment (MA) report (2005), define ecosystem services as benefit people obtain from the ecosystem service and distinguishes four categories of the ecosystem services: they are provisioning service, such as the production of food and water;

“product obtained from ecosystem” are sea food and game, crops, wild food and spices, minerals and diatomite, pharmaceuticals, bio-chemicals and industrial products, energy, hydropower, biomass fuels. Regulating service include the control of climate and disease, “benefits obtained from the regulation of ecosystem processes such as carbon sequestration and climate regulation, waste decomposition and detoxification, purification of water and air, crop pollination, pest and disease control; supporting as in nutrient cycles and seed dispersal that are necessary for the production of all other ecosystem services”, such as nutrient dispersal and cycling, seed dispersal. Non-material benefits people obtain from ecosystem services are spiritual enrichment, cognitive development, reflection, recreation and aesthetic experiences, such as cultural, intellectual and spiritual experiences (including ecotourism and scientific discovery) (M.A., 2005).

Wetland ecosystems are important natural habitat, which must be conserved (Williams, 1990). They are associated with a diverse and complex array of direct and indirect uses. Direct uses include the use of the wetland for water supply and harvesting of wetland products such as fish and plants resources, while indirect benefits are derived from environmental functions such as flood water retention, ground water recharge/discharge, nutrient abatement etc. Human activities in the wetland themselves may be fairly related to alternations; they may also be caused by activities in the wetland watersheds and predominantly by agricultural ones i.e. crop and livestock‟s production (Zalidis et al., 1997). Changes in wetland area may significantly affect the ecosystem processes and services. Concern about changes in the size and quality of many of the world‟s wetlands ecosystem has been growing as more and more wetlands are being converted to agricultural or urban land use and by natural factors like drought (Ringrose et al., 1988; Gerakis and Kalburtji, 1998, Chopra et al., 2001).

Despite their high productivity and provision of many benefits, wetlands ecosystems are still facing serious threats. These include inadequate or inappropriate human activities within the catchments and in the wetlands, lack of coordinated and holistic policy guideline, as well as climate change. The threats have induced changes that eroded the ecological and socio-economic values and services derived from the wetland (Ramsar, 2011). There is therefore an urgent need to efficiently manage urban development in wetland ecosystems to mitigate the threats and ensure ecological sustainability.

Remote Sensing (RS) and Geographic Information System (GIS) are now providing new tools for advanced ecosystem management. The collection of remotely sensed data facilitates the synoptic analyses of Earth – system function, patterning, and change at local, regional and global scales over time; such data also provide an important link between intensive, localized ecological research and regional, national and international conservation and management of biological diversity (Wilkie and Finn, 1996).

Therefore, an attempt will be made in this study to map out the classes of land use/land cover of Port-Harcourt metropolis between 1984 and 2013 with a view to detecting the land consumption rate and the changes that have taken place in these classes, particularly, in the built-up areas and wetlands so as to predict possible changes that will take place in these classes within a period of 29 years using Remote Sensing data.

1.2 Statement of the Research Problem

Man‟s relationship with his environment has always changed with time, depending on his understanding and knowledge of the physical environment. However, the natural environment is generally endowed with a variable quantity of resources within the space. Thus, man has come to regard his environment as a way of housing his needs and therefore, he always seeks a way of extracting the resources within it. Sadly, however, this always leads to the neglect of the environmental sustenance of a number of environmental stresses (Ezeaku et al., 2008; Jimoh et al., 2012).

The Port-Harcourt metropolis is partly situated on a wetland ecosystem. As a result of rapid population growth, urban migration and the failure of successive governments to manage urban growth, the Port Harcourt metropolis has expanded in an unplanned way which has led to acquisition of more lands in the wetland area. Port Harcourt wetland has suffered major encroachment in the recent past. A visit to the wetland reveals a lot of new activities, which signify recent massive encroachment. The activities include; residential and commercial buildings as well as car washing bays, among others. There is a significant reduction in the vegetation cover, and the wetland now experiences more visible instances of flooding than before during heavy rains. All these activities put a lot of pressure on the wetland, affect its ecological function and cause degradation. It is believed that these activities are a consequence of the increasing rate of development and urbanization in the Port Harcourt Metropolis. Though there is insufficient data at the present to link urbanization with encroachment on wetland, the size and biodiversity of unconverted portions of wetlands have drastically diminished, with some areas completely converted. In 2000, it was noted that 13% of the wetlands in Port Harcourt was severely degraded and by 2010, only 3.3% was remaining; even this remnant was being degraded (Nwankwoala, 2012; Wizor, 2012).

This uncontrolled urban expansion in an unsystematic manner has had serious repercussions on the environmental quality of many parts of the metropolis. Brody et al. (2007), submit that rising population density in coastal area is usually associated with greater amounts of impervious surfaces, alteration of watershed, coupled with diminished capacity of these systems to naturally hold surface runoff. Studies suggest that, like in many coastal cities of the world, the precise impacts of these human activities on coastal wetlands are poorly understood (James et al., 2007). In this case, the precise nature of these changes is largely unknown and unreported. Although Odunuga and Oyebande (2007), Taiwo and Areola (2009) have provided useful insight into wetland conversion in parts of the Lagos coastal area, a comprehensive study which assessed quantitatively the spatial changes in the wetlands of Lagos/Lekki Lagoons and their consequences is yet to be reported.

Almost every type of wetland has been studied with satellite imagery. But only few of these studies have been reported in a developing country like Nigeria (Campbell, 1996; Li et al., 2005; Neale et al., 2007; Fabona et al., 2007; Jenson, 2007; De rock et al., 2008; Taiwo et al., 2009; Olaleye et al., 2009; Tijani et al., 2011; Klemas, 2011). In some studies, multi-temporal imageries often aided classification of wetlands as well as their separation from other land cover classes. Included in the types of wetland studied with remote sensing are marshes, swamps, Lagoons, coastal tidal marshes, mangroves and other coastal wetlands, bogs and fens, inland fresh water marshes, forested wetlands or swamps, open water areas, wet meadows and submerged aquatic vegetation (Obiefuna et al., 2013).

Scientific studies fault the use of natural resource management rather than managing whole ecosystem when dealing with a particular resource for human use (Kellert et al., 2000). With the main objective of sustainability for future generations, ecosystems manage strive to balance natural resources exploitation and conservation over a long time (Ascher, 2001). In the last few years, there has been an unprecedented rate of urbanization in the Port-Harcourt metropolis due to the closure of the Western Division of Shell Petroleum Development Company leading to the relocation of their oil facilities to Port-Harcourt and insurgency by the Boko Haram sect in the North. The large influx of industries has led to urban growth and expansion into wetland because of need for land and new housing (Obinna, Owei and Mark, 2010). Port Harcourt which is among the largest cities in Sub-Saharan Africa, is in fact the largest city in the Niger Delta Region. The current demographical estimate (NPC, 2006) of the population of the Port Harcourt urban area (urban agglomeration) is 1, 000, 908, covering an area of approximately 371 square kilometers for a density of 2695 per square km. Indeed, the struggle for land has led to massive destruction of wetland ecosystem for developmental purposes (Obinna, Owei and Mark, 2010). Wetland reclamation, Population increase, industrialization and urbanization resulted in an increased demand for space for housing and other infrastructure. Multinational companies, particularly those in the oil and gas industry, also reclaim wetland for their use (Etuonovbe, 2007).

Port-Harcourt wetlands have been variously affected by conversion to developmental uses such as residential and commercial purposes. This is clearly seen in such areas as Iwofe/UOE, Marine Base, Mgbuoba, Reclamation Road, Rukpokwu, Choba, Rumuokwurushi, Eneka, GRA Phase 1-3, Eagles Island, Elioparanwo and Woji etc. Wetlands along Marine Base and Reclamation Road are mostly devastated and degraded by continuous sand filling and conversion for uses that bring economic as against the idea of conserving the wetlands. The institutional/legal frame works such as the Nigerian urban regional planning law as amended, Decree No. 18 of 1999, FEPA, Decree No.86 of 1992, EIA Act of 1992 and NESREA Act no.25, 2007 have not addressed the issue of urbanization and loss of wetland in the Port-Harcourt metropolis. Hitherto, none of the studies has provided the necessary information needed for urbanization and loss of wetland in Port Harcourt. Therefore, there is need to close this yawning gap which forms the problem of this research. There is also a clear need for further research and improvement on this issue.

1.3 Aim and Objectives of the Study

The aim of this study is to examine urbanization and loss of wetland in Port-Harcourt metropolis. This will be achieved through some objectives, namely to:

Identify types, size and nature of wetland ecosystem in the Port-Harcourt metropolis.
Identify land use and land cover classes in the wetland ecosystem of the Port Harcourt metropolis.
Identify the causes of land use and land cover changes in the wetland ecosystem of the Port Harcourt Metropolis.
Forecast the future pattern of land use and land cover change in the wetland ecosystem of the Port Harcourt metropolis.

1.4 THE STUDY AREA

1.4.1 Location

Geographically, the Port-Harcourt metropolis is positioned between Latitudes 4^◦45^′N,

and 4^◦55^′N and Longitudes 6^◦55^′E and 7^◦ 05^′ E. Port-Harcourt metropolis is located at about 25 km from the Atlantic Ocean and it is situated between the Dockyard Creek/Bonny River and the Amadi Creek (Okoye, 1975; Oyegun and Adeyemo et al., 1999). Port-Harcourt, originally known, as “Igwe-Ocha” was founded in 1913 by the British in an area traditionally inhabited by the Ikwerres. It was named after Lewis Viscount Harcourt, the then Secretary of State of Colonies. The main City of Port Harcourt is the Port-Harcourt City Local Government Area. It serves as the Headquarters of Rivers State (Alagoa and Derefaka, et al., 2002). Today, the PortHarcourt metropolis is made up of two Local Government Areas, namely Port-Harcourt L.G.A and Obio-Akpor LGA (See Figs 1 and 2).

Figure 1: Rivers State Showing Port Harcourt and Obio/Akpor L.GA.

Source: Cartography and GIS, Dept. of Geography and Env. Mgt. UNIPORT (2014).

Figure 2: Port Harcourt Metropolis

Source: Cartography and GIS, Dept of Geography and Env. Mgt. UNIPORT (2014).

1.4.2 Climate

The Port-Harcourt metropolis features within a tropical monsoon climate of transitional zone of Koppen Af climatic types with prolonged and heavy rainy season and very short dry season months in the city. Only the months of December and January truly qualifies as dry season months in the city. The harmattan, which climatically influences many cities in West Africa, is less pronounced in Port-Harcourt. The heaviest precipitation in Port-Harcourt occurs between March and October (Oyegun and Adeyemo et al., 1999). The mean annual rainfall is put at 2,000mm (Ayoade, 1993). The Port-Harcourt metropolis usually has a temporary cessation of rain commonly known as “August Break” (a dry spell) that comes in between the middle of the rainy season. The area has an average monthly temperature above 27⁰C and there is adequate moisture in virtually all the months.

In the city, temperatures are relatively constant (high with a mean maximum of about 34^oC and a mean minimum of about 21⁰C); showing little variation throughout the course of the year,. Relative humidity over Port-Harcourt metropolis is over 80-90% during the rainy season as a result of the prevalence of warm moist air mass and high evaporation from the numerous creeks and rivers during this season. In January, depicting the dry season, relative humidity is reduced considerably to about 50-60% as a result of the impact of the drier tropical continental air mass (Inyang, 1975).

1.4.3 Relief and Drainage

The relief of the area is low-lying and the rivers are influenced by tidal fluctuation. The Port-Harcourt metropolis lies at an average altitude of about 12m above mean sea level. In terms of general surface features, the Port-Harcourt metropolis is very unique. The area falls within the coastal belt dominated by Low-Lying coastal plains which structurally belong to the sedimentary formation of the recent Niger Delta (Umeuduji and Aisuebeogun, 1999). It consists mainly of muddy deposit pushed out of the River Niger into a relatively tide-less salt sea. The PortHarcourt metropolis is drained by many rivers such as, Ntawogba, New Calaber, Amadi creek, Dockyard creek, Dick Fiberesima creek, Isaka River, Mini Apalugo, Elechi creek, Primose River, Mgbuodohia River, etc (See Fig. 3). Izeogu and Aisuebeogun (1989) viewed the beach ridge barrier islands as depositional land forms which receive fine coarse grained sands from the sea with elevation of just about 13m above sea level. Generally, the land surface slopes gently (3^o-5^o on the average) on a NW-SE direction. The Northern Quadrants of the region are characterized by gently rolling plains while swamp tidal basin and flats and sand bars predominate in the southern section of the area. Although the region may be said to be essentially composed of gently rolling coastal plains or lowlands, the composite landform features can be more clearly discerned at the micro-relief level. Areola (1983), describes the drainage of Port-Harcourt as poor, essentially because the streams in the area are south-flowing streams, which are turbid during the wet season as a result of discharge of clay and silt into the drainage channel. In the dry season however, the discharge turbidity is highly reduced. The channels are subject to tidal influences and floods. In places where the mangrove swamp occurs, they are bordered on the land-ward side by firm sedimentary rock of coastal plain formation. The Bonny River begins its flow from the West towards the East before turning sharply to flow down to the South. Smaller rivers drain creeks in the southern part of Diobu (such as the Elechi Creek) as well as creeks which empty into the West-East reach of the Bonny River at its Northern bank. This Creek joins the trunk known as the Primose Creek, which links Bonny River with the New Calabar River (Umeuduji and Aisuebeogun et al., 1999).

Figure 3: Wetland/ Drainage of Port Harcourt Metropolis

Source: Cartography and GIS, Dept of Geography and Env. Mgt., UNIPORT (2014)

The Abonnema River drains the Southern part of Diobu. Surface run-off from Rumuigbo area mainly empties into Mini Apalugbo stream, which flows Northeast-wards before joining the Woji River, which itself flows South-Easterly to Trans-Amadi industrial area, and then into the mangrove swamps near the Port Harcourt Zoological Garden. Virtually the whole of Rainbow Town which is drained by Elekahia River flows into Amadi Creek. Amadi Creek is also joined at the Western flank by the Ntawogba River which has a lengthy course of up to 9 km and virtually divides Port Harcourt built-up areas into two portions. The Ntawogba River drains Rumuokwuta, Ikwerre road, G.R.A. Phase I, II, III and IV and Amadi flats. With the Bonny River to the West and Amadi Creek to the East, Dockyard lies to the south of Port Harcourt Township and Borikiri; an area where it makes a unique network with swamps and several creeks including Isaka River and Dick Fiberesima Creek (Umeuduji and Aisuebeogun, 1999, Chiadikobi et al., 2011). A close observation of the rivers and creeks in Port Harcourt and the surrounding area shows that the network pattern created does not easily fit the convectional, typical dendritic and trellised pattern of drainage. The entire area is criss-crossed by several rivers and creeks which empty into the Atlantic Ocean (Chiadikobi et al., 2011).

1.4.4 Soil and Vegetation.

The Port-Harcourt metropolis consists of Deltaic plain soils which are found in wetland and upland areas. The remnant wetland deltaic plain soil has sand (75%) with low clay content which increases down the subsoil. Surface soil colors are brown or very dark grayish brown. Surface soils are well drained having no mottles. The soils are strongly acid (pH 4.5). But acidity decreases down the profile. Organic matter content is low (2.5%). The carbon to nitrogen ratio is fairly high (Ayolagha and Onuegbu, 2001). Ofomata (1975) describes the soil of Part-Harcourt as being ferrallic soil which is rich in iron, but has low mineral reserve and therefore low fertility. He further attributes this to latitudinal location of the area that leads to heavy rainfall, which leaches the soil. The vegetation of the Port-Harcourt metropolis according to Udo (1981) is made up of equatorial rainforest. The vegetation could be subdivided into two major groups; the tropical rainforest and swamp forest (which is further sub-divided into fresh and mangrove swamps).

However, the tropical forest and swamp forest characteristics have been lost to continuous agriculture and urbanization in such a way that the few patches that remain are found in shrines. The dominant plant species found in this area include; Elaeis guineensis (oil palm tree), Rhizophora racemoasa (Red mangrove) Dacroydes edulis (African pear),Psidium guajava (Guava), Mangifera indica (Mango), Lophira alata, Gmelina arborea (Gmelina tree), Avicennia africana, R. mangle, R. harrisonia, Avicenia gerninas, Laguncularia recemosa, Nypa fruticus, Acrosticulum aureum and Paspalim vaginatum (NDES, 1997, Phil-Eze, 2001).

1.4.5 Population

The population of Port-Harcourt city (within its municipal boundaries) has grown from 7,000 residents in 1921 to more than 538,558 in 2006. According to the 1963 National population census results, Port-Harcourt had a population of 179, 563 persons (Ogionwo, 1979). With increase in the number of residents, the 1991 National population census results showed that Port-Harcourt and Obio-Akpor LGAs had a population of 703, 416 persons (Akpoghomeh, 2001). However, in 2006, the population of thee Port Harcourt Metropolis grew to 1, 000, 908 persons (National population Commission, 2006) with Obio-Akpor LGA having 462,350 persons while Port Harcourt LGA had 538,558 persons (NPC, 2006). This present figures of the two Local Government Areas gave the cumulative population density of the study area to be 2695per square kilometers.

1.4.6 Economic Activities

The Port-Harcourt metropolis is the capital city and economic hub of Rivers State. PortHarcourt has long been an important merchant port and, today, it is the centre of Nigerian‟s Oil Industry (NDES, 2000). Its major exports include petroleum and oil palm products. The city is a major industrial centre as it has a large number of multinational companies as well as other industrial concerns, particularly businesses related to the petroleum industry. It is the chief oilrefining city in Nigeria, oil being one of Nigeria‟s most important commodities and the main foreign exchange earner. The seaport and railway attracted government institutions, foreign enterprises, works and business men from other parts of Nigeria and West Africa. Most economic activities in Rivers State are based in the Port-Harcourt metropolis and these are mostly concentrated in Trans-Amadi Industrial Layout, Diobu axis, Port-Harcourt Township, Rumuola, Rumuokwuta, Mgbuoba, Choba, Rumuokoro, Rumuodora and Aba Road. High profile industries exist in the area. Industries in the industrial layout are chiefly those that have interest in; pharmaceuticals, tyre, textiles, fertilizers, petro-chemicals, food processing, cement, construction and printing. There are also agro-allied industries as well as financial institutions. The expansion of industrial and commercial activities during the consolidation period of 19251944 is what led to the creation of this industrial area (Chikezie, 1984); and increase in economic activities naturally serves as a trigger for population growth and urban development.

1.5 Literature Review

Through large-scale manipulation of the environment and management of wetland, the resultant urbanization heralded important new discoveries in sciences such as medicine, chemistry, astronomy and mathematics, and a bloom of creativity in arts, literature and craftwork. These advances established the foundation upon which the civilized world, some five millennia later, forged a turbulent symbiotic marriage between humans and wetland – a marriage that persists up to to the present day (Mclnnes, 2008). The balance of the global population has shifted since Sumerians first tried to master the Tigris and Euphrates. For almost 5,000 years, humans remained predominantly rural. However, since the mid-2000s, more than half of the world‟s population has been residing in the urban environment (UN, 2009). This trend is predicted to continue at an average global annual growth rate of approximately 1.6 % – the rate of growth varies between developed and developing nations.

Looking at the rate at which urban population has increased in more developed countries, we can predict a reduction over the next 40 years; with mean annual growth rates of less than 0.4% predicted for the periods 2010-2050. The predicted most rapid increase is across the least developed countries with mean annual growth rates of more than 3.7% predicted for the period 2010-2050 (UN, 2009). The urban population growth rate for the less developed nations, such as Brazil, South Africa, China and India, is closer to the global average with a predicted rate of 2.0% expected between 2010 and 2050 (UN, 2009). Cities can be a driving force for social and economic development. They have the ability to focus tremendous energy and to generate significant creative economic betterment. They offer shelter, jobs and services and provide a nexus of productivity. Consequently, cities act as a magnet for human population, attracting more and more people and generating an ever increasing proportion of Gross Domestic Product (GDP). Whilst this demographic shift is significant, the demand on natural resource consumption and use to sustain urban populations is ever greater (Faulkner, 2004).

Comparisons between the demands humankind places on nature and the biosphere‟s ability to regenerate resources and provide services have demonstrated that the global average demand on biologically productive land equals 2.2 hectares per person versus an available 1.8 hectares per person (Wackernagel et al., 2006). This measure of human demand on earth‟s ecosystems has been referred to as the „ecological footprint‟ (Rees, 1992). A study of the ecological footprint of Vancouver, Canada, demonstrated that the city required an area some 200 times larger than its actual geographic area to support its population (Rees and Wackernagel, 1996). A more extreme picture emerges for London. The ecological footprint of Londoners has been estimated at 49 million hectares, which is 293 times its geographical area. This is approximately twice the size of the UK, and roughly the same size as Spain (BFF, 2002).

The hypothesis that urbanization can have direct and indirect impacts on the environment and that wetlands are particularly susceptible to negative change, has long been proven (Darnell, 1976; Maltby, 1986). Despite this, however, the march of urbanization continues to degrade and destroy natural capital. For example, Lagos, currently the fifth largest city in the world, is the largest manufacturing and port city in West Africa, and a focal point for business and economic development in Nigeria. Metropolitan Lagos is situated on a narrow lowland coastal area which originally supported mangrove swamps. To facilitate city development, rapid and unplanned land reclamation has been achieved by infilling coastal swamps and floodplains (Adelekan, 2009). Not only has this impacted directly on wetland biodiversity, but the destruction of mangroves and wetland has also reduced the flood storage capacity of the land, resulting in increased flooding.

McGranahan et al. (2007) notes that while economic activity and urban development often increase the environmental pressures that lead to flooding, it is usually the low income settlements and poorest groups within urban settlements that tend to be most vulnerable. Ramsar, (2010) is of the opinion that there are many organizations currently active in the fields of urban development, planning, management, protection, restoration, enhancement of wetland and their biodiversity. These include the UN-Habitat and the Ramsar Convention. Many of these organizations are implementing joined up initiatives which are benefiting people and biodiversity (Ramsar, 2010; UN-Habitat, 2010)

The astronomical growth of urban centers in the developing counties, the rapid rate of rural-urban migration, urban poverty, urban environmental deterioration, high unemployment rate, decreasing standard of urban dwellers and other negative scenarios have engendered urban planning (Adeyemo, 2004). As the United Nations Centers for Human Settlement (UNCHS) 1987 has noted, from 1950-1970, the total population of the developing countries increased by 151%. From 1970-1990, the population of the cities in developing countries not only doubled again but the proportion living in the cities of a million or more increased from about 30% to about 40%.

As Brain (1973) observes, “rapid urbanization has not been accompanied by a rise in economic development, as was the case in Europe and North America, and instead has been associated with unemployment, low level of life expectancy, poor nutritional status, and low levels of education”. In the same vein, World Bank (1988) ascertains that urban development in developing countries leads to infrastructural development; “despite heavy subsidies, many urban services are underprovided, 23% of urban population in developing world has no potable water within 200 meters; road congestion is spreading and escalating, transport costs have reduced productivity, housing shortages are common in many cities that resulted in degradation of wetland ecosystem”. The above scenarios show that cities in the developing countries should be managed, planned and renewed to make systems functional.

The concentrations of human and economic activities in few urban centers have drastically altered the ecology or ecosystem of the urban centers. The growth and development of ghettos/slums, widespread solid garbage, air/water pollution and reduction of recreational open spaces are consequences of human activities and over-urbanization. Urbanization affects the structure and function of natural systems both directly, through converting the land surface; and indirectly, by modifying energy flows and the availability of nutrients and water. Urban ecological studies have shown that the number of native plant and animal species occurring in isolated patches decreases as the patch size decreases. The effect of the patch size on native species is a direct effect of habitat loss (George, 2002). Urban growth and land conversion due to human activities such as housing development, development of industrial estates, manufacturing activities and intra-city road network development are major threats to wetland ecosystem. These activities have seriously altered the urban ecosystem to the detriment of human health in the Port Harcourt Metropolis (Adeyemo, 2004).

The urban fabric of the Port Harcourt metropolis has undergone dramatic changes during the last decades. From a colonial city clearly delineated in its historic boundaries, Port Harcourt has grown and continues to grow into the surrounding landscape, swallowing even more villages, coastlines, and previously unspoiled landscape, transforming into an ever increasing urban conglomerate. After the 1980s, multi-center development of cities and its catalytic impact on reshaping of the economic landscape in metropolitan areas has drawn much attention (Hackworth, 2005). During the last quarter of the twentieth century, Port Harcourt experienced tremendous structural transformation due to population and economic growth, the development of its transportation and communication systems and the impact of globalization (Obinna, Owei and Okwakpam, 2010). Like many cities in Nigeria, Port Harcourt has recorded a rapid growth in population and aerial spread. From an estimated population of 500 in 1915 it grew to 30, 200 in 1944. By 1963, its population was 179, 563 and by 1973 it has reached 231, 532 persons. The

Port Harcourt municipality‟s population was given as 440,399 by the 1991 national census (Okoye, 1975; Ogionwo, 1979; Alagoa and Derefaka, 2001). The 2006 national census showed this population had reached more than a million (Obinna, Owei and Mark, 2010). In terms of its physical size, the city grew from 15.54 sq. km in 1914, to a metropolis covering an area of 360 sq. kilometers in the 1980s. Urban development is denser on the corridors determined by geographic thresholds and major transportation connections.

As a result of population increase and economic growth, Port Harcourt spreads to the periphery as in the other metropolitan cities. However, this decentralization is not realized with an integral and regional planning but with patchwork of partial plans. This causes negative effects on urban environment; forests, fertile agricultural land, wetlands and cultural values are threatened. This kind of sprawling process creates a settlement pattern that increases the costs of infrastructure. Residential development dynamics of Port Harcourt has been very rapid (Wizor, 2012): physical spread has occurred in both a south – easterly direction and a northerly direction. To the south, growth was through marshland colonization in squatter settlements locally called

“waterfronts”. In the last few years, settlements in these waterfronts have been demolished by the Rivers State Government. Growth has also occurred in north – westerly and north – easterly direction through the entrapment of indigenous enclaves of semi – rural and rural communities within the built – up area of the city.

The Port Harcourt urban fringe currently stretches to Iriebe, Eleme, Elelenwo, Rukpokwu Igwuruta, Omagwa, Aluu, Woji, Choba, Rumokwurusi and Onne (Wizor, 2012). Much of this growth is unplanned and unregulated (Owei, Ede, Obinna and Akarolo, 2008). As part of its efforts to manage the city‟s growth, the Rivers State Government in 2009 established the Greater Port Harcourt City Development Authority with jurisdiction covering Port Harcourt city and Obio Akpor Local Government Areas (LGA) and parts of eight other local government areas. It covers an area of approximately 1, 900 square kilometers (40, 000 hectares of land) with a projected population of about two (2) million people (GIBB, 2009). Rapid urban development and increasing land use changes due to increasing population and economic growth is being witnessed in Port Harcourt and cities in other developing countries. The measurement and monitoring of these land use changes are crucial to understand urban development dynamics over different spatial and temporal scales. Today, with rapid urbanization, there is increasing pressure on land particularly in the metropolitan cities. The cities are expanding in all directions resulting in large scale urban sprawl and changes in urban land use. The spatial pattern of such changes is more clearly noticed on the urban fringes or city peripheral areas than in the city centre. This has made the fringe area of the city to be the most dynamic landscape (Kirk, 2003). After a study in Delhi, India, Kumar, Love, Sharma and Rabu (2003) conclude that pressure for conversion of wetlands for developmental purposes is very high especially in the case of urban riparian wetlands. These wetland ecosystems provide many tangible and intangible benefits on a sustainable basis not only to the urban society but also to the associated dependent ecosystem. Wetland areas on the fringes of river channels in a city are looked upon as a precious property resource with different potential land uses such as agriculture, site for human settlements, industries, civic construction and waste dumping sites, to mention but few. All the literature sited above show that economic activities such as grazing and draining wetlands for agricultural purposes have great effect on wetland ecosystems. Port-Harcourt wetlands have been variously affected by conversion to developmental uses such as residential and commercial purposes.

UN-Habitat (2010) reports that, rapid urbanization and urban areas are known to generate negative impacts on the environment as they lead to change in landscapes patterns, ecosystem functions and their capacity to perform functions in support of human populations. This is especially so when rapid or unplanned growth occurs in an area of highly vulnerable systems such as wetlands. Also, Odunuga and Oyebande (2007) note that the conversion of large tracts of wetlands into built-up areas results in increased impervious surfaces which can lead to flooding and altered aquifer recharge. Flores, Olivas and Chavez, (2008) asserted that quantifying such changes in the landscape patterns can be useful in tracking the capacity of natural ecosystems to render services in support of human systems.

Olarewaju et al. (2011) have studied the benefit of selected wetlands in south western Nigeria and concluded that wetland benefits are low in the area of ecosystem balancing. Balkare et al. (2011) study of wetland ecology in Ijebu-Ode, South West Nigeria showed a wetland loss of 1.04 km² between 1985 and 2007 with a perimeter of 11.56 km² in 1985; the perimeter was 17.4 km² and the wetland covered area was 1.38km². This indicates that about 0.34km of the wetland areas has been lost to different uses such as construction between the year 1985 and 2007. A further analysis indicated that over a period of 12 years, wetland reduced in Ijebu-Ode at 0.02km annually. Orimoogunje et al. (2009) in their study of wetlands in Ilesha in Osun State through field mapping, reveal that between 1986 and 1991, the total land area for wetland decreased from 258 hectares to 148 hectares, there was further decrease of wetland areas as at 2002 to 89 hectares while other land uses such as agricultural activities and settlement within this period increased. The authors attribute this to increase in population and developmental processes in Ilesha. The authors also note that the usage of the wetland area is for settlement and infrastructural development. Based on Orimoogunje et al. (2009), the alarming rate at which the Nigeria‟s wetland is vanishing obviously portends some dire consequences. The authors are of the opinion that wetlands destruction has greater consequences on water supply and water resources management in various part of the country. This is to say that, wetland loss and degradation increase the challenges of water resources management.

Hopkinson and Day (1980) predict that an urban area bordering a swamp forest would increase runoff volumes by 4.2 times. Stockdale (1991) suggests that greater surface runoff is also to increase velocities of flow to wetlands, which disturb wetlands biota and scour wetland substrates. USEPA (1993) states that increased amount of storm water runoff in wetland alters water level response times, depths, and duration of water detention. Reduction of watershed infiltration capacity is likely to make wetland water depths rise more rapidly following a storm event (Ajibola et al., 2012). Azous (1991) buttresses that diminished infiltration in wetland watersheds can also reduce stream base flows and ground water supplies to wetlands, lengthening dry periods and impacting species dependent on the water column. All these are glaring effect which urbanization in Port-Harcourt has on the wetlands. In the past few years, the rate of water run- off within the metropolis has increased to an alarming rate. Even a slight rain now has devastating effects in the metropolis due to high rate at which wetland ecosystems are still being converted into economic uses. Impact on wetland hydrology and water quality can, in turn, affect wetland vegetation. Horner (1989) states that emergent zones in Pacific Northwest wetlands receiving urban runoff are dominated by an opportunistic grass species, Phalaris arundinaceous, while non-impacted wetlands contain more diverse groupings of species. There have been numerous reports on the tolerance to flooding of wetland and non-wetland trees and plants (US EPA, 1993). Uluocha and Okeke, 2004; Ofodile, 2006; Tijani, 2006; Nwankwoala, 2011, are of the view that Nigeria is naturally endowed with abundant surface and ground water resources, but the water supply situation in the country for various uses remain far below expectation. In the same vein, Uluocha and Okeke (2004) submit that a major factor aggravating the problem of water management in the country is the fact that wetlands, which naturally recharge and protect both the surface and ground water resources, are being unscrupulously degraded at a rather alarming rate.

Fabona, Omojola and Onyeahialam (2007) are of the view that the integration of remote sensing and GIS has made possible the systematic inventory and assessment of land resource and land degradation over space and time for intervention strategies to be instituted to safeguard the health of the ecosystem. Also, integrating temporal satellite data GIS and historic maps facilitates effective monitoring tools for land usage as they provide a firm portrayal of growth patterns and how development results in profound changes to the landscape (Olaleye, Abiodun and Igbokwe, 2009). Remote sensing has been widely used to observe and record the earth‟s land and water surfaces through the means of reflected or emitted electro- magnetic energy (Jensen, 2007; Campbell, 1996). Recent advances in sensor design and data analysis are making remote sensing very practical and attractive for monitoring natural and anthropogenic wetland changes (Klemas, 2011).

Some of the recent studies to identity or monitor wetlands and their changes with remote sensing and GIS, involve the assessment of the extent and changes in the mangrove ecosystem of Niger Delta (James et al., 2007); monitoring of land degradation along Ondo coastal zone of Nigeria (Abbas, 2008); the monitoring of wetlands in the semi-arid west, USA (Neale et al.,

2007); the mapping of Canada‟s wetland with optical, radar and DEM data (Li and Chen, 2005); the inventory monitoring of temporary and permanent wetlands of western Cape, South Africa (De Roeck et al., 2008) and the spatial-temporal analysis of wetland losses in the Lagos coastal region (Taiwo and Areola, 2009). Tijani et al. (2011) in their study of Eleyele Wetland in Ibadan through GIS based assessment revealed a reduction in the riparian wetland forest of 1.25km² as at 1984 to 0.70km² by 2004 with a projected decline of 0.42km² by 2014. One could infer from the different empirical studies as highlighted above, that there is an enormous negative impact of the human induced influence on the wetland ecosystem through urban development activities, therefore, depriving human and aquatic lives the benefits of wetlands.

Land Use Land Cover (LULC) in urbanized areas is often a mosaic of human induced land uses; infrastructure (roads, bridges, and railways), built-up area, agricultural land, drainage/ water-bodies, waste land, etc. Therefore, conventional ground methods of land use mapping become labor intensive and time consuming. These maps soon become outdated with the passage of time, particularly in a rapidly changing environment. In fact, according to Olorunfemi (1983), monitoring changes and time series analysis is quite difficult with traditional method of surveying. In the last three decades there are large numbers of studies carried out on LULC change. Many authors have convincingly argued that LULC change in urbanized area is different from that of non-urbanized area (Cohen, 2006). Urbanized areas are predominantly covered with impervious area or built- up area with scattered & fragmented natural area. Emergence of low cost satellite imageries from Global Land Cover Facility mapping (GLCF, http://glcfapp.umiacs.umd.edu: 8080/esdi/index.jsp) has now made it possible to study the historical LULC data and monitor changes at regular intervals of time. Ever since the launch of the first remote sensing satellite (Landsat-1) in 1972, LULC studies were carried out on different scales for different users. Xiaomei Y et al. (1999) note that information about change is necessary for updating land cover maps and the management of natural resources.

Hence by using the historical/multi-temporal data and with the help of GIS functionalities we can now access and evaluate the land use/land cover change of an area over a given period of time. This is what is called change detection technique. Change detection technique has proved to be of immense use in studying the processes of urbanization and spatial growth of urban features. Interestingly, Singh (1989) defines change detection technique as a process of identifying differences in the state of an object or phenomenon by observing it at different times. Besides it is an important process in monitoring and managing natural resources and urban development because it provides quantitative analysis of spatial land cover and land use. Macleod and Cognation (1998) list four aspects of change detection: i) Detecting the changes that have occurred, ii) identifying the nature of the change, iii) measuring the area extent of the change, and iv) assessing the spatial pattern of the change. Therefore, data on land use change are of great importance to planners and environmentalists in monitoring the environmental consequences of land use change. Such data and techniques are of value to resources management and agencies that plan and assess land use patterns and in modeling and predicting future changes. In this study, change detection technique has also been used to assess the LULC change in Delhi.

LULC has become a widely studied phenomenon in landscape ecology, climate change, earth science and ecology. Therefore, directly or indirectly, LULC change affects the climate, geology and environmental process. One of the first exercises carried out in land use land cover change in NCR was that by CISMHE (1993) which was perhaps a maiden attempt to record the land use change over the three decades of urbanization and its impact on Delhi‟s environmental resource base. The study also made some important recommendations to the Central Ministry of Environment & Forests, Government of India. Pandy and Nathawat (2006) carried out a study on land use land cover mapping of Panchkula, Ambala and Yamunanger districts of Haryana state in India. They observed that the heterogeneous climate and physiographic conditions in these districts have resulted in the development of different land use land cover. A maiden study on Himalayan land use land cover was carried out recently by Pandit et al., (2007) wherein the authors highlighted the extensive deforestation in the region with serious consequences on native biodiversity.

Beside there is a large number of studies carried out in developing countries on LULC mappings and change. Moreover, the studies related to urbanization in the least developed countries are significantly increasing over the last decade. Most of the techniques and methods used are conventional ground mapping, GIS and remote sensing technique and survey methods (Taubenbock et al., 2009). It is also true in the case of India which has had a large number of studies conducted on urbanization and LULC change in the last decade. Literature review on LULC change and urbanization in India has resulted in 35 published scientific papers: most of these studies have been carried out using remote sensing technology. A comprehensive study on LULC change and urbanization in India was carried out by Taubenböck et al., (2009). This study was carried out in 12 major cities, namely: i) Mega cities like Mumbai, Kolkata and Delhi, ii) incipient mega cities including Hyderabad, Bengaluru, Ahmadabad, Chennai, and iii) urban agglomeration comprising Pune, Jaipur, Kanpur, Surat and Lucknow. These authors used remote sensing technology and change detection technique. They assessed the similarities and difference between spatial growth patterns in the 12 cities. Besides, they quantified the spatio-temporal growth pattern and found that incipient mega cities are mimicking the spatial growth pattern of mega cities.

Furthermore, a detailed literature survey on LULC change in Delhi was carried out simultaneously and more precisely by Wentz et al. (2007). These authors conducted a study on urban LULC change of Delhi and later a comparative study with Phoenix Arizona, USA, was carried out. They used an expert system transferability model developed by Stefanov and Netzband (2005) for Phoenix. Expert system transferability model is based on the spectral Signatures of remotely sensed data. However, they failed to address the LULC change and they lacked the spatio-temporal data for the study. In another study Rahman et al. (2011) carried out a detail study of LULC change in the eastern district of Delhi. However, they failed to address the issue over the entire study area. Moreover, the study was focused on the quality of urban environment. They assessed the urban environmental quality with built-up area, open spaces, household density, occupancy ratio, population density, accessibility to roads, noise and smell affected area. The study shows that the urban environment has been largely degraded when compared from 1982 to 2003. Therefore, the study covered the entire Delhi and the LULC change will be studied for three different time periods (1987, 1999 & 2006), using the GIS and remote sensing technology.

In their studies, Wright et al. (2006) highlighted a number of tools towards wetland management and protection. These are, land use planning, land conservation, aquatic buffer, better site design, erosion and sediment control, storm water treatment, non-storm water discharges and watershed stewardship. These strategies are all encompassing. In an urban development through land use planning, aquatic buffer and better site design all help to ensure that urban development does not erode wetland areas. Also, erosion and sediment control through buffer construction in and around wetland will help to reduce the occurrence of encroachment on wetland site; however, beyond physical barriers there is need to ensure strict implementation of the process and ensure that defaulters are punished. Most times the government itself is guilty, as seen in various land reclamation activities in Port Harcourt embarked on by the Rivers State government. Effective wetlands ecosystem management requires reliable information on rate, quality and quantity of available wetlands (Akinpeju, 2012). Springate and Baginski et al. (2009) are of the opinion that there is need to involve the stakeholders at different levels to appreciate the importance of wetlands to ecological system. This measure will enhance awareness on wetlands and further increase the appreciation we have on wetland benefits.

From the literature reviewed, no work was done using remote sensing techniques to examine urbanization and loss of wetland in Port-Harcourt metropolis. Thus, this study is set to fill this gap in literature.

1.6 Conceptual/Theoretical Framework

In this research, a numbers of concepts and theories related to the urbanization and wetland will guide us. This concepts and theories are those that will enable us to achieve the aims and objectives set out in this research.

Conceptual Framework

1.6.1 Concept of Urbanization

Urbanization, simply defined, is the shift from a rural to urban society, and involves an increase in the number of people in the urban area during a particular year (World Bank, 1990). Urbanization is the outcome of social, economic and political developments that lead to urban concentration and growth of large cities, changes in the land use and transformation from rural to metropolitan pattern of organization and governance (World Bank, 1990; Angotti, 1993). In a generic sense, urbanization appeared with the first permanent human settlement 8,000 years ago. Since then, urban development has occurred all across the world, although at different times and in different ways depending on the location.

Urbanization occurs in three broad stages. First, there is an early period when improvement in agriculture lead to population growth and more densely populated settlements (Menezes, 2001; Almeida, 2001). However, urbanization emerged with the industrial revolution, particularly in the developed countries which became industrialized first. Only in the second half of the twentieth century, after the Second World War, were developing countries exposed to urbanization, but this has intensified over the last 40 years.

In 1960, one third of the world‟s population lived in the cities. Now-a-days, almost half of the planet‟s population concentrates in the cities and, by 2030, residents of urban areas will represent more than 60% of total world population. Forecasts indicate that 2007 will be the turning point. From then on, more people will be living in the cities than in rural areas in the world. Most of the urban population growth will take place in poorer countries and will involve poor people moving into the cities, looking for the opportunities they do not have in rural area (Almeida, 2000). The population of the cities in developing countries has almost doubled since 1960, going from 22% to 40% of the total. At the same time, urban population percentage increases in developed countries was only from 61% to 76 % (Menezes, 2001).

1.6.2 Concept of Sustainable Development

The Concept of Sustainable Development is applied to this study. The concept of sustainable development was propounded by the World Commission on Environment and Development (WCED) in 1987. Development involves the purposeful change of the inherently complex environmental systems. The natural resources (agricultural products, climatic factors, mineral resources) are consumed and multi-purpose in terms of their social and economic roles. The anthropogenic resources system (infrastructural facilities) is used to enhance improvement in the standard of living of the people. Consequently, the effects of bad management are often wide spread both geographically and socially (Birch, 1973). From the foregoing, it is crystal clear that agricultural activities, environmental factors, human needs and infrastructural facilities are independent. A system analysis or assessment of the total environment and basic socioamenities should be part of the overall planning process. In making developmental decisions to maintain or improve environmental quality, sustainable provision of basic socio-amenities and food security should be given sufficient weight. This is the basis of the concept of sustainable development, an idea first proposed in the eighties by the World Commission on Environment and Development (Railwani and Osayande, 2003).

Again, Sustainable urban development is an offshoot of sustainable development. It thus implies that the present generation embarks on development with the consciousness of the implication of their development efforts. The concept of sustainable development thus incorporates concerns for the environment at the inception of development activity (Akinpeju, 2012). Sustainable development is a development that meets the needs of the present without compromising the ability of future generations to meet their needs (WCED, 1987). The primary objective of sustainable development is to reduce the absolute poverty of the world‟s poor through providing lasting and secure livelihoods that minimize resource depletion, environmental degradation, cultural disruption and social instability (World Commission on Environment and Development, 1987). The earth summit (UNCED), which recognized the pressing environment and development problems of the world, and through the adoption of agenda 21, produced a global program of action for sustainable development in the 21st century. Agenda 21 stresses the importance of partnership in improving social, economic and environmental quality in urban areas. It suggests renewed focus on effective land use planning to include adequate environmental infrastructure, water, sanitation, drainage, wetland transportation and solid waste management, in addition to a sound social infrastructure capable of alleviating hunger (Afonja, 1999). Hence, sustainable urban development entails engaging in urban physical development with adequate considerations given to the implication of such development on ecosystem. Nigeria is blessed with a variety of environmental resources among which is wetlands; however, to better enjoy the benefits derived from these resources, there is need for better management and effective policy framework.

1.6.3 The Concept of Wise Use in Wetland Ecosystem

The concept of the wise use of wetlands has been even more of a focal issue to the Ramsar Convention since the Wise Use Working Group began its work in 1988. Much work has subsequently been done throughout the world on the wise use of natural resources. The present publication reflects part of this work which, thanks to a number of international organizations such as IUCN and the World Conservation Union (and in particular the IUCN Wetlands Program), has permitted a clearer understanding of the sense and strengths of the concept, which will prove helpful in conserving wetlands (RCB,1990; Davis, 1993).

According to the guidelines adopted in Montreux 22, November 1990 and published as the Annex to recommendation REC C.4.10, wise use of wetlands involves the establishment of national wetland policies. Whether or not national wetland policies are being prepared, priority actions at national level and at particular wetland sites should be defined. The principal elements of national wetland policies may be grouped in the following sections (RCB, 1990).

Improvement of institutional arrangements so that wetland policies can be fully integrated into the planning process; and the establishment of mechanisms and procedures for incorporating this integrated, multi-disciplinary approach into planning and execution of projects concerning wetlands.
Review of existing legislation and government policies (including subsidies and incentives), application of existing legislation and policies, adoption of new ones and use of development funds for wetlands.
Increasing knowledge and awareness of wetlands and their values, including exchange of information, propagation of their benefits and values (a statement of which is given), review of traditional techniques and training of appropriate staff.
Review of the status of wetlands in the national context, including compilation of a national inventory and definition of each wetland’s particular values and conservation

priorities.

Addressing of problems at particular wetland sites, by integrating environmental considerations into their management, regulated utilization, establishment of management plans, designation as appropriate for the Ramsar List, establishment of nature reserves and, if necessary, restoration.

Defining a national wetland policy is often a very long process, and governments may wish to promote priority aspects of the wise use of wetlands before the actual adoption of a comprehensive policy. In this context, they need to identify short-term priority actions to be taken at national level, as well as priority actions at specific sites (RCB, 1990; Davis, 1993).

The convention on wetlands came into force in Nigeria on 2 February, 2001. Nigeria presently has 11 sites designated as wetlands of International Importance, with a surface area of 1,076, 728 hectares. Wetlands are also used extensively for recreational aesthetic and educational purpose. All over the world, wetlands are used as recreational sites in various ways – boating, picnics, yachting, fishing festival, boat regatta etc (Chidi & Ominigbo, 2009; Asibor, 2009; Chidi & Erhabor, 2009).

Nigeria is richly endowed with abundant wetlands ecosystem, the majority of which are found in the Niger, Benue and Chad basins. Wetlands represent 2.6% of the country‟s area of about 923,768km². The Niger Delta is one of the most important wetlands in Nigeria, the largest in Africa and third largest area in the world.

Oyebande, et al. (2003) and Asibor, (2009), identify fourteen (14) major wetland belts in Nigeria. These includes: Sokoto-Rima, Komadugu Yobe, Lake Chad, Upper Niger and Kainji lake, Middle Niger – Lokoja – Jebba – Lower Kaduna, Lower Benue – Makurdi, Cross River,

Lower Niger, Niger Delta, Benin – Owena and Okomu, Lagos Lagoon and Lekki Peninsula, Lower Ogun River, Ologe Lagoon, Badagry and Yewa Creeks and the transboundary wetlands of the Upper Benue. Despite the existence of many important wetlands in Nigeria, most of them are not well documented and gazetted (Chidi & Ominigbo, 2010). For example, in the entire country, only eleven (11) wetland sites are recognized as Ramsar sites, both inland and coastal

(Asibor, 2009). Even the Niger Delta, Nigeria‟s largest and richest biodiversity region, is yet to be recognized (Table 1) and gazetted as Ramsar site (Chidi & Erhabor, 2009; Nwakwola, 2012).

Table 1: Nigeria’s 11 Ramsar Sites (1, 076, 728 hectares)

S/N	Site	Date of Designation	State (s)	Area (ha)	Coordinates
1	Nguru lake (and Marma Channel) complex	02/10/2000	Jigawa & Yobe	58, 100	10⁰22′ N 012⁰46′ E
2	Apoi Creek Forests	30/04/2008	Bayelsa	29, 213	05⁰47′ N 004⁰42′ E
3	Baturiya Wetlands	30/04/2008	Kano	101, 095	12⁰31′ N 010⁰29′ E
4	Dangona Sanctuary Lake	30/04/2008	Yobe	344	12⁰48′ N 010⁰44′ E
5	Foge Islands	30/04/2008	Kebbi & Niger	4, 229	10⁰30′ N 004⁰33′ E
6	Lake Chad Wetland	30/04/2008	Borno	607, 354	13⁰04′ N 013⁰ 48′ E
7	Lower Kaduna-Middle Niger Floodplain	30/04/2008	Kwara & Niger	229, 054	08⁰ 51′ N 005⁰45′ E
8	Maladumba Lake	30/04/2008	Bauchi	1, 860	10⁰24′ N 009⁰ 51′ E
9	Oguta Lake	30/04/2008	Imo	572	05⁰42′ N 006⁰ 47′ E
10	Pandam & Wase Lake	30/04/2008	Nasarawa	19, 742	08⁰42′ N 008⁰ 58′ E
11	Upper Orashi Forests	30/04/2008	Rivers	25, 165	04⁰ 53′ N 006⁰ 30′ E

(Source: Asibor, 2009)

Theoretical Framework

1.6.4 Theory of Ecosystem Management

Ecosystem management is a process that aims to conserve major ecological services and restore natural resources while meeting the socioeconomic, political and cultural needs of current and future generations (Brussard et al., 1998; Szaro et al., 1998). The principal objective of ecosystem management is the efficient maintenance and ethical use of natural resources (Szaro et al., 1998). Ecosystem management acknowledges that the interrelation of socio-cultural, economic and ecological systems is paramount to understanding the circumstances that affect environmental goals and outcomes (Lackey, 1998). It is a multifaceted and holistic approach which requires a significant change in how the natural and human environments are identified. Several approaches to effective ecosystem management engage conservation efforts at both a local or landscape level and involve: adaptive management, natural resource management, strategic management, and command and control management.

The definitions of ecosystem management are typically vague (Lackey, 1998). Several core principles define and bound the concept and provide operational meaning: (1) ecosystem management reflects a stage in the continuing evolution of social values and priorities; it is neither a beginning nor an end; (2) ecosystem management is place-based and the boundaries of the place must be clearly and formally defined; (3) ecosystem management should maintain ecosystems in the appropriate condition to achieve desired social benefits; (4) ecosystem management should take advantage of the ability of ecosystems to respond to a variety of stressors, natural and man-made, but all ecosystems have limited ability to accommodate stressors and maintain a desired state; (5) ecosystem management may or may not result in emphasis on biological diversity; (6) the term sustainability, if used at all in ecosystem management, should be clearly defined – specifically, the time frame of concern, the benefits and costs of concern, and the relative priority of the benefits and costs; and (7) scientific information is important for effective ecosystem management, but is only one element in a decision-making process that is fundamentally one of public and private choice (Lackey, 1998).As a concept of natural resource management, ecosystem management remains both ambiguous and controversial, in part because some of its formulations rest on policy and scientific assertions that are contested (Lackey, 1998). These assertions are important to understanding much of the conflict surrounding ecosystem management. Professional natural resource managers, typically operating from within government bureaucracies and professional organizations, often mask debate over controversial assertions by depicting ecosystem management as an evolution of past management approaches.

1.6.5 Ecosystem Model

An ecosystem model is an abstract, usually mathematical, representation of an ecological system (ranging in scale from an individual population, to an ecological community, or even an entire biome), which is studied to gain understanding of the real system (Hall et al., 1990). Using data gathered from the field, ecological relationships – such as the relation of sunlight and water availability to photosynthetic rate, or that between predator and prey populations – are derived, and these are combined to form ecosystem models. These model systems are then studied in order to make predictions about the dynamics of the real system. Often, the study of inaccuracies in the model (when compared to empirical observations) will lead to the generation of hypotheses about possible ecological relations that are not yet known or well understood. Models enable researchers to simulate large-scale experiments that would be too costly or unethical to perform on a real ecosystem. They also enable the simulation of ecological processes over very long periods of time (i.e. simulating a process that takes centuries in reality can be done in a matter of minutes in a computer model) (Hall and Day, 1990).

There are two major types of ecological models, which are generally applied to different types of problems: (1) analytic models and (2) simulation/computational models.

Analytic models are often more mathematically complex, and work best when dealing with relatively simple (often linear) systems, specifically those that can be accurately described by a set of mathematical equations whose behavior is well known. Simulation models on the other hand, use numerical techniques to solve problems for which analytic solutions are impractical or impossible. Simulation models tend to be more widely used, and are generally considered more ecologically realistic, while analytic models are valued for their mathematical elegance and explanatory power. Jorgensen & Sven (1996), Grant & Swannack, (2008), Hall & Day (1990) are of the view that an Ecopath is a powerful software system which uses simulation and computational methods to model marine ecosystems. It is widely used by marine and fisheries scientists as a tool for modeling and visualizing the complex relationships that exist in real world marine ecosystems (Paul et al., 2000; Christensen & Walters, 2004; Christensen, 2009). This model was adopted because it seeks to explain the relationship and interaction between forms of disturbances that occurs in space and how they affect changes in other ecosystems. That is, there exists a relationship among individual wetlands, which means that any adverse impact on one may affect the function of another or several others.

1.6.6 Land Use/ Land Degradation Model

In this context land use represents human use of land while land degradation tells us about the bio-physical depletion of land or the reduction in the capacity of land to function sustainably. The land use/degradation model was adopted for this work to show the relationship between land use/land degradation which causes changes in biological diversity that can lead to wetland loss (Campbell and Olson, 1991). Campbell and Olson bring society and environment interaction in what is reflected as the kite framework which rest on five main principles or doctrines.

Principle of integrating environmental and societal processes as active component of land use systems.
Principle of different processes especially population growth and development having different temporal characteristics.
Principle of temporal processes having bi-directional changes; i.e. land use intensification due to socio-economic context, and interaction of processes can result in feedback effects mechanism.
Principle of examination of interactions over space, recognizing that events in one area may have repercussions in other areas through processes as infrastructural development, migration and increased socio-economic competitions and institutional change(s).
Principle of recognizing the role of power in affecting outcomes of policy and resolving competition and conflicts.

By implication, interactions between societal and biophysical processes at the global, national, regional and local levels result in environmental changes. Thus, this model clearly explains how change in land use as a result of rapid urbanization in a place like the Port-Harcourt metropolis has impact on the biodiversity and vegetation composition which ultimately have direct effect on wetland functions and services.

1.7 Research Methodology

Reconnaissance Survey

In order to properly undertake this research, a reconnaissance survey has been carried out to enable the researcher familiarize with the study area (Appendix 1). Remote sensing are the techniques of analysis not for reconnaissance rather, coordinates of various land use and land cover of the study area have been ascertained and validated in order to improve the accuracy of the classification that has been adopted to the imageries in question (study area).

Figure 4: Flow Chart of the Study Methodology

Data Acquired and Sources

Sources of data for this study were acquired from a time series of landsat Thematic Mapper (TM) and Enhanced Thematic Mapper plus with Thermal Infrared Sensor (TIRS) images were used to derive land use and land cover maps of the Port-Harcourt metropolis. The data set include a notable period of four years for, 1984, 1999, 2003 and 2013 (Table 2). The raw satellite data were obtained from the archive of the United States Geological Survey and Earth Explorer. The maps were projected using Universal Transverse Mercator (UTM) and datum WGS 84 of zone 32.

Table 2: Data Source

S/N	SATELITE/ DATA TYPE	SENSOR	PATH/ROW	DATE	SACLE	BANDS	CLOUD COVER	SOURCE
1	Landsat 5	Thematic Mapper (TM)	188/057	13/12/84	30m	1,2,3,4,5,6 and 7	0	Courtesy of the U.S. Geological Survey. Earth Explorer.
2	Landsat 7	Enhanced Thematic Mapper plus (ETM+)	188/057	29/11/1999	30m	1,2,3,4,5,6 and 7	10%	Courtesy of the U.S. Geological Survey. Earth Explorer.
3	Land sat7	Enhanced Thematic Mapper plus (ETM+)	188/057	08/01/2003	30m	1,2,3,4,5, 6 and 7	0	Courtesy of the U.S. Geological Survey. Earth Explorer.
4	Land Sat7	Enhanced thematic Mapper plus (ETM+)	188/057	21/12/2013	30m	1,2,3,4,5, 6 and 7	0	Courtesy of the U.S. Geological Survey. Earth Explorer.

Source: USGS, (11-19-2014)

These data sets sensors have repeat cycles of 20 days, ground pixel dimension of 57 x 79m (TM), 16-bit pixel for values TIRS and the spectral range includes seven spectral bands in the visible/near infrared (VNIR)-Bands 1, 2, 3 and 4), shortwave infrared (SWIR – Bands, 5 and 7) and thermal infrared TIR – Band 6) parts of the electromagnetic (EM) spectrum. The spectral resolution of Landsat TM and ETM+ (30m) data makes it very useful for land use change and land cover classification and general mapping.

1.7.3 Geo- Referencing Properties of the Images

The Geo-referencing properties of 1984, 1999, 2003 and 2013 made up of universal

Transverse Mercator (UTM) projection, and datum WGS 84, zone 32

1.7.4 Software Used

Below are software used in this research work.

ERDAS Imagine (2014): This was used for displaying processing, enhancement and classification of the imageries. It was used for the delineation of the study area imagery.
IDRIS SELVA: This was used for the development of land use land cover prediction classes for the study area
ArcGIS 10.1: This was used in developing, display and processing of the location maps.
Microsoft Word Office 2010: was used basically for the presentation of the research work.
Microsoft Excel: was used in producing the Bar chart and graph also used in converting the coordinates into x and y degree of decimals

1.7.5 Image Enhancement

Enhancement operations are normally applied to image data after the appropriate restoration procedures have been performed. Noise removal is an important precursor to most enhancements without it; the image interpreter is left with the prospect of analyzing enhanced noise. Basically, there are three techniques for digital enhancement such as:

Contrast Manipulation: Grey – level threshold, level slicing and contrast stretching
Spatial Feature Manipulation: Spatial filtering, image enhancement and fourier analysis.
Multi-Image Manipulation: Multi-spectral band rationing and differencing, principal components, canonical components, vegetation components, intensity – hue saturation (HIS) colour space transformations and de-correlation stretching.

1.7.6 Image Classification

Image classification procedure is to automatically categorize all pixels in an image into land use/land cover classes. Normally, multi spectral data are used to perform the classification and the spectral pattern present within the data for each pixel is used as the numerical basis for categorization, i.e. the different combinations of DNs based on their inherent spectral reflectance and remittance properties. Spectral pattern recognition refers to the family of classification procedures that utilizes this pixel – by – pixel spectral information as the basis for automated land cover classification.

Spatial pattern recognition involves the categorization of image pixels on the basis of their spatial relationship with pixels surrounding them. Spatial classifiers might consider such aspects as image texture, pixel proximity, feature size, shape, directionality, repetition and context. These types of classifiers attempt to replicate the kind of spatial synthesis done by the human analyst during the visual interpretation process.

Temporal pattern recognition uses times as an aid in feature identification. In agricultural crop surveys, for example, distinct spectral and spatial changes during a growing season can permit discrimination on multi-date imagery that would be impossible given any single date.

As with the image, classifiers may be used in combination in a hybrid mode. Also there is no single “right” manner by which an image classification problem can be approached. The particular approach one might take depends upon the nature of the data being analyzed, the computation resources available and the intended application of the classified data.

To emphasize, spectrally oriented classification procedures are used for land cover mapping.

Supervised classification, the image analyst “supervisor” the pixel categorization process by specifying, to the computer algorithm, numerical descriptors of the various land cover types present in a science. To do this, representation sample sites of known cover type, called training area, are used to compile a numerical “interpretation key” that describes the spectral attributes for each feature type of interest. Each pixel in the data set is then compared numerically to each category in the interpretation key and labeled with the name of the category it “looks most like”. The other classification is unsupervised classification. The procedure is applied in two separate steps. The fundamental difference between these techniques is that supervised classification involves a training steps followed by a classification step.

In the unsupervised approach, the image data are first classified by aggregating image. The analyst determines the land cover by comparing the classified image data to ground reference data.

1.7.7 Classification Smoothing

Classified data offer manifests a hand and glove appearance due to the inherent spectral variability encountered by a classifier when applied on a pixel – by – pixel basis. For example, in a built up area, several pixels scattered throughout urban infrastructure and road may be classified as land use. In such situation it is often desirable to “smooth” the classified output to show only the dominant classification.

One means of classification smoothing involves the application of a statistical fitter. In such operations, a moving window is passed through the class within which the window is determined. If the center pixel in the window is not the majority class, its identity is changed to the majority class. If there is no majority class in the window, the identity of the center pixel is not changed. As the window progresses through the data set, the original class codes are continually used, but not the labels as modified from the previous window positions. The classified map was prepared in this manner, applying a 3×3 pixel medium filter to the data.

Medium filters can also incorporate some form of class and/or spatial weighting function. Data may also be smoothed more than once. Certain algorithms can preserve the boundaries between land cover regains and also involve a user specified minimum area of any given land cover type that will be maintained in the smoothed output.

1.7.8 Selection of a Classification Scheme

Anderson et al., (1976) are of the view that “there is no one ideal classification of land use and land cover, and it is likely that one could even be developed”. In Nigerian, there is no ideal or standard classification scheme that can be adopted for a study (Ogwuche, 1994). A classification scheme is required to organize the needed information into a structure that satisfies the researcher‟s problem and objectives, as well as the type of resource data being sought and the physical nature of the terrain (Ogwuche, 1994).

Based on the prior knowledge of the study area for over 30 years and a brief groundrouting with additional information from previous research in the study area, a classification scheme was developed after Anderson et al (1976). The classification scheme developed gives a rather broad classification where the land use/land cover was identified by a single digit. Table 3 Shows the five land use/land cover classification identified in the Port Harcourt metropolis considering the scale and resolution of the remote sensor data, interpretation of more elements of the image such as colour, texture, shadow, pattern, association, shape and size of the data (resource data), research objectives, field visit and the physical nature of the wetlands terrain in the Port Harcourt metropolis.

Table 3: Land Use/Land Cover Classification

S/N	LEVEL 1, LAND USE /LAND COVER CATEGORIES	LAND USE/LAND COVER DESCRIPTION
1	FALLOW LAND	This includes farmland, sparse vegetation and thick vegetation.
2	SALTWATER WETLAND	Salt water ecosystem of tidal/sub tidal lands, salt water estuaries‟ habitats, and beach, flat or contiguous lowland subjected to tidal action.
3	BUILT UP AREA	Urban area, industrial layout, bare soil, residential, commercial, educational, infrastructure, road network, pipeline, flow station, oil and gas facilities, flow lines, open and cleaned areas.
4	FRESHWATER WETLAND	These are fresh water ecosystem mainly swamps, marshes and bogs etc.
5	WATER	Exposed water bodies within the study area including river, stream, rivulet creek

Source: Anderson et al., 1976

This involved identifying a set of sample locations and conducting field visit to the study site on Monday 22^nd June and Tuesday 7^th July, 2015 to validate these locations. The land use and land cover found were compared to that which was mapped in the image for the same locations. Photographs and coordinates of the various land-use land-cover were obtained with a hand held GPS (Appendix .1)

Cohen‟s Kappa statistic was used to measure the level of accuracies of land use/land cover classification categories.

1.7.9 Method of Data Analysis

The main methods of data analysis adopted in this research include:

Calculation of the area in hectare of the resulting land use/land cover types for each study year and subsequently comparing the results
Markov Model for predicting change
Overlay operations
Maximum likelihood classification.
The first three methods above were used for identifying change in the land use/land cover types. Therefore, they have been combined in this research.

The comparison of the land cover statistics assisted in identifying the percentage change, trend and rate of change from 1984 – 2013. In achieving this, the first task was to develop a table showing the area in hectare and the percentage change from each year (1984, 1999, 2003 and 2013) measured against each land cover type. Percentage change to determine the trend of change is calculated by the value of the preceding year and multiplied by 100. i.e.:

= (trend) percentage change = ………….. (1)

In obtaining rate of change, the percentage change is divided by 100 and multiplied by the total number of years 1984 – 2013 (29 years) of the study.

The second method (Markov Model) is a convenient tool for modeling land cover change when changes and processes in the landscape are difficult to describe. A Markovian process is one in which the future state of a system can be modeled purely on the basis of the immediately preceding state. Markovian chain analysis will describe land use change from one period to another and use this as the basis to project future changes. This is achieved by developing a transition probability matrix of land use change from time one to time two, which shows the nature of change while still serving as the basis for projecting to a later time period. For example, the probability of each land use changing to another land use vice versa was estimated and predicted to 2023(10 years), 2033(20 years) and 2043 (30 years) using Markovian transition estimator in Idrisi Selva. The transition probability may be accurate on a percentage category basis, but there is no knowledge of the spatial distribution of occurrences within each land use category. Hence, it was used to add spatial character to the model.

Overlay operations, which is the last method of the three, identifies the actual location and magnitude of change. Boolean Logic was applied to the result through the re-class module of Idrisi Selva which assisted in mapping out separate areas of change for which magnitude was later calculated.

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THE CONTRIBUTION OF URBANIZATION TO SLUM DEVELOPMENT IN NIGERIA

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THE CONTRIBUTION OF URBANIZATION TO SLUM DEVELOPMENT IN NIGERIA

CHAPTER ONE

INTRODUCTION

Background of the study

necessarily entail analyses concerning those situated on the margins of society and the environment and how to ensure environmental sustain- ability.

Statement of the problem

There may have been previous researches in this subject. This work gives further explanations and analysis in the contribution of urbanization to slum development in Nigeria

Objectives of the study
To understand the contribution of urbanization to slum development in Nigeria
To understand the relationship between the contribution of urbanization and slum development in Nigeria

Research questions
What is the the contribution of urbanization to slum development in Nigeria
What is the relationship between relationship between the contribution of urbanization and slum development in Nigeria

Research hypothesis

H0: There is no relationship between the contribution of urbanization and slum development in Nigeria

H1: There is a relationship between the contribution of urbanization and slum development in Nigeria

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