Monitoring desertification in south west Tripoli using multi-temporal remotely sensing data and GIS
type: CreativeWork
description: Remotely sensed data has potential value for vegetation change detection and mapping in arid/semi-arid environments, which can be used and analysed to extract information relevant to the understanding of useful information for the study of desert environments and desertification monitoring, assessment and mapping. In Libya, the vast agricultural development which occurred during the last decades was accompanied by desertification ofdifferent areas. Desertification varied in type and degree according to the geographical site, irregularity of rainfall and the prevalence of strong wind which significantly affects the stability of the fragile ecosystem. The potential of this study was to offer answers to the understanding of desertification indicators and has identified criteria for desertification assessment and the creation of land degradation maps using remote sensing data and a geographic information system (GIS). The indicators which mainly impact the study area are wind erosion, vegetation degradation, salinization, and deterioration of water resources etc. Landsat TM imagery has been used as a source of data to monitor land cover and its change over large areas.In this study, multi-temporal Landsat TM imagery has been used in order to map land cover and their changes during five-year intervals from 1988 to 2000. This was achieved by using a soil adjusted vegetation index formula to detect vegetation Thealgorithm classification technique has been used to map vegetation cover, Eolian Mapping (EM) vegetation of various densities, by used the Soil Adjusted Vegetation Index (SA VI) images: TM 1988, TM 1992, TM 1996 and TM 2000. The results of this technique show areas that have vulnerability to wind erosion susceptibility. and change detection algorithm has been used to calculate the vegetation changes in theperiod from 1988 to 2000. This is therefore one land degradation factor that can be created from remotely sensed data. The analysis clearly demonstrates a net dec…
abstract: Remotely sensed data has potential value for vegetation change detection and mapping in arid/semi-arid environments, which can be used and analysed to extract information relevant to the understanding of useful information for the study of desert environments and desertification monitoring, assessment and mapping. In Libya, the vast agricultural development which occurred during the last decades was accompanied by desertification ofdifferent areas. Desertification varied in type and degree according to the geographical site, irregularity of rainfall and the prevalence of strong wind which significantly affects the stability of the fragile ecosystem. The potential of this study was to offer answers to the understanding of desertification indicators and has identified criteria for desertification assessment and the creation of land degradation maps using remote sensing data and a geographic information system (GIS). The indicators which mainly impact the study area are wind erosion, vegetation degradation, salinization, and deterioration of water resources etc. Landsat TM imagery has been used as a source of data to monitor land cover and its change over large areas.In this study, multi-temporal Landsat TM imagery has been used in order to map land cover and their changes during five-year intervals from 1988 to 2000. This was achieved by using a soil adjusted vegetation index formula to detect vegetation Thealgorithm classification technique has been used to map vegetation cover, Eolian Mapping (EM) vegetation of various densities, by used the Soil Adjusted Vegetation Index (SA VI) images: TM 1988, TM 1992, TM 1996 and TM 2000. The results of this technique show areas that have vulnerability to wind erosion susceptibility. and change detection algorithm has been used to calculate the vegetation changes in theperiod from 1988 to 2000. This is therefore one land degradation factor that can be created from remotely sensed data. The analysis clearly demonstrates a net dec…
author: Oune, Omar
language: eng
date published: 2006
date modified: 2026-07-24T02:07:25Z
provider: University of Dundee
publisher: Networked Digital Library of Theses and Dissertations
type: WebPage
source organization: University of Dundee