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Land cover change and hydrological regimes in the Shire River Catchment, Malawi

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dc.contributor.advisor Prof. H.J. Annegarn en
dc.contributor.author Palamuleni, Lobina Getrude Chozenga
dc.date.accessioned 2010-11-09T06:52:35Z
dc.date.available 2010-11-09T06:52:35Z
dc.date.issued 2010-11-09T06:52:35Z
dc.date.submitted 2009-03-20
dc.identifier.uri http://hdl.handle.net/10210/3474
dc.description D.Phil. en
dc.description.abstract Land cover changes associated with growing human populations and expected changes in climatic conditions are likely to accelerate alterations in hydrological phenomena and processes on various scales. Subsequently, these changes could significantly influence the quantity and quality of water resources for both nature and human society. Documenting the distribution of land cover types within the Shire River catchment is the foundation for applications in this study of the hydrology of the Shire catchment. The aim of this study is to investigate the relationships between the measured land cover changes and hydrological regimes in the Shire River Catchment in Malawi. Maps depicting land cover dynamics for 1989 and 2002 were derived from multispectral and multi-temporal Landsat 5 (1989) and Landsat 7 ETM+ (2002) satellite remote sensing data for this catchment. Other spectral-independent data sets included the 90-m resolution Shuttle Radar Topographic Mission (SRTM) digital elevation model (DEM), Geographical Information System (GIS) layers of soils, geology and archived land cover. Core image-derived data sets such as individual Landsat bands, Normalized Difference Vegetation Index (NDVI), Principal Components Analysis and Tasseled Cap transformations were computed. From generated composite images, land cover classes were identified using a maximum likelihood algorithm. Eight land cover classes were mapped. A hierarchical multispectral shape classifier with an object conditional approach determined by the Food and Agriculture Organisation (FAO) Land Cover Classification System (LCCS) legend structure was used to map land cover variables. LCCS was used as a basis for classification to achieve legend harmonization within Africa and on a global scale. Flexibility of the hierarchical system allowed incorporation of digital elevation objects, soil and underlying geological features as well as other available geographical data sets. This approach improved classification accuracy and can be adopted to discriminate land cover features at several scales, which are internally relatively homogeneous.In addition to compatibility with the FAO/LCCS classification system, the derived land cover maps have provided recent and improved classification accuracy, and added thematic detail compared to the existing 1992 land cover maps. Fieldwork was conducted to validate the land cover classes identified during classification. Accuracy assessment was based on the correlation between ground reference samples collected during field exercise and the satellite image classification. The overall mapping accuracy was 87%, with individual classes being mapped at accuracies of above 77% for both user and producer accuracy. The combination of Landsat images, vector data and detailed ground truthing information was used successfully to classify land cover of the Shire River catchment for years 1989 and 2002. en
dc.language.iso en en
dc.subject Effect of human beings on nature en
dc.subject Landscape changes en
dc.subject Landscape ecology en
dc.subject Hydrologic models en
dc.subject Shire River Watershed (Malawi and Mozambique) en
dc.title Land cover change and hydrological regimes in the Shire River Catchment, Malawi en
dc.type Thesis en


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