Complete Project Work

APPLICATION OF GEOGRAPHIC INFORMATION SYSTEM IN

MAPPING OPTIMAL SITE SELECTION FOR SOLID WASTE

COLLECTION POINT AND DISPOSAL IN NEW OWERRI, IMO

STATE

BY

OKEKE CHIKA M.

20081614735

A PROJECT SUBMITTED IN PARTIAL FULFILMENT

OF THE REQUIREMENTS FOR THE AWARD OF

BACHELOR OF TECHNOLOGY (B.TECH) DEGREE IN

GEOLOGY

DEPARTMENT OF GEOSCIENCES

SCHOOL OF SCIENCE

FEDERAL UNIVERSITY OF TECHNOLOGY

OWERRI

MARCH, 2014

ii

DECLARATION

I hereby declare that this project work titled “Application of Geographic

Information System in Mapping Optimal Site Selection for Solid Waste Collection

Point and Disposal in New Owerri, Imo State” was undertaken by the researcher

and has not been presented anywhere for any academic award.

Previous works of other authors used here has been duly acknowledged and

referenced.

………………………………. ..……………………..

OKEKE CHIKA M. DATE

20081614735

iii

CERTIFICATION

This is to certify that this study entitled "Application of Geographic Information

System in mapping optimal site selection for solid waste collection point and

disposal in new Owerri, Imo State" was done by Okeke Chika Marcyprian

with the registration number 20081614735 and a final year student of Department

of Geosciences in the school of science, Federal University of Technology Owerri.

…………………………. …………………

Dr. C.C.Z. Akaolisa Date

(Supervisor)

…………………………. …………………

Prof. K.K. Ibe Date

(Head of Department)

…………………………. …………………

Prof. F.O.U. Osuala Date

(Dean, School of Science)

…………………………. …………………

External Examiner Date

iv

DEDICATION

This work is dedicated to the glory of the Almighty God for his mercies and

kindness towards its success.

Also, to my lovely father Mr. Marcel Okeke and mother Mrs. Edith Okeke.

v

ACKNOWLEDGEMENT

My profound gratitude goes to my supervisor Dr. C.C.Z Akaolisa of my department

for his encouragement, gracious time and constructive criticism structured towards

achieving an effective and successful project.

I also want to acknowledge my course adviser Dr. Alex Opara for his good advice

to me towards my academics in order to reach a goal of being an outstanding

student in my department. I will not fail to thank the Head of my Department, Prof.

K.K Ibe and other lecturers of my department for devoting their crucial time in

bringing me up to the real world of Geosciences.

I express my thanks to my guardian Mr. Albert C. Ndubizu, the General Manager of

Imo State Geographic Information Agency for releasing the GIS software needed

for the success of this work. My thanks also go to Okorondu Ugochukwu Victor

and to my fellow students in my department for their kind gestures and ceaseless

time in assisting me towards the success of this work.

I express my gratitude to surveyor Mr. Chinedu and his team from Imo State

Ministry of Land and Survey for releasing the layout maps of all the areas in the

study area. Also, not left behind are surveyor Mr. Marcel and town planner Mr. O.

Akolan of Owerri Capital Development Authority for their assistance in releasing

information and in decoding land use features on Owerri Master Plan map.

Finally, I am deeply recognizing the assistance of Chief Chris Onwuegbuchulam

(Ministry of Environment) despite his ill health and limit time painstakingly taught

and gave me an overview of how I will go about this project so as to achieve an

effective and successful work.

May God Almighty Bless You All.

vi

ABSTRACT

In Nigeria, waste disposal have been a problem both in the urban and rural areas.

Wastes are indiscriminately dumped on open plots of land and particularly along

streets rendering the roads impassable and reducing the aesthetic value of the area.

Optimum selection of waste collection points is therefore necessary in other to

prevent the indiscriminate dumping of waste which is hazardous to human health

and also to effectively and efficiently manage the solid waste to promote hygienic

environment. Site evaluation for waste disposal describes the important criteria used

in evaluating land for waste disposal. The factors to be considered in such

evaluations include: climate, topography, drainage, soil properties, groundwater and

surface water. GIS consists of a set of computerized tools and procedures that can

be used to effectively store, retrieve, overlay, correlate, manipulate, analyze, query,

display (both graphically and numerically) and disseminate land related

information. This study used Geographic Information Systems (GIS) as a solution

to select suitable locations for solid waste collection points and disposal land use

option in New Owerri. A total of 5 thematic maps determinants obtained from

different sources were employed for GIS operation. These include road map, river

map and (3) different land use maps (residential, commercial and public use land

uses) of the study area. These maps are the thematic data layers for GIS operation

and were collected as existing maps from different sources to serve the purpose of

manipulation and analyses so as to procure the most suitable site for collection point

of solid waste generated in New Owerri, Imo State. The maps were scanned,

digitized, georeferenced, and polygonized using AutoCAD drawing capabilities to

convert them into vector format and later exported to arc view 3.2a software for

analysis. The final analysis like buffering, overlay by union, clipping and query

operations display areas of preferred collection point for solid waste generated in

New Owerri, Imo State.

vii

TABLE OF CONTENT

PAGE

Title Page - - - - - - - - - - - i

Declaration - - - - - - - - - - - ii

Certification - - - - - - - - - - iii

Dedication - - - - - - - - - - iv

Acknowledgement - - - - - - - - - v

Abstract - - - - - - - - - - - vi

Table of Content - - - - - - - - - - vii

List of Figures - - - - - - - - - - xi

List of Tables - - - - - - - - - - xiv

List of Plates - - - - - - - - - - xv

Chapter One

1.0 Introduction - - - - - - - - - 1

1.1 Statement of the Problem - - - - - - - 3

1.2 Location of the Study Area - - - - - - - 4

1.3 Physiography of the Study Area - - - - - - 6

1.4 Hydrogeology of the Study Area - - - - - - 7

1.5 Aim of Study - - - - - - - - - 8

1.6 Objectives of Study - - - - - - - - 8

1.7 Scope of Study - - - - - - - - - 9

1.8 Significant of the Study - - - - - - - - 9

1.9 Limitation - - - - - - - - - - 9

Chapter Two

2.0 Geology of the Study Area - - - - - - - 12

2.1 Stratigraphy Of The Study Area - - - - - - - 13

viii

2.2 Previous Work - - - - - - - - - 20

Chapter Three

Designing, Creation and Analysis of Digital Spatial Database

3.0 Research Methodology, Results and Interpretation - - - - 26

3.1 Database Design - - - - - - - - - 26

3.1.1 View of Reality - - - - - - - - - 27

3.1.2 Conceptual Design - - - - - - - - 28

3.1.3 Logical Design - - - - - - - - - 30

3.1.4 Physical Design - - - - - - - - - 30

3.2 Data Acquisition - - - - - - - - 32

3.2.1 Data Source - - - - - - - - - 32

3.2.2 Data Conversion - - - - - - - - - 32

3.2.3 Geometric Data Acquisition - - - - - - - 33

3.2.3.1georeferencing - - - - - - - - - 34

3.2.3.2digitizing - - - - - - - - - 35

3.2.4 Attribute Data Acquisition - - - - - - - 35

3.3 System Design - - - - - - - - - 39

3.3.1 Hardware Requirement - - - - - - - - 39

3.3.2 Software Requirements - - - - - - - - 39

3.4 Database Creation - - - - - - - - 40

3.5 Database Maintenance - - - - - - - - 40

3.5.1 Data Quality - - - - - - - - - 40

3.5.2 Data Security - - - - - - - - - 41

3.5.3 Data Integrity - - - - - - - - - 41

3.6 Spatial Data Analysis, Result Presentation and Interpretation - - 41

3.6.1 Introduction - - - - - - - - - 41

ix

3.6.2 Criteria for Selecting Suitable Solid Waste Collection Points - - 43

3.6.3 Cartographic Modelling - - - - - - - - 44

3.7 Spatial Analyses Performed - - - - - - - 47

3.7.1 Digital Mapping Processes on Map of New Owerri - - - 47

3.7.2 Buffering Operation - - - - - - - - 50

3.7.2.1 Analysis of Buffering Operation - - - - - - 51

3.7.3 Overlay Operations - - - - - - - - 55

3.7.3.1 Analysis of Overlay Operation - - - - - - 56

3.7.4 Polygon Clipping Operations - - - - - - - 65

3.7.4. 1 Analysis of Clipping Operation - - - - - - 65

3.8 Spatial Query/Search - - - - - - - - 68

3.8.1 Single Criteria Query - - - - - - - - 68

3.8.2 Multi Criteria Queries - - - - - - - - 79

3.8.2.1 Input for Multi-Criteria Queries - - - - - - 79

3.8.2.2 Output for Multi-Criteria Queries - - - - - - 80

3.9 Interpretation of Results - - - - - - - 88

Chapter Four

Setting Criteria for the Selection of the Most Final Suitable Disposal Sites for

Solid Waste Generated From the Collection Points

4.0 Research Methodology, Results and Interpretation - - - 98

4.1 Soil Types in Owerri West - - - - - - - 98

4.2 Soil Sampling - - - - - - - - - 99

4.3 Land Use (LU) And Land Cover (LC) Study in Owerri - - - 100

4.3.1 Methodology Of The Land Use And Land Cover Study - - - 102

4.3.2 Results And Interpretation Of The Land Use And Land Cover Study - 102

x

4.4 Owerri West Land Capability Indices Determination For

Solid Waste Disposal Land Use Option - - - - - 104

4.4.1 Laboratory Analysis of the Soil Samples - - - - - 104

4.4.2 Results and Interpretation of the Soil Sample - - - - 104

4.5 Owerri West Soil Erodibility Indices Determination

For Solid Waste Disposal Land Use Option - - - - 109

4.5.1 Laboratory Analysis Of The Soil Samples - - - - - 109

4.5.2 Erosion Prediction - - - - - - - - 109

4.5.3 Results And Interpretation - - - - - - - 110

4.6 Determination Of Soil Textural Characteristics

For Solid Waste Disposal Land Use Option at Avu Dumpsite - - 112

4.6.1 Soil Sampling at Avu Dumpsite - - - - - - 112

4.6.2 Laboratory Analysis of the Soil Samples at Avu Dumpsite - - 112

4.6.3 Results and Interpretation from the Soil Analysis at Avu Dumpsite - 113

Chapter Five

5.0 Discussion, Conclusion and Recommendation - - - - 118

5.1 Discussions - - - - - - - - - - 118

5.2 Conclusions - - - - - - - - - - 120

5.3 Recommendations - - - - - - - - - 122

5.4 Design Of A Modern Sanitary Landfill For The Area - - - 124

References - - - - - - - - - - 125 - 129

Appendixes - - - - - - - - - - 130 - 137

xi

LIST OF FIGURES

PAGE

Figure 1.1 Location Map of the Study Area - - - - - - 5

Figure 2.1 Geology Map of Imo State Showing the Study Area - - - 18

Figure 2.2 Geology Map of the Study Area - - - - - 19

Figure 2.3The Functional Elements of Solid Waste Management System - 23

Figure 3.1Designs and Construction of Phases of Spatial Database - - 27

Figure 3.2 An Entity Relationship Diagram Representing the

Spatial Data Structure for Vector Maps - - - - - 29

Figure 3.3 layout of composite map of the study area (New Owerri) - - 44

Figure 3.4 Cartographic model of the study - - - - - 46

Figure 3.5 Georeferenced New Owerri Map in an AutoCAD Environment - 48

Figure 3.6 Digitized map of New Owerri in an AutoCAD environment - 49

Figure 3.7 Layout of shape file of imported digitized Map of

New Owerri In Arcview 3.2a - - - - - - 50

Figure 3.8layout of the buffer of otamiri river and nworie stream - - 51

Figure 3.9 Layout of buffer of roads in New Owerri area - - - 52

Figure 3.10 Layout of buffer of public use theme in New Owerri area - 53

Figure 3.11 Layout of buffer of commercial land use theme in

New Owerri area - - - - - - - 54

Figure 3.12 Layout of buffer of residential land use theme in

New Owerri area - - - - - - - - 55

Figure 3.13 Layout of union of residential and public land use theme - - 57

Figure 3.13.1 Layout of shape file of union of residential and public

Land use theme - - - - - - - - 58

Figure 3.14 Layout of the union of residential and public and

Commercial land use theme - - - - - - 59

xii

Figure 3.14.1 Layout of shape file of the union of residential and public and

Commercial land use theme - - - - - - 60

Figure 3.15 layout of union of buffered road and river - - - - 61

Figure 3.15.1 layout of shape file of union of road and river - - - 62

Figure 3.16 layout of union of residential and public and commercial

and river and road land use (final union) - - - - 63

Figure 3.16.1 layout of shape file of final union - - - - - 64

Figure 3.17 layout of result of clipping operation (candidate site) - - 66

Figure 3.17.1 layout of shape file of clipping operation - - - - 67

Figure 3.18 query input and output of 10m from road - - - - 69

Figure 3.18.1 layout of result of road query in shape file - - - - 70

Figure 3.19 query input and output of 20m from residential - - - 71

Figure 3.19.1 layout of result of residential land use query in shape file - 72

Figure 3.20 query input and output of 40m from public land use - - 73

Figure 3.20.1layout of result of public land use query in shape file - - 74

Figure 3.21 query input and output of 20m from commercial land use - 75

Figure 3.21.1 layout of result of commercial land use query in shape file - 76

Figure 3.22 query input and output of river - - - - - 77

Figure 3.22.1 layout of result of river query in shape file - - - - 78

Figure 3.23 query input and output for suitable site within residential

and commercial land use - - - - - - 80

Figure 3.24 layout of suitable site within residential and commercial land use 81

Figure 3.25 query input and output for suitable site within residential

and public land use - - - - - - - 82

Figure 3.26 layout of suitable site within residential and public

Land use - - - - - - - - - 83

xiii

Figure 3.27 query input and output of suitable site within public and

Commercial land use - - - - - - - 84

Figure 3.28 layout of suitable site within public and commercial land use - 85

Figure 3.29 layout of union of suitable site within residential and

Commercial and public land use - - - - - 86

Figure 3.30 layout of most suitable site - - - - - - 87

Figure 4.1 Unified soil classification system-plasticity chart - - - 108

Figure 4.2Particle size distribution curve for Avu dumpsite soil - - - 117

xiv

LIST OF TABLES

PAGE

Table 2.1 Stratigraphic Units of the Niger Delta Basin - - - - 14

Table 2.2 Generalized Stratigraphy of the Study Area, Imo State - - 14

Table 3.1 logical design of data structure - - - - - - 30

Table 3.2 Physical design showing attribute table of land use map - - 31

Table 4.1 LU and LC Classes in 1986 - - - - - - - 103

Table 4.2 LU and LC Classes in 2000 - - - - - - - 104

Table 4.3 Summary of Laboratory, Field and Literature Data - - - 107

Table 4.4 Average erodibility index (K) of project locations and

predicted soil losses for the various communities

using Hudson (1995) equation - - - - - - - 110

Table 4.5 Standard erodability indices - - - - - - 112

Table 4.6: Summary of mean concentration of elements of soil samples

from Avu Dumpsites and its corresponding crustal abundance - - 116

xv

LIST 0F PLATES

PAGE

Plate 1 An overview of Avu dumpsite in Owerri, Imo State - - - 11

Plate 2 Polluted surface water due to leachate from solid waste dumpsite - 11

Plate 3 picture showing georeferencing and digitizing of scanned map - 37

Plate 4 picture showing analysis of the operation performed using

ArcView 3.2a software - - - - - - - - 38

Plate 5: A modern sanitary landfill designed to replace Avu open dumpsite - `124

1

CHAPTER ONE

1.0 INTRODUCTION

According to World Health Organization (WHO); solid waste is defined as useless,

unwanted or discarded materials arising from domestic, trade, commercial,

industrial and agricultural as well as from public services. Solid wastes are grouped

into two viz: biodegradable and non-biodegradable wastes. The biodegradable

wastes are the wastes that can easily be decomposed by the action of anaerobic

bacteria. Examples are organic matter such as food, fruit and vegetable waste. The

non-biodegradable wastes on the other hand are those that cannot easily be

decomposed by the action of the anaerobic bacteria. Examples are glass waste,

metal waste, rubber waste, plastic waste, medical waste, electronic waste (e-waste).

The collection and disposal of solid waste is today a major public health issue and a

vital factor affecting the quality of our Nigerian cities. It is one of the most intrinsic

causes of environmental problems today found mainly in the deterioration of

environmental parameters (air, land and water quality); which leads to destruction

of the aesthetic beauty of the environment, traffic jam, flooding, and environmental

air pollution. The increase in the volume of solid waste being generated daily in

most Nigerian cities especially in Owerri municipal is due to rapid population

growth of migrant population, urbanization and general economic growth (NEST

1991). In many Nigerian cities, the volume of solid waste generated has

overwhelmed the capacity of urban administrators to plan for its collection and

disposal.

The purpose of land use planning is to make the best, most sensible, practical, safe

and efficient use of each parcel of land. Mapping of a land unit for a particular

purpose is an aspect of Land use planning which ensures maximum and safe

utilization of land. Problems of improper waste disposal are always associated with

over population in developing countries of the world. This condition usually causes

2

environmental degradation leading to contamination/pollution of the environment.

In Owerri Municipality, solid wastes are mainly deposited in to open dumps and

landfills. This is because landfills are the simplest, cheapest and most effective

method of disposing wastes. For instance, wastes dumped at the Avu landfill in

Owerri West on the Port Harcourt highway are mainly solid wastes. The landfills

are poorly conceptualized in design with no adequate engineered systems to contain

landfill emissions. They are indiscriminately sited within the municipality without

regard to the nature of soil, hydrogeology and proximity to living quarters.

Also in Owerri Municipal, major solid waste generated is from residential and

commercial activities. The volume has recently grown above planned limits,

becoming a threat to the initial sufficient and effective collection and disposal of

solid waste. The unimaginable rapid population growth together with the poor and

unsustainable planning has given the municipality less significant and no suitable

solid waste collection point. Solid waste are disposed of indiscriminately; often on

open spaces such as markets places, road sides “as in Aladimma” and area A of

World Bank dump, in between dual major roads “as in Douglas Road dump”,

streets, river banks, gutters etc., and during heavy rain falls. This causes traffic jam,

imposes threats to the health of man and his environment at large.

However, the advent of Geographic Information System (GIS) in Nigeria has paved

way for the analysis of points for the collection and disposal of solid waste after

considering certain factors and criteria. GIS role in solid waste management is as

large as its many aspects of planning and operation which is dependent on the

spatial data.

1.1 STATEMENT OF THE PROBLEM

Owerri has experienced rapid population and industrial growth since it became the

capital state of Imo in 1976. The population and industrial growth have elevated the

3

generation of solid waste. The increase in the volume of solid waste being

generated daily in most Nigerian cities especially in Owerri municipal is due to

rapid population growth of migrant population, urbanization and general economic

growth (NEST 1991). The volume of this solid waste generated has overwhelmed

the capacity of urban administrators to plan for its collection and disposal. It is one

of the most intrinsic causes of environmental problems today found mainly in the

deterioration of environmental parameters (air, land and water quality); which leads

to destruction of the aesthetic beauty of the environment, traffic jam, flooding, and

environmental air pollution. In Owerri Municipality, solid wastes are mainly

deposited in to open dumps and landfills. This is because landfills are the simplest,

cheapest and most effective method of disposing wastes. For instance, wastes

dumped at the Avu landfill in Owerri West on the Port Harcourt highway are

mainly solid wastes.

However, new Owerri is an emerging town from Owerri municipal with some

areas densely populated producing large and voluminous waste that are dumped

illegally on untied roads (area A of world bank) and on open spaces. This attitude

although is less expensive, imposes higher cost to the society through pollution of

air, water and land and may extend to flooding due to blockage of drainage channel.

There has not being suitable points for collection and disposal of waste generated

by people living in this area. The efficacy of selecting solid waste collection points

anddisposal sitesare based on the consideration of three relevant issues namely;

Social, Environmental and Economic factors. It is important to determine best waste

collection and disposal points based on the efficient consideration of the above

three factors. Having seen that the problem of solid waste collection and disposal

are spatial problems too, it is therefore the aim of this project to apply GIS in

resolving it for new Owerri.

4

1.2 LOCATION OF THE STUDY AREA

The study area is New Owerri within Owerri Metropolis, Imo State. New Owerri by

land mass covers over 55% of Owerri metropolis area. It is located on the south

west part of Imo State in the dug deltaic formation of the Niger Delta basin, south

eastern Nigeria. The area is bounded by longitudes7o 00’E and 7o 05’20’’E and

latitudes 5o 27’4’’N and 5o 32’20’’N. New Owerri is bound in the north by New

Road, Irete, in the east by Old Owerri (along Nworie River), in the south by Nekede

(along Otamiri) area and in the west by Umuguma. New Owerri comprises World

Bank areas, Federal Low Cost Housing Estate area, Concord Hotel area, the new

State Secretariat area, Federal Secretariat area, Nekede extension, zoo area,

Umugwueze and UmuejechiNekede area, New Industrial Layout and other layouts

identified as Area A, B, C to Y and more.

5

Fig 1.1: Location Map of the Study Area

6

1.3 PHYSIOGRAPHY OF THE STUDY AREA

The prevalent climatic condition in the area is marked by two main regimes: the

rainy and the dry seasons. The rainy season is from April to October during which

the temperature varies from 25℃ to 29℃, and this season is associated with the

prevalent moisture-laden south-west trade wind from the Atlantic Ocean. The wet

season is also characterized by double maximum rainfall during which the first peak

occur in July and the second occurs in September with a mean annual rainfall of

2152 mm (Ezeigbo, 1990). The dry season starts in November, when the dry

continental northeastern wind blows from the Mediterranean Sea across the Sahara

desert and Samarian desert and down to the southern part of Nigeria. Due to

vagaries of weather, the August break sometimes occurs in July or early September.

Humidity is usually low and clouds are absent, during the dry season. The effect of

the harsh north easterly wind, also called Harmattan, is felt within the period. The

average monthly temperatures are high throughout the year. It has a mean annual

rainfall of about 2250-2500 mm. The mean temperature is 25-27°C.

The area lies within the tropical rain forest belt of Nigeria. The natural vegetation in

greater part of the area had been replaced by derived savanna grassland interspersed

with oil palm trees due to anthropogenic activities and also most vegetative cover

has been removed due to human activities such as farming and construction of civil

structures. The topography is fairly low and with comparatively few undulations. Its

average elevation is about 12.2m above sea level. The area is well drained by rivers

Otamiri, Nworie and seasonal Okitankwo an offshoot of Imo River.Owerri

Municipal inhabitants are mainly traders, few artisans, civil servants and farmers

who are predominantly natives.

7

1.4 HYDROGEOLOGY OF THE STUDY AREA

The geology of an area to some extent controls the occurrence and types of the

aquifer found on the area. The study area is outcropped by the Oligocene Benin

Formation which is known as the ‘coastal plain-sand’ (Fig1.3). It consists mainly of

sands, sandstone and gravel with clays occurring in lenses. The sands and

sandstones ranges from fine to coarse grained and is largely unconfined, with

thickness ranging from 2.0 m to 2100.0 m (Avbovbo, 1978). The environment of

deposition is partly lagoonal and partly fluvio- lacustrine/deltaic (Reyment, 1965).

The formation which dips south westward starts as a thin edge layer at its contact

with the Ogwashi - Asaba Formation in the northern part of the area, and thickens

southwards to about 1000.0 m in Owerri area. The Benin Formation is composed

mainly of high resistant fresh water-bearing continental sands and gravels with

minor clay intercalations (Onyeagocha, 1980). The sediments represent upper

deltaic plain deposits. The Formation is generally water bearing and hence it is the

main source of portable ground water in the municipality. The aquifers are

recharged mainly by surface precipitation and nearby drainages sediments

deposition and groundwater flow are generally in the NW – SE trend, in line with

the regional trend of the basin. The sandy unit which constitutes about 95% of the

rock in the area is composed of over 96% of quartz (Onyeagocha, 1980).

1.5 AIM OF STUDY

The aim of this work is to apply Geographic Information System (GIS) to determine

optimum collection points and most suitable sites for the final disposal of the solid

waste in New Owerri, Imo State.

8

1.6 OBJECTIVES OF STUDY

The objectives of this work is to generate a database by creating different layers

(roads, stream and land use) to serve the purpose of manipulation and analyses to

procure the collection point and most suitable disposal site for the solid waste

generated in New Owerri, Imo State. These objectives are as follows:

1. Designing and creation of digital spatial database “Owerri street guide map” of

the study area (data conversion from analogue to digital format).

2. Georeferencing and digitization of digital data.

3. Identification of roads, rivers and different land uses within the study area.

4. Creation of topological relationship between geographic feature and their

attributes.

5. Performing spatial analysis such as converting layers to shape files,

polygonizing, buffering, overlaying union and interception, erasing and

querying in order to get the most suitable collection points.

6. Setting criteria for the selection of the most final suitabledisposal sites for solid

waste generated from the collection points. These criteria are as follows:

a. Land use and land cover study in owerri.

b. Determination of land capability indices for solid waste land use option in

owerri west.

c. Geotechnical study of soil erodobility indices of land use determinant in

owerri west.

d. Geotechnical study on soil textural characteristics of Avu dumpsite.

9

1.7 SCOPE OF STUDY

This study is limited to the new Owerri municipal inside Owerri municipal, Imo

State. It focuses on site selection for solid waste collection and disposal, having

considered the existence of waste dumpsite at the eastern and northern part of the

town,

1.8 SIGNIFICANT OF THE STUDY

To promote the health of man and his environs through a GIS technology approach

to solid waste management for efficient and effective determination of most suitable

point for collection and disposal of solid waste generated in new Owerri. In

addition, to achieve sustainable developmental objectives as well as certifying the

saying the health is wealth and a healthy person is wealthy as well.

1.9 LIMITATION

1. The map of street guide otherwise called master plan of Owerri has not been

updated since 1976 that the state was created. Thus, the recently developed

path of new Owerri has its features and roads not named in the map, making

field work a difficult task toward attribute data acquisition.

2. Majority of the southern, western and part of the northern side of new Owerri

are still big forest, this makes identification of a tangible point for

georeferencing difficult.

3. The study area was too large consisting of over 30 layouts at a scale of

1:20,000 each which made its mapping a difficult task.

10

4. The large size of the study area made the spatial analysis to be poorly visible

in project presentation.

5. Financial constraints for the procurement of the necessary hardware and

software required for the project as well as expatriate consultancy.

6. The problem of mobility during field observation and acquisition of

geographic data.

7. Problem of securing data from virus and other hardware and software

problems.

8. Access to data, lack of up-to-date data and incomplete data.

11

Plate 1: An overview of Avu dumpsite in Owerri, Imo State

Plate 2: Polluted surface water due to leachate from solid waste dumpsite

12

CHAPTER TWO

2.0 GEOLOGY OF THE STUDY AREA

Geologically, the study area is underlain by a sequence of sedimentary rocks. The

lithological and geologic setting of the study area controls the occurrence and flow

of the ground water. Moreover, the area is underlain by the coastal plain sands of

the Benin Formation (Simpson, 1955), ranging from Miocene to recent in age

(Reyment, 1965). The Benin Formation is made up of thick friable sands with

minor intercalations of clay beds and lenses. The sand units are medium to coarse

grained, pebbly, poorly-sorted and locally contain lenses of fine-grained sandstone

and sandy clay (Short and Stauble, 1967; Onyeagocha, 1980).

The grains of the Formation are sub-angular to well-rounded. The colour of the

sands and the sandstones are white or yellowish brown as a result of Alumonite

coatings. Lignite occurs in the streaks or finely dispersed fragments; haematite

grains and feldspars are common. The clay is grayish brown, sandy or silky and

contains some plant remains and dispersed lignite. The sands and the sandstones

units of the formation are deposits of upper continental deltaic plain environment

(Short and Stauble, 1967)

Petrographic analysis of the rocks shows that the quartz makes up about 95 to 98%

of all the grains (Onyeagocha, 1980). Benin Formation has variable thickness and it

has been shown that the average thickness of the formation at the area is about

800m (Avbovbo, 1978).

However, in some places enclosed by the study area, the Formation is overlain by a

considerable thickness of red earth composed of iron stained regolith formed by

weathering and subsequent ferruginization of the weathered materials. The Benin

Formation is conformably underlain by the Ogwashi - Asaba formation. The

13

Ogwashi -Asaba formation consists of a lignite series and predominantly made up

of sands with minor shale units. Its average thickness is 200m. The age is partly

Oligocene (Kogbe, 1974).

2.1 STRATIGRAPHY OF THE STUDY AREA

The stratigraphy of southeastern Nigeria has been studied in details by Uma and

Egboka (1985). The Stratigraphic succession of rocks in the study area (Table 2.1)

consists of Imo-Shale-Formation, being the oldest formation and followed by

Ameki Formation, Ogwashi-Asaba Formation while the youngest is the Benin

Formation (Uma and Egboka, 1985). The coastal plain sand belonging to the Benin

Formation extends to a considerable depth in the area and with good hydraulic

properties for groundwater development. The formation consists predominantly of

very thick coastal sand, sandstone, clays and sandy clays occur in lenses. The Benin

Formation is in part cross-stratified with the forset beds alternating between coarse

and fine-grained sands. Petrographic study on several thin sections (Onyeagocha,

1980) shows that quartz makes up more than 95% of all grains. Groundwater occurs

abundantly in the coastal plain sands (Benin Formation) and the static water level

(SWL) ranges from 8.0 – 65.0 meters depending on the location and the time of the

year. The Benin Formation is a good aquifer with an average annual replenishment

of about 2.8 billion cubic meters per year (Onyegocha, 1980). In most areas, the

sandy components form more than 90% of the sequence of the layers therefore

permeability, transmissivity and storage coefficient are very high.

14

Table 2.1: Stratigraphic Units of the Niger Delta Basin (After Short and

Stauble, 1967)

Outcropping Units Subsurface Units Present-day Equivalents

Benin Formation Benin Formation Continental (fluviatile) deposits

mainly sandstones

Ogwashi–Asaba

Formation

Agbada Formation Mixed continental brackish water

Ameki Formation Marine deposits, sandstones and

clays

Imo Shales Akata Formation Marine deposits, mainly clays

Table 2.2: Generalized Stratigraphy of the Study Area, Imo State (After Uma

and Egboka, 1985).

Age Formation Maximum

approximated

Thickness (m)

Lithology

Miocene - Recent *BeninFormation 2000 Unconsolidated, yellow and white

sandstones occasionally pebbly

with lenses of grey sand clay.

Oligocene - Miocene Ogwashi – Asaba

Formation

500 Unconsolidated, sandstones with

carbonaceous mudstones, sandy

clays and lignite seams.

Eocene Ameki Formation 1460 Sandstones with grey argillaceous

sandstones shalesand thin

limestone units.

Paleocene Imo Formation 1200 Blue to dark grey shale and

15

subordinate sandstones. It includes

three sandstone members, the

Igbabu, Ebenebe and Umunna

sand.

Upper Maastrichtian Nsukka Formation 350 White to grey coarse-medium

grained sandstone: carbonaceous

shales, sandy shales, subordinate

coals and thin limestones.

Lower Maastrichtian Ajali Sandstone 3504 Medium-coarse grained cross

bedded sandstones, poorly

consolidated with subordinate

white and pale grey shale.

All other Formations except the Benin formation were included to give a general

overview of the geology of the area (Imo State). However, all the depths of interest

in this project work terminated in the Benin formation.

A striking feature in the geology map is the similarity in the pattern of surface

outcrops of the Formations. Almost all the Formations at the study are occurring

along the NW – SE bands that were grossly parallel to the regional strike. The rock

units also get younger southwestward, a direction that is parallel to the regional clip

of the Formation.

The Ajali sandstone (Maastrichtian) is the oldest exposed geologic Formation in

the Imo River Basin. It outcrops along a NW – SE (2 to 4km wide) band at the

northeastward margin of the basin. The Formation consists of thick friable poorly

consolidated sandstones, typically white in colour but sometimes iron-stained.

There is a marked banding of coarse and fine grained layers and the sands grains

16

and layer fragments are sub-angular with a spores cement of white clay (Reyment,

1965). Unit of this sandstone are typical cross-bedded and both the major and

foreset bedding planes are frequently lined with very thin white clay streaks. The

maximum thickness of the Formation within the Imo basin is about 300m (Uma,

1986).

The Nsukka Formation conformably overlies the Ajali sandstones and occupies a

relatively broader stretch of land west of the area underlain by the Ajali sandstone.

The Nsukka Formation dips at 2o to 7o to the west and southwest with an average

dips at 6o SW but may decrease to about 1oor 2o especially increase north of the Imo

basin. The rock unit consists of an alternating succession of sandstones, dark shales

and sandy shales with thin coal seams at various horizons. The basal units of the

Formation consist of fine – medium grained loosely-consolidated sandstones. The

Imo Formation consist of a thick sequence of blue and dark grey shales with

occasional bands of clay iron stone and subordinate thin sandstone (Sward and

Casey, 1961).

The Imo Formation dips at relatively higher angles of 17o to 25o to the southwest

and south and it include the sandstone members: the Igbabu, Ebenebe and Umuna

sandstones with the last two outcropping at the Imo River Basin. The Imo

Formation is succeeded vertically by the younger Ameki Formation (Eocene),

which consist of a series of highly fossiliferous grayish-green sandy-clay with

calacareous concretions and white clayey sandstones. It has two lithological groups

recognized in parts, the lowers with fine to coarse sandstones and intercalations of

calcareous slide and thin shelly limestone and the upper with coarse, cross-bedded

sandstone, bands of fine, grey-green sandstone and sandy clay (Reyment, 1965).

The Ameki Formation constitutes the main bulk of Eocene strata overlying the

Imo Formation and the thickness may attain as much as 1400 meters in some

17

places. The Ameki Formation is in turn succeded by the Ogwashi/Asaba Formation.

It is Oligocene to Miocene in age consisting of variable sequence of clay,

sandstones grills and thick seams of lignite alternating with grity clay (Desauvagie,

1974). A characteristics feature of the Formation within the Imo Basin is the up dip

and down dip pinch outs and the thickness of the lignite seams is more than 6m in

some area (Reyment, 1965). This Formation is only known from isolated outcrops

and in boreholes.

The Ogwashi/Asaba Formation is overlain by the Benin Formation which is the

youngest Formation (Miocene to Recent) in the Imo Basin. It occupies the middle

and lower regions and directly overlies more than half of the Basin.

The Benin Formation is made up of very friable sands with minor intercalations of

clays. It is mostly coarse-grained, pebbly, poorly-sorted and contains pods and

lenses of fine grained sands, sandy clays and clays (Whiteman, 1982 and Umu and

Egboka 1985). The Formation is in part cross-stratified and the foreset beds

alternate between coarse and fine grained sands. The dominance of sandy horizon in

the Benin Formation is also indicated by the logs of boreholes drilled through the

Formation. The strata logs of more than 85% of the over 400 water wells examined

indicated sand horizons of more than 90% with sandy clays making up the rest.

18

19

Fig 2.2 Geology map of the study Area (Source: Amadi, 2010)

20

2.2 PREVIOUS WORK

A Geographic Information System (GIS) is basically an organized collection of

computer hardware, software, geographic data and personal, designed to efficiently

capture, store, manipulate, analyze and display all forms of geographically

referenced information (ESRI, 1991). GIS acts as a decision support system by

facilitating the management, manipulation and analysis of spatial-temporal data. For

example:

Iro (2009) applied GIS in mapping Otamiri River water shed in Owerri, Imo state.

Olajide (2007) applied GIS in mapping solid waste disposal point in Ogbomosho

North Local Government, Oyo State.

Awosan (2006) applied GIS in mapping solid waste collection point in Ajoda New

Town, Ibadan”. GIs applications are dimensionless ranging from micro level to

macro level planning (Burroughs, 1986 and Nnabugwu, 2007). However, the

boundless capabilities are limited by one’s ability to visualize its implications. GIS

is used extensively in government business and research for a wide range of

applications including environmental resource analysis, land use planning, location

analysis, tax appraisal, utility and infrastructure planning, real estate analysis,

marketing and demographic analysis, location analysis or site selection, water

quality management, agriculture and forest managements, etc (Mather, 1991,

Nnabugwu, 2003 and Olajide, 2007).

Kufoniyi, (1998) stressed that the solution of environmental problem relies on the

use of appropriate tool for managing urban areas. Hence, GIS becomes the efficient

tool for such task. He further stated that a well-designed GIS has capability of

providing new flexible form of output such as customized maps, quick and easy

21

access to large volume of data, the ability to merge one dataset with another and the

means to analyze spatial characteristics of data.

Jeffery and John (1989) reported that “Site selection using a GIS” is a classical case

of land capability analysis. Since, solid waste generation is a land-based activity,

hence, proper analysis, visualization and mapping of the volume, frequency, variety

and distribution of solid waste generation is best handled with GIS technology.

Njoku (2010), stated that spatial decision making problems such as site selection

requires the consideration of multiple and conflicting criteria and objectives,

therefore a solution method that contributes towards consensus building is required,

supporting decision making in a spatial context is the implication in the use of GIS.

A land suitability modeling can be presented using environmental, economic and

other location criteria through the use of a GIS. Selection of suitable sites for a

research center according to ESRI (1996) identified the following techniques;

- Preparing data for analysis - Creating buffer zones

- Using boundary operations - Performing polygon overlay

- Manipulating tabular data - displaying spatially referenced data.

From the foregoing review, GIS is observed to be an efficient tool for land

suitability analysis selection. It has the capability of accepting data from diverse

source integrating them with other useful in formations and performing query and

carry out spatial analysis. Thus, with these capabilities, this study intends to exploit

GIS in mapping out solid waste collection and disposal points in new Owerri.

Hornsfal et al (1999) defined solid waste as non-liquid, non-soluble material arising

from human and animal activities, which are discarded as being useless or

22

unwanted. They range from municipal garbage to industrial solid waste that

contains complex and hazardous substances.

Anderson (1982) sees solid waste as any garbage, refuse, sludge from waste

treatment plant or any pollution control facility or any other discarded material

resulting from industrial, commercial, mining and agricultural operation and

community activities.

Olarjinde (2007) describes solid waste as substances or objects discarded as

worthless or unwanted, defective or of no further value for manufacturing or

production process.

Similarly, NEST (1997) in the same opinion added that these unwanted materials

are disposed off according to the provision of natural law. Sridhar (1996), defined

solid waste as any unavoidable material resulting from domestic and individual

material which must be disposed off.

However, the rate of solid waste generation increases with increase in

industrialization, population growth, urbanization, and technological advancement,

(Njoku 2010).

23

Fig 2.3The Functional Elements of Solid Waste Management System

Nwadike (2004) in his work defined solid waste collection as the gathering of solid

waste and the hauling of collected waste to approved site for processing or disposal.

Most of the operational cost in solid waste management is in collection Salvato

(1991). He puts the cost estimate to represent about 80% of the total cost in disposal

by sanitary landfill and 60% when incineration is used. In view of the cost

involved, Ogedengbe (1998) was of the opinion that three fundamental questions

often arise namely ;(a)Who shall collect the waste? (b) How should to be collected?

And(c) When should collection be done? He added that to address the above

questions, a municipal authority may use direct labour (i.e. staff), contract it to a

private organization or leave it in the hands of individual households who would be

expected to make their own contract agreements with private companies.

According to Nkwocha, (2002), various types of collection system are used in

municipal for collection of solid waste generated. They can be classified into; (a)

Waste Bins, (b) Waste Bags and (c) Collection Vehicles. Based on mode of

operation, there are two categories of collection vehicle system namely;

Waste Generation

Storage

Collection

Disposal

Transfer and Transport Processing and

Recovery

24

(i) Hauled Container System HCS; in this method, the container used for

storage of solid waste are hauled to the processing or disposal site, emptied and

returned either to their original location or another location. HCS are of two types;

tilt-frame HCS and Trash trailer HCS.

(ii) Stationery Container System SCS; these are collection system in which the

container used for the storage of solid waste remain at the point of generation,

except when moved for collection of solid waste. The two types of SCS are; theone

in which self-loading compactors are used and the one in which manual loading

vehicles are used.

According to Peary et al., (1986) and Nwadike, (2004), solid waste collection routes

are routes laid out to enable the workforce and equipment to function effectively.

The layout of collection route follows a four-step process;first, location maps are

prepared on large scale showing the area to be serviced. Also, the following are

plotted for each solid waste pick-up; location point, number of containers,

collection frequency and the estimated quantity of solid waste to be collected at

each pick-up location if a stationery container system is used. Second, data

summaries are prepared containing the estimated quantity of solid waste that can be

collected at each pick-up location serviced daily and the determined number of

location that will be serviced during each pick up cycle.Third, the preliminary

collection routes are laid out starting from dispatched stations or where the

collection vehicles are parked to the last location nearest to the disposal

point.Fourth, a balanced route is developed incorporating the haul distance for each

route after preliminary route has been laid out. Also, the labour requirement per

day, work times per day, and the lost solid waste transfer and transport locations are

determined.

25

According to (Okorie, Nwagwo, 1993 and Nkwocha, 2002), the four main methods

adopted by local government and state waste management agencies in Nigeria are

house-to-house, communal depots, curbside collection and block collection method.

26

CHAPTER THREE

DESIGNING, CREATION AND ANALYSIS OF DIGITAL SPATIAL

DATABASE

3.0 RESEARCH METHODOLOGY, RESULTS AND INTERPRETATION

3.1 DATABASE DESIGN

Database design otherwise known as data modeling is the process of defining

features to be included in the database, their attributes and relationships, and their

internal representation. Database is the core or heart of any GIS operations. It

allows system to meet up with the information or needs of the people (purpose) for

which a GIS project is carried.

Kufoniyi (1998) defined database design as the process by which real word entities,

their attributes and relationships are analyzed and modeled in such a way that

maximum benefits are derived using the minimum sets of data. Database design

passes through the following phases;

(i) Conceptualization design (ii) Logical design and

(iii) Physical design.

Below is the diagram showing the phases of database design.

27

Fig: 3.1Designs and Construction of Phases of Spatial Database (Kufoniyi, 1998)

3.1.1 VIEW OF REALITY

View of reality is the mental abstraction of reality for a particular relevance to the

application or group application at hand. It is simply the perception of reality as

they actually existed. E.g. the roads, rivers and land uses are seen on the study area

as they actually existed. View of reality forms the bases of which observed features

are represented in the stages of data modeling.

Reality

View of Reality View of Reality

View of Reality

Construction

Phase Spatial Database

Conceptual Design

Logical Design

Physical Design

28

3.1.2 CONCEPTUALISATION OF REALITY

This is also called external view. It is concerned with the way in which the data is

viewed by end users (individual perception of reality). At this stage of the database

design, decisions are made on how the view of reality will be represented in a

simplified manner and still satisfy the information requirement of the user.

Conceptual design is a concise describes the data types, relationships and

constraints expressed using the concepts provided by the high level data model. The

objective however is to determine the basic entities, the spatial relationships

between them and their attributes and how they will be modeled in such a way as to

satisfy desired need.

In this project, the vector model was adopted for use as Linear (1 – D), area (2 – D)

objects depending on the features geometric structure). The location of objects in

the data are given as X and Y coordinates, they are adopted for use and their

represented relatives were treated as points, lines and polygon feature class. The

entities or layers generated in this project were;

- Land use layer (polygon) - Road layer (line)

- River layer (line) and - Ward boundary layer

(polygon)

29

As used in Fig. 3.2, the term area feature is used to describe a homogenous extent of

the earth bounded by one or more features, such as land use. A linear feature is a

geographic feature that can be represented by a line or set of lines such as road or

river. Area and Linear features are represented by arcs. In the same vein an arc is

an ordered string of vertices that begin at one location and end at another, connected

by line. The vertices at each end point of an arc are called nodes, which are the

beginning and ending locations of an arc.

30

3.1.3 LOGICAL DESIGN

Logical design otherwise called data structure describes how entities and their

attributes are represented or simply the recording pattern of data in computer

system.

The conceptual data model in Fig. 3.2 was translated into a relational logical design

data structure as below;

Table 3.1 logical design of data structure

Entity Attribute field

Road Rd-id Rd-type Rd-name Rd-length

Boundary Bndry-id Bndry-name Bndry-area

Land use Ld-id Ld-type Ld-status Ld-area Ld-pop

dsty

River Rv-id Rv-name Rv-length

3.1.4 PHYSICAL DESIGN

This is an implementation stage in which the internal data structure and

organization for the database were specified. It is also referred to as a high-level

representation of data sets and the representation is guided by well spelt-out

constraints. At this stage, the field name, data types and width are specified. The

representation of features is determined by the type of software used. Arcview 3.2a

software used in this project represented lines, point object and areas as polygons.

31

Table 3.2 physical design showing attribute table of land use map

Table

Name

Attribute Description Data Type Data

Width

Road Rd-id

Rd-type

Rd-length

Rd-name

Road unique identifier

Road type

Road length in meters

Road name

Numeric

String

Numeric

String

3

9

8

30

Boundary Bndry-id

Bndry-

name

Bndry-area

Boundary identifier

Boundary name

Boundary area in

hectares and square

meters

Numeric

String

Numeric

1

30

8

Land use Ld-id

Ld-type

Ld-status

Ld- pop

dsty

Land use identifier

Land use type

Land use status

Land use population

density

Numeric

String

String

string

3

30

25

15

River Rv-id

Rv-length

Rv-name

River unique identifier

River length

River name

Numeric

Numeric

string

1

8

20

32

3.2 DATA ACQUISITION

The main data required for this project are land related data such as maps,

coordinate values, name and length of roads, status of land uses, etc.

3.2.1 DATA SOURCE

Generally, there are two types of data namely; primary and secondary data.

The data source for this project relies mainly on secondary data; they are:

A. Owerri Street Guide map and Owerri master plan collected from state

ministry of land and survey, new secretariat, Owerri. This contains the land

use data at a scale of 1: 20,000, map of Imo state showing Owerri municipal

area and Owerri west area.

B. Other secondary sources includes documented materials such as magazines,

newspapers, libraries, written texts, related journals, maps and satellite

imagery of the study area gotten from Google Earth in the internet.

Also, the firsthand information obtained from the study area arecalled primary data.

They include:

A. The Geographical coordinates of three points using Google earth software,

B. The name of the areas and streets, the length of roads as well as a ground

thruthing field observation embarked upon to confirm the features on the

maps.

3.2.2 DATA CONVERSION

The maps used in this project were in analogue format. They were however

converted into digital format through the process of vectorization (scanning with

scanner and georeferencing and digitizing with auto cad software). The digitization

of the map produced the following layers;

33

(i) Land use (ii) Road and (iii) River.

3.2.3 GEOMETRIC DATA ACQUISITION

Geometric data were acquired through the use of Google earth software from

internet to supply the coordinate values of points in the study area (in geodetic

format). The geographical co-ordinates were converted to rectangular (using the

Geo-calc software) which is the acceptable referencing system for geo-referencing

maps in the AutoCAD software.

The coordinate points are as follows:-

(i) First reference point (Assumpta Cathedral Owerri)

N 060 27’ 16.95”

E 070 03’ 15.32”

(ii) Second reference point (Imo Concorde Hotel)

N 060 28’ 21.63”

E 070 03’ 10.65”

(iii) Third reference point (junction between NMT1 and WMT2 Highway

along Umuguma)

N 050 25’ 45.64”

E 060 55’ 52.83”

3.2.3.1 GEOREFERENCING

This is the process of bringing the scanned map into its true earth (location)

coordinate on the computer system using an acceptable referencing system. The

Universal Traverse Mercator (UTM) with referencing to Mina datum was used. The

34

geographical co-ordinates obtained with Google Earth software were converted to

rectangular (using the Geo-calc software) which is the acceptable referencing

system for geo-referencing maps in the AutoCAD software. Thus, each image was

corrected for scale and station and geo-referenced using the following converted

coordinate points.

i) First reference point (Assumpta Cathedral) East

X 2 61755.320 E

Y 615970.756 N

ii) Second reference point (Imo Concorde Hotel) South

X 271595.728 E

Y 614230.920 N

iii) Third reference point (junction between NMT1 and WMT2 Arterial

Highway along Umuguma) West

X 267170.976 E

Y604796.745 N

3.2.3.2 DIGITIZING

This is the systematic extraction of important features from the map to be used in

GIS spatial analysis. The features on the map were digitized as points, lines and

polygons and were classified into themes for proper identification, differentiation,

thematic map creation and other analytical operations. The onscreen digitizing was

35

done with the use of AutoCAD Land Development 2i where the map was digitized

into the following layers;

(i) Land use - Commercial

- Residential

- Public (including recreational, administrative,

reserve and religious land uses)

(ii) Road (iii) River and (iv) Boundary layers.

3.2.4 ATTRIBUTE DATA ACQUISITION

The attribute data were collected through primary and secondary data sources.

They are for residential, commercial and public use land uses, roads, river and

boundary. “The attribute tables for the various land use types mentioned above are

shown on appendix ii below”

Thus, in the process of carrying out the project, the following operations were

performed for efficient and effective actualization of this plan;

1. Procurement of digital map of new Owerri from internet and coordinate

points with the aid of Google Earth software which is to be combined with

analogue maps of the same area gotten from Ministry of Land and Survey

and Owerri Capital Development Authority (OCDA), all from Imo State.

2. Conversion of procured geodetic (geographic) angle from Google Earth

software to Rectangular (projections) coordinates with the aid of

Geocalculator software for georeferencing in AutoCAD.

3. Conversion of analogue map to digital map followed by georeferencing and

digitization in AutoCAD which is exported into Arcview software.

36

4. Design and creation of database that will support the integration of record of

land use, rivers and road network of the area, which will permit updating and

retrieval of information pertaining to the study area.

5. Collection and structuring of the attribute data using Arcview 3.2a software.

6. Performing analysis using Arcview 3.2a software.

Plate 3: picture showing georeferencing and digitizing of scanned map

37

Plate 4: picture showing analysis of the operation performed using ArcView

3.2a software.

38

3.3 SYSTEM DESIGN

3.3.1 HARDWARE REQUIREMENT

Ahp pavilion v4225nr personal computer (laptop) was used with the following

configurations;

1. Intel ® Celeron (PM) CPU, rated at 3.2 window experience index (named Xp

window 7), manufactured at Haiter,

2. 5.12MB of RAM of 32-biting operating system type,

3. A mustakAz Scanner

4. A HP DeskJet D1560 Printer

3.3.2 SOFTWARE REQUIREMENTS

The following software was used for this project;

- Microsoft Window XP Professional window 7 viena, Service

pack 3, version2008-2009.

- Arc View GIS Version 3.2a for spatial analysis of site selection.

- AUTOCAD Land Development 2i for georeferecing and

digitizing the scanned map

- GEO CALC (Geographic Calculator 3.09) Software for

conversion of coordinates from geographical to rectangular and

vice – verse.

- Google Earth Software for acquiring satellite imageries and

geographical coordinates.

39

3.4 DATABASE CREATION

This is the construction phase of obtaining GIS database after three levels of design

phase. It involved the organization of the data in the forms that were compatible

with the relevant software. The analogue map digitized in AutoCAD was exported

to Arc View where area features were polygonized. Both acquired spatial and

attribute data were used in creating the database. The process went thus;

Launch Arc View 3.2a, click “Open theme”, icon table was displayed. Click “edit

menu”, select “start editing”, select “add field”. A dialogue box was displayed.

Input name, i.e. land use area, land use type, land use status etc., input data type i.e.

string, number or Boolean as appropriate then click “edit menu”. Select “add

record” and type in the entire attribute in the table and click “edit menu” and finally

“stop editing”.

3.5 DATABASE MAINTENANCE

This is an aspect of database management system concerned with the maintenance

of data to retain its value. It involves management of quality, integrity and security

aspect of the database.

3.5.1 DATA QUALITY

This is the application of quality assurance and quality control measures while

carrying out the project to ensure high confidence limit in the guaranteeing of the

work. The measures include;

1. The hard copy map was obtained from the state ministry of land and survey,

new secretariat, Owerri, Imo State.

2. The georeference points (coordinates) were collected directly from internet

with Google Earth software etc.

40

3.5.2 DATA SECURITY

Security measures adopted in this project includes;

1. Data were properly protected in the system with the use of password codes,

2. Backups were put in place to protect the data from being lost as well as

devices being used,

3. Data transfer and transaction were done with utmost care.

3.5.3 DATA INTEGRITY

This ensures the consistency and correctness of data stored in a database, the data

integrity adopted for this project is the domain integrity were the data type, width

and decimal of attribute were all specified.

3.6 SPATIAL DATA ANALYSIS, RESULT PRESENTATION AND

INTERPRETATION

3.6.1 INTRODUCTION

Spatial analyses are the operations performed on spatial data to find solutions to

spatial problems. It involves the organization of database into layers for the purpose

of providing rapid access to the data that might be required for geographic analysis.

By applying the abstraction process, real world entities were stimulated into the

computer. The process involved;

(i) Identifying the spatial feature form the real world that are of interest in the

context of an application and choosing how to represent them in the conceptual

model.

41

(ii) Representing the conceptual model by an appropriate spatial data model.

(iii) Selecting an appropriate spatial data structure to store the model within the

computer.

For this research work, spatial analyses were performed to locate the best locations

for solid waste collection within New Owerri in Owerri, Imo State. Investigation

from local authority and field survey revealed that there were no standard criteria

for ascertaining and zoning of solid waste collection points in Imo State. For this

reason, the user-based criteria based on the United Nations (UN) standard criteria

requirement was adopted for this research work.

The spatial operations used in the spatial analysis include buffering, overlay

(union), clipping and querying of data to arrive at the needed goal, the entities of

interest, (i.e. Roads, rivers and other land uses) were buffered. The buffering cut

across the study area at 100meters away from the features of interest at a distance

10meters per-ring, generating 10 rings on around the feature. This was done to take

care of the situation at hand as well as future expansions.

3.6.2 CRITERIA FOR SELECTING SUITABLE SOLID WASTE

COLLECTION POINTS

In selection of solid waste collection points, the following selection criteria set

based on the United Nations Standard Criteria Requirement was adopted. They are;

- The collection point should be 10m away from roads (for easy collection and

to prevent road blockage).

- The collection point should not be less than 70m away from water bodies e.g.

rivers.

42

- They should be 40m away from public use areas

- They should be 20m away from commercial areas.

- They should be 20m away from residential areas (thus within the proximity

of prospective users).

- A collection point must be at least 100m away from one another.

- The population density must determine the number of collection points

within each layout.

- It must be along the road/street junctions

(Source: www.gisdevelopment.net)

43

Fig 3.3 layout of composite map of the study area (New Owerri)

44

3.6.3 CARTOGRAPHIC MODELLING

A cartographic model is a set of interacting, ordered map operation that act on raw

data as well as a derived and intermediate map data to stimulate a spatial decision

making process (Michael, 1997). It is simply a graphical representation of data and

analytical procedures employed in building up a spatial database. It is also the

process of linking or organizing basic analysis operations in a logical sequence such

that the output from one is the input to the next. In this project, the cartographic

model revealed the step by step procedures of combining declared data (themes) to

generate the product i.e. the most suitable sites.

One unique aspect of GIS is its capabilities of carrying out analysis on real word

data, it allows for analysis of an existing database on geographic relationships. GIS

analysis used in this project includes buffering, overlay operations (unioning),

clipping and spatial queries. These operations were carried out to analyze all the

established criteria necessary for the location of solid waste collection points.

(i) Buffering of roads, rivers, residential, commercial and public use land uses

(buffer of 100m at an interval of 10m).

(ii) Union of buffered results

(iii) Clipping of unioned results with boundary

(i) Single and multi-criteria queries.

45

Fig. 3.4 Cartographic model of this study

Res + Pub. Use

Residential use

layer

Residential

theme

Buffered

residential

Commercial

theme

River layer Road layer Public use

layer Boundary

layer

Public theme Commercial

theme

Road theme River theme Boundary

theme

Buffered

public

Buffered

commercial

Buffered road Buffered river

Union union Com + Pub +

residential

Union Road + river

Union

Com + pub + res + road + river Clip

Query 1

Query (2)

Candidate site

Base map

Scanned land use map

Georeferenced

Digitized

Residential Commercial Public road

Possible areas Possible areas Possible areas Possible areas

Pub &com

use

comcomm.

Res&pub use Com & res use

Suitable site Suitable site Suitable site

Union

Most suitable site

46

3.7 SPATIAL ANALYSES PERFORMED

3.7.1 DIGITAL MAPPING PROCESSES ON MAP OF NEW OWERRI

Owerri street guide map was scanned and imported into the AutoCAD land

development software where it was georeferenced and digitized. Arcview GIS 3.2a

was launched and the digitized map was exported from Auto CAD to Arc view. The

road, boundary, rivers, residential, public and commercial layers were converted to

shape files after which the various entities were polygonized with Arcview script.

Thus, all the features were converted from polylines to polygons which are the

acceptable shapes for spatial analysis in the Arcview environment.

47

Fig 3.5Georeferenced New Owerri map in an AutoCAD environment

48

Fig 3.6 Digitized map of new Owerri in an AutoCAD environment

2013, Field Work

49

Fig 3.7 layouts of shape file of imported digitized map of new Owerri in Arcview

3.2a

50

3.7.2 BUFFERING OPERATION

One important spatial operation is the determination of spatial proximity or

nearness of various geographic features. The operation performed by the buffer

command generates one or more polygons surrounding geographic features and the

polygon is called BUFFER ZONE. In this study, buffering operation of 100m at an

interval of 10m was carried out on all the entities.

3.7.2.1 ANALYSIS OF BUFFERING OPERATION

Make the theme (feature) to be buffered e.g. river theme active click the ‘theme’

menu on the toll bar and select ‘create buffer’. A dialogue box is shown. Click

‘next’ and select ‘as multiple rings’ then input the number of rings, distance

between rings and units. Click next and on the new dialogue box, click on ‘yes’ for

dissolve barriers between buffers?’ Also select ‘only outside the polygon’, then

save in a new theme and click finish. The new theme will definitely show.

51

FIG 3.8 TO FIG 3.12SHOWS ALL THE BUFFERING OPERATIONS

PERFORMED.

Fig 3.8layout of the buffer of otamiri river and nworie stream

52

Fig 3.9 layout the buffer of roads in New Owerri area

53

Fig 3.10 layout of the buffer of public use theme in New Owerri

54

Fig 3.11 layout of the buffer of commercial land use in New Owerri

55

Fig3.12 layout of the buffer of residential land use in New Owerri

3.7.3 OVERLAY OPERATIONS

This is a GIS analytical tool used to merge two themes representing different data

sets to generate a new set of information. Topological overlay can be used for

different objectives such as theme updating, feature extracting, merging adjacent

themes and merging feature attributes.

The concept of overlay is by combining two or more themes (features), usually in

preparation for further analysis. For this research, overlay by union of entities was

applied. Overlay by union is used to combine features of an input theme with the

56

polygons from an overlay theme, to produce an output theme that contains the

attributes and full extent of both themes.

For this project, the following overlay operations were performed;

(i) First Overlay: The buffered residential land use theme was overlaid (unioned)

with the buffered public use land use theme to have another output theme called

union of residential and public use land uses.

(ii) Second Overlay: The buffered commercial theme was overlaid with union of

residential and public use theme to produce a new output theme called; union of

commercial, public use and residential land uses.

(iii) Third overlay: The buffered road theme was overlaid (unioned) with the

buffered river theme to have another output theme called union of road and river.

(iv) Fourth overlay: The unioned road and river were overlaid with the union of

commercial, public use and residential land uses, to produce a new output theme

called; final union made up of the union of commercial, public use, residential,

river and roads theme.

3.7.3.1 ANALYSIS OF OVERLAY OPERATION

Click on ‘view’ on the tool bar menu and select ‘geo processing wizard’. A

dialogue box is shown; select ‘union two themes’ and click next on the new

dialogue box, specify the two themes involved e.g. buffer of commercial layer and

buffer of public use layer. Specify the output file and click ‘finish’. The new theme

will definitely show.

57

FIG 3.13 TO FIG 3.16 SHOWS ALL THE OVERLAY BY UNION

OPERATIONS PERFORMED.

Fig 3.13 layout of the union of residential and public land use

58

Fig 3.13.1 shape filelayout of the union of residential and public use theme

59

Fig 3.14 Layout of union of buffered commercial, public use and residential land

uses

60

Fig 3.14.1 shape file layoutof the union of residential and public use and

commercial land use

61

Fig 3.15 Layout of union of buffered road and river

62

Fig 3.15.1 shape filelayoutof the union of river and road theme

63

Fig 3.16 layout of the union of public, commercial and residential land use and road

and river i.e. final union

64

Fig 3.16.1 shape file layout of the final union of public, commercial and residential

land use and road and river

Boundary shape1.shp

Final union.shp

1000 0 1000 2000 3000 Meters

N

EW

S

shapefile o f un ion of road, river, residentia l, com merc ia l and public land use

field work, 2010field work, 2010

276000

276000

277000

277000

278000

278000

279000

279000

280000

280000

281000

281000

282000

282000

602000 602000

603000 603000

604000 604000

605000 605000

606000 606000

607000 607000

608000 608000

609000 609000

2013, Field Work

65

3.7.4 POLYGON CLIPPING OPERATIONS

This is the spatial extraction of those features from one coverage that resides

entirely within a boundary defined by features in another coverage (called clip-

coverage). In line with analysis for this study, the boundary of the study area was

clipped with the theme; union of commercial, public use, residential and roads to

produce the candidate site for further research.

3.7.4. 1 ANALYSIS OF CLIPPING OPERATION

Click on ‘view’ on the tool bar menu and select ‘geo-processing wizard’ A dialogue

box is shown. Select ‘clip one theme based on another’ and click on ‘next’. On the

new dialogue box, select the input theme i.e. union of commercial, public use,

residential, river and roads, as well as the polygon overlay theme i.e. boundary

layer. Specify the output file and click ‘finish’. The new theme will definitely show.

66

Fig 3.17 Layout of result of clipping operation (candidate site)

67

Fig 3.17.1 shape file of the candidate’s site layout of result of the clipping operation

68

3.8 SPATIAL QUERY/SEARCH

This is the major analytical operation carried out on the attribute table of various

entities. The spatial search was performed by querying the database. It is the

process of acquiring information from a GIS by asking spatial questions from the

geographic data.

Spatial query is the process of selecting features based on location or spatial

relationship (e.g. selecting all areas 20m from residential areas). Database querying

is achieved through a query expression built to precisely define what to be selected.

Query expressions can either be single or multiple criteria.

In this project, the single criteria query was carried out after buffering and the

resultant output ( in shape file) were unioned, and clipped to form a candidate shape

file which was queried multiply to obtain most suitable sites for the present need

only.

However, the future need were also incorporated by overlaying the buffered land

use theme without querying and clipping the final union to form a candidate site to

be queried either singly or multiply to obtain desired result.

3.8.1 SINGLE CRITERIA QUERY

Single criteria query was used to determine the possible areas for solid waste

collection points for all the land uses including roads. This didn’t produce the final

result but gave an insight to the possible areas where the collection containers can

be placed. This was done using the set criteria as stated in 4.2. It was inputted into

the query builder as follows; 10m from roads (Roads=10m) for easy collection and

to prevent road blockage, 20m from residential areas (Res=20m) and 20m from

commercial areas as well (com=20m) so it will be within the proximity of users and

69

40m from public use (public use =40m) so it wouldn’t constitute nuisance to people

using public facilities.

POSSIBLE AREAS FOR ROADS

(Rd Dist.=10m)

Fig 3.18 Query input and output of 10m from road

70

Fig 3.18.1 shape file layout of the result of road output query

71

POSSIBLE AREAS FOR RESIDENTIAL

(Res Dist.=20m)

Fig 3.19 Query input and output of 20m from residential

72

Fig 3.19.1 shape file layout of the result of residential land use output query

73

POSSIBLE AREAS FOR PUBLIC USE

(Pub Use Dist. =40m)

Fig 3.20 Query input and output of 20m from public use

74

Fig 3.20.1 shape file layout of the result of public land use output query

75

POSSIBLE AREAS FOR COMMERCIAL

(Com Dist. =20m)

Fig 3.21 Query input and output of 20m from commercial

76

Fig 3.21.1 shape file layout of the result of commercial land use output query

77

POSSIBLE AREAS FOR RIVER

(River Dist.>70m)

Fig 3.22 query input and output for river

78

Fig 3.22.1 shape file layout of the result of river output query

79

3.8.2 MULTI CRITERIA QUERIES

Multi criteria queries were used to determine the suitable sites as well as the most

suitable sites for solid waste collection within New Owerri area. This query

combines more than one entity in a particular land uses to select the suitable sites

within the land thereof. Three multiple criteria query was carried out in this project.

(i) First; identification of most suitable points within residential and

commercial area at 20m interval respectively

(ii) Second; identification of suitable points on areas within residential and

public land use at 20m and 40m interval respectively.

(iii) Third; identification of most suitable points on areas with commercial

and public land use at 20m and 40 interval respectively

The result of this query shows sites that are suitable for users at the same time in the

two land uses. The result is a union of points or areas where the land uses meet /

intersect with the set criteria in place within a particular land use type.

3.8.2.1 INPUT FOR MULTI-CRITERIA QUERIES

- First: Res_Buff DIST = 20 and Com_BuffDIST=20 and RdDIST = 10

- Second: Res_BuffDIST=20 and Pub_BuffDIST = 40 and RdDIST = 10

- Third: comm._BuffDIST=20 and Pub_BuffDIST=40 and RdDIST = 10

80

3.8.2.2OUTPUT FOR MULTI-CRITERIA QUERIES

- SUITABLE SITES WITHIN RESIDENTIAL AND COMMERCIAL

Fig 3.23 Query input and output for suitable sites within residential and commercial

land use

81

Fig 3.24 Layout of suitable sites within residential and commercial land use

82

- SUITABLE SITES WITHIN RESIDENTIAL AND PUBLIC USE

Fig 3.25 Query input and output for suitable sites within residential and public use

83

Fig 3.26 Layout of suitable sites within residential and public use

84

- SUITABLE SITES WITHIN COMMERCIAL AND PUBLIC USE

Fig 3.27 Query input and output for suitable sites within commercial and public use

85

Fig 3.28 Layout of suitable sites within commercial and public use land use

86

Fig 3.29 Layout of union of suitable sites within commercial, residential and public

use land uses

According to the map sourced from State Ministry of Land & Survey and Owerri

Capital Development Authority, New Owerri area is characterized mainly by

residential areas, public use areas as well as commercial areas.

Thus, there is need to make available more waste bins for these areas, especially the

high density residential areas.

Afterwards, points that were within 100m proximity were expunged using the

measure tool on ArcView window.

87

Fig 3.30Layout of most suitable sites

88

3.9 INTERPRETATION OF RESULTS

Figures 4.22, 4.24 and 4.26 were overlaid to have a combined suitable sites (fig.

4.27), which again was queried to have the suitable sites, after which points that

were within 100m proximity were expunged using the measure tool on ArcView

window (as seen in figure 4.28) thus giving the most suitable sites for locating solid

waste collection points in New Owerri.

In Fig 4.28, the collection points were identified as points in relation to their

coordinate values and layout. The following coordinate values represent the

locations specified by the Geographic Information Systems as well as the attributes

of the points. Thus, in all the sited collection points, the distances to similar land

use type are the same as stated in the criteria with respective distances of;

road=10m, commercial land use=20m, public land use=40m, river >70m and

residential land use=20m.

INDUSTRIAL LAYOUT

This has nine collection points with respective coordinate values of:

278421.01E&609192.64N, 278897.32E&608762.14N,

279053.03E&608606.42N, 279282.03E&608285.83N, 279126.31E&608029.36N,

278851.52E&608837.00N, 278411.85E&607827.84N, 277770.67E&607827.84N,

277092.85E&607837.00N

AMAKAOHIA POCKET LAYOUT

This has five collection points with respective coordinate values of:

278824.04E &609320.88N, 279098.83E & 609063.41N, 279300.35E &

608872.05N, 280042.29E &608991.13N, 280427.00E &609046.09N

89

ARUGO LAYOUT

This has four collection points with respective coordinate values of:

279.538.50E & 608340.79N, 279987.33E & 608716.34N, 280060.61E &

608020.20N, 280616.19& 608203.39

UMUJECHI NEKEDE VILLAGE LAYOUT/NEW OWERRI SOUTH


280332.46E&603065.10N, 280550.21E&603255.63N,

280822.39E&603037.88N, 280631.86E&602847.35N.

UMUGWULE NEKEDE VILLAGE/NEW OWERRI SOUTH

This has only one collection point of 279965.00E & 602888.18N.

UMUMBAZU NEKEDE VILLAGE/NEW OWERRI SOUTH

This has two collection points with respective coordinates of:

279992.22E&602262.14N and 279651.98E&601758.59.

PUBLIC BUILDING/NEW OWERRI SOUTH

This has only one collection point with coordinate values of

279189.26E&602670N.

AREA H LAYOUT

This has four collection points with respective coordinate value of:

280196.36E&604017.76N, 280060.27E&603677.52N, 280278.02E&603691.13N,

280880.21E&603772.79N.

90

AREA G LAYOUT


280550.21E&604412.43N, 280836.00E&604439.65N, 280754.35E&604276.34N,

281121.80E&604249.12N, 280890.44E&603936.10N.

AREA F LAYOUT

This has three collection points with respective coordinate value of:

281257.96E&604453.26N, 281475.65E&604589.35N and

281217.07E&604439.65N.

AREA E LAYOUT

This has three collection points with respective coordinate values of:

280659.08E&605310.26N, 280509.38E&605092.90N and

280550.21E&604725.45N.

AREA C LAYOUT


280904.05E&605378.70N, 280890.44E&605092.90N, 281366.77E&605378.70N

281462.04E&604956.81N.

COMMERCIAL DISTRICT LAYOUT


278222.99E&604548.53N, 278359.09E&604181.07N,

278616.67E&604279.34N, 278944.29E&604834.32N, 279325.36E&605011.25N,

279393.41E&604861.54N, 279760.86E&605160.95N, 280101.10E&605065.68N

280169.14E&605297.04N.

91

AREA R LAYOUT


279338.97E&603364.51N, 279883.34E&603595.87N and

279230.09E&603677.52N.

AREA P LAYOUT

This has two collection points with respective coordinate values of:

279447.84E&604643.79N and 278989.86E&604317.17N.

AREA B LAYOUT


279815.30E&604902.37N, 279842.52E&604643.79N, 279651.98E&604398.82N,

280196.36E&604521.31N 279937.78E&604289.95N.

AREA U LAYOUT

This has only one collection point with coordinate value of

278495.18E&603105.93N.

AREA U’A LAYOUT


279053.17E&603282.85N.

AREA T LAYOUT


278168.56E&603759.18N, 278359.09E&603976.93N and

278386.31E&603677.52N.

92

FEDERAL MINISTRY OF WORKKS & HOUSING/SITE SERVICES

SCHEME LAYOUT


276630.69E&603078.71N, 277351.99E&602929.00N and

277351.99E&603364.51N.

AREA V LAYOUT


277488.09E&603881.66N and 277841.93E&604126.63N.

AREA W LAYOUT


277773.06E&602888.18N and 278073.29N

SECRETARAIT LAYOUT


279284.53E&605174.56N.

PUBLIC BUILDING/EXHIBITION GROUND LAYOUT NEW OWERRI

WEST


277134.24E&604984.03N, 276889.27E&604371.60N, 276739.57E&603745.57N,

277365.60E&604357.99N, 277814.71E&604602.96N.

AREA A LAYOUT

This has seven collection points with respective coordinate values of:

93

278862.98E&606194.71N, 279487.80E&606246.77N,

279088.61E&605925.68N, 279591.94E&606055.86N, 279574.59E&605582.29N,

279279.53E&605778.16N,

AREA N LAYOUT WORLDBANK

This has ten collection points with respective coordinate values of:

278.584.25E&606168.18N, 278406.47E&605895.21N,

278876.21E&606001.81N, 278434.20E&605775.09N, 278819.13E&605771.83N,

278533.69E&605629.93N, 278027.90E&605678.86N, 278848.49E&605595.68N,

278598.93E&605504.34N and 278414.62E&605435.83N.

PUBLIC BUILDING LAYOUT

This has fifteen collection points with respective coordinate values of:

279661.35E&608077.86N, 279826.25E&607366.25N, 279140.68E&607791.48N,

278741.49E&607678.66N, 278889.01E&607531.13N, 279010.51E&607305.50N,

278481.14E&607192.69N,278463.79E&608858.89N,

278524.54E&606923.67N, 278377.01E&607522.46N, 278229.48E&607175.33N,

278298.90E&606845.56N,277760.86E&607366.25N,

277717.47E&607062.52N, 277396.38E&607123.26N.

WORLD BANK AREA M LAYOUT


278437.75E&606672.00N, 278472.47E&606481.08N, 278533.21E&606316.20N,

278281.55E&606177.35N, 278706.77E&606264.13N, 278186.09E&606426.37N,

278264.19E&606602.58N, 277977.81E&606455.05N, 278047.24E&606307.52N

94

AREA S LAYOUT


277514.05E&606459.65N, 277342.80E&606199.93N, 277476.94E&606051.51N,

277808.34E&605874.56N

AREA X LAYOUT

This has eight collection points with respective coordinate values of:

276540.80E&606511.02N, 276809.08E&606462.50N, 277228.64E&606448.23N,

276869.02E&606302.67N, 277094.49E&606237.03N, 276786.25E&606128.57N,

277017.43E&606125.72N, 276820.50E&605831.75N

ONITSHA YOUTH CENTRE LAYOUT

This has seven collection points with respective coordinate values of:

280052.92E&607407.97N, 280297.30E&607270.24N, 280306.18E&607074.74N,

280488.36E&607123.61N, 280417.26E&606919.22N, 280634.98E&607012.53N,

280266.20E&606483.79N,

AREA D LAYOUT


279525.29E&606379.38N, 279736.35E&605940.61N, 280114.02E&606368.27N,

AREA L LAYOUT

This has six collection points with respective coordinate values of:

95

279158.73E&607079.18N, 279069.87E&606834.80N, 278831.05E&606640.41N,

278814.38E&606462.69N, 279180.95E&606623.75N, 279375.34E&606529.33N,

NEW D LAYOUT


277417.06E&605509.23N, 277768.06E&605494.16N, 278010.96E&605306.59N,

277668.17E&605206.70N, 277425.57E&605175.36N, 277222.93E&605149.62N,

AREA Y LAYOUT


277277.16E&605700.16N, 277162.99E&605646.23N, 277157.28E&605417.90N,

276754.85E&605489.25N,

FEDERAL LOW COST HOUSING ESTATE TAN2


277812.93E606580.51N, 277700.11E&606481.08N, 277865.00E&606402.98N,

277804.25E&606272.81N, 277847.64E&606125.28N, 277891.03E&605943.04N

FEDERAL LOWCOST HOUSING ESTATE TAN1


278003.85E&605726.09N, 278151.38E&605804.19N, 278029.88E&605647.98N,

278246.83E&605658.66N, 278246.83E&605457.07N, 278116.66E&605465.74N

The available portions specified by the system are the most suitable sites. Thus, the

local government can now use their discretion to place the waste bins (containers) at

96

strategic points as specified. If the bins are properly placed at these points, New

Owerri territory will be;

- A healthy environment for the inhabitants.

- Void of health hazards associated with indiscriminate dumping of solid

wastes.

- Made a clean area in contrast to other cities of Nigeria and in line with the

state governments’ programme of ensuring a “clean and green” city.

- Void of induced flooding caused by blocking of drainage as a result of

indiscriminate dumping of solid wastes.

- Made a model area in terms of efficient and effective solid waste

management.

97

CHAPTER FOUR

SETTING CRITERIA FOR THE SELECTION OF THE MOST FINAL

SUITABLE DISPOSAL SITES FOR SOLID WASTE GENERATED FROM

THE COLLECTION POINTS

4.0 RESEARCH METHODOLOGY, RESULTS AND

INTERPRETATION

These criteria for determining the most final suitable sites for disposal of solid

waste are as follows:

a. Land use and land cover study in owerri.

b. Determination of land capability indices for solid waste land use option in

owerri west.

c. Geotechnical study of soil erodobility indices of land use determinant in

owerri west.

d. Geotechnical study on soil textural characteristics of Avu dumpsite.

4.1 SOIL TYPES IN OWERRI WEST

Owerri West Local Government Area with its headquarters at Umuguma is located

between latitudes of 5o 23’ and 5o 34W and between longitudes of 6o 5o’ and 7oE,

and has 15 autonomous communities namely Obinze, Avu, Nekede, Ihiagwa,

Amakohia Ubi, Ndegwu, Okuku, Eziobodo, Oforola. Ohi, Umuguwaand Orogwe,

Okolochi, Emeabiam and Irete.

With the soil map of Imo State, using the United States Department of Agriculture

(Peech et al. 1947) and Food and Agricultural Organization of the United Nations

(FAO 1976) classification systems, there are three classes of soil in Imo State.

They are Ferralitic soils from the coastal plain sand and the escapement are

occupying an area of about 7,798 square kilometers, which is 61% of the total area

98

of flat to undulating topography characterized by good drainage. Hydromorphic

soils from plateau and Cross-River plain are occupying an area of about 31% of the

total landmark and have developed along the escapement found in the Northeastern

part of the State.

Alluvial soils occupy about 8% of the total area of the state and are found along the

low terrace of the Cross-River and Orashi River. They are poorly drained and are

subject to permanent or periodic flooding.

The communities living in these areas hardly go through each year without adverse

effect of soil erosion especially that due to water.

4.2 SOIL SAMPLING

A total of 19 soil samples each were collected for the study in determining the land

capability indices and soil erodobilty indices in Owerri west; and also the soil

textural characteristics of the refuse dumpsite in Avu.

15 soil samples each were collected at 15 (fifteen) autonomous communities in

owerri west L.G.A from pits dug at a depth of 5 meters using auger to determine the

land capability and soil erodobility indices. These autonomous communities are

Obinze, Avu, Nekede, Ihiagwa, Amakohia Ubi, Ndegwu, Okuku, Eziobodo,

Oforola, Ohi, Umuguma, Orogwe, Okolochi, Emeabiam and Irete.

2 (two) soil samples were also collected at the vicinity of Avu dumpsites between

1.0 – 2.5 meters depth to determine the textural characteristics of the soil while

additional 2 (two) samples at the same depth range were collected far away from

the dumpsite, to serves as control samples. Sampling tools were washed with water

and dried before the next sample was collected. They were placed in polythene

bags, and transported to laboratory for analysis. Method of random sampling was

adopted in which 19 (nineteen) soil samples covering the entire soil types of the

area were collected.

99

4.3 LAND USE (LU) AND LAND COVER (LC) STUDY IN OWERRI

Land use study is the act of planning to make the best, most sensible, practical, safe

and efficient use of each parcel of land. On the other hand, LU refers to the manner

in which these biophysical assets are used by people [for details, see Cihlar and

Jansen, 2001]. Land use and land cover dynamics has been common place around

Owerri and environs. Owerri and environs are characterized by natural and

man-made problems and rapid land use and cover changes such as flooding,

erosion, induced soil infertility and degradation, deforestation, etc. This study

examines the application of multi-temporal remotely-sensed data in the detection of

static LU and LU changes between 1986 and 2000. The study provides temporal

empirical comparative assessment of TM 86 and ETM+ 2000, while identifying the

primary drivers of the intra-class dynamics during the periods in order to predict

what types will dominate the area in the future.

The study area, Owerri metropolis is a closely-settled built-up area and the

administrative capital of Imo State of Nigeria. The pre-1976 Owerri comprised

largely pockets of rural settlements of predominantly subsistence farmers. It lies

between latitude 50 25’N and 50 34’ N and longitude 60 7’E and 70 06’E covering an

area of approximately 5,792.72 km2. The 1991 population of Owerri was 289, 721

[NPC 1991]. In 1998, the projected population was put at 353, 665 people [Imo

State Government, 2000] While in 2006, the population was 401, 873 [NPC 2006].

The area is within the humid tropics and is characterized by high temperature and

rainfall regimes with a mean maximum temperature of about 320oC and a mean

minimum of about 210oC.

Recent studies (Nnaji, 1998, 1999 and FGN, 2003) however reported declining

trend in rainfall characterized by large spatial and temporal variations. The area lies

in the rainforest belt of Southeastern Nigeria characterized by low- land tropical

rainforest, which has virtually given way to secondary forest re-growths of mostly

100

tree crops and shrubs separated by crops at various stages of growth. In the area,

vegetation plays the dual role of humus supply and protection of the soil from the

ubiquitous soil erosion.

Owerri and environs are within the densely populated region of Southeastern

Nigeria. In spite of the increasing population which presses on land availability,

market gardening is largely practiced. The growth rate of the population growth,

its size structure, density, spatial distribution and urbanization characteristics

are critical factors of the environment likely to affect LU and LC dynamics.

Being the administrative capital of Imo State, associated infrastructure, education

opportunities and employment potentials in the city attracts growing migrants from

distant and adjourning towns and villages. The emergence of small and medium

sized agro-husbandry industries in the peripheral, semi urban villages have attracted

urban sprawl and rapid socio-economic activities. Hence, subsistence agriculture,

petty trading, white collar jobs (paid employment), artisanship characterize and

significantly influence the contemporary LU and LC patterns. This has exerted

great pressure on the ecological resources, even without any eco-conservations

efforts.

Similarly, soil erosion, flooding, increasing soil infertility resulting in bare surfaces

also contributed in shaping these patterns.

4.3.1 Methodology of the land use and land cover study

The study was undertaken with 1:100,000 administrative map of Imo State covering

the study area which was obtained from the Ministry of Lands and Urban

Development, Owerri Nigeria. The map was used for the enhancement of LU and

LC classification, orientation and geometric registration of the imageries during

interpretation. The satellite imageries were obtained from the National Space

Research and Development Agency [NASRDA] Abuja, Nigeria. The LU and LC

101

patterns represented on the map were used as the starting point of the contemporary

LU and LC classification in the present study. This done, the regularity of LU and

LC conversion of the different classes were analyzed.

4.3.2 Results and interpretation of the land use and land cover study

The results of the study revealed significant shift between the two periods. The

imageries proved very useful and effective in the accurate mapping of ground

features. The bare/eroded surfaces class gave the highest PAVM value of 65.7%

followed by water body 44.9. The major LU and LC classes identified in the study

are: built-up area, poorly dispersed forest vegetation, cultivation, bare/eroded

surfaces and water body. The variants of forest vegetation was the dormant LU and

LC type in 1986 and 2000 and covered a total area of 2,792.72km2, especially

around the out-lying peri-urban areas. Land areas and features were assigned

different spectral signatures to represent changes from one class to the other. The

largest inter-class change occurred between the cultivation and the forest vegetation

classes. The forest vegetation class has the largest unchanged portion among the

classes.

Simple percentages were used to show the differences and to represent the relative

amount of the LU and LC classes as a percentage of the total area. The strength of

their differences is shown using the Percentage Absolute Variations of Mapping

[PAVM] values expressed as:

𝑃𝐴𝑉𝑀 =(𝐴1 − 𝐴2) × 100

(𝐴1 + 𝐴2)

Where A1 = Landsat TM 86 map percentage of the LU and LC classes within the

study area.

A2 = the absolute differences in values between A1 and A2

The values show that there was an overall change of about 26.9% between the data

sets. The forest vegetation showed the lowest (4.31%), while the eroded/bare

102

surfaces showed the highest change of 65.74%. This portrays the ability of the two

imageries to accurately map identical features.

Table 4.1: LU and LC Classes in 1986

LANDSAT TM 86 [19thDecember

1986]

Area in km2

Bare/Eroded surface 21.96

Cultivation 891.94

Forest Vegetation 1, 431.25

Built-up 438.04

Water Body 9.53

Total 2, 792.72

Table 4.2: LU and LC Classes in 2000

LANDSAT ETM+ [of 12th December

2000]

Area in km2

Bare/Eroded surface 4.54

Cultivation 680.40

Forest vegetation 1,560.00

Built-up 543.88

Water Body 3.62

Total 2,792.72

103

4.4 OWERRI WEST LAND CAPABILITY INDICES DETERMINATION

FOR SOLID WASTE DISPOSAL LAND USE OPTION

4.4.1 Laboratory Analysis of the Soil Samples

The collected soil samples were subjected to the following analysis using specified

equipment. Atterberg limits, (using Cassagrande apparatus), particle size

distribution, (using British electric shaker machine), porosity and permeability

(using permeameter), consolidation settlement using (consolidometer), shear

strength (using triaxial shear box) and finally compressive strength. Analysis were

done using ASTM D, 4318-98(2000) and ASTM, 1988 standard specifications. All

analytical procedures are shown in (Robert et al 2001).

4.4.2 Results and Interpretation of the soil sample analysis

The average results of laboratory, filed and literature studies are shown in Table 3.

The table is a reference guide in the rating of the basic determinants of land use

factors. From the table, while the forralithic soil is poorly graded, the

hydromorphic and ferralithic soil are well graded. Forralithic soil and lithosoil

tilt towards Sandy clay while that of ferralithic and hydromorphic soils tilt

towards silty clay.

Soils that tilt towards sand have high shear and compressive strength , while those

tilting towards silt have high attenuative power in handling waste effluents,

Gauley and Krone (1966), Krynine and Jude (1957). The result shows that while the

clay fraction of hydromorphic soil is 13% that of ferralithic soil is 13.5%. From

these, the activity indices of ferralithic and hydromorphic soils were calculated to

be 1.84 and 2.02, while their liquidity indices, were calculated as -0.24 and -0.41.

This was obtained using the relation according to Robert et al (2001):

104

…………(1)

and

………(2)

Where PI is plasticity Index, W natural moisture content and PL is Plastic Limit.

The result of this calculation indicates that the two soils hydromorphic and

ferralithic soils are expansive and weak, therefore unsuitable for residential and

industrial buildings, (Robert, 2001).

Permeability and porosity result show that the permeability and porosity of

hydromorphic soil is measured 1.97 x 10-2 cm/sec and 0.31 that of ferralithic

soilis measured 1.89 x 10-2 cm/sec and 0.30, while lithosoil has 1.70 x 10-2 and

0.30; the Forralithic soil also has 1.70 x 10-2 and 0.30.

Where τ is shear strength, C = cohesion, δn = effective stress on soil and ө =

Frictional angle based on total stress analysis. Employing equation 3 and

parameters C and tan ө from graph of shear versus Normal stress, the shear

strength for hydromorphic, forralithic, ferralithic and lithosoils are

85.56KN/m2, 96.09KN/m2, 87.82KN/m3 and 88.36 KN/m3 respectively.

The shear strength of hydromorphic and ferralithic soils are lower than forralithic

andlithosoils, also the angle of internal friction is high for forralithic soils indicating

a high shear strength (Aria, 2003).

Hydromorphic and ferralithic soils show high cohesion, there is likelihood of shear

failure when subjected to load like industrial buildings, since saturated clays fail if

subjected to vibration, (Aria 2003).

The result of compressive strength shows that forralithic soil has compressive

strength of 9.10KN/m2 with test load of 14.43KN/m2, ferralithic soil 2.10 KN/m2

test load 20.16 KN/m2. Hydromorphic soil 2.176KN/m2 test load 56.0 KN/m2 while

lithosoil has 3.24KN/m2 with test load of 21.34 KN/m2.

105

Earlier, Terzaghi and Peck (1967) observed that any rock or soil mass with

compressive strength between 2KN/m2 and 7KN/m2 is weak while those above

these values are strong based on this, forralithic soil is stronger. The moisture-

density curve indicates (OMC) of 11.02% and maximum dry density (MDD) of

1.51kg/m3, that of hydromorphic soil has 13.01 and 1.52 kg/m3, while that of

forralithic soil is 14.0 and 1.90kg/m3. Forralithic soil satisfied conditions for

accommodating heavy buildings (Terzaghi and Peck, 1967). The lower dry density

and higher moisture content of the hydromorphic and ferralithic soils indicated

higher affinity for water which makes them expansive and weak (Aria, 2003).

The result of soils engineering classification, employing grain size and Atterberg

limit result and using Unified Soil Classification System (USCS) shows that

Forallithic soil is classified as ML-CL (Clay = Silt and poorly graded),

Hydromorphic soil SP-CL (Silty clay and well graded), ferralithic soil is SW-CL

(Silty clay and well graded ) while lithosoil is silty clay and poorly graded. The

above results are relevant guides in rating of land use determinants.

106

Table 4.3: Summary of Laboratory, Field and Literature Data

107

Figure 4.1: Unified soil classification system-plasticity chart.

108

4.5 OWERRI WEST SOIL ERODIBILITY INDICES DETERMINATION

FOR SOLID WASTE DISPOSAL LAND USE OPTION

The method of field test developed by Wischmeier et al. (1958) was used to

determine soil erodibility. The in situ permeability test was also used along with the

field test of dropping clods from known height.

4.5.1 Laboratory Analysis of the Soil Samples

The hydrometer test was carried out to determine the percentage of sand, silt

and clay in the samples of soils taken from these communities. From this,

erodibility index (K) was determined using Bouyoucos (1935) equation.

The percentage of sand, silt and clay were determined as follows:

% 𝒔𝒂𝒏𝒅 =𝒔𝒂𝒎𝒑𝒍𝒆 𝒘𝒆𝒊𝒈𝒉𝒕 − 𝟒𝟎 𝒔𝒆𝒄𝒐𝒏𝒅𝒔 𝒓𝒆𝒂𝒅𝒊𝒏𝒈

𝒔𝒂𝒎𝒑𝒍𝒆 𝒘𝒆𝒊𝒈𝒉𝒕

% 𝐜𝐥𝐚𝐲 = 𝟖 𝐡𝐨𝐮𝐫𝐬 𝐫𝐞𝐚𝐝𝐢𝐧𝐠 × 𝟏𝟎𝟎

𝒔𝒂𝒎𝒑𝒍𝒆 𝒘𝒆𝒊𝒈𝒉𝒕

% silt = 100% - (100% + 100% clay).

4.5.2 Erosion Prediction

Using the relationship given by Roose (1977), the rainfall factor (R) was

determined:

R = 0.5 H,

Where H is the mean annual rainfall.

Prediction of the amount of soil loss in each of these communities was carried

out putting this in the revised USLE equation:

A = 2.24 R K,

Where A is the soil loss converted to tons/ha/yr. by multiplying by 2.24, R is the

rainfall factor and K is the Erodibility factor (Hudson 1995).

4.5.3 Results and Interpretation

109

The results of the determined erodibility indices in the various communities are as

shown in Table 4. From the erodibility indices of the soils in the various

communities, it can be observed that the soils in Ohi are more erodible with a value

of (0.044). The least indices were found in soils at Obinze (0.029) and Ihiagwa

(0.029). The results of the predicted soil losses in the various communities under

study are also shown in Table 5. Ohi being the most erodible has the highest

predicted soil losses of 9.462tons/ha/yr. This is followed by Amakohia-Ubi

(8.602tons/ha/yr) and Orogue (89.6 tons/ha/yr). Obinze and Ihiagwa have the least

predicted soil losses of 6.236 tons/ha/yr each.

Table 4.4: Average erodability index (K) of project locations and predicted soil

losses for the various communities using Hudson (1995) equation.

Location Average K-index Soil loss (tons/ha/yr)

Ndegwu

Orogwe

Amakohia Ubi

Obinze

Oforola

Avu

Umuguma

Okolochi

Emeabia

Eziobodo

Ihiagwa

Nekede

Irete

Ohi

Okuku

0.035

0.040

0.40

0.029

0.032

0.03

0.036

0.036

0.033

0.032

0.029

0.034

0.036

0.044

0.037

7.526

8.602

8.602

6.236

6.881

6.451

7.741

7.741

7.096

6.881

6.236

7.311

7.741

9.462

7.956

From the particle size analysis sandy soils were found to be the most common.

Erodibility factors of Ohi, Orogwe and Amakohia-Ubi communities were found to

110

be high which is due to the presence of high quantity of sandy soils in these areas.

Sandy soils are known to have low cohesive force and therefore are more prone to

detachment and transportation by water and wind. Furthermore, high sandy soil

content encourages high rate of permeability of water into the soil, which induces

landslide and erosion. The communities with high clay content have low erodibility

factor because of the higher binding and interbinding forces that help in resisting

detachability of soil by wind and water.

The erodibility indices for the samples of soils from the fifteen communities when

compared with standard erodibility indices which showed that the erodibility

indices of the communities in Owerri West Local Government Area fall into group I

(Table 4.5), indicating that the soils are permeable, well drained with stony

substrata.

Table 4.5:Standard erodability indices.

Group K-Factor Nature of Soil

I 0.0 – 0.1 Permeable gracia outwash well drain soils

having stony substrata

II 0.11– 0.17 Well drain soils in sandy graded free

material

III 0.18– 0.28 Graded loams and silt, loam

IV 0.29– 0.48 Poorly graded moderately fine and textured

soil

V 0.49– 0.64 Poorly graded silt or very fine sandy soil,

well and moderately drain soils

111

4.6 DETERMINATION OF SOIL TEXTURAL CHARACTERISTICS

FOR SOLID WASTE DISPOSAL LAND USE OPTION AT AVU

DUMPSITE

4.6.1 Soil Sampling at Avu Dumpsite

2 (two) soil samples were also collected at the vicinity of Avu dumpsites between

1.0 – 2.5 meters depth to determine the textural characteristics of the soil while

additional 2 (two) samples at the same depth range were collected far away from

the dumpsite, to serves as control samples.The samples were collected once every

month for 4 months during rainy season from April to July, 2013.

4.6.2 Laboratory Analysis of the Soil Samples at Avu Dumpsite

The soil samples were air-dried in the laboratory at room temperature, grounded to

fine mixture using pestle and mortar before sieved under 2 mm mesh. The samples

were labeled appropriately, stored in sealed polythene bags and transported to the

laboratory for digestion and analysis. The soil samples were digested in a mixture

concentrated nitric acid (NHO3), concentrated hydrochloric acid (HCl) and 27.5%

hydrogen peroxide (H2O2) according to the USEPA method 3050B for the analysis

of heavy metals and major ions (USEPA, 1996). The pH measurement of the

aqueous suspension 1:5 (w/v) of the <2 mm fraction of the soil was performed. The

pH was measured with Consort 2000 pH-meter equipped with a combined pH

electrode. Conductivity meter and filter membrane method were used for the

determination of conductivity and bacteria count respectively. The distilled water

used for the preparation of the suspension had been previously boiled and cooled

and the sample for determination of bacteria count was incubated for at least 24

hours.

The determination of heavy metals (Cu, Zn, Mn, Cd, Pb and Fe) was made using

the inductively coupled plasma atomic emission spectrometer, ICP-AES, with

112

simultaneous detection Optima 5300 DV (Perkin Elmer), with axial and radial dual

vision, while for the determination of major ions, the ELAN DRC II (Perkin Elmer)

inductively coupled plasma atomic emission spectrometer, ICP-AES was used.

4.6.3 Results and Interpretation from the Soil Analysis at Avu Dumpsite

The average concentration of the parameters analyzed from Avu dumpsite and the

crustal abundance of elements as adopted from Dineley et al., (1976) are contained

in Table 6. The particle size distribution curve of soil samples from Avu dumpsite

are illustrated in Figure 2.

In order to determine the textural characteristics of the soil where these refuse

dumps are domiciled, which invariably influences the rate of leachate migration,

soil samples from Avu dumpsite were subjected to sieve analysis. The results of the

sieve analysis showed that the dominant formation was sand (Figure4.2).This

agrees with the findings of many authors (Reyment, 1965; (Avbovbo, 1978;

Onyeagocha, 1980; (Uma and Egboka, 1985) regarding the geology and

hydrogeology of the area. The sandy formation is porous and permeable and this

implies that plume from dumpsite will migrate easily into the unconfined shallow

aquifer to contaminate the groundwater system. According to Uma (1989), the

average linear groundwater flow in area is approximately 400 m/yr while leachate

moves at about 6 km away from its source in every 15 years interval. These

findings suggest that soil/aquifer contamination via dumpsite plume is inevitable on

the long-run due to accumulation effect. Although the contamination is localized at

the top-soil, the sub-soil which is uncontaminated presently may be polluted in

future if the dumping of refuse persists at the dumpsite because of the vulnerability

of the soil formations, since it lacks the capacity to impede downward migration of

leachate (Amadi, 2011).

113

A total of 15 soil quality parameters (Copper, Zinc, Manganese, Lead, Iron,

Sodium, Potassium, Calcium, Chlorine, and Fluorine, pH, Temperature,

Conductivity and Bacteria count) were used for this study. The mean concentration

ofmanganese, lead, iron, pH and bacteria count were found to be higher in Avu

dumpsite soil. The concentration of all the parameters analyzed is far below the

crustal abundance of the individual elements concerned except cadmium (Table 6).

The high concentration of cadmium may be due to the decay of abandoned electric

batteries and other electronic components (Mull, 2005). The thickness of lateritic

sand (overburden) is higher in Owerri and decreases southwards towards Aba area.

Iron is responsible for the reddish-brown colouration in laterites and the leaching of

iron oxide is a function of PH. The low pH in the region could be attributed to acid-

rain caused by long-term gas flaring in the region, and has also increase the

temperature in the area. The dumping of human and animal excreta (faeces) in the

area is responsible for the enrichment of the soil with Bacteria such as total

coliform and E. coli and it is an indication of poor sanitary situation in the area

(Tijani, 2004). The enrichment of the soil with manganese and lead may be

attributed the various human activities going on in the area. High copper and zinc

concentration are coming from the decomposition of electrical materials, roofing

sheets, cooking utensils, alloys, electroplating and chemical effluents (Odero et al.,

2000).

114

Table 4.6: Summary of mean concentration of elements of soil samples from Avu

Dumpsites and its corresponding crustal abundance (Adopted from Dineley et al.,

1976)

PARAMETERS (PPM)

AVU

CRUSTAL

ABUNDANCE (PPM)

Copper

21.00

70.00

Zinc

78.20

132.00

Manganese

27.14

1000.00

Cadmium

0.18

0.15

Lead 12.50

16.00

Iron 239.38

50000.00

Sodium 410.67

28300.00

Potassium 110.45 25900.00

Calcium 98.00

36300.00

Chlorine

355.00

314.00

Fluorine

23.00

900.00

PH

5.10

_

Temperature (℃)

29.00

_

Conductivity (μs/cm) 200.00 _

Bacteria Count (cfu/mg)

20.86

_

115

Figure 4.2:Particle size distribution curve for Avu dumpsite soil

It is interesting to note that the concentrations of soil samples collected far away

from the dumpsites are lower compared the ones collected in the vicinity of the

dumpsites. The enrichment of the soil by these elements may be due to its contact

with leachate from the dumpsites.

116

CHAPTER FIVE

5.0 DISCUSSION, CONCLUSION AND RECOMMENDATION

5.1 DISCUSSIONS

The database required for this project was designed using the conceptual and logical

design, after which the actual implementation of the database was carried out with

the physical design.

The data required were captured through scanning and georeferencing an analogue

map obtained from State ministry of Land & Survey and Owerri Capital

development Authority. The Georeferenced map was digitized using AutoCAD

Land Development 2i. The digitized drawing was then exported into Arc view

3.2a, where the layers were converted to shape files and then polygonized.

Afterwards, attribute tables were created for each land use and finally, the required

analyses were performed using the same Arc View 3.2a.

LC is largely of natural origin or is created by LU but is characterized by the

biophysical features of the terrestrial environment. It is the employment of LC and

management strategy used on a specific class by human agents for land managers

[Baulies and Szejwach, 1997]. LC may be created by LU as defined by

infrastructural facilities such as roads, buildings, etc. This implies that the LU and

LC underwent massive transformation and change in the referred period. This may

be as a result of massive land/physical development due to rising spate of

urbanization around Owerri and environs. Apart from these, irregular and scattered

LU and LC patterns characterizes the study area, thereby making lack of spatial

specialization a hindrance to integrated land management and development with

consequent environmental problems such as soil erosion, solid waste, loss of

biodiversity, soil infertility and loss of environmental aesthetics.

117

Land capability index study shows that Forralithic soil and lithosoil tilt towards

Sandy clay while that of ferralithic and hydromorphic soils tilt towards silty clay.

Soils that tilt towards sand have high shear and compressive strength, while those

tilting towards silt have high attenuative power in handling waste effluents. (Gauley

and Krone (1966) Krynine and Jude, (1957). Thus the ferralithic and hydromorphic

soils indicate a good land use option for solid waste disposal due to its high

attenuated power in handling waste effluents.

The results of the Soil erodibility index study in Owerri West Local Government

Area of Imo State showed that the soils in the area are mainly sandy soils. The

hydrometer test used in the computation of the erodibility indices revealed that Ohi

has the highest erodibility indices of 0.044 followed by Orogwe and Amakohia-Ubi

with 0.040. The least erodibility indices were obtained in Obinze and Ihiagwa

towns, both with erodibility indices of 0.029. The data obtained from this study will

be useful in the design of a sanitary landfill and construction of conservative

structures that can adequately check the menace of erosion in these communities in

Imo State.

Geotechnical study on soil textural characteristics of Avu dumpsite established that

the dumpsite is still in its active stage. The mean concentrations of manganese, lead,

iron, pH and bacteria count were found to be higher in Avu dumpsite soil while the

other parameters are lower in concentration. The concentration of all the parameters

analyzed is far below the crustal abundance of the respective elements except

cadmium. The high concentration of cadmium may be due to the decay of

abandoned electric batteries and other electronic components on the dumpsites. The

soil samples collected far away from the dumpsites have lower concentrations

compared to those from the vicinity of the dumpsites. This is a signature that

118

leachate from the waste dumps which are rich in heavy metal are interacting with

the soil and thereby enriching it. The graph of sieve from the dumpsite implies

similarity in wastes materials and geohistory. A modern sanitary landfill system that

will protect the soil and aquifer from contamination was designed for the area.

Construction of future dumpsites in the area should follow the prescribed design.

5.2 CONCLUSIONS

The use of GIS technology is a better way of decision making on complex issues

related to the earth (land suitability) and the people living therein, such as

agriculture, forestry, health, resource management, land administration, water

resource planning, location analysis etc. In this study, GIS technology was applied

for decision making in municipal solid waste management via the selection of

possible and suitable points for solid waste collection. This was done in line with

the purpose and set criteria for selection of suitable sites for waste collection points.

The geographic database was tested by defining and executing some criteria, which

gave the result as shown in chapter four. Thus, this has shown the capabilities of

GIS as a system to solve spatial problems and provide information to aid decision

making.

The work done so far indicates that the geology of the study area is made of Benin

Formation which is known as the ‘coastal plain-sand’. It consists mainly of sands,

sandstone and gravel with clays occurring in lenses. Based on these, three soil types

were identified with the soil map of Imo State, using the United States Department

of Agriculture (Peech et al. 1947) and Food and Agricultural Organization of the

United Nations (FAO 1976) classification systems. These soils are ferralithic,

hydromorphic and forralithic.

The purpose of land use planning is to make the best, most sensible, practical, safe

and efficient use of each parcel of land. Mapping of a land unit for a particular

119

purpose is an aspect of Land use planning which ensures maximum and safe

utilization of land. Improper management and disposal of solid waste in owerri is a

result of problem of land use option. LU and LC patterns characterizes the study

area, thereby making lack of spatial specialization a hindrance to integrated land

management and development with consequent environmental problems such as

soil erosion, solid waste, loss of biodiversity, soil infertility and loss of

environmental aesthetics.

In other to solve this problem of solid waste disposal in owerri, GIS was applied to

determine the collection points for these solid wastes but the problem cannot be

fully solved if a good suitable site for the disposal of this collected waste from the

study area is not determined too.

This further led to the study of the land use and land cover in owerri. The land

capability index study reveals that the Forralithic soil and lithosoil tilt towards

Sandy clay while that of ferralithic and hydromorphic soils tilt towards silty clay.

Based on these, soils that tilt towards sand have high shear and compressive

strength, while the soils along Avu (ferralithic and hydromorphic) tilts towards silt

thus having high attenuative power in handling waste effluents.

Soil erodobility index study for the land use determinant for solid waste also shows

that solid waste should not be disposed in areas prone to erosion. Based on this,

areas with the least erodibility indices were obtained in Obinze and Ihiagwa towns,

both with erodibility indices of 0.029 and Avu 0.03 should be a good suitable site

for the disposal of solid waste.

The geotechnical study of the soil textural characteristics closer and farther from

Avu shows that the soil samples collected far away from the dumpsites have lower

concentrations compared to those from the vicinity of the dumpsites. Based on

these, a modern sanitary landfill system that will protect the soil and aquifer from

contamination should be designed for the area.

120

Finally, the correlation of these studies indicates that these collected solid wastes

from the study area with the use of GIS should be disposed completely in a good

suitable site like Obinze, Ihiagwa town and the Avu area since the soils along those

sites are less prone to erosion and have high attenuated power for the waste effluent.

5.3 RECOMMENDATIONS

As a result of the findings of the study and the limitations encountered, the

following recommendations are made for proper solid waste management;

Decision makers and stakeholders in the management of solid waste should adopt

Geographic Information System (GIS) as a tool in decision making in their

everyday operations.

Digital land use maps should be introduced in the aspect of waste collection, since it

is an important tool for planning and management of waste in given geographical

entities. It helps in having a holistic view of the entire area at a glance.

GIS laboratories should be introduced in higher institutions and government

agencies. This will enable the production and updating of spatial data such as maps.

GIS projects should be funded by the government, private agencies and other

organizations. This will enhance human development and growth especially in our

developing economy.

Large scaled projects should be carried out in phases for efficient and effective

actualization of good result and high visibility.

A good engineering structure like the modern sanitary landfill that incorporates the

geomorphology, geology and hydrogeology of the area that will offer protection to

the soil and aquifer should be designed due to the indications of possible soil and

aquifer contamination as a result of leachate migration from the dumpsite.

121

The design should be air tight to avoid overcrowding by Venice and the waste must

be treated preliminarily to remove non-biodegradable and recyclable materials

usually called xenobiotics; a way of regulating and controlling solid waste

pollution.

This design should also incorporate two clay liners which are capable of impeding

any downward movement of leachate into the soil and aquifer horizon. Leachates

collected from the collection point can as well be transported and treated at the

treatment plant before been discharged. This will help in making dumpsite leachate

harmless to the ecosystem. Gas generated in the decomposition of wastes in the

modern sanitary landfill is usually rich in methane and can also be channeled to

generate electricity, a way of turning waste into wealth.

122

5.5 DESIGN OF A MODERN SANITARY LANDFILL FOR THE

AREA

Plate 5: A modern sanitary landfill designed to replace Avu open dumpsite.

123

REFERENCES

Adesida, A. A. and Igboku, A. O (1998): Solid Waste Management: SPDC

Approach Environmental New (NES Quarterly Publication), Vol. 5, No 1,

Pg 19-22.

A.N. Amadi, M. I. Ameh, and J. Jisa. The impact of dumpsites on groundwater

quality in Markurdi Metropolis, Benue State. Natural and Applied Sciences

Journal, 2010, 11(1): 90 – 102

Awosan, Samuel Akinsola (2006): GIS Application in Site Selection For Solid

Waste Collection Points, A Case Study of Ajoda New Town. An

Unpublished PGD Research Report, Federal School Of Surveying, Oyo,

Oyo State.

Baulies, X and G. Szejwach, eds. (1997): Survey of needs, gaps and priorities on

data for Land use/ land cover change research. Report presented at the

LUCC data requirement workshop, 11 – 14

B. J. Alloway. Heavy metals in soil. John Wiley and sons Inc., New York, 1990

339p

Bouyoucos, G.J. 1935. The clay ratio as a criterion of susceptibility of soils to

erosion. J. Amer. Soc. Agron. 27(9): 738–41.

Chapin, F.J. 1965. Urban land use planning, Illinois, University press pp 34 -48

Chengliu, and Evett, (2000). Soil properties 2nd Ed, Prentice Hall Inc, A Div of

Simon and Schuster Englewood Cliffs, New Jersey 06232, pp 28

124

Cihlar J. and L. J. M. Jansen (2001). From land cover to land use: A methodology

for efficient Land use Mapping over large areas, Professional Geographer 53

[2], pp 275 – 289, Association of American Geographers.

Crynine, (1977). Land disposal of solid wastes CBS publishers and distributors,

Darya Garji New Delhi pp. 850 – 930

Davis, R and Rogers, 1975. Land fill evaluation and Siting study New Jersey. John

Wiley and Sons publishers pp 240 – 285

ESRI (1999): “Understanding GIS”. British Library Catalogue in Publication

Data Lessons 8, pg 10.

Falade J. F. (2000): Managing Solid Waste Developing Countries, New Nigeria

Newspaper on Sunday, January 16th 2000.

FAO (1976). A framework for land evaluation. FAO Soil Bulletin No. 32.

FAO, Rome, Italy.

Federal Government of Nigeria (2003). “First National Communication on Climate

Change (Final Draft)”, Federal Ministry of Environment, Abuja.

FEPA (1998): Federal Environmental Protection Agency, Federal Government of

Nigeria.

125

Tahri, M. Benya, E. I. Bounakla, J. J. Bilal (2005). Multivariate analysis of heavy

metal in soils, sediments and water in the region of Meknes, Central

morocco. Environ. Monitor. Asses., 102: 405 – 417

Hudson, N.W. (1995). Soil conservation.3rd Ed. Iowa State University Press,

Ames, IA, USA.

Imo State Government, (2000). Imo State of Nigeria Populations Projections by

Local Government Areas, Imo State Planning and Economic Development

Commission, Owerri.

Iro S. I. (2009): Application of GIS in Mapping Otamiri River watershed in

Owerri, Imo State. An Unpublished MSc Research Report Submitted to the

Department of Geography and Environmental Management, Imo State

University Owerri.

Jeffrey, S. and John E. (1989). Geographic Information Systems: An Introduction,

Prentice Hall, New Jersey. Pg 18.

Jensen (1985). Solid and Hazardous Waste Disposal Site selection using Digital

GIS Technique. The Science of Total Environment, Vol. 56.

Kufoniyi O. (1998). Basic Concept in GIS in Ezigbo, C. U. Principle and

Application of GIS, Lagos, Panas Press.

Malter P. M. (1991): computer Application in Geography, widely press, New York

(pg 61-62).

126

M. Banar, O. Aysun, K. Mine (2006). Characterization of the leachate in an urban

landfill by physicochemical analysis and solid phase microextraction.

GC/MS. Environ. Monitor. Assess., 121: 439 – 459

Morgan, R.P.C. (2001). A simple approach to soil loss prediction: a revised

Morgan-Morgan-Finney model. Catena 44(4): 305-22.

Nathawat, M. S. and Shrivastava U. (2001): www.gisdevelopment.net

NEST (1999). Nigerian Threatened Environment: A National Profile, Nigerian

Environmental Study/Action Team (NEST) Publication, Ibadan.

Njoku C. (2010). Application of GIS in Selecting Solid waste Collection Point

in Ikenegbu Layout, Owerri. An Unpublished B.Sc. Thesis Submitted to the

Department of Geography, Imo State University.

Nkwocha E. E. (2010). Paper Presentation on Solid Waste management and Effect.

MSc Lecture Note on Solid and Hazardous waste Management.

Nnabugwu O. U. (2003): micro Simulation Model for Evaluating and Mapping

Domestic Waste Generation (NCA Publication).

Nwadike O. (2004). Solid Waste management in Owerri Municipal Area. An

Unpublished B. Tech Thesis Submitted to the Department of Environmental

Technology Owerri, Imo State.

Ogra A. (2002). Municipal Application of Geographic Information Systems for

effective solid waste management system, Dehradum, pg 2-3.

http://www.gisdevelopment.net/

127

Olaribe M.A. (2007), Application of GIS in Selection of Solid Waste Disposal

Site.A case study of Ogbomosho North L.G.A., Oyo State. An Unpublished

PDG Thesis submitted to the Department of Geoinformatics, Federal School

of Survey, Oyo State.

Uchegbu S. N. (2002) Environmental Management and Protection. 2nd Ed. Enugu:

Spotlite Publishers, pg 39-46, 63-70, 75-83.

www.gisdevelopment.net/gisglossary - geographic information science

Lin, Y. P. Teng, T. P. Chang, T. K. (2002). Multivariate analysis of soil heavy

metal pollution and landscape in Changhua Country in Taiwan. Landscape

Urban Plan. 62: 19 – 35 November, Barcelona

128

APPENDIXES

APPENDIX I

SYMBOL MEANING

Com Commercial land use

Com_BuffDist Commercial buffer distance

ECTAH1 Eastern Central Tangent Arterial Highway road 1

ECTAH2 Eastern Central Tangent Arterial Highway road 2

NCTAH Northern Central Tangent Arterial Highway road

NMTAH1 Northern Middle Tangent Arterial Highway road 1



NETF Northern External Tangent/Freeway road

Pub Public land use

Pub_BuffDist Public use Buffer Distance

Res Residential land use

Res_BuffDist Residential use Buffer Distance

SETF Southern External Tangent/Freeway road

SCTAH southern Central tangent Arterial Highway road

SMTAH1 Southern Middle Tangent Arterial Highway road 1

SMTAH2 Southern Middle Tangent Arterial Highway road 2

129

WETF Western External Tangent/freeway road

WMTAH1 Western middle Tangent Arterial Highway road 1



130

APPENDIX II

ATTRIBUTE TABLE FOR VARIOUS LAND USE TYPES

Attribute table for boundary

131

Attribute of commercial land use

132

Attribute of public land use

133

Attribute table for roads

134

Attribute table for river

135

Attribute table for residential land use

Complete Project Work

Documents