Using Remote Sensing Applications (Vegetation Indices) to Estimate the Land Use and Land Cover in Semi-Arid Areas of Sudan


  • Majdaldin Rahamtallah Abualgasima Environment, Natural Resources and Desertification Research Institute-Khartoum, Sudan
  • Babatunde Adeniyi Osunmadewa Dresden University of Technology, Photogrammetry and Remote Sensing- Dresden, Germany
  • Elmar Csaplovics Dresden University of Technology, Photogrammetry and Remote Sensing- Dresden, Germany
  • Hanadi Mohamed Shawgi Gamal University of Khartoum, Faculty of Forestry, Forest Products and Industries Department-Khartoum, Sudan


Remote sensing, Vegetation, NDVI, SAVI, GSI, Sudan


Vegetation is one of the most dynamic elements of the ecosystem. Hence, monitoring vegetation degradation through the use of various vegetation indices plays an important role in the quantitative assessment of its vigour, which can be used for detecting land use change pattern and vegetation density in semi-arid region. In Sudan where fragile ecosystems are dominant, the vast majority of the rural population depends solely on agriculture, and pasture as a means of living, the ecological pattern had been greatly impaired, resulting into loss of vegetation cover coupled with variation in climate. This study describes the use of normalized difference vegetative index (NDVI) to quantitatively examine the vigour of vegetation in Sudan through different vegetation indices. Cloud free multi-spectral remotely sensed data from LANDSAT Thematic Mapper (TM) and Enhance Thematic Mapper plus (ETM+) for the dry season months of 1985 and 2010 were used in this study. In this study, vegetation indices (NDVI, SAVI, GSI) comprising of two or more spectral bands were used to examine vegetation degradation over 25 years. The normalized difference vegetation index (NDVI) was used to assess areas, which had been undergoing changes over time. The results of this study shows conversion of vegetation cover to other land use type, which is an indication of vegetation degradation. The results of the NDVI in 1985 (vegetated area) showed that an area of about 21% was covered by vegetation while 50% of the area were covered with vegetation in 2010. Similar increases in vegetated area were observed from the results of SAVI and GSI for 2010 respectively. Variation in the results of bare and cultivated land was observed from the results of this study. An increase in area covered by sand land was observed from the results of soil adjusted vegetation index (SAVI) and topsoil grain size index (GSI).

The result of SAVI showed that about 30% of the total area was covered with sand land in 2010 as compared to that of 1985 in which the area covered with sand land accounts for 27%. In addition, the results of GSI showed an increase of about 40% in the area covered with sand land in 2010 and 53% in 1985. The results obtained from SAVI and GSI is an indication of loss in vegetal cover due to conversion of land such as agricultural activities and extensive rangeland expansion.  Although, increase in vegetated area were observed from the result of this study, this increase has a negative impact as the natural vegetation are degraded due to human induced activities which gradually lead to the replacement of the natural vegetation with invasive of tree species (Mesquite). The results of this study shows that vegetation degradation in the semi arid region of Sudan is associated with increase in sand land on expense of cultivable land. Hence, the study therefore suggest the use of different imagery with high resolutions to further analyse vegetation degradation  in order to increase the validity and accuracy of vegetation change patterns and their relation to climatic variability in the semi-arid lands of Sudan.


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How to Cite

Majdaldin Rahamtallah Abualgasima, Babatunde Adeniyi Osunmadewa, Elmar Csaplovics, & Hanadi Mohamed Shawgi Gamal. (2019). Using Remote Sensing Applications (Vegetation Indices) to Estimate the Land Use and Land Cover in Semi-Arid Areas of Sudan. International Journal of Applied Sciences: Current and Future Research Trends, 4(01), 1–11. Retrieved from