Land use characterization of Ile-Ife

LAND USE CHARACTERIZATION OF ILE-IFE.

BY

ARODUDU OLUDUNSIN TUNRAYO

GLY/2001/065

A DISSERTATION SUBMITTED IN PARTIAL FULFILMENT OF

THE REQUIREMENT FOR THE AWARD OF BACHELOR OF

SCIENCE DEGREE IN THE DEPARTMENT OF GEOGRAPHY,

FACULTY OF SOCIAL SCIENCES, OBAFEMI AWOLOWO

UNIVERSITY, ILE-IFE, OSUN STATE, NIGERIA.

NOVEMBER 2008

ii

CERTIFICATION

This is to certify that ARODUDU OLUDUNSIN TUNRAYO with registration number

GLY/2001/065 of the Department of Geography, Faculty of Social Sciences, Obafemi

Awolowo University, Ile – Ife, Osun State, wrote this dissertation under the supervision of

Prof F.A Adesina.

Prof. F.A Adesina Date

Project Supervisor

.

Dr. Aderemi Adediji Date

Head of Department

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DEDICATION

To the Almighty; my source, my inheritance, my lot, my hope and my exceeding great

reward.

iv

ACKNOWLEDGEMENT

To Him who found me in the wilderness and had helped thus far, He instructed and

kept me as the apple of his eye, He made a nest for me, nurtured me and bore me on the

wings of the eagle, He alone led me and there was no strange god with me and made me to

ride on the high places of the earth. THANK YOU

To my Late Dad; thoughts of you are always sources of continuous inspiration for me, I

wished had lived longer to savour this moments. To the greatest Mum in the World; you

are first among equals, one in a million, thank you for your support and good training, Your

relentless love had made me stay in the race. I will always love and cherish you. To my

sisters; Sister Toyin, Sister Kemi, Sister Sade and Sister Tolu, you’ve been my defense and

security, come rain or shine, you have always been there for me, may you not lack any

Good thing in your life. To my only brother, far greater than Ali, you are the greatest.

Thank You

To the first people I met in this department, the clerical staffs, May God in his

infinite mercy take care of you and yours. To the first citizen of this department, when I

was about coming in, Prof A.S Aguda, what God has helped you to accomplish in my life

may you not lose the reward in Jesus name. Thank you for giving me another life, a new

lease of hope I am grateful to you for allowing God use you for me.

My profound gratitude goes to my Project supervisor, Prof. Adesina that I fondly

call Baba. I will want to say this that you are a rare specie on the earth, men like you are

very few and not easy to come by, I am glad to have passed through, you are indeed a rare

gem, I celebrate your forthrightness, achievements and life legacy of hard work and service

to humanity. Your glowing touch of idealism which to you is a lifestyle will remain with

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me for the rest of my life and I as a person (Dunsin) promise not to betray your ideals as

father as we go into the larger society to contribute our share as stakeholders and policy

makers in a new emerging Nigeria of our dreams.

I thank all the lecturers in the department of Geography for their contribution to my

success on this campus. May heaven reward your labour of love over me, Keep doing the

good work that you are all doing. God bless you all.

I want to specially thank and appreciate Mr. Olawole and Dr Adeoye, through thick

and thin, you’ve been there for me; May the Almighty, whom I serve and whose I am make

sure that you and your offsprings never lack help in the name of Jesus. To Dr.

Orimoogunje, Mr Eludoyin and Dr.Olayiwola, Dr Babatimehin, Dr Odekunle, Dr Adediji,

you are all wonderful people; may God’s goodness and mercy rest on your habitations

forever and may God make our lives a testimony of your ceaseless labour over us. Amen.

To my church folks, you are all wonderful people, in your love and apathy,

togetherness and strife, through it all, you’ve helped me learn God, which is the essence of

our common salvation an eternal life; thank you all for the part you played in my stay on

campus, regardless of our differences, you have played the part that God will have you play

in my life, Thank you CLF, Living Seed Ministries and my Beloved pastor, Pastor Mrs.

Adetiloye, Thank you for your understanding.

To my own Gabu father, Oluh, Remson, Ilafa, Ogaaba, Lamidi, Segedu1, Christain

Love, Opasco, Jendor, Simon Ben Judah, Biola, Lola, Wale, Feyi, Lamide, Samson Nee,

Aworawo, Shobo, Yemi Aye, Alex Aye, Wale Aye, S O Jakes, Okay, TJ, Wardd; Blessed

be the day I met you all, The world has never known a better company than ours; Our

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season of revelation and manifestation had just began. Thank you for being worthwhile

investments.

Arodudu Oludunsin Tunrayo

NOVEMBER 2008.

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Table of content

Title page i

Certification ii

Dedication iii

Acknowledgement iv

Table of content vii

List of Tables xi

List of Figures xii

List of Charts xv

Abstract xvi

CHAPTER ONE: GENERAL BACKGROUND

1.11 Introduction 1

1.11 Land Use Issues 1

1.111 Issues in Land Use 3

1.112 Concept of Land Use an Environmental Concept 4

1.12 Land Use Characterization 5

1.2 Objectives 6

1.3 Statement of Problem 6

1.4 Justification of Study 6

1.5 The Study Area 6

1.51 Location 6

1.52 Climate and Vegetation 7

1.53 Population Characteristics 8

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CHAPTER TWO: LITERATURE REVIEW

2.1 Classes of Land Use 12

2.11 Rural Land Uses 12

2.12 Urban land uses 12

2.2 Factors Influencing Land Use 13

2.21 Population 13

2.22 Economic Growth 14

2.23 Efforts, Plans, Legislations and Policies 14

2.24 Available Resources 15

2.3 Land Use Study 16

2.31 Contemporary land use models 17

2.311 Models to predict total Land Use 18

2.3121 Build out Analysis 18

2.3122 Cellular Models 19

2.3123 Agent Based Models 19

2.32 Classification Schemes 20

2.33 Use of Remote Sensing Capabilities 24

2.331 What Is Remote Sensing 24

2.3311 Camera Remote Sensing 29

2.3312 Satellite Remote Sensing 29

2.332 Limitation of the Remote sensing Imageries 32

2.333 Problem of Remote Sensing In Developing Countries 37

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CHAPTER THREE: METHODOLOGY

3.1 Materials Required 40

3.2 Methodology 41

3.21 Data Collection 41

3.211 Primary Data 41

3.2111 Reconnaissance Survey (Recce) 41

3.2112 Land Use Field Survey 41

3.21121 Land Categorization 42

3.211211 Land Categorization Principles 43

3.212 Secondary Data 47

3.22 Image Processing 47

3.221 Pre-Processing 47

3.222 Classification 48

3.2221 Unsupervised (Automatic) Classification 48

3.2222 Supervised Classification Method 48

3.223 Pre- Classification 48

3.2231 Loading of the Coordinate System 50

3.2232 Colour Separation 56

3.2233 Map List Creation 60

3.2234 Georeferencing 62

3.2235 Domain or Class Creation 68

3.2236 Sample Set Creation 72

3.2237 Training of Sites 76

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3.224 Classification Procedure 79

3.225 Digitization 83

3.23 Geo-Presentation or Result Presentation 84

3.231 Image Statistics Display 85

3.232 Overlay Operations 89

3.3 Limitation of the Study 93

CHAPTER FOUR: RESULT AND ANALYSIS

4.1 Observations 94

4.2 Land Use Characterization Map 94

4.3 Image Statistics Display 96

CHAPTER FIVE: SUMMARY AND CONCLUSION

5.1 Summary 101

5.2 Issues and Recommendation 101

REFERENCES 104

APPENDICES 106

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List of Tables

Table 1: Table showing the areal extent and percentage covered by the key land cover types and land

use types in Ile-Ife. 96

Table 2: Table showing the areal extent and percentage covered by the key land cover types in Ile-

Ife. 98

Table 3: Table showing the percentages of land uses in the Built Up areas of Ile-Ife. 99

Table 4: Table showing the selected coordinate points collected in the field for feature identification

and image processing 109

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List of Figure

Fig 1: Map showing the location of Ile-Ife 9

Fig 2: Procedure 1 50





















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Fig 44: Flowchart of the Methodology 92

Fig 45: Land Use characterization map of Ile-Ife 95

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Fig 46: Scanned Image of Ile-Ife Roadmap 106

Fig 47: The Coordinate System used for the study 107

Fig 48: The Georeference editor of LandSat ETM+

2002 Imagery of Ile-Ife. 108

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List of Charts

Chart 1: Pie chart showing the percentage of land cover types and land use types in Ile-Ife 97

Chart 2: Bar chart showing the percentage of land cover types and land use types in Ile-Ife 97

Chart 3: Pie chart showing the percentage of land cover types in Ile-Ife 98

Chart 4: Bar chart showing the percentage of land cover types in Ile-Ife 99

Chart 5: Pie chart showing the percentage of the different built-up land use classes in Ile-Ife 100

Chart 6: Bar chart showing the percentage of the different built-up land classes in Ile-Ife 100

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ABSTRACT

This study attempts to characterize the key land uses in Ile-Ife. The study aims at

identifying the key land uses in Ile-Ife, producing a land characterization map of Ile-Ife and

obtaining information about the key land cover and land uses from remote sources.

In order to achieve the above aim, we undergo land use surveys so as to familiarize

ourselves with the study area and take coordinates of important features needed in the

characterization process.

Landsat Enhanced Thematic mapper (2002) imagery of Ile-Ife is obtained from

secondary sources and classified into key land uses and covers based on the information

gathered in the field using ILWIS 3.2, an image processing software; each layer or segment

of land cover types and land use types are created by digitization in the ILWIS 3.2

environment and the statistics of each layer or segment of the digitzied image is also

displayed in ILWIS 3.2 environment. The layers or segments of the digitized image

representing the various land use cover types and land use types are exported to Arcview

GIS 3.2a were they are overlain to produce a land characterization map of Ile-Ife.

In the course of our study, we identified five key land cover types in Ile-Ife; they

include Built-Up Areas or Built-Up settlements, Vegetation, Bare Soil, Water Body and

Wetland. We also identified three key land use types; they include Residential,

Commercial, and Institutional Land Use areas.

Based on the image analysis, the estimated total land area of the study area is

approximately 668.83 Km2 with 407.07Km

2 (61.16%) of it covered by Vegetation, mostly

secondary vegetation. About 172.59Km2

(25.81%) is covered by residential built-up

settlements, about 37.63 Km2

(5.63%) is covered by institutional built-up settlements, about

35.27 Km 2

(5.27%) is covered by Bare soil, about 8.00 Km2 (1.20%)

is covered by

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wetlands, about 5.29 Km2

(0.79%) is covered by commercial built-up settlements while

remaining 0.15% ( about 0.98 Km2) is covered by pockets of water bodies. The total area of

built-up settlements in Ile-Ife put together is about 215.51 Km2 representing about 32.22%

of the total land in the area.

Although, vegetation covers most of the ground surface of the study area (about

61.16%), the ecosystem of the study area is still under threat because of the secondary

nature of the vegetation and the continuous rise in land use for urban purposes; therefore an

efficient land use planning structure that makes use of relevant technologies and

information such as that which this study is designed to produce need be put in place to

ensure sustainability of the environment and its capacity to continue to support life.

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Chapter One

GENERAL BACKGROUND

1.1 Introduction

The term “Land Use” is usually used to describe the different kinds of

uses that portions of land are put to. It has often been used interchangeably with the term

“Land Cover” although they differ in meaning. Land Cover refers to the surface cover on

the ground or the physical state of the land surface; which may be in form of vegetation

or urban infrastructures such as buildings, churches, schools, asphalt laid roads, concrete

floors and pavements and features such as water, bare soil, wetland, swamp, Mangrove,

rocky surfaces etc while land use refers to the purpose the land serves or the purpose the

land is used for; examples include recreational land uses such as wildlife and game parks

and reserves, amusement parks, hotels, holiday Inns, hotels, brothels, motels etc.

Land use usually involves human modification of the natural environment

as wilderness into built up environments such as fields, Pastures and settlements. Land

use can be defined as the total arrangements, activities and inputs that people undertake

in a certain land cover type [FAO, 1997a; FAO/UNEP, 1999].

1.11 Land Use Issues

Land use is crucial because it directly touches on issues relating to man‟s survival

on earth. Man through his use of land to secure livelihood has destroyed the environment

which is the basis of his livelihood in the first instance.

Over the last three centuries, it has been observed that human population

had continue to grow at a rate that is astronomical when compared to the limited nature of

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the resources available within reach to cater for the growing population. In 1798, English

clergymen and College Professor Robert Thomas Malthus in his Essay “the principle of

population” postulated that “man can only increase its means of subsistence at an

arithmetic progression while population increased at a geometric progression” and

suggested measures for checking such astronomical population increase so as to be able

to slow down the increase to march the level of subsistence. Numerous scholars had

argued that the persistence of such a scenario as these can cause the depletion of the

resources that once supported man‟s livelihood on earth to an extent that he can no longer

do so due to the wanton destruction of the environment. It has also been noted that such

wanton destruction could result in a widespread outbreak of hunger, famine, diseases and

pestilence which could also lead to conflict as it is the case today in many parts of Africa.

Land is “ a delineable area of the earth‟s terrestrial surface, encompassing

all attributes of the biosphere immediately above and below this surface including near-

surface climate, the soil and terrain forms, the surface hydrology (including shallow

lakes, rivers, marshes and swamps), the near surface sedimentary layers and associated

ground water reserves, the plant and animal populations, the human settlement pattern

and physical results of past and present human activity such as terracing, water storage or

drainage structures, infrastructures, buildings” [UN,1995] and not just the solid part of

the earth or the medium or bedrock on which man depends for the provision of his

physical, economic, religious and cultural wants or needs. This definition of land

encompasses all the attributes and aspect of resources needed for the survival, subsistence

and sustenance of its growing population on earth. Basic human needs and wants include

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shelter, Clothing, housing, food, wealth, money, Comfort, warmth, cultural and religious

obligations.

A school of thought referred to as Marxists believe that population problems are

not due to population increase but unequal distribution of resources and all of such

resources are tied to land by the UN definition making land use an indispensable issue or

subject matter in many fields of sciences designed to proffer solutions to human

problems.

1.111 Issues in Land Use

Man uses land for varieties of purposes which satisfies his varieties of

wants and needs; such wants and needs are usually for physical, economic, cultural or

even religious purposes and are essential for man‟s survival and continued existence.

Consequently, Land had always been in high demand and such demands had always

increased with increase in population.

Land is fixed, immobile and irreplaceable in nature, limited in availability

and by boundaries as opposed to the belief that it is limitless and inexhaustible. At the

rate at which land is being used, there may be nothing left for the coming generation and

so the fear of exhaustion of land and land resources within delimited territories is the first

issue in land use and the need to control its use within such boundaries is the second and

this requires proper planning and implementation.

Planning for land use in a way that its execution will both be environmental and

human friendly is the third major issue in land use. It should be noted in planning of

whatever form that plans are meant for man and not man for plans i.e. that plans are made

for man by man to help man and so a plan that is not altogether environmentally, socially

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and economically friendly in tackling man‟s problem is not fit for implementation.

Principles such as suitability of the environment for a certain use considering its local

physical, social and economic characteristics, optimization of whatever use land is been

put to and sustainability of whatever land use is proposed to ensure that the future of the

environment to run itself and support the continuity of human life is not compromised are

to be taken into consideration in planning and execution of projects for a better, more

productive and sustainable environment. However the principles mentioned above are

known to constitute the other issues in land use and they are thus issues of suitability,

issues of optimization of use and issues of sustainability.

1.112 Concept of Land Use an Environmental Concept

Many fields have evolved in the environmental sciences as man continues to

strive to understand himself and the environment enough to be able to effectively control

his resources for the common good of all in a way that its present needs and wants will be

satisfied without compromising the future capacity of the environment to run itself

continuously according to the natural order of life without being alienated and the future

capacity of the environment to support the continuity of human life on it (earth).

The term “Land use” had continue to find its way into very many environmental

fields of studies namely ecology, Biodiversity studies, Planning, Resource Management

and economic planning, Climatology, meteorology, hydrology, geomorphology etc

because it affects every element of the natural environment which are the subject matter

that those disciplines study.

Land use offsets the balance of the ecosystem which man is a component of. Land

use is one of the determinants of the distribution and prevalence of species on earth. Land

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use practices produces and releases gases into the atmospheres that degrades the local,

regional and global air and precipitation quality and contributes to global warming. Land

use is a major determinant of hydrological processes and balance; it is capable of causing

a change in the course of hydrological processes or shifts in hydrological balance. Land

use is major determinant of the quality of water in basins; discharge rate, recharge rate

and volume of basins per time. Land use is one of the agents that influences the

distribution and formation of land forms and slopes in whatever environment whether

tropical, humid, temperate or Polar Regions and one of the factors that aid the agents of

land form formation such as wind, wave, ice and running water.

Increased Land use causes expansion of urban facilities and leapfrog development

into neighbouring boundaries (urban sprawl); this cause boundary violation which

precipitate into communal and inter-boundary conflicts.

Information on land use such as the stock of land used, the type of land uses and

the patterns and trends of land use within particular boundaries are essential tools for

making decision in planning and re-organization schemes and in distribution and

allocation of national resources for sustainable development.

1.12 Land Use Characterization

Land Use Characterization involves the classification of portions of land in an

area into different land use types based on its predominance, relative significance or its

association with other land use types that has wider definitions; for instance most

recreational land use forms exists for commercial purposes and so could be classified

under commercial land use in certain cases. Land use are usually characterized to take the

stock of land cover and land uses and provide relevant information (data and maps)

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needed for subsequent planning or re-planning in lieu of development for meeting the

present needs of a man without compromising the ability of man to develop in the future.

1.2 Objectives

The specific objectives and scope of this study are to:

i. To identify key land use types in Ile-Ife.

ii. Attempt the production of a land use map for Ile-Ife.

iii. Provide an estimate of the key land use types in Ile-Ife

1.3 Statement of Problem

Effective Land resources management requires specific information on

what uses the land of a particular area is put to and this is lacking for many cities in

Nigeria. This present study is an attempt to provide such information to fill this gap for

Ile-Ife.

1.4 Justification of Study

Ile-Ife like other Nigerian cities is evidently growing at an unprecedented rate and

a good knowledge of the extent of the various land uses is not known. Such information

are required for rational planning of the city and for the provision of municipal services.

A study like this is needed to provide the information.

1.5 The Study Area

1.51 Location

The study area is Ile-Ife, covering the whole of Ife Central Local

Government Area and most parts of Ife East Local Government Area of Osun State,

Nigeria. Ile-Ife is located between latitude 7o 31‟N and 7

o34‟N of the equator and

between longitude 4o30‟E and 4

o34‟E of the prime meridian. The Area is bounded in the

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North by Atakumosa West Local Government Area, in the North West by the Ede South

Local Government Area, in the East by Atakumosa West Local Government Area, in the

West by Ife North Local Government Area and in the South by Ife North and South Local

Government Areas.

1.52 Climate and Vegetation

Ile-Ife falls within the humid tropical environment (Adejuwon, 1979) and

therefore has high temperature and rainfall typical of the tropics. It is characterized by

marked wet and dry seasons. The wet season which is associated with the tropical air-

mass (mT) varies between seven and nine months. It lasts from around April to

November. The annual rainfall variability lies between 90% and 120% annually. The dry

season is associated with the tropical continental airmass (cT), temperature and relative

humidity are generally high. The mean monthly temperature ranges between 23°C and

27°C (Ojo, 1977). This climate supports the rainforest formation as described by

Richards (1952). In the dry season, the temperature can be as high as above 29.4°C and in

the rainy season it can be as low as 25.6°C. The relative humidity is very high between

67% and 88%. The dry season usually begins towards the end of October and ends

around March thus, lasting five months. The rainy season begins around April and ends

in October. Ile-Ife is located within the rain forest belt of Nigeria where the climate

encourages forest growth. Its forest cover supports the growth of cash crops such as

Cocoa, kolanut and Oil Palm. Ife Area generally is the home of valuable economic timber

resources such as Iroko, Oganwo, Obeche, Idingbo, Afa, and Ole making lumbering and

saw-milling a major industry in the area. The town is also a collecting centre for

agricultural products which has attracted traders from Northern Nigeria to settle and trade

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especially in kolanut. Other occupations of the people include vocational practices,

trading, civil service, arts etc.

1.53 Population Characteristics

Figures from the last conducted national population and housing census in

2006 revealed that Ife central local government has an estimated total population

of about 167,254; comprising of about 84,653 male and about 82,601 female

while Ife East has an estimated population of about 188,087; comprising of about

92,054 male and about 96,033 Female.[NPC, 2007]

The total population of the Study area is estimated at about 355,341;

comprising of about 176,707 male and about 178,634 female.

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Fig 1: Map showing the location of Ile-Ife

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CHAPTER TWO

LITERATURE REVIEW

Land has been defined differently by different individual scholars, bodies of

scholars and organizations based on their different perceptions of what it actually is. It is

viewed by many as the solid part of the earth invaluable and necessary for human

existence and by many others as the plane on which human activities of whatever form or

magnitude take place. Such human activities could be industrial, agricultural or

commercial or economic or religious or cultural or even academic in native.

Economists view land as a factor of production comprising all naturally occurring

resources needed for production and on which production is done; Christian and Steward

(1968) said “land was synonymous to terrain”. Adeniyi (1986) defined land “as a major

resource that is a common base to all development effort”. Food and Agricultural

Organization (FAO), a United Nation Body in 1985 defined land initially as “an area of

the earth‟s surface, the characteristics of when embraces all reasonably stable or

predictably cyclic attributes of the biosphere vertically above and below this area

including those of the atmosphere, soil and underlining geology, the hydrology, the plant

and animal population, and the results of past and present human activities and the extent

that those attributes exert a significant influence on its present and future uses by

humans” but later redefined it in 1995 as “a delineable area of the earth terrestrial surface,

encompassing all attributes of the biosphere immediately above or below this surface

including those of near surface climate, the soil and terrain forms, the surface hydrology

(including shallow lakes, rivers, marshes and swamps), the near surface sedimentary

layers and associated ground water reserve, plant and animal populations, the human

11

settlement pattern and physical result of past and present human activity such as

terracing, water storage or drainage structures, infrastructures and buildings”, so as to

make it all encompassing to include non-cyclic attributes left out in the initial definition

which defined land only to encompass reasonably stable and predictably cyclic attributes

of the biosphere.

Most of the definitions of land touch on certain aspects if not all parts of resources

that man needs to survive; this had made the term “Land” and its usage central to all

discourse on resources in every walks of life globally as man continued to strive to meet

his needs in the face of growing population concerns and accompanying pressure on

limited available resources without destroying the environments capability to run itself

and to continue to support life in the future.

Generally land and its use are evaluated in terms of characteristics, qualities and

capabilities. Land characteristics are directly observable properties of land such as

productivity, fertility, ruggedness, erodibility etc. (Jeje, 1986); land quality is the degree

to which certain tract of land can be put to certain kinds of use, while land capability

refers to the fitness of the land to perform a definite use (Townshend, 1981).

Land use usually involves either a modification or conversion of the natural

environment or wilderness or cover type by human activities from the initial natural

condition to a newer less natural condition e.g. modification of a forest to a farm land for

agricultural use; or conversion of a grass land or a grazing fields or a farmland into a built

up residential house for residential use or conversion of a virgin land to a car park for

transportation use.

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2.1 Classes of land use

Land use can be broadly classified into rural and urban land use.

2.11 Rural land uses

Rural land uses are usually primary or primitive in nature; they comprise of largely

extractive land uses such as agricultural land uses such as land use for farming, grazing

and fishing and mining land uses such as excavation for solid minerals, rocks and sands,

drilling for water, liquid minerals such as oil, gaseous minerals such as natural gas and

residential land uses such as huts, farmhouse, camps, tents and country houses and to a

lesser extent commercial land uses such as food markets; industrial land uses such as

crafts, artisanship etc traditional and cultural land uses such as traditional landmarks and

hotspots; recreational land uses such as open spaces, playing fields and playgrounds and

fewer educational land uses usually 1 or 2 primary and secondary schools.

2.12 Urban land uses

Urban land uses on the other hand are usually more modern and sophisticated.

Urban land use is usually composed of lesser extractive land uses i.e. lesser mining and

agricultural land uses. The few extractive land uses found in urban areas however

include drilled boreholes and wells (mining land use) gardens and orchards (agricultural

land use). Urban land uses usually compose of more of uses that are secondary, tertiary,

quaternary and quinary in nature because of its usual nearness to availability of all the

resources and infrastructures that favours such land use decisions and activities.

More predominant land uses in urban areas include industrial land uses example light

manufacturing such as food processing and heavy manufacturing such as steel rolling

mill, building and constructions such as block-making, industries etc and more service

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oriented uses e.g. shops, shopping malls, filling stations, departmental stores, central

markets, banks and insurance companies etc. Residential uses such as estates,

Government reserve areas, streets, avenues, crescents etc, more modern religious land

uses such as churches, mosques and temples, educational land uses such as day cares,

kindergartens, primary schools and secondary schools, continuing education centre

(CECs) etc; transportation land uses such as car parks, road networks, bus stops, public

motor parks and garages etc, recreational land uses such as hotels, motels, brothels,

museums, cinemas, media and game houses, golf courses, stadia, amusement parks etc

and conservational land uses such as wildlife, games and forest reserves and parks.

“Land use is the result of continuous field of tension created between available

resources and human needs acted upon by human effort” (Vink, 1975). Land use, land

use decisions and patterns are therefore usually driven mainly by the size and dynamics

of human population and degree of human activities that such population size of

dynamics attracts, the state function and size of available land and its resources and the

action control, legislation and policies that man imposes on land use for optimization and

sustainability of his resources.

2.2 FACTORS INFLUENCING LAND USE

2.21 Population

Population growth occasioned either by natural increase or high rate of migration

increases the number of residents and the intensity of land use especially for residential

and commercial purposes in an area because more homes and places to work and shop

will be needed. Population growth could also cause a significant change in land use types

in an area because of the new functions or status that such an area could assume as a

14

result of natural increase or an increase in the number of immigrants and the new

demands that accompany such new function role or status. A decline in population in an

area due to disasters, incidences, epidemics, economic emmigration, economic crisis,

conflicts, economic depression, war, famine and hunger generally reduces the intensity of

land use for whatever purposes and could also modify the land use types in such an area.

The demographics of a particular area i.e. population structure and composition

also determines the land use types and patterns in an area. Different races, tribes, ethnic

groups, nations, age groups and sexes are known to have different needs and therefore

exhibit different land use characteristics and behaviours due to dissimilarities in physical

environment, ideologies and perceptions, historical, cultural and religious beliefs and

backgrounds, poverty and prosperity levels and also their biological differences.

2.22 Economic Growth

Population increase in different parts of the world together with the development

of the monetary economy in such areas had increased the volume and degree of economic

and commercial activities and jobs, the demand for land and the intensity of land uses in

such areas. The adverse effects of economic decline on the other hand can cause

reduction in the population, the economic and commercial activities due to emmigration

or natural decrease and could reduce the intensity of land use or stimulate indiscriminate,

unlawful, inordinate, over-ambitious, unplanned and improper land use behaviours in

such areas.

2.23 Efforts, Plans, Legislations and Policies

Individual and corporate efforts, regional and local plans, policies and legislations

made by constituted authorities based on recommendations from research studies made

15

by different organizations and interest groups prescribes, determines and effects land use

decisions, patterns and schemes. Zoning, preferential tax treatments, purchase of

development rights and Transfer of Development Rights are examples of policies which

influences land use. Zoning is a set of regulation that specify where different land use

types can occur and the magnitude and limits of development of such lands; preferential

tax treatment is given by government to tax payers to preserve land in its current use;

Purchase of development rights involve payment for development rights to land owner of

a valuable land by government or non-profit agency to prevent development of such land

for other uses other than the present use even if it is to be sold by the owner the land use

type must be preserved. Example includes wetlands or wildlife habitats; Transfer of

development rights is given to owners of land who wants more land for a particular use

other than he is allowed by the law, this allows him to secure the right for such an

acquisition from land owners in other areas where such land use is allowed.

2.24 Available Resources

The natural state of the physical environment in terms of soil, climate, topography

and vegetation characteristics determines the characteristics, quality and capability of

such land resource available, what it could be used for (land use type) and the extent to

which it could be used (intensity). A forest may be home to heavy logging activities or

modified into agricultural lands or plantation fields but heavy logging in woodlands and

savanna is not likely due to the fact that the nature of the physical environment does not

support that.

Plantation agriculture might not be feasible in an urban city due to the fact that

there might not be enough land for such a function in a city and because the function and

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nature of city structures conflicts with agricultural land use of such a magnitude. The

size of lands available and the area covered by a certain land cover type in a particular

location determines the possible land use types and the intensity of such land uses in such

an area.

2.3 Land Use Study

Land use has been studied in a variety of ways depending on what such study is

designed to achieve or what information we intend to produce from such study. The

earliest study of land use attempted the description and explanation of land use patterns

and the prediction of future changes in land use pattern using various models. Such

attempts include Burgess (1925), Hoyt (1939) and Harris and Ulman (1945). Burgess

concentric zone and Hoyt‟s sector model has its use centred around the description and

prediction of changes in basic structure of land use pattern while the multiple nuclei

theory of Harris and Ulman was intended as a summary of the urban land use pattern at a

given point in time. However, the earlier land use model had so many limitations and

their use was criticized by a number of scholars for variety of reasons. Many of them

were only applicable to the study of urban land use; for instance Burgess theory focused

on urban residential patterns while Hoyt and Harris and Ulman only studied the structure

of all urban land use which are not usually applicable in studying the structure of rural

land use. Many of the models were criticized for not been in tune with the reality on

ground in many places but are were only applicable in their places of origin, an example

is the Mann‟s model (1956) patterned according to the history of British cities in the post

second world period and so many of such models were criticized for being myopic in

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view, not essentially universal and not contemporary with current trends in the present

day world.

Today, more contemporary methods are being used in the study of land use;

unlike earlier methods and models that imposed models of land use pattern on areas and

try to see how land use structure of different areas conform to such models for whatever

advantage they think such models have over the others, more contemporary methods

collects information either directly or indirectly without contact with the land and use

such information collected in producing land use / cover maps, analyzing land use

structures and proffering solutions to problems arising from such land use structures.

2.31 Contemporary land use models

More recently, different models has been adopted by different scholars and

professionals in describing land use patterns and predicting or projecting future land use

and / or land cover depending on nature of their study. However, such models have been

classified into two broad categories: (a) models that predict total land use change for a

region, and (b) models that predict Land Use for specific parcels or grid cells (for vector

images). If the analyst wants to know the total amount of land use change that will occur

in a large region like a state, then the first type of model is appropriate. On the other

hand, if the analyst wants to know where in the region land use change will occur, or to

project what will happen at a specific place, then the second type of model is appropriate.

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2.311 Models to predict total Land Use

These models predict the total amount of land use or land cover change that will occur

for a region (county, state, etc.), but do not predict where in the region that change will

occur. For example, these models use equations or formulas to predict how much new

development will occur, based on projections of population. A simple model could

assume that for each new resident of a region, a fixed amount of land will be developed.

A more complex model will use an equation to project land use change, based on initial

population, population growth, available land, and other factors.

2.312 Models that predict Land Use for Specific Parcels or Grid Cells

This category of models can be subdivided in three broad categories:

1) Build out analysis, 2) Cellular Automata Models and 3) Agent based models.

2.3121 Build out Analysis

A build out analysis projects future land use based on zoning regulations within the

region of analysis. A build out analysis is used to estimate levels of residential,

commercial and industrial uses that might happen in the future, given a zoning

specification, and to visualize where that development will occur. Build out refers to a

hypothetical future where all the available land has been developed at the maximum

density allowed according to its zoned use.

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2.3122 Cellular Models

In these models, a region is subdivided into square cells that form a regular grid. For

each cell, an initial land use is measured. The analyst defines a set of rules that describe

the probability that a cell will transition from one land use to another. These rules depend

on the topography of the cell, its proximity via roads and highways to business centers,

and the pattern of land use in neighboring cells. The transition probabilities can be

estimated from historical data on land use. These models can be used to simulate the

spatial pattern of land use change over time.

2.3123 Agent Based Models

In contrast to cellular models, where the focus is on the interaction among neighboring

cells, Agent Based Models focus on the interactions among decision makers (individual

land owners, firms or institutions). Most Agent Based Models combine cellular models,

representing different land uses in the study area, with a model representing human

behavior. For example, an agent based model might simulate the decisions made by a

large number of farmers, each of whom is considering converting their farm to housing.

Because the price of vacant land depends on how much of it is available, each farmer‟s

decision affects the profits of all the other farmers.

In contemporary times, before producing maps of land use, a proper study of such

lands are done by field surveys; during such field surveys, a classification or

categorization schemes is chosen to suit the purpose of such study and such classification

schemes are used in generalizing, characterizing and classifying lands into land use types

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and in determining the extents of such land use types. Information gotten from such

surveys are used in producing land use classification maps which are used in stock

taking, land use analysis and future land use planning.

2.32 Classification Schemes

A Classification scheme is a set of rules used during land use surveys for generalizing;

characterizing and classifying lands into land use / cover types. A primary component of

mapping land use and land cover is adopting or developing a land cover classification

system or schemes. There are many land use and land cover classification schemes and

many of them are designed specifically for use with remotely sensed data. Many of these

classification systems often resemble or incorporate other classification systems in order

to maintain cohesiveness and allow for data integration. A hierarchical framework is

often implemented within such classification system; this type of framework allows the

level of detail to vary for different project scopes and for the creation land use and land

cover categories that are compatible with other classification systems (Foti et al, 1994).

Many of these schemes are based on a classification level system developed by James

Anderson and coauthors in 1976 for different scales of study.

Different organizations set up their classifications differently, because they are

interested in different aspects of land use and land cover. An organization whose mission

involves local economic development will want to distinguish between a school and an

office building, but may not care about the difference between cropland and forests while

an organization whose mission involves storm water management may distinguish

between cropland and forests but not between a school and an office building.

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Anderson et al (1967) developed a hierarchical land use and land cover classification

system for utilization with remote sensor data which has been adopted by the U.S.

Geological Survey for 1:250,000 and 1:100,000 scale land use and land cover mapping of

the United States. The Anderson classification system and or Anderson derived land use

and land cover classifications have been adopted in most contemporary land use and land

cover research utilizing remotely sensed satellite data.

A hierarchical classification framework is composed of different levels of land use

categories which are dependent upon the level of detail required by the project scope.

Level I categories are often broad classification categories with examples such as urban,

forest, agricultural land, and water classes. Level II categories offer more detail and are

usually subdivisions of the level I categories. Examples of level II categories are

coniferous forest, deciduous forest, and possibly mixed forest classes. Level III categories

are often employed in local studies which incorporate species level land classes such as

oak hickory forest or oak hickory pine forest (Anderson et al, 1976).

Anderson‟s classification combines information on land use and land cover, placing all

land into one of 9 level-I categories:

Anderson Level-I Categories

1. Urban or Built Up Land

2. Agricultural Land

3. Rangeland

4. Forest Land

5. Water

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6. Wetland

7. Barren Land

8. Tundra

9. Perennial Snow or Ice

Subcategories make finer distinctions. For example, Level-I Category 1 (Urban Land)

could be divided into Level-II subcategories such as:

One Possible Set of Level-II Subcategories

11. Low density residential

12. Medium density residential

13. High density residential

14. Commercial

15. Industrial

16. Institutional

17. Extractive

18. Open urban land, including parks and golf courses

Each of these subcategories also can be divided. For example, Level-II subcategory 14

(Commercial) could be divided to distinguish between office buildings and shopping

malls, or to distinguish among commercial buildings associated with different industries

(retail, health care, etc.).

The user has to be careful when comparing two different land use maps, because Level-

II categories can differ from map to map. Some maps even use different Level-I

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categories. Land use data obtained at any level of categorization certainly is not restricted

to any particular level of user groups or to any particular scale of presentation. Information

at Levels I and II would generally be of interest to users who desire data on a nationwide,

interstate, or statewide basis but more detailed land use and land cover data such as those

categorized at Levels III and IV usually will be used more frequently by those who need

and generate local information at the intrastate, regional, county/local government or

municipal level. It is intended that these latter levels of categorization will be developed by

the user groups themselves, so that their specific needs may be satisfied by the categories

they introduce into the structure.

On a small scale land use characterization can be done by a team of surveyors but these

is not practical on large scale; on a large scale, it is can done by land owner surveys which

involves determining the land use or land cover for each land parcel using appropriate land

use classification schemes. This has been done by organizations such as Census of

Agriculture surveys that is conducted every five years in every farm in the United States

where the quantity of land that a land owner has in different agricultural uses is mapped

other parcel specific mapping include the local Tax Assessment survey which is done to

determine the property taxes for each parcel and also state-wide mappings undertaken by

State Governments to maintain parcel maps showing national, state and local parks,

national and state forests, and agricultural lands. For example, Maryland State in the

United States maintains a state-wide parcel-specific database on land use.

However, the large scale land use characterization method used more contemporarily

is the use of Remote Sensing Capabilities. It usually involves the use of pictures taken by

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satellites and by airplanes to determine the land use and land cover for each piece of

land. This can involve someone mere looking at an aerial photo with a magnifying glass

or the use of computers in processing of data from hundreds of satellite images.

2.33 Use of Remote Sensing Capabilities

Before we can effectively capture the use of remote sensing, we need to ask ourselves

what remote sensing is all about.

2.331 What Is Remote Sensing?

Remote Sensing is the science and art of obtaining information about an object, area,

or phenomenon through the analysis of data acquired by a device that is not in contact

with object, area, or phenomenon under investigation (Lillesand and Kiefer, 1987). Some

others define it as the art, science and technology of obtaining information about an

object, area, or phenomenon without coming in contact with them, through the analysis of

Electromagnetic Energy. The Groupement pour le Development de la Teledetection

Aerospatiale (GDTA) journal of Remote Sensing (1990) titled Remote Sensing defines it

as the name given to the family of techniques used to observe the earth from a distance

and to process the data obtained concerning terrestrial objects.

Acquiring information about the Earth's surface without actually being in contact with

it (Remote Sensing) is a reading process where sensors detects or senses and records

reflected or emitted energy or electromagnetic radiation from the earth‟s surface,

processes, analyzes, and applies those information.

Remote sensing systems which measure energy that is naturally available are called

passive sensors. Passive sensors can only be used to detect energy when the naturally

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occurring energy is available. For all reflected energy, this can only take place during the

time when the sun is illuminating the Earth. There is no reflected energy available from

the sun at night. Energy that is naturally emitted (such as thermal infrared) can be

detected day or night, as long as the amount of energy is large enough to be recorded.

Active sensors, on the other hand, provide their own energy source for illumination. The

sensor emits radiation which is directed toward the target to be investigated. The

radiation reflected from that target is detected and measured by the sensor. Advantages

for active sensors include the ability to obtain measurements anytime, regardless of the

time of day or season. Active sensors can be used for examining wavelengths that are not

sufficiently provided by the sun, such as microwaves, or to better control the way a target

is illuminated. However, active systems require the generation of a fairly large amount of

energy to adequately illuminate targets. Some examples of active sensors are laser

fluorosensor and synthetic aperture radar (SAR).

Multispectral sensors acquire multiple images of the same target object at different

wavelengths (bands). Each band measures unique spectral characteristics about the target.

A spectral band is a data set collected by the sensor with information from discrete

portions of the electromagnetic spectrum.

In much of remote sensing, the process involves an interaction between incident

radiation and the targets of interest by the use of imaging systems although it also

involves the sensing of emitted energy and the use of non-imaging sensors which collects

data in diverse other forms other than electromagnetic radiation distributions; such forms

may include force distribution, acoustic wave distributions. The seven major elements

involved in remote sensing are described as follows

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1. Energy Source or Illumination - the first requirement for remote sensing is to have

an energy source which illuminates or provides electromagnetic energy to the target of

interest.

2. Radiation and the Atmosphere – as the energy travels from its source to the target, it

will come in contact with and interact with the atmosphere it passes through. This

interaction may take place a second time as the energy travels from the target to the

sensor.

3. Interaction with the Target - once the energy makes its way to the target through the

atmosphere; it interacts with the target depending on the properties of both the target and

the radiation.

4. Recording of Energy by the Sensor- after the energy has been scattered by, or

emitted from the target, we require a sensor (remote - not in contact with the target) to

collect and record the electromagnetic radiation.

5. Transmission, Reception, and Processing- the energy recorded by the sensor has to

be transmitted, often in electronic form, to a receiving and processing station where the

data are processed into an image (hardcopy and/or digital).

6. Interpretation and Analysis - the processed image is interpreted, visually and/or

digitally or electronically, to extract information about the target which was illuminated.

7. Application- the final element of the remote sensing process is achieved when we

apply the information we have been able to extract from the imagery about the target in

order to better understand it, reveal some new information, or assist in solving a

particular problem. These seven elements comprise the remote sensing process from

beginning to end.

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Electromagnetic energy may be detected either photographically or electronically. The

photographic process uses chemical reactions on the surface of light-sensitive film to

detect and record energy variations. It is important to distinguish between the terms

images and photographs in remote sensing. An image refers to any pictorial

representation, regardless of what wavelengths or remote sensing device has been used to

detect and record the electromagnetic energy. A photograph refers specifically to images

that have been detected as well as recorded on photographic film. Photos are normally

recorded over the wavelength range from 0.3 μm to 0.9 μm - the visible and reflected

infrared. Based on these definitions, we can say that all photographs are images, but not

all images are photographs. Therefore, unless we are talking specifically about an image

recorded photographically, we use the term image.

A photograph could also be represented and displayed in a digital format by

subdividing the image into small equal-sized and shaped areas, called picture elements or

pixels, and representing the brightness of each area with a numeric value or digital

number. The computer displays each digital value as different brightness levels. Sensors

that record electromagnetic energy, electronically record the energy as an array of

numbers in digital format right from the start. These two different ways of representing

and displaying remote sensing data, either pictorially or digitally, are interchangeable as

they convey the same information (although some detail may be lost when converting

back and forth).

As the human eyes see colour because it detects the entire visible range of

wavelengths and our brains process the information into separate colours so does sensors,

they only see very narrow ranges of wavelengths or colours. The information from a

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narrow wavelength range is gathered and stored in a channel, also sometimes referred to

as a band. We can combine and display channels of information digitally using the three

primary colours (blue, green, and red). The data from each channel or band is represented

as one of the primary colours and, depending on the relative brightness (i.e. the digital

value) of each pixel in each channel, the primary colours combine in different proportions

to represent different colours. When we use this method to display a single band or range

of wavelengths, we are actually displaying that band through all three primary colours

because the brightness level of each pixel is the same for each primary colour, they

combine to form a black and white image, showing various shades of gray from black to

white. When we display more than one channel or band each as a different primary

colour, then the brightness levels may be different for each channel/primary colour

combination and they will combine to form a colour image.

The three remote Sensing modes widely used in environmental surveys today are, the

aerial photographs or images, (camera remote sensing) the satellite and radar imagery.

However it should be noted that the term “images” and “imageries” are essentially the

same as they are both pictorial representation of detected and recorded electromagnetic

energy but their basic difference is the platform (moving or stationary medium on which

images or imageries are taken) from which they are taken. Images are usually products of

the platforms such as the human eye and camera platform while imageries are usually

products of radar and satellite platforms. Products of radar and satellite platforms can be

loosely referred to as images but products of the human eye and camera platforms cannot

at any instance be referred to as imageries.

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Less commonly used remote sensing modes in developing countries is the satellite and

radar remote sensing, but the least used is the radar remote sensing. We are going to be

examining the two mostly used remote sensing modes in developing nations like ours

which is the camera and satellite remote sensing.

2.3311 Camera Remote Sensing

This basically involves taking aerial photographs either at a near vertical or vertical or

low or high oblique angles from the kill of camera attached to specially adapted moving

aircrafts, helicopters, air balloons or parachutes which are analyzed and interpreted using

colour, tone, size, shape and textural properties. The products of camera remote sensing

are aerial photographs and topographical maps. Topographic maps are made by merging

sequences of aerial photographs or images using a stereoscope which enables us to see

perfect coincidence of overlaps of aerial photographs in Three-Dimensions. Types of

aerial photographs are known these include Panoramic, convergent, multi spectral and

continuous strip photographs. Both topographic base map and aerial photographs are used

in georeferencing (marking ground control point that had been accurately taken on the

field or accurately marked on an aerial photo or topographic base map on a satellite

imagery and inputing the geographical coordinates to register geographical coordinates of

sampled features on digital satellite imagery). Aerial photographs can be panchromatic

i.e. Black and white (B/W), Infrared (IR) black and white, Colour infrared (C.I.R.), and

colour photographs.

2.3312 Satellite Remote Sensing

Satellite remote sensing involves taking of imageries from heights above the ground

using via artificially erected space platforms called satellites at angles which may be

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vertical or oblique. Remote sensors on space platforms are programmed to operate in

different atmospheric windows or electromagnetic bands and make measurements using

detectors tuned to these specific wavelength frequencies which pass through the

atmosphere. Spectral reflectance characteristics of common earth surface materials are

located within the visible and near to mid-infrared range (Richards, 1986).

In most contemporary land use studies which employ remote sensing imagery from

multispectral sensors, the foremost task is the observation of spectral characteristics of

measured electromagnetic radiation from a target or landscape. Analysts develop

signatures based upon the detected energy‟s measurement and position in the

electromagnetic spectrum. A signature is a set of statistics that defines the spectral

characteristic of a target phenomenon or training-sites. Image analysts determine the

measurement of signature separability by determining quantitatively the relation between

class signatures. Signatures are refined by improved ground-truth and accuracy

assessment analysis. By utilizing the developed signatures in multispectral classification

and thematic mapping, the analyst generates new data for analysis (ERDAS, 1999).

Today, remote sensing image data of the Earth‟s surface acquired by spacecraft

platforms is readily available in a digital format. Digital remote sensing systems convert

electromagnetic energy (color, light, heat, etc…) to a digital form. Spatially, the data is

composed of discrete picture elements, or pixels, and radiometrically it is quantized into

discrete brightness levels (ERDAS, 1999). The great advantage of having data available

digitally is that it can be processed by computer either for machine assisted information

extraction or for the enhancement by an image interpreter.

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Resolution is an important term commonly used to describe remotely sensed imagery.

Resolution is the quality or property of a pixel unit of an image or imagery. However,

there are four distinct types of resolution that must be considered. These four types of

resolution are spatial, spectral, radiometric, and temporal. These resolution characteristics

help to describe the functionality of both remote sensing sensors and remotely sensed

data. The ERDAS, Earth Resources Data Analysis System, Field Guide (1999) further

describes each type of resolution as described below.

Spatial resolution is the minimum size of terrain features that can be distinguished

from the background in an image, or the ability to differentiate between two closely

spaced features in an image. It is also defined by the area on the ground that a pixel

represents in a digital image file. Large scale in remote sensing refers to imagery in

which each pixel represents a small area on the ground. Small scale refers to imagery in

which each pixel represents a large area on the ground.

Spectral resolution refers to the number and dimension of specific wavelength

intervals in the electromagnetic spectrum to which a sensor or sensor band is sensitive or

can record. Wide intervals in the electromagnetic spectrum are referred to as coarse

spectral resolution, and narrow intervals are referred to as fine spectral resolution.

Radiometric resolution refers to the dynamic range, or number of possible data files

values in each band. This is referred to by the number of bits into which the recorded

energy is divided. The total intensity of the energy, from 0 to the maximum amount, the

sensor measures is broken down, for example, into 256 brightness values for 8-bit data.

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The data file values range from 0, for no energy return, to 255, for maximum return, for

each pixel. Landsat TM imagery is classified as 8-bit data.

Temporal resolution is a measure of how often a given sensor system obtains imagery

of a particular area, or how often an area can be revisited. The temporal resolution of

satellites is on a fixed schedule. The fixed schedule of satellites allows for more repetitive

views. This revisit capability makes it possible to use several passes, perhaps covering

two or three seasons or multiple years, for interpretation. In addition, new satellite

technology is incorporating pointable or directional sensors allowing for even quicker

revisit capabilities. Temporal resolution is an important factor to consider in change

detection studies. Landsat 5 can view the same area of the globe every 16 days (Wilkie &

Finn, 1996).

Remote sensing has become an important tool applicable to developing and

understanding the global, physical processes affecting the earth. As current trends

continue, additional and higher resolution satellites will become available providing the

means to produce more accurate land use and land cover maps characterized by finer

levels of detail.

2.332 Limitation of the Remote sensing Imageries

Remotely sensed imageries are one of the most important sources of spatial data for

environmental studies. They are images obtained by remotely placed sensors located at

variable heights in orbits level. Remotely sensed data allows land use and land cover to

be mapped quickly, relatively cheaply and when frequently needed. With improved

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mapping of rapidly changing areas, planners and researchers will be able to better address

issues associated with land use analysis. However the type of data used has influence on

the accuracy of the classification. Each remote sensing application has specific demands

on the amount of area to be covered, the frequency with which measurements will be

made, and the type of energy that will be detected. Thus, a sensor must provide the

spatial, spectral, and temporal resolution necessary to meet the needs of the application.

While it is commonly thought that greater spatial resolution is the key to better land use

classification, finer spectral and radiometric resolution also have potential advantages

that remain only partially explored. (Cushnie, 1987).

Some of the most commonly used remote sensing data sets for mapping land use

and land cover in developing countries including Nigeria are those from Landsat, SPOT

and more recently, NigeriaSat-1 satellites The Landsat sensors are known to have greater

spectral resolution and a longer time series, while SPOT provides better spatial

resolution. Less traditional sensors may provide additional information that can improve

mapping accuracy. The NigeriaSat-1 has 3 spectral bands as compared 6 bands for

Landsat (not including the thermal band) and 4 bands for SPOT‟s multispectral scanner.

(Salami, A.T. et al, 1999).

Among the factors that may influence classification accuracy are a sensor‟s

spatial, radiometric and spectral resolutions. Spatial resolution describes the size each

pixel represents in the real world. For example, a satellite with 30 m resolution produces

pixels that measure a 30 x 30 m area on the ground. Radiometric resolution, in contrast,

is the smallest difference in brightness that a sensor can detect. A sensor with high

radiometric resolution has very low noise. Finally, spectral resolution is the number of

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different wavelengths that a sensor can detect. A sensor that produces a panchromatic

image has very low spectral resolution, while one that can distinguish many shades of

each colour has high spectral resolution.

Generally, spatial resolution is accepted as the most important factor of the three

for land use and land cover definition. For example, a study in Indonesia showed that

SPOT Multispectral (XS) images are better than Landsat Multispectral Scanner (MSS)

images for mapping of heterogeneous near-urban land cover because of SPOT‟s superior

spatial resolution (Gastellu-Etchegorry 1990). In heterogeneous areas, such as

residential areas, it has been shown that classification accuracies may improve by up to

20% as spatial resolution increases (Cushnie, 1987). This occurs due to the potentials of

urban features to blend together to form composite distinctive “urban signals” that can be

distinguished from other land covers.

Spectral resolution also affects the ease and reliability of land use classification.

For example, in the mapping of farmland and urban land uses in New Zealand (Gao and

Skillcorn 1998), used the Multi-spectral SPOT XS, because of its ability to reveal

vegetative land covers with its high spatial resolution. In cases where different land uses

have similar but separable spectral resolution, High spectral resolution will likely

improve mapping accuracy when land uses are spectrally inseparable (Cushnie, J.L.

1987).

However, most developing countries are constrained by shortage of funds and are

therefore unable to acquire the most appropriate data types for various purposes. In

Nigeria, the three types Landsat, SPOT and NigeriaSat-1 are the most readily accessible.

Landsat products up to 2003 are available almost without any costs, SPOT-1 data are also

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fairly commonly used as one of the first generation of high resolution imageries, made

available commercially by SPOT IMAGE Company and NigeriaSat-1 data are owned by

the Nigerian Government, also available without any cost. These images are of coarse

resolution but are the ones most readily accessible to researchers in Nigeria.

Available spectral bands either singly or as combined composites cannot reveal all

information needed for a particular study, therefore they have to be displayed correctly or

combined correctly to reveal information needed for particular studies .For instance

Landsat Thematic Mapper sensor record electromagnetic radiation in seven bands. Bands

1, 2, and 3 are in the visible portion of the spectrum. Bands 4, 5, and 7 are in the

reflective-infrared portion of the spectrum. Band 6 is in the thermal portion of the

spectrum. The following list describes each of the seven TM bands and the information

they reveal:

Band 1 – Visible Blue, 0.45 – 0.52 um; useful for mapping coastal water areas,

differentiating between soil and vegetation, forest type mapping, and detecting cultural

features.

Band 2 – Visible Green, 0.52 – 0.60 um, the green colour Corresponds to the green

reflectance of healthy vegetation. It is also useful for cultural feature identification.

Band 3 – Visible Red, 0.63 – 0.69 um; useful for discriminating between many plant

species. It is also useful for determining soil boundary and geological boundary

delineations as well as cultural features.

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Band 4 – Reflective - infrared, 0.76 – 0.90 um; this band is especially responsive the

amount of vegetation biomass present in a scene. It is useful for crop identification and

emphasizes soil/crop and land/water contacts.

Band 5 – Mid - infrared, 1.55 – 1.74 um; this band is sensitive to the amount of water

in plants, which is useful in crop drought studies and in plant health analyses. This is also

one of the few bands that can be used to discriminate between clouds, snow, and ice.

Band 6 – Thermal - infrared, 10.40 – 12.50 um; this band is useful for vegetation and

crop stress detection, heat intensity, insecticide applications, and for locating thermal

pollution. It can also be used to locate geothermal activity.

Band 7 – Mid - infrared, 2.08 – 2.35 um; this band is important for the discrimination

of geologic rock type and soil boundaries, as well as soil and vegetation moisture content.

Different combinations of the TM bands can be displayed to create different

composite effects. The following combinations are commonly used to display images:

Bands 3, 2, and 1 create a true color composite. True color means that objects look as

though they would to the naked eye, similar to a photograph. Bands 4, 3, and 2 create a

false color composite. False color composites appear similar to an infrared photograph

where objects do have the same colors or contrasts as they would naturally. For instance,

in an infrared image, vegetation appears red, water appears navy or black. Bands 5, 4, and

2 create a pseudo color composite. (A thematic image is also a pseudo color image.) In

pseudo color, the colors do not reflect the features in natural colors. For instance, roads

may be red, water yellow, and vegetation blue. With the adequate knowledge of band

37

properties and the appropriate combination of Landsat TM bands, the extraction of

numerous themes, land use and land cover classes; can be achieved for various mapping

applications.

2.333 Problem of Remote Sensing In Developing Countries

The development of Remote Sensing techniques in the third world countries has

met with several problems. Some of these can be discussed under inadequate

infrastructure, inadequate financing, inadequate expertise and lack of technological

awareness. (Onyebuchi, 1993).

Infrastructure development involving the provision of material, finances and

manpower is the pivot on which the success of any technology resolve. Monitoring of the

environment including earth‟s natural resources need time-based data. Absence of recent

aerial photographic coverage of Nigeria at the Federal Surveys Department makes studies

and mapping of selected parts of the country difficult. Basic interpretation instrument like

pocket and mirror stereoscopes for teaching are by far too small in number in the tertiary

institutions. The acute shortage of equipment for digital image processing with

appropriate hardware and software system for research and teaching at higher degree

levels makes large scale adoption and meaningful contribution to the development and

utilization of the technology seemingly unattainable. Associated with equipment shortage

and maintenance is the persistent problem of unstable electric power supply which is

capable of causing serious damage to electronic hardwares.

The launching of Nigeria Sat 1 and the location of a Ground receiving Station in

Abuja for regular and sequential acquisition of images covering the country encourages

38

the present trends of acquisition of scenes on selective basis. However this is the only

satellite owned by a West African country and just one of the three owned by an African

country (others being Algeria and South Africa). Abuja Base Station is also the only

ground receiving station in Nigeria and the whole of West Africa; these are grossly

insufficient for data acquisition in the sub-region. This means that vast areas are neither

studied nor monitored for many years.

Dearth of Remote sensing specialists in various organizations employing the

techniques affects the growth of technology. Lacks of necessary equipment in tertiary

institutions also limit the scope of training where specialists are available. To cope with

the enormous environmental, earth and land resources management challenges of these

third world countries, more local Remote Sensing scientist with different background

need to be trained. Also the inability of some organizations and establishment to maintain

available equipments due to low technological competence handicaps the growth of the

technology.

Another problem is inadequate financing. Non-acquisition of remote sensing facilities

is linked to inadequate financing and prohibitive costs involving foreign exchange since

they are not locally made. Inability of research agencies to initiate researches into current

environmental degradation and natural resources conservation are to be blamed on

inadequate allocation of funds.

The insufficient utilization of Remote sensing technology in many developing

countries has been ascribed to lack of adequate awareness on the new technology among

those who allocate funds, manage resources, control advanced education and influence

professional careers. However, the development of remote sensing technologies in

39

developing countries can be achieved by a conscious effort by Government, private and

Non-Governmental organizations to increase their spending on sponsoring of training

programmes and organizing of short-term training courses on remote sensing

technologies, purchase and installation of necessary infrastructure, creation of awareness

at all levels and the channeling of such funds to the appropriate quarters.

40

METHODOLOGY

3.1 Materials Required

1. A Satellite imagery of Ile-Ife for classification

2. A Road map or Topographical map of Ile-Ife for Georeferencing

3. Computer System Unit with motherboard rating of not less than Pentium III

and operating System, Windows XP is advised because of the incompatibility (inability

of) of most of the available application softwares to work with lower version of

operating systems. It is the electronic platform for data classification, analysis and

presentation

4. Applications softwares (i) Image processing softwares used include ERDAS

IMAGINE 9.1 and ILWIS 3.2 for image processing operations, ILWIS 3.2 and ArcGIS

3.2a for image digitizing and vectorization, GEOCAL for conversion of coordinates

from one coordinate system to the other for Georeferencing and Microsoft Excel for

collating, recording and display of coordinate data. They are software programs written

for solving data classification and analysis problems (ii) Presentation and animation

softwares such as Microsoft PowerPoint, Macromedia Flash 8. They are software

programs written for the purposes of making general presentations and visualization of

changes using animated sequences.

5. Optical Scanners and digitizing tables of different sizes A4, A3, A2, A1 and

A0 for imputing images of aerial photographs and topographic base maps into the

computer.

6. Standard Garmin 12 GPS for marking coordinates of points in the field for

georeferencing of satellite imagery.

41

3.2 Methodology

The workflow of the methodology of this study like any other GIS-based study

is compartmentalized into three phases namely

(i) Data Collection

(ii) Image processing

(iii) Geo-Presentation

3.21 Data collection

This phase of the study requires the collection of both primary and secondary

data.

3.211 Primary Data

The primary data collected for this study were done by an initial reconnaissance

survey (Recce) followed by an intensive land use survey involving taking of GPS

readings of various locations in Ile-Ife and visual categorization of land uses in Ile-Ife.

3.2111 Reconnaissance Survey (Recce)

This involves an inventory of land resources, uses and management in the

study area with a view of capturing the spatial patterns of these features. The survey is

also used in updating the topographic base map of the area.

3.2112 Land Use Field survey

The old approach to land use/cover type in many parts of the developing world

involves the use of aerial photographs complemented with the traditional ground survey

techniques. The ground surveying provides the sample data which are used to interpret

the aerial coverage of the whole area of interest. This approach is however laborious,

time consuming and less reliable in terms of accuracy. They involve moving along and

42

across defined traverses all over the area to be surveyed at a walking speed but more

contemporarily used today is the taking of exact positions (elevations, latitude and

longitudes) of places using more accurate and less laborious ground remote sensing

device called Global Positioning Systems (GPS) which takes the coordinates of points

using the earth‟s electromagnetic field to pick up satellite signals for accurate

measurements of particular points on the earth at a very appreciable accuracy or error

level; usually below 10m. GPSs have different characteristics and different accuracy

levels.

The GPS readings of coordinates of highly conspicuous urban features such as

road junctions, turnings and T-junctions were taken for the georeferencing of the digital

imagery and creation of land use layers. Land use Survey also involves the

categorization of lands into their different uses.

3.21121 Land Categorization

The categorization of lands into their various uses is an essential part of the field

study and they are usually done by visual evaluation using a set of principles derived

from various categorization schemes. The most widely endorsed and used

categorization scheme is the Anderson‟s classification system; it has been certified by

the UN for most of their land characterization studies.

Most categorization schemes used in land characterization are hybrids of

different other categorization schemes, they are usually user tailored to meet the user‟s

demand and purposes of study.

3.211211 Land Categorization Principles

43

As generally prescribed by most categorization scheme used, Urban or Built-up

Land should comprise of areas of intensive use with much of the land covered by man-

made structures. Included in this category are cities, towns, villages, strip developments

along highways, transportation, power, and communication facilities, and areas such as

those occupied by mills, shopping centers, industrial and commercial complexes, and

institutions that may, in some instances, be isolated from urban areas like OAU is to

Urban Ile-Ife.

As development progresses, lands located in the midst of urban or Built-up areas

having less intensive or nonconforming uses are generally included in the urban or

built-up category. Agricultural land, forest, wetland, or water areas on the fringe of

urban or Built-up areas are not included except where they are surrounded and

dominated by urban development. The Urban or Built-up category takes precedence

over others when the criteria for more than one category are met. For example,

residential areas that have sufficient tree cover to meet Forest Land criteria will be

placed in the Residential category.

Residential land uses range from high density, represented by the multiple-unit

structures of urban cores, to low density, where houses are on plots of more than an

acre, on the periphery of urban expansion. Linear residential developments along

transportation routes extending outward from urban areas included in the residential

land category.

Areas of sparse residential land use, such as farmsteads are included in

categories to which they are related. In some places, the boundary will be clear where

new housing developments are adjacent to intensively used agricultural areas, but the

44

boundary may be vague and difficult to discern when residential development occurs in

small isolated units over an area of mixed or less intensive uses. Residential sections

which are integral parts of other uses may be difficult to identify but however, housing

situations such as those existing on military bases, at colleges and universities, living

quarters for laborers near a work base, or lodging for employees of agricultural field

operations or resorts are placed within the Industrial, Agricultural, or Commercial and

Services or institutional categories to which they belong.

Areas used predominantly for the sale of products and services are regarded as

Commercial areas. They are often adjoined by residential, agricultural, or other

contrasting uses which help to sustain them. Components of the Commercial and

Services category are urban central business districts, shopping centres in suburban and

outlying areas, junkyards, resorts, commercial strip developments along major

highways and access routes to cities like Gbagi in Ibadan; and so forth. The main

buildings, secondary structures and areas supporting the basic use are all included, they

include office buildings, warehouses, driveways, sheds, parking lots, landscaped areas

and waste disposal areas. Commercial areas may include some noncommercial uses too

small to be separated out. Central business districts commonly include some

institutions, such as churches and schools, and commercial strip developments may

include some residential units. When these noncommercial uses exceed one-third-of the

total commercial area, the Mixed Urban or Built-up category is used. There is no

separate category for recreational land uses since most recreational activity is pervasive

throughout many other land uses.

45

Recreational facilities that form an integral part of an institution should be

included as institutional land use category. The intensively developed sections of

recreational areas would be included in the Commercial and Services category. Various

educational, religious, health, correctional, and military facilities are also components of

Institutional land uses. All buildings, grounds, and parking lots that make up the facility

are included within the institutional unit, but areas not specifically related to the purpose

of the institution should be placed in the appropriate category. Auxiliary land uses,

particularly residential, commercial and services, and other supporting land uses on a

military base would be included as institutional land use category, but agricultural areas

that are not specifically associated with correctional, educational, or religious

institutions are placed in the appropriate agricultural category. Institutional units such as

churches, secondary and elementary schools would be mapable only at scales large

enough for such consideration and will usually be included within another category,

such as Residential or commercial as deemed fit.

Industrial areas are areas with a wide array of land uses ranging from light

manufacturing to heavy manufacturing plants. Light industries are differentiated from

heavy industries based on the type, number and density of building dedicated to the use,

the intensity of trucking service that the industry requires and uses, the volume of

threshold capital needed to start and run such industry effectively, the sophistication of

labour, equipments and technology employed, the volume of market and labour it

attracts and the value complexity and relative importance of the products being

manufactured.

46

Light industrial areas use relatively cheap and easily gotten raw materials such

as food substances, plant extract, earth materials and soil substances, their products are

usually less expensive processed food products, artworks, crafts etc. Heavy industries

use raw materials such as iron ore, timber, or coal. Included in this category are steel

mills, pulp and saw mills, electric power generating stations, oil refineries and tank

farms, chemical plants, and brick making plants. Stockpiles of raw materials and waste-

product disposal areas are usually visible, along with transportation facilities capable of

handling heavy materials.

Surface structures associated with mining operations are included in the

industrial category. Surface structures and equipment may range from a minimum of a

loading device and trucks to extended areas with access roads, processing facilities,

stockpiles, storage sheds, and numerous vehicles. Spoil material and slag heaps usually

are found within a short trucking distance of the major mine areas and may be the key

indicator of underground mining operations.

Transportation, Communications, and Utilities uses occur to some degree within

all of the other Urban or Built up categories; they usually are considered an integral part

of the land use within which they occur and can only be mapped separately at an

exceedingly large scale.

Farmsteads intermixed with strip or cluster settlements will be included within

the built-up land, but other agricultural land uses should be excluded. Mixed Urban or

Built-up areas consist of varieties of land uses, all of which occur so significantly as to

make classification under one particular use difficult.

47

3.212 Secondary Data

The data from other sources used for this study are images already taken at

heights near ground and far from the ground by camera sensors and imageries taken at

great heights via satellite sensors. Some of the data are obtainable in raw form while

some others have been pre-processed (radiometrically and geometrically corrected, and

georeferenced) for image analysis. However, the Secondary data used for this study

include Landsat Enhanced Thematic Mapper (ETM) 2002 imagery of Ile-Ife which was

obtained from the Centre for Space Science and Technology Education, OAU, Ile-Ife

and the electronic Road map of Ile-Ife which was obtained at The Department Of

Geography, OAU, Ile-Ife.

3.22 Image Processing

3.221 Pre-Processing

These are adjustment processes undergone at the base stations immediately after

data acquisition by satellite sensors. They are designed to adjust the resolution, clarity

(picture quality) and formats of imageries acquired to suit the studies they are to be used

for. Pre-processing adjusts the effect of natural and environmental phenomenon on

imageries; they include the reduction of noise effects from noise, vibration, cloud cover,

smog, smoke, sun burn, sun shade, strong wind and downpour. This could be done

using softwares such as ERDAS Imagine 9.1; ILWIS usually pre-processes file

automatically when creating bands during color separation processes.

They include: (i) Radiometric Enhancement (ii) Geometric Enhancement

Radiometric Enhancement: Linear stretching and filtering of low contrast

images for easier visualization

48

Geometric Enhancement: Conversion of images from satellite download formats

to readable formats.

3.222 Classification

There are two major methods of classifications built into image processing

softwares; they include

(i) Unsupervised (automatic) classification

(ii) Supervised classification

3.2221 Unsupervised (automatic) classification

The basic idea is that the computer separates the image using information

theory, into a classification that „best‟ (in an information-theoretic sense) differentiates

pixels. This method is however not used most of the time because it usually does not do

the classification according to that which had been accurately done on the field using

appropriate categorization or classification schemes; it may combine classes which may

not be necessarily compatible. The most reliable and widely accepted method of image

classification is the Supervised Classification.

3.2222 Supervised classification Method

The basic idea of this method is to train the computer to recognize landscape

elements by their spectral signatures in a particular band, assuming that we know what

is where in some training sites. For the purpose of this study, we will be using

Supervised Classification.

3.223 Pre- Classification

Before supervised classification can be done in ILWIS 3.2, there are pre-

classification processes that we have to embark on; they include

49

(i) Loading of the Coordinate system

(ii) Colour separation

(iii) Map List Creation

(iv) Georeferencing

(v) Domain or Class Creation

(vi) Sample Set Creation

(vii) Training of sites

To begin working with ILWIS 3.2, the following procedure is to be followed:

1. Click on the Start Button,

2. Go to All Programs

3. Navigate to ILWIS 3.2 Academic sub Menu and Click ILWIS 3.2 in the

Pop-up Menu.

50

Fig 2: Procedure 1

3.2231 Loading of the Coordinate System

This is done to load the appropriate coordinate system for the study been

undertaken. For Nigeria, the coordinate projection we use is UTM, the ellipsoid is

CLARKE 1880, the datum is Minna Nigeria and the Zone Number 31. It is done

following the procedures described below:

1. Click the file menu.

2. Navigate to coordinate system and click it.

3. A dialog box appears.

51

Fig 3: Procedure 2

4. Click on CoordSystem Projection and click OK.

5. It shows a new dialog box that helps you define the new coordinate projection

you intend to use.

52

Fig 4: Procedure 2

6. Click the projection button to chose the appropriate projection; in this case it

is the UTM.

53

Fig 5: Procedure 4

7. The above dialog box appears , from where you chose the ellipsoid and the

Datum system by clicking there respective buttons and choosing the appropriate

options; the ellipsoid to be used by us is CLARKE 1880 while the Datum

system is MINNA Nigeria while our Zone number is 31.

54

Fig 6: Procedure 5

8. Choose the ellipsoid applicable Clarke 1880.

55

Fig 7: Procedure 6

9. Choose the Datum applicable: Minna Nigeria.

56

Fig 8: Procedure 7

10. Enter the Zone Number applicable: 31.

11. Click OK to leave the dialog box.

The Next is process is colour Separation.

3.2232 Colour Separation

Colour Separation or band creation involves the creation of colour bands to suit

the objective of the study. It is done following the procedures described below:

57

Fig 9: Procedure 8

1. Click on operations menu

2. Navigate to the image processing sub-menu and click color separation under

it.

58

Fig 10: Procedure 9

4. Click the colour band that you intend to create individually, say Red; click

the name of the file of the imagery from which the bands are created and

name the colour band; then click show on the dialogue box.

5. It first takes you to another dialogue box where you indicate your display

options.

59

Fig 11: Procedure 10

6. Click OK after you have indicated your display options to show the individual

band you have just created. An example of the individual band created is as seen

below.

60


7. Repeat the process for the other bands needed for the study; in this case

green and blue.

Next is Map list Creation.

3.2233 Map List Creation

This is done to create a list of the color bands needed for this study. It is done

using the procedures described below:

1. Click on file menu

2. Navigate to map list sub-menu and click it.

61


3. A dialog box appears, create a map list name and click on the insertion

button in between the two windows in the dialogue box to insert the bands

earlier created by colour separation and click OK

62


Next is georeferencing.

3.2234 Georeferencing

This involves defining or referencing features the way they are in relation to the

Globe Earth using the appropriate coordinate system suitable for the locality being

studied. It is usually done by marking the coordinates of conspicuous and easily

recognizable features on the imagery using previously georeferenced satellite imageries,

aerial photographs, topographical maps, street maps or even previously taken GPS

readings as Ground control points (GCPs) and registering them in the GIS environment

as tie lines at the appropriate coordinate system suitable for the area under study. To do

this, we follow the procedures described below:

63

1. Click on file Menu.

2. Go to create sub-menu and then click GeoReference under it.


3. The dialog box below appears

64


4. On the dialog box, give the georeference a name, Choose GeoRef Tiepoints

option, the name of coordinate system and the map list earlier created and

Click OK.

5. The dialog box below appears, fill in the display options in the correct order

(123, RGB) and click OK to go to the GeoReference editor window.

65


6. Select GCPs (Ground Control Points) and the add tie lines dialog box appears.

7. Register the UTM values of those GCPs into the X and Y axis column of the

add tie lines dialog box as appropriate.

66


8. Keep adding Tie lines until the Sigma Value drops to a little above or below

0.5 to ensure a high accuracy level. For the purpose of this study my sigma

was 0.516

67


68


The Next process is Domain or Class creation.

3.2235 Domain or Class Creation

This helps in entering classes of land uses and land covers observed in the study

area.

This is done by following the procedures described below:

1. Click the file Menu, Navigate to domain and click it.

69


2. A dialog appears, type in domain name and click OK

70

Fig 22 Procedure 21

3. A new window appears, it enables you create land use and cover classes or

see those that have been created in the process of training sites.

71


4. To add classes; click on edit menu in the domain window and navigate to add

item, then click it. It then brings out a dialog box where you can add class name and

code.

72


5. Click OK after indicating the necessary parameters.

6. Repeat this for all other classes.

3.2236 Sample Set Creation

This is done to enable computer to be able to train sites in the study area.

This is done by following the procedures described below.

1. Click on file menu

2. Navigate to sample set sub-menu and click it

73


3. It brings out a dialog box; fill in it the name you intend giving the sample set,

and the name of the domain and map list you created earlier and click OK.

74


4. It brings out a dialog box to set the display options; indicate the right order

(RGB) of the band composite and click OK to go to the sample set editor.

75


5. The sample statistics window also opens with the sample set editor.

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Training of Sites

This involves selecting enough sample sites for each class created so as

to train the computer to recognize the classes that we are about to classify the

study area into.

To train the computer to recognize a class, you follow the following

procedures:

1. Use the Normal tool in the sample set editor to select the

rectangular samples of the class all over the imagery.

2. Right click as soon as you finish selecting a sample site and

click edit on the pop up menu

77


3. A dialog box appears where you can fill in the right class for the site selected,

after filling in the class, click OK to register the sample site.

78


79


4. Repeat this for all other classes.

3.224 Classification Procedure

The analyst selects the land use/land cover legend (based on an existing

system). If on inspection of the image it is obvious that some classes are divided into

several spectral groups, the legend may be split accordingly. Example: forest in sun and

shade. These will be classified separately and then combined in the final map.

80

The computer is made to allocate to each cell in the complete image a land use /

cover class based on its cell value in the selected bands according to the classification

options such as maximum likelihood, minimum distance to centroid, bounding

parallelepiped, box classifier, prior probability, minimum mahalanobis distance.

Usually used is the maximum likelihood because it gives the most accurate results. The

classified map will then be digitized i.e. made into real maps by tracing out the

boundaries and outlines. The procedure for classification is as illustrated below.

1. Click on operations menu, navigate to classify and click on it.


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2. It brings out a dialog box asking you for the name of sample set made earlier

and the classification options; click the name of sample set you created from the drop

down menu by the sample set option, choose maximum likelihood for classification

method and name the image you are classifying and click on Show button.


82

3. It brings out a dialog box showing display option, choose the appropriate

options and click OK

.


4. It brings out the classified image of Ile-Ife. After this you can then digitize the

classified image.

83


3.225 Digitization or Segment Map Creation

This involves the transformation of classified images in raster form into vector

primitives of points, lines and polygons by the process vectorization or polygonization.

The map vectorization will be done in such a way that different layers (themes)

are created. These themes includes the boundary of the study area, various land use /

cover types of the study area and creation of different layers. All this are done in ILWIS

3.2.

84


Digitization is however followed by the presentation and display of the data

image statistics in numerical and graphical form.

3.23 Geo-Presentation or Result Presentation

This involves the presentation of land use / Cover information extractable from

the image analysis of the study area in numerical, graphical, written and geographic

forms, either electronically or on paper. Geo-Presentation comes in two forms; namely

Image Statistics Display and Overlay Operations.

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3.231 Image Statistics Display

This is the display of the statistics of the classified image in numerical, graphical

and written form, either electronically and on paper. This is done by following the

following procedure:

1. Click on the image file of the layer that you intend to display its

statistics on the work frame.


2. Right click on the layer and navigate to statistics, then click on

histogram sub menu.

86


3. A dialog box is displayed, so that you could change the layer you intend to

display if you so choose, click on the show button after confirming your options to

display the image statistics for the map layer which in this case is either a land use or a

land cover.

87


Below here is a sample for the image statistics displayed

88


We can export the digitized image with many layers such as Bare soil,

Vegetation, Water Body, Built-up, Wetlands, Rivers, Roads, institutional land

uses, residential land uses and commercial land uses to Arcview GIS 3.2a image

were a legend can be added and the colours of classes can be Changed if they

are not representative of the features being used to represent them. For instance,

change water body to blue, secondary vegetation to green and so on, so as to

make them real maps which may be left in electronic form or printed in

hardcopy.

89

3.232 Overlay Operations

This involves the Geo-visualization of land use / cover as single layers and also

as overlays for visualization of the spatial structure and dimensions of land use classes

in Ile-Ife. This is usually also done in Arcview GIS 3.2a image following the procedure

described below.

1. Click OK on the first screen after opening Arcview 3.2a to open with a new

view.


2. Click YES Option to add data to the view

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Click the files of the layers in their appropriate file locations to add them to the

view one after the other.

3. Arrange layers one after the other (overlay) in the sequence you

would want them to appear in the layout. Overlays are usually made

with linear features like roads and rivers arranged on top of polygon

91

features in the view window because putting polygon features over

linear features will block the visibility of the linear features.


Place the map in Layout, then print it out in hardcopy or store in hard disk as

soft copy.

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Below here is a diagrammatic representation of the workflow for this study.

Fig 44: Flowchart of the Methodology

IMAGE PROCESSING: USING ILWIS 3.2 COORDINATE REGISTRATION

RADIOMETRIC ENHANCEMENT

GEOMETRIC CORRECTION

PRE-CLASSIFICATION: Loading of the Coordinate system, Colour

separation, Map List Creation, Georeferencing, Domain or Class Creation, Sample

Set Creation and Training of sites

SUPERVISED CLASSIFICATION AT MAXIMUM

LIKELIHOOD

DIGITIZING OR SEGMENT MAP CREATION

DATA COLLECTION: PRIMARY DATA:

RECONNAINSANCE SURVEY

LAND USE FIELD SURVEY: Marking Ground Control Points Using GPS and

Land Categorization

SECONDARY DATA: FROM THE CENTRE FOR SPACE RESEARCH AND

TECHNOLOGY EDUCATION, OAU, ILE-IFE AND THE CARTOGRAPHIC/MAP

LABORATORY OF THE DEPARTMENT OF GEOGRAPHY, OAU, ILE-IFE

GEO-PRESENTATION OR RESULT

PRESENTATION: IMAGE STATISTICS DISPLAY

OVERLAY OPERATIONS

RESULTS

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Limitation of the Study

It should be noted that embarking on this study is not without its own

limitations. The resolution of the imagery used seems not to go beyond Level -1

classification due to the poor resolution of the imagery used (LandSat ETM

2002). Many areas and features were not easily located as imageries appear to

pixellate easily when certain degree of detail is required. In identifying land

uses for more detailed analysis such as this study requires, higher spatial

resolution imageries such as Quick Bird and IKONOS are required although

they are not readily and cheaply available like the LandSat imagery we used for

this study which is mostly obtained free.

In classifying the land uses, into 3 generalized key land uses, we had to

use our knowledge of those areas and coordinates collected from the field to

draw land use boundaries for the study area. For instance, the settlements along

the road from May fair to Sabo which represents the central business district

(CBD) of Ile-Ife were all considered and marked on the imagery as commercial

land use areas by digitizing it as a separate layer using the GPS coordinates

taken during the field survey. Institutional land use areas such as OAU Campus,

environs of OAUTH Complex and 7-day Adventist areas were also marked and

digitized separately as institutional land use areas.

94

CHAPTER FOUR

RESULT AND ANALYSIS

This chapter is designed to present and analyze the observation gotten from the

field survey and GIS analysis of land uses and land cover in Ile-Ife. In the course of our

study, we identified five major land covers and three major land uses; we produced a land

use characterization map of Ile-Ife and compiled the statistics of all the land use/land

covers of Ile-Ife.

4.1 Observations

The five key land use cover identified include Built-Up Areas or Built-Up

settlements, Vegetation, Bare Soil, Water Body and Wetland while the three key land use

areas identified include Residential, Commercial, and Institutional Land Use areas; other

land uses occur pervasively all over Ile-Ife and are not regarded as separate land use

categories because they don‟t measure up in terms of concentration and density to change

the status of those areas and be regarded as separate categories.

4.2 Land Use Characterization Map

The final land use characterization map of Ile-Ife is produced in Arcview 3.2a by

overlaying layers or segment maps of land covers and land uses created in ILWIS 3.2 by

image digitization to form one whole land use characterization map. The final land use

characterization map produced is shown below.

95

Fig 45: Land Use characterization map of Ile-Ife.

Source: Author‟s Work (2008)

96

4.3 Image Statistics Display

From the classified image of Ile-Ife produced in ILWIS 3.2, the areal extent and

percentage of the land covers and land uses within Ile-Ife can be gotten and displayed in

tabular form. This is shown in the tables below.

Table 1: Table showing the areal extent and percentage covered by the key land

cover types and land use types in Ile-Ife.

Land use/cover

Area covered (km2)

Percentage (%)

Institutional Built-Up Areas

37.63

5.63

Commercial Built-Up Areas

5.29

0.79

Residential Built-Up Areas

172.59

25.81

Vegetation

407.07

61.16

Water Body

0.98

0.15

Wetland

8.00

1.20

Bare Soil

35.27

5.27

Total

668.83

100.0


Based on the Result of the image analysis, the estimated total land area of Ile-Ife

is 668.83 Km2 with 407.07 Km

2 (61.16%) of it covered by Vegetation, about 172.59

Km2

(25.81%) is covered by residential built up, another 37.63 Km2

(5.63%) is covered

by institutional Built-Up, about 35.27 Km 2

(5.27%) is covered by Bare soil, about 8.00

97

Km2 (1.20%)

is covered by wetlands, about 5.29Km

2 (0.79%) is covered by commercial

built up while remaining 0.15% (0.98 Km2) is covered by pockets of water bodies.

Institutional Built-

Up AreasCommercial Built-

Up AreasResidential Built-

Up AreasVegetation

Water Body

Wetland

Bare Soil

Chart 1: Pie chart showing the percentage of land cover types and land use types

in Ile-Ife.


0

50

100

150

200

250

300

350

400

450 Institutional Built-

Up Areas

Commercial Built-

Up Areas

Residential Built-

Up Areas

Vegetation

Water Body

Wetland

Bare Soil

Chart 2: Bar chart showing the percentage of land cover types and land use types

in Ile-Ife.


98

Table 2: Table showing the areal extent and percentage covered by the key land

cover types in Ile-Ife.

Land Cover

Areal Extent (km2)

Percentage (%)

Built Up Areas

215.51

32.22

Vegetation

409.07

61.16

Water Body

0.98

0.15

Wetlands

8.00

1.20

Bare Soils

35.27

5.27

Total

668.85

100.0


From this statistics, about 409.07 km2 (61.16 %) of land in Ile-Ife is covered by

Vegetation, about 215.51 Km2

(32.22 %) is covered by Built-Up settlements, about 35.27

Km2 (5.27 %) is covered by Bare Soils, about 8.00 Km

2 (1.20 %) of total land area is

covered by Wetlands, while the remaining 0.98 Km2

(0.15 %) is covered by Water

Bodies.

Built Up Areas

Vegetation

Water Body

Wetlands

Bare Soils

Chart 3: Pie chart showing the percentage of land cover types in Ile-Ife.


99

0

100

200

300

400

500

Built Up A

reas

Veg

etat

ion

Wate

r Bod

y

Wetla

nds

Bar

e Soils

Chart 4: Bar chart showing the percentage of land cover types in Ile-Ife.


Table 3: Table showing the percentages of land uses in the Built Up areas of Ile-Ife.

Land use/cover

Areal Extent (km2)

Percentage (%)

Built Up

215.51

100.0

Institutional Built Up Areas

37.63

17.46

Commercial Built Up Areas

5.29

2.46

Residential Built Up Areas

172.59

80.09

Total

668.83

100.0


Built-Up Areas in Ile-Ife represents about 215.51Km2

(32.22 %) of the total land

coverage area; out of the built up areas, about 172.59 Km2 (80.09%) are regarded as

residential land use areas; about 37.63 Km 2

(17.46 %) a re regarded as institutional land

use areas, while the remaining areas which constitute about 2.46 % (5.29 Km2) are

commercial areas.

100

Institutional

Built Up Areas

Commercial

Built Up Areas

Residential

Built Up Areas

Chart 5: Pie chart showing the percentage of the different built-up land use classes in Ile-

Ife.


0

50

100

150

200

Institu

tional

Built

Up

Are

as

Com

merc

ial

Built

Up

Are

as

Resid

ential

Built

Up

Are

as

Chart 6: Bar chart showing the percentage of the different built-up land use Classes in

Ile-Ife.


101

CHAPTER FIVE

SUMMARY AND CONCLUSION

5.1 Summary

This study has enabled us to identify the key land use cover and uses in Ile-Ife and

helped us obtain information on how they are distributed on the ground. The final

information obtained from this study is valuable for planning of land use in Ile-Ife.

In the course of our study, we identified five key land cover types in Ile-Ife; they

include Built-Up Areas or Built-Up settlements, Vegetation, Bare Soil, Water Body and

Wetland. We also identified three key land use types; they include Residential,

Commercial, and Institutional Land Use areas.

Based on the image analysis, the estimated total land area of the study area is

approximately 668.83 Km2 with 407.07Km

2 (61.16%) of it covered by Vegetation,

mostly secondary vegetation since most of the natural vegetation had been degraded and

depleted in an attempt to develop. About 172.59Km2

(25.81%) is covered by residential

built-up settlements, another 37.63 Km2

(5.63%) is covered by institutional built-up

settlements, about 35.27 Km 2

(5.27%) is covered by Bare soil, about 8.00 Km2 (1.20%)

is covered by wetlands, about 5.29 Km2

(0.79%) is covered by commercial built-up

settlements while remaining 0.15% (0.98 Km2) is covered by pockets of water bodies.

The total area of built-up settlements in Ile-Ife put together is about 215.51 Km2

representing about 32.22 % of the total land area in Ile-Ife.

5.2 Issues and Recommendation

Although 61.16% of the total land area of Ile-Ife is covered by mostly secondary

Vegetation, if dynamic and purposeful planning aimed at sustainability is not embarked

102

on using the relevant technologies and information (like the one that this project is

designed to produce) the continued existence of the environment and its capacity to

continue to support life will be in doubt because of the significance of such forests since

the initial natural forests have been lost.

If the current secondary vegetation is not sustained there will be a great rise in

urban heat effect in Ile-Ife; the capacity of Ile-Ife to achieve sustainable water supply will

also be in doubt because there are only few water bodies to serve the growing urban

population. If the vegetation at heights within and outside Ile-Ife which acts as water shed

and drains to the area‟s most reliable drainage Basin, the Opa Drainage basin as observed

on the satellite imagery is touched, then there is great possibility of acute water Shortage

as most water are lost via run off. The touching of the vegetation also raises fear of

possible devastating flood in the land.

Lower rates of oxygen and higher rates of atmospheric pollution will also be

result of the loss of vegetation which acts as carbon sinks. The increase in runoff is also

likely to trigger the loss of farmlands to erosion which could cause crop failure and local

food scarcity. The local food scarcity is also capable of raising the general price level of

food and related items thereby causing hardship on the local economy.

Sustainable planning and development of Ile-Ife is a must and the implementation

of information technologies like we did in this study is a strong requirement for such.

Plans should be put in place to put a check on the rate at which secondary forests are been

depleted and degraded as a result of conversion for developmental purposes because of

the future hazardous implications of such a trend.

103

Sustainable developmental projects designed to stabilize the ecosystem such as

tree planting and agroforestry can be embarked on to prevent an eventual total loss of the

secondary forest to urban development.

104

REFERENCES

James R. Anderson, Ernest E. Hardy, John T. Roach, And Richard E. Witmer

(1976) “A Land Use And Land Cover Classification System For Use With Remote

Sensor Data” United States Government Printing Office, Washington. Pg 7-23.

Cushine J.L (1987) “ the Interactive Effect of Spatial Resolution and Degree of

internal Variability within land–cover types on classification Accuracies”

Photogrammmetic Engineering & Remote Sensing . Pg 15-29.

Gao. J and Skillcorn. D. (1998)“capability of SPOT XS Data in producing

Detailed Land cover Maps at the Urban Rural periphery” International Journal of

Remote Sensing. Pg 2877-2891

Gastellu-Etehegory, JP (1990) “ An Assessment of SPOT XS Landsat MSS Data

for Digital classification of Near-Urban Land cover”. International Journal of Remote

Sensing. Pg 225-235.

Jensen. JB (April 1982). “Detecting Residential land –Use Development at the

Urban Fringe” Photogrammetric Engineering & Remote Sensing . Pg 629-643.

Daniel Ayalew mengistu and Ayobami T. salami (2007) “Application of remote

sensing and GIS inland use/land cover mapping and change detection in a part of South

Western Nigeria” , Department of geography, Bahir Dar University, Bahir Dar, Ethiopia

and Space Applications and environmental science Laboratory, Institute of Ecology and

Environmental Studies, Obafemi Awolowo University, Ile-Ife, Nigeria.

David G. Rossiter (1994), Lecture Notes on Land Evaluation “ data sources for

Land Evaluation” Cornell University college of Agriculture & Life Sciences,

Department of soil, Crop, & Atmospheric sciences

105

Adeoye Nathaniel Olugbade (1989) “Geographical analysis of the urban land use

pattern in Ile-Ife”. Unpublished B.Sc Dissertation. University of Ile-Ife.

Brandon R. Bottomley, B.A. (1998) Mapping Rural Land Use & Land Cover

Change In Carroll County, Arkansas Utilizing Multi-Temporal Landsat Thematic Mapper

Satellite Imagery (1984 - 1999) University of Arkansas.

106

APPENDIX I

Fig 46: Scanned Image of Ile-Ife Roadmap

SOURCE: CARTOGRAPHIC/MAP LABORATORY OF THE DEPARTMENT

OF GEOGRAPHY, OAU, ILE-IFE

107

APPENDIX II

Fig 47: The Coordinate System used for the study

108

APPENDIX III

Fig 48: The Georeference editor of LandSat ETM+ 2002 Imagery of Ile-Ife.

Sigma value = 0.516

109

APPENDIX IV

POINTS LOCATION NORTHINGS (o) EASTINGS (

o)

P1 PARAKIN JUNCTION 07.4915 004.5305

P2 LAGERE ROUNDABOUT 07.4868 004.5477

P3 ADEREMI JUNCTION 07.4964 004.5068

P4 OAU CAMPUS GATE 07.4952 004.5217

P5 TOLL GATE 07.4942 004.4923

P5 SABO TRAFFIC POST 07.4913 004.5562

P6 MAYFAIR ROUNDABOUT 07.4899 004.5314

P7 SEVEN ADVENTIST 07.4890 004.5413

P8 ODUDUWA COLLEGE JUNCTION 07.4915 004.5565

P9 ILESHA GARAGE JUNCTION 07.4962 004.5683

P10 ONDO ROAD JUNCTION O7.4889 004.5340

Source: Author‟s Field Work.

Land use characterization of Ile-Ife

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