Characterizing and Relating Meridional Variability in Satellite Images of the West African Sudano-Sahel to Desertification and Food Security
This document is available on cd for U.S.$30, cheaper than ordering from UMI; furthermore, the cd shows all images in color, which neither the UMI paper medium nor its microfilm can do. To order, send check or money order to:
Dr. L. Milich
The Office of Arid Lands Studies
The University of Arizona
1955 E. Sixth St.
Tucson, AZ 85719 (USA)
Abstract
At the 7.6 km spatial scale in which remotely-sensed satellite imagery is used in many studies of subcontinental-scale vegetation vigor and dynamics, the information acquired has yet to be fully understood and integrated with ground-level reality. This dissertation reports results and analysis from ground-truth-sampling in the arid lands of West Africa's Sudano-Sahelian zones. The geographical locations of the transects investigated were obtained from areas exhibiting steep gradients in the interannual (1980-1994) coefficients of variation (CoV) of the mean annual monthly maximum composite of the Global Area Coverage's (GAC) Normalized Difference Vegetation Index (NDVI) from the Advanced Very High Resolution Radiometer (AVHRR) series of satellites.
I begin this work by disaggregating the term “food security” into its various components, then continue by exploring what is generally understood by the concept of “desertification” and what this actually translates to in terms of land degradation. I then discuss how an error in NASA's method for calculating interannual NDVI CoVs impacted both my own work and our concepts of the Sahel's boundaries. Field data I gathered in the central and northern Sahel indicate that cogent, simple explanations of latitudinal variations in CoV do exist, albeit not everywhere. The Gourma region of Mali provides an excellent example of how complexity confounds any neat quantization of information. For the more southerly agropastoral zone, high CoV variability flags rapid, dynamic desertification processes. Results of village- and household-level profiles along a transect in the heart of Hausaland confirm that rapid, dynamic land degradation corresponds with a high interannual CoV.
Climate, especially rainfall and potential evaporation, form the basis of an analysis the outcome of which explains how and why the Malian Gourma shows a nonlinear, “anomalous” NDVI response to rainfall. I also explore the strong correlation between rainfall and NDVI in the southern Sahel, but conclude that if there is a link between NDVI and crop yields, it is very weak indeed. Finally, my research highlights several policy measures that may retard desertification and enhance food security.
Table of Contents
Chapter 1
1. General Overview
1.1. Project Summary
1.2. A Roadmap to This Dissertation
1.3. Food Security
1.3.1. NDVI, desertification, and food security
1.3.2. Cultural ecology and food security
1.3.3. Definitions of food security
1.3.4. Food security and the link to population parameters
1.3.5. Household studies: Linking cultural ecology, ecological change, and food security
1.3.6. Gender and food security
1.4 Hypotheses
1.5. Questions To Be Examined
1.6. Research Objectives
1.7. Research Methods
1.8. Steep Gradients: The Transect Set
Chapter 2
2. Desertification
2.1. Introduction
2.2. Land Degradation
2.3. Fragility vs Resilience
2.4. Reversibility vs Irrecuperability
2.5. Anthropogenic Desertification vs ‘Natural’ Climate Trends
2.6. The Ferlo Case Study: Poor Development Strategies Result in Localized Anthropogenic Desertification
2.7. Is It Possible To Construct A Universal Model of Desertification?
Chapter 3
3: The Satellite Images and Their Manipulation
3.1 The Normalized Difference Vegetation Index
3.2 Available AVHRR Data
3.3 Limitations to the Accuracy of AVHRR Data
3.3.1. Solar zenith angle
3.3.2. Sensor drift
3.4. NDVI Studies on Northern African Arid and Semiarid Lands
3.5. The Maximum-Value Monthly Composite (MVMC) Technique and Its Limitations
3.6. The Interannual Coefficient of Variation Image (CoV) and Its Limitations
3.7. Implications of Correctly Calculating CoVs from NDVI Values
3.7.1. Effect on CoV magnitude
3.7.2. Changes in the character of the Sahel
3.7.2.1. Comparisons with GSFC's Sahel definition of CoVs >0.25
3.7.2.2. A well-defined Sahel – Sahara boundary
3.7.2.3. Comparison with GSFC's Sahel definition of a 200-mm isohyet
3.8. Comparing True CoV Values Calculated from NDVI with Artifacts Calculated from DNs
3.9. Conclusion
Chapter 4
4. Transects in the Grazing Lands of Mali and Mauritania
4.1. Introduction
4.2. Aspects of the Ecology of Sahelian Rangeland
4.2.1. Species composition
4.2.2. Biomass
4.2.3. Tree cover and density
4.2.4. The ecological role of livestock
4.2.5. The effects of fire
4.2.6. Summary
4.3. Transects in Mali
4.3.1. Mali 1
Summary:
4.3.2. Mali 2: The Gourma transect
Summary:
4.3.3. Mali 3
4.4. Transects in Mauritania
4.4.1. Mauritania 1
Summary:
4.4.2. Mauritania 2
Summary:
4.4.3. Mauritania 3
Summary:
4.5. Summary and Conclusions
Chapter 5
5. The Niger Transect
5.1. Introduction
5.2. The Rapid Rural Appraisal Method of Collecting Information from Rural Households
5.3. Hausaland and the Hausa
5.3.1. Introduction
5.3.2. An Overview of Hausaland's Biophysical Factors
5.3.3. Famine in Hausaland
5.3.4. Risk, Uncertainty, and Household Options
5.3.5. Indigenous Knowledge and Household Options in 19th Century Hausaland
5.3.6. Colonialism, Cash Crops, and Class
5.3.7. Gender Issues
5.3.7.1. Fertility
5.3.7.2. Sexuality and labor: normative vs. residual mores
5.3.7.3. Intrahousehold conflict and gender inequity
5.4. The Niger Transect
Summary:
5.5. Village-Level and Economic-Group Household Profiles Constructed from RRA Questionnaires
5.5.1. Villages in the vicinity of Waypoint A (Niger)
5.5.2. Villages in the vicinity of Waypoint B (Niger)
5.5.3. Villages in the vicinity of Waypoint C (Niger)
5.5.4. Villages in the vicinity of Waypoint D (Nigeria)
5.5.5. Villages in the vicinity of Waypoint E (Nigeria)
5.5.6. Summary of household profiles along the Niger 1 transect
5.6. Time Series: Economic Classes in Doukou Doukou, Niger
5.6.1. Millet yield vs. farm size, 1994
5.6.2. Time series of mean annual millet yields
5.6.3. Manure and fertilizer inputs, 1994
5.6.4. Summary and implications for food security
5.7. Models of Desertification and Food Insecurity
5.7.1. Watts' ‘Political Economy of Underdevelopment’ model
5.7.2. Hill's ‘Rural Economy’ model
5.7.3. Bryceson's ‘Social Division of Labor’ model
5.7.4. Franke and Chasin's ‘Colonialism and Ecological Crisis’ model
5.7.5. van Apeldoorn's ‘Coerced Underdevelopment’ model
5.7.6. Environmental degradation, turmoil, and food insecurity
Chapter 6
6. Rainfall
6.1. Drylands Rainfall and Its Anomalies
6.1.1. Drought
6.1.2. The Stochastic Nature of Convective Storms
6.1.3. Variability in Sahelian Rainfall
6.1.5. Sahelian Rainfall and the El Niño/Southern Oscillation (ENSO)
6.1.6. Summary
6.2. The ILCA Raingage Network in the Gourma, Mali
6.2.1. Data Distribution
6.2.2. Spatiotemporal Analyses
6.2.3. Rainfall and GAC NDVI
6.2.4. Potential Evaporation and GAC NDVI
6.2.5. Water Deficit
6.2.6. Summary
6.3. Rainfall along the Niger 1 Transect
6.3.1. Rainfall and NDVI at Bangui, Niger
6.3.2. Spatial Variation in Rainfall
6.3.3. Rainfall and NDVI along a 40-km Transect Centered at Bangui, Niger
6.3.4. Rainfall and Millet Yield, Doukou Doukou, Niger
Chapter 7
7. Conclusions and Recommendations
7.1. Synopsis of Chapters 1 - 6
7.2. Summary of Findings from Chapters 1 - 6
7.3. Potential Interventions in Desertification–Food Insecurity Linkages
References
Appendix 1
Photographs and Video at Ground Level
Appendix 2
Photographs and Images from Space
Appendix 3
Rapid Rural Appraisal Questionnaires
Back to Curriculum Vita