Recent advances in remote sensing and GIS in Sub-Sahara Africa / editors, Courage Kamusoko, Charles Ndegwa Mundia, Yuji Murayama.

Format:

Book

Contributor:

Kamusoko, Courage.

Mundia, Charles Ndegwa.

Murayama, Yūji, 1953-

Series:

Computer science, technology and applications.

African political, economic, and security issues series.

African political, economic, and security issues

Computer science, technology and applications

Language:

English

Subjects (All):

Remote sensing--Africa, Sub-Saharan.

Remote sensing.

Geographic information systems--Africa, Sub-Saharan.

Geographic information systems.

Land use--Africa, Sub-Saharan.

Land use.

Africa, Sub-Saharan--Geography.

Africa, Sub-Saharan.

Physical Description:

1 online resource (225 p.)

Edition:

1st ed.

Place of Publication:

Hauppauge, N.Y. : Nova Science Publishers, 2011.

Language Note:

English

Summary:

This book focuses on impending serious problems of socio-economic conditions in the sub-Saharan countries utilising remote sensing and GIS techniques. In Africa, the use of remote sensing data and analysing techniques such as GIS is essential for any studies that involve an extensive area because more often than not, topographic maps at a scale of 1:50,000 or larger are not available for detailed mapping on the ground. In addition, basic socio-economic and physical data, such as census data, environmental data, and infrastructure data, are lacking or not kept updated for modelling analyses.

Contents:

Intro

RECENT ADVANCES IN REMOTE SENSING AND GIS IN SUB-SAHARA AFRICA

LIBRARY OF CONGRESS CATALOGING-IN-PUBLICATION DATA

CONTENTS

FOREWORD

REFERENCE

PREFACE

ABOUT THE EDITORS

ABOUT THE CONTRIBUTORS

Chapter 1 INTRODUCTION: USEFULNESS OF SPATIAL ANALYSIS WITH REMOTE SENSING AND GIS IN SUB-SAHARA AFRICA

1.1. INTRODUCTION

1.2. SUMMARY OF BOOK CHAPTERS

Chapter 2 MODELING SPATIAL PROCESSES OF URBAN GROWTH IN AN AFRICAN CITY: A CASE STUDY OF NAIROBI

ABSTRACT

2.1. INTRODUCTION

2.2. DATA AND METHODOLOGY

2.3. CALIBRATING CELLULAR AUTOMATA MODEL

2.4. ACCURACY ASSESSMENT

2.5. RESULTS AND DISCUSSION

2.6. SUMMARY AND CONCLUSIONS

REFERENCES

Chapter 3 MARKOV-CELLULAR AUTOMATA APPROACH FOR MODELLING LAND USE/COVER CHANGES IN AN AFRICAN RURAL LANDSCAPE: A CASE STUDY IN THE BINDURA DISTRICT, ZIMBABWE

3.1. INTRODUCTION

3.2. BACKGROUND

3.2.1. Markov Chain Analysis

3.2.2. Cellular Automata

3.2.3. Markov-Cellular Automata Model

3.3. STUDY AREA

3.4. METHODOLOGY

3.4.1. Data

3.4.2. Markov-Cellular Automata Modelling Framework

Computation of Land Use/Cover Transition Potential Maps

Computation of Transition Probabilities Using Markov Chain Analysis

Spatial Allocation of Simulated Land Use/Cover Probabilities

3.5. RESULTS AND DISCUSSION

3.5.1. Analysis of Land Use/Cover Changes and Transition Probabilities

3.5.2. Validation of the Markov-Cellular Automata Model

3.5.3. Simulated Future Land Use/Cover Changes

3.6. SUMMARY AND CONCLUSIONS

ACKNOWLEDGMENTS

Chapter 4 URBAN LAND USE CHANGE AND LANDSCAPE FRAGMENTATION IN LAGOS, NIGERIA

4.1. INTRODUCTION

4.2. STUDY AREA

4.3. METHODS

4.4. RESULTS AND DISCUSSIONS.

4.4.1. Quantitative Data on Land Use Change

4.4.2. Characterization of New Residential Land Use Change

4.4.3. The Logistic Regression Models

4.4.4. Landscape Fragmentation Metrics

4.5. SUMMARY AND CONCLUSIONS

ACKNOWLEDGMENT

Chapter 5 A MULTISTAGE-ARTIFICIAL NEURAL NETWORK AND EXPERT SYSTEM (MANNES) APPROACH FOR CLASSIFYING URBAN BUILT-UP AREAS BASED ON ALOS DATA: THE CASE OF HARARE, ZIMBABWE

5.1. INTRODUCTION

5.2. STUDY AREA

5.3. METHODS

5.3.1. Data

5.3.2. Preprocessing

5.3.3. Multistage-Artificial Neural Network and Expert System (MANNES) Approach

Artificial Neural Network (ANN) Classification

Texture Analysis

Expert System Classification

Classification Accuracy Assessment

5.4. RESULTS AND DISCUSSIONS

5.4.1. Classification Accuracy Assessment and Urban Land Use/Cover Mapping

5.5. CONCLUSIONS

Chapter 6 SPATIAL-TEMPORAL PATTERNS AND DRIVING FORCES OF LAND USE/COVER CHANGES IN AN AFRICAN WILDLIFE SANCTUARY

6.1. INTRODUCTION

6.2. STUDY AREA

6.3. DATA AND METHODS

6.4. RESULTS AND DISCUSSION

6.4.1. Land Use/Cover and Wildlife Population Changes

6.4.2. Factors Driving Land Use/Cover and Wildlife Population Changes

6.5. IMPLICATIONS AND THE WAY FORWARD

6.6. CONCLUSIONS

Chapter 7 EXPLORATORY WOODLAND FRAGMENTATION ANALYSIS BASED ON MATHEMATICAL MORPHOLOGY AND LANDSCAPE METRICS

7.1. INTRODUCTION

7.2. STUDY AREA

7.3. METHODOLOGY

7.3.1. Data

7.3.2. Woodland Fragmentation Analyses Based on Mathematical Morphology and Landscape Metrics

7.4. RESULTS AND DISCUSSION

7.4.1. Land Use/Cover Changes

7.4.2. Woodland Fragmentation Analyses

7.4.3. Factors Driving Woodland Fragmentation

7.5. CONCLUSIONS

REFERENCES.

Chapter 8 EXPLORATORY LAND USE/COVER CHANGE ANALYSIS IN A MUNICIPALITY IN KENYA USING MARKOV CHAIN MODEL

8.1. INTRODUCTION

8.2 STUDY AREA

8.3. METHODOLOGY

8.3.1. Land Use/Cover Change Analysis

8.3.2. Descriptive Modeling of Land Use/Cover Change Processes

8.4. RESULTS

8.4.1. Supervised Land Use/Cover Classifications

8.4.2. Land Use/Cover Changes

8.4.3. Land Use/Cover Change Projections

8.5. CONCLUSION

Chapter 9 OPEN SOURCE WEB MAPPING TECHNOLOGIES: CAN DEVELOPING COUNTRIES LEVERAGE AND TAP THE POTENTIAL THEY PORTEND?

9.1. INTRODUCTION

9.2. METHODOLOGY

9.2.1. Web Mapping Software

Geomedia Webmaptm

UMN Mapserver

9.2.2. Open Source Spatially Enabled Databases

9.2.3. Data and Sources

9.2.4. Performance Considerations

9.2.5. Basic Web Mapping Considerations

9.2.6. Design Strategies

9.3. Web GIS Implementation

GeoMedia WebMap

9.3.1. The Concept Implemented

9.3.2. The Map Interfaces

9.4. ANALYSIS AND DISCUSSION

9.4.1. The Site Pages

9.4.2. Benchmarking Metrics

9.5. CONCLUSION

Chapter 10 SDI REQUIREMENTS FOR TRANSPORT PLANNING: A CASE STUDY OF KAMPALA, UGANDA

10.1. BACKGROUND

10.2. STUDY AREA

10.3. SDI COMPONENTS

10.4. METHODOLOGY

10.4.1. Review of Current Policy Issues

10.4.2. Interviews, Field Discussions and Visits

The Netherlands

Kampala

10.4.3. Analysis

10.4.4. Workshop

10.5. RESULTS: SITUATIONAL ANALYSIS

10.5.1. The Netherlands Case

Collecting, Maintaining and Use of Real Time Data

Bureau of Transport Statistics

Strategic Planning Department

Others

10.5.2. Kampala Case

Involvement in Transport Planning

Institutional Collaboration

Political Interference.

Absence of Formalized Polices for Transport Planning and Data Exchange

Unskilled Staff in Geospatial Data Management

Incomplete Data

Limited Resources for Metadata Compilation

Overall Analysis

10.6. RECOMMENDATIONS FOR SDI REQUIREMENTS IN THE TRANSPORT SECTOR

10.7. CONCLUSION

Chapter 11 REMOTE SENSING AND GIS: CURRENT STATUS AND FUTURE PROSPECTS IN SUB-SAHARA AFRICA

11.1. INTRODUCTION

11.2. INFRASTRUCTURE AND THE CURRENT STATUS OF REMOTE SENSING AND GIS IN AFRICA

11.3. FUTURE PROSPECTS OF REMOTE SENSING AND GIS IN AFRICA

11.4. CONCLUSION

INDEX.

Notes:

Includes index.

Description based on print version record and cip data provided by publisher.

ISBN:

1-61761-512-9

OCLC:

847729093