2008Geo-spatial Information ScienceOpen access

Land degradation due to salinization in arid and semi-arid regions with the aid of geo-information techniques

Mushtak Jabbar, Xiaoling Chen

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Abstract

This study applied a computerized parametric methodology to monitor, map, and quantify land degradation by salinization risk detection techniques at a 1:250 000 mapping scale using geo-information technology. The northern part of the Shaanxi province in China was taken as a case. Multi-temporal remotely sensed materials of both Landsat TM and thematic maps (ETM+) were used as the bases to provide comprehensive views of surface conditions such as vegetation cover and salinization detection. With ERDAS ver. 9.1 software, the Normalized Differential Salinity Index (NDSI) and Salinity Index (S.I.) were computed and then evaluated for land degradation by salinization. Arc/Info ver. 9.2 software was used along with field observation data (GPS) for analysis. Using spatial analysis methods, results showed that 19 973.1 km2 (72%) of land had no risk of land degradation by salinization, 3 684.7 km2 (13%) had slight land degradation by salinization risk, 2 797.9 km2 (10%) had moderate land degradation by salinization risk, and 1 218.9 km2 (4%) of the total land area was at a high risk of land degradation by salinization. The study area, in general, is exposed to a high risk of soil salinization.

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What this paper is about

This study applied a computerized parametric methodology to monitor, map, and quantify land degradation by salinization risk detection techniques at a 1:250 000 mapping scale using geo-information technology. The northern part of the Shaanxi province in China was taken as a case. Multi-temporal remotely sensed materials of both Landsat TM and thematic maps (ETM+) were used as the bases to provide comprehensive views of surface conditions such as vegetation cover and salinization detection. With ERDAS ver. 9.1 software, the Normalized Differential Salinity Index (NDSI) and Salinity Index (S.I.) were computed and then evaluated for land degradation by salinization. Arc/Info ver. 9.2 software was used along with field observation data (GPS) for analysis. Using spatial analysis methods, results showed that 19 973.1 km2 (72%) of land had no risk of land degradation by salinization, 3 684.7 km2 (13%) had slight land degradation by salinization risk, 2 797.9 km2 (10%) had moderate land degradation by salinization risk, and 1 218.9 km2 (4%) of the total land area was at a high risk of land degradation by salinization. The study area, in general, is exposed to a high risk of soil salinization.

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Available abstract

This study applied a computerized parametric methodology to monitor, map, and quantify land degradation by salinization risk detection techniques at a 1:250 000 mapping scale using geo-information technology. The northern part of the Shaanxi province in China was taken as a case. Multi-temporal remotely sensed materials of both Landsat TM and thematic maps (ETM+) were used as the bases to provide comprehensive views of surface conditions such as vegetation cover and salinization detection. With ERDAS ver. 9.1 software, the Normalized Differential Salinity Index (NDSI) and Salinity Index (S.I.) were computed and then evaluated for land degradation by salinization. Arc/Info ver. 9.2 software was used along with field observation data (GPS) for analysis. Using spatial analysis methods, results showed that 19 973.1 km2 (72%) of land had no risk of land degradation by salinization, 3 684.7 km2 (13%) had slight land degradation by salinization risk, 2 797.9 km2 (10%) had moderate land degradation by salinization risk, and 1 218.9 km2 (4%) of the total land area was at a high risk of land degradation by salinization. The study area, in general, is exposed to a high risk of soil salinization.

Key concepts: Soil salinity, Land degradation, Thematic map, Environmental science, Arid, Vegetation (pathology), Hydrology (agriculture), Land use

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Land degradation due to salinization in arid and semi-arid regions with the aid of geo-information techniques — Research Paper | ScholarLens