Assessing the vulnerability of resource-poor households to disasters associated with climate variability using remote sensing and GIS techniques in the Nkonkobe Local Municipality, Eastern Cape Province, South Africa
- Authors: Chari, Martin Munashe
- Date: 2016
- Subjects: Climatic changes -- Forecasting Natural resources -- Remote sensing Droughts -- South Africa -- Eastern Cape
- Language: English
- Type: Thesis , Masters , MSc
- Identifier: http://hdl.handle.net/10353/2425 , vital:27837
- Description: The main objective of the study was 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 Geographic Information System (GIS)-based mapping approach. The research methodology was comprised of 1) assessment of vulnerability levels and 2) 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 1985 to 2014 in order to objectively determine the temporal recurrence of drought in Nkonkobe Local Municipality. Vulnerability of households to drought was determined by using a multi-step GIS-based mapping approach in which 3 components comprising exposure, sensitivity and adaptive capacity were simultaneously analysed and averaged to determine the magnitude of vulnerability. Thereafter, the Analytical Hierarchy Process (AHP) was used to establish weighted contributions of these components to vulnerability. The weights applied to the AHP were obtained from the 2012 - 2017 Nkonkobe Integrated Development Plan (IDP) and perceptions that were solicited from key informants who were judged to be knowledgeable about the subject. A Kruskal-Wallis H test on demographic data for water access revealed that the demographic results are independent of choice of data acquired from different data providers (χ2(2) = 1.26, p = 0.533, with a mean ranked population scores of 7.4 for ECSECC, 6.8 for Quantec and 9.8 for StatsSA). Simple linear regression analysis revealed strong positive correlations between NDWI and NDVI ((r = 0.99609375, R2 = 1, for 1985), 1995 (r = 0.99609375, R2 = 1 for 1995), (r = 0.99609375, R2 = 1 for 2005) and (r = 0.99609375, R2 = 1 for 2014). The regression analysis proved that vegetation condition depends on surface water arising from rainfall. The results indicate that the whole of Nkonkobe Local Municipality is susceptible to drought with villages in south eastern part being most vulnerable to droughts due to high sensitivity and low adaptive capacity.
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Monitoring changes in vegetation distribution to ascertain the extent of degradation in the savannas of Nkonkobe Local Municipality, Eastern Cape, South Africa
- Authors: Masiza, Wonga
- Date: 2016
- Subjects: Savanna ecology -- South Africa -- Eastern Cape Land degradation -- South Africa -- Eastern Cape Vegetation management -- South Africa -- Eastern Cape
- Language: English
- Type: Thesis , Masters , MSc
- Identifier: http://hdl.handle.net/10353/2027 , vital:27598
- Description: Savanna degradation is an environmental problem occurring in most countries around the world and it poses threats to biodiversity conservation, the food industry, and other economic sectors. According to FAO, South Africa’s rangelands exhibit the highest rate of fragmentation in comparison to range ecosystems in neighbouring countries including Lesotho and Swaziland, and consensus among researchers is that communal rangelands are more degraded than commercial rangelands. Although researchers and communities have identified the occurrence of land degradation in communal savannas at a local scale, land degradation has been poorly estimated because little has been done to quantify the extent and dynamics of perceived and observed changes associated with land degradation. The main goal of this study is to provide empirical insights on the direction of changes in the communal savannas of Nkonkobe Local Municipality in order to inform policy formulation and implementation. Additional to the communal sites is a private farm included for comparative analysis of trends in communal and commercial savannas. Landsat imagery was used to map, assess, and quantify the extent of land degradation in Nkonkobe Local Municipality, over a period of 30 years between 1984 and 2014. Field investigations were undertaken in June 2015 to acquire reference data to guide supervised classification of Landsat images. Three algorithms (Mahalanobis-distance, Minimum-distance, and Maximum likelihood classification) were compared to identify a classifier that produced the best results. The maximum likelihood classifier produced the best results with classification accuracy levels of 95.24 percent, 89.66 percent, and 95.65 percent for Honeydale Farm, Thyume, and Sheshegu respectively. Regression analysis revealed that both communal and private lands have experienced statistically significant increases in bush encroachment and decreases in surface water. Communal savannas have been confronted more by expansion of built-up area, decrease in open grassland, abandonment of arable land, soil erosion, and a steady invasion by Acacia Karroo compared to the privately owned commercial farm. The land cover changes measured through this investigation suggest an environmental shift that threatens biodiversity and agricultural activity. The study provides empirically informed insights about the direction to which these savannas are changing with the hope that the findings will prompt formulation and implementation of effective policies.
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