Investigating rural poverty and marginality in Burkina Faso using remote sensing-based products

International Journal of Applied Earth Observation and Geoinformation

Volumn 26, Issue 1, 2014, Pages 322-334

  Imran, M ^a   Stein, A ^a   Zurita Milla, R ^a  

^a UNIVERSITY OF TWENTE   (Netherlands)

Author keywords

Composite asset index; Food security; Geographical weighted regression; SPOT NDVI; TAMSAT rainfall

Indexed keywords

AGRICULTURAL PRODUCTION; ENVIRONMENTAL FACTOR; FOOD CONSUMPTION; FOOD SECURITY; LIVING STANDARD; NDVI; POVERTY; RAINFALL; REGRESSION ANALYSIS; REMOTE SENSING; RURAL AREA; SPOT;

BURKINA FASO;

EID: 84897878817     PISSN: 15698432     EISSN: 1872826X     Source Type: Journal    
DOI: 10.1016/j.jag.2013.08.012     Document Type: Article

References (34)

1. AGRISTAT, 2010. Réultats définitives campagne (2008-2009). Burkina Faso. Tech-nical report. Statistiques sur l'Agriculture et l'Alimentation du Burkina Faso(AGRISTAT), Ouagadougou, Burkina Faso.
2. Alasia, A., Bollman, R.D., Parkins, J., Reimer, B., 2008. An Index of Community Vulner-ability: Conceptual Framework and Application to Population and EmploymentChanges (1981 to 2001). Statistics Canada, Agriculture Division.
3. Anselin, L., 1995. Local Indicators of Spatial Association - LISA. Geogr Anal 27,93-115.
4. Benson, T., Chamberlin, J., Rhinehart, I., 2005. An investigation of the spatial deter-minants of the local prevalence of poverty in rural Malawi. Food Policy 30 (5-6),532-550.
5. Berlage, L., Terweduwe, D., 1988. The classification of countries by cluster and byfactor analysis. World Dev. 16 (12), 1527-1545.
6. Bigman, D., Dercon, S., Guillaume, D., Lambotte, M., 1999. Community Targeting forPoverty Reduction in Burkina Faso. Faculty of Economics, KU Leuven.
7. de Graaf, J., Nikiema, R., Tapsoba, G., Nederlof, S., 2001. Socio-economic land useanalaysis in Sahelian villages. In: Stroosnijder, L., van Rheenen, T. (Eds.), Agro-Silvo-Pastoral Land Use in Sahelian Villages. Catena Verlag GMBH, Germany, pp.23-71.
8. Dreschel, P., Gyiele, L., Kunze, D., Cofie, O., 2007. Population density, soil nutri-ent depletion, and economic growth in sub-Saharan Africa. Ecol. Econ. 38 (2),251-258.
9. Ebert, U., Welsch, H., 2004. Meaningful environmental indices: a social choiceapproach. J. Environ. Econ. Manage. 47, 270-283.
10. FAO, 2012. Food Insecurity, Poverty and Environment Global GIS database (online),http://www.fao.org/geonetwork/ (accessed 20.11.12)].
11. Fotheringham, A., Brunsdon, C., Charlton, M., 2002. Geographically WeightedRegression: The Analysis of Spatially Varying Relationships. Wiley, NY, USA.
12. Gao, J., Li, S., Zhao, Z., Cai, Y., 2003. Investigating spatial variation in the relation-ships between NDVI and environmental factors at multi-scales: a case study ofGuizhou Karst Plateau, China. Int. J. Remote Sens. 33 (7), 2112-2129.
13. Gatzweiler, F.W., Baumuller, H., Ladenburger, C., von Braun, J., 2011. Marginal-ity: Addressing the Root Causes of Extreme Poverty. Center for DevelopmentResearch. University of Bonn, Germany.
14. Grimes, D., Pardo, E., Bonifacio, R., 1999. Optimal areal rainfall estimation usingraingauges and satellite data. J. Hydrol. 222, 93-108.
15. HarvestChoice, 2012. Sub-national Sub-Saharan Africa datasets. Har-vestChoice/International Food Policy Research Institute (IFPRI) (online),http://harvestchoice.org/products/data (accessed 20.11.12).
16. Hoddinott, J., Quisumbing, A., 2003. Methods for Micro economic Risk and Vulner-ability Assessments. The World Bank, USA.
17. Horn, J., 1965. A rationale and test for the number of factors in factor analysis.Psychometrika 30, 179-185.
18. Hurvich, C., Simonoff, J., Tsai, C.L., 1998. Smoothing parameter selection in nonpara-metric regression using an improved Akaike information criterion. J. R. Stat. Soc.Ser. B. 60, 271-293.
19. Hyman, G., Larrea, C., Farrow, A., 2005. Methods, results and policy implications ofpoverty and food security mapping assessments. Food Policy 30, 453-460.
20. IIASA/FAO, 2012. Global Agro-ecological Zones (GAEZ v3.0). IIASA/FAO, Laxenburg,Austria/Rome, Italy.
21. Joint Research Centre (JRC), 2012. Distribution of VEGETATION data in Africa throughEUMETCast (online), http://www.vgt4africa.org/ (accessed 20.11.12).
22. Leyk, S., Norlund, P.U., Nuckols, J.R., 2012. Robust assessment of spatial non-stationarity in model associations related to pediatric mortality due to diarrhealdisease in Brazil. Spat. Spatiotemporal. Epidemiol. 3 (2), 95-105.
23. Nelson, A., Rogers, D., Robinson, T., 2012. Poverty Mapping in Uganda: Extrapo-lating Household Expenditure Data Using Environmental Data and RegressionTechniques. FAO, Rome, Italy.
24. Neter, J., Kutner, M.C., Nachtsheim, C., Wasserman, W., 2005. Applied Linear Statis-tical Models. McGrawHill Irwin, Boston, MA.
25. Parkins, J.R., MacKendrick, N.A., 2007. Assessing community vulnerability: A studyof the mountain pine beetle outbreak in British Columbia. Glob. Environ. Change17 (3-4), 460-471.
26. Robinson, T., Emwanu, T., Rogers, D., 2007. Environmental approaches to povertymapping: an example from Uganda. Inf. Dev. 23, 205-215.
27. Roerink, G., Menenti, M., Verhoef, W., 2000. Reconstructing cloudfree NDVI compos-ites using Fourier analysis of time series. Int. J. Remote Sens. 21 (9), 1911-1917.
28. Tucker, C.J., 1979. Red and photographic infrared linear combinations for monitoringvegetation. Remote Sens. Environ. 8 (2), 127-150.
29. USAID, 2009. USAID Office of Food for Peace Burkina Faso Food Security CountryFramework FY 2010-2014. USAID, Washington, DC.
30. USGS, 2012. Hydro Africa Datasets (HYDRO1k) of Earth Resource Observation andScience Center (EROS). United States Department of the Interior Geological Sur-vey (USGS) (online), http://eros.usgs.gov/ (accessed 20.11.12).
31. Verhoef, W., 1996. Application of Harmonic Analysis of NDVI Time Series (HANTS).In Fourier Analysis of Temporal NDVI in the Southern African and AmericanContinents. Winand Staring Centre for Integrated Land, Soil and Water Research,Wageningen, The Netherlands.
32. West, C.T., Roncoli, C., Ouattara, F., 2008. Local perceptions and regional climatetrends on the Central Plateau of Burkina Faso. Land. Degrad. Dev. 19 (3), 289-304.
33. Wheeler, D., Tiefelsdorf, M., 2005. Multicollinearity and correlation among localregression coefficients in geographically weighted regression. J. Geogr. Syst. 7(2), 161-187.
34. Wood, S., Hyman, G., Deichmann, U., Barona, E., Tenorio, R., Guo, Z., Castano, S.,Rivera, O., Diaz, E., Marin, J., 2010. Sub-national Poverty Maps for the Develop-ing World Using International Poverty Lines: Preliminary Data Release (online),http://povertymap.info (accessed 20.11.12).