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Mr Martin Munashe Chari

 

 

 

M.Sc. in Applied Remote Sensing & GIS

Department of GIS and Remote Sensing

University of Fort Hare

                                                                                                  

     Abstract               

INVESTIGATING THE VULNERABILITY OF RESOURCE-POOR HOUSEHOLDS TO CLIMATE VARIABILITY RELATED RISKS USING REMOTE SENSING AND GIS TECHNIQUES IN NKONKOBE LOCAL MUNICIPALITY IN THE EASTERN CAPE PROVINCE OF SOUTH AFRICA.

The main objective of the study is to assess the extent to which resource-poor households in selected villages of Nkonkobe Local Municipality in the Eastern Cape Province of South Africa are vulnerable to drought by using an improvised remote sensing and GIS-based mapping approach. The research methodology comprises assessment of 1) vulnerability levels, 2) drought hazard and 3) drought risk. The entire assessment will be based on the calculation of established drought assessment indices comprising the Normalized Difference Vegetation Index (NDVI) and the Normalized Difference Water Index (NDWI) from wet-season Landsat images covering a period of 29 years from 1984 to 2013 in order to objectively determine the temporal recurrence of drought in Nkonkobe Local Municipality. Vulnerability of households to drought will be determined by using a multi-step GIS based mapping approach in which 3 components comprising exposure, sensitivity and adaptive capacity will be simultaneously analyzed and averaged to determine the magnitude of vulnerability. Thereafter, the Analytical Hierarchy Process (AHP) will be used to establish weighted contributions of these components to vulnerability. The weights to be applied to the AHP will be obtained from the 2012 - 2017 Nkonkobe Integrated Development Plan (IDP) and perceptions that will be solicited from key informants knowledgeable with the subject. The drought risk assessment will be done by combining the drought hazard with the vulnerability assessment in a Geographic Information System.  The Root Mean Square Deviation (RMSD) will be used to check errors in NDVI calculations and the K statistic used to check the accuracy of the results.

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