To investigate whether the desertification risk index (DRI) which was originally developed for the coastal area of Turkey in a previous work, could be used as an effective desertification indicator in other Mediterranean areas such as the Lebanon.
The calculation of the DRI is based on the use of climatic factors and the normalized difference vegetation index (NDVI). As a result, climatic data were obtained and spatial interpolation techniques were applied to derive temperature and precipitation maps within a GIS environment while the NDVI was derived from satellite imagery. Spatial models were employed in order to produce the DRI map of Lebanon. Geographical analysis and standard statistical techniques were employed to investigate the relationships between: desertification risk and two topographic factors, namely, elevation and distance from the sea and desertification risk and the type of land cover. The accuracy of the index was assessed by comparison with recently published official maps and documents.
The paper demonstrates the efficiency of a desertification index to identify areas at risk. The DRI map proved to be accurate when compared to the map of desertification prone areas recently produced by the Lebanese Ministry of Agriculture. The areas with the highest degree of desertification risk are located in the North‐Eastern part of the country, in the area of the Bekaa Valley. This is in agreement with the reports of the United Nations Convention for combating desertification. A strong correlation was found between desertification risk and distance from the sea (the larger the distance the higher the risk) while shrubland appears to be the land cover type with the highest risk of desertification.
This research work demonstrates how satellite imagery and modern spatial analysis techniques could provide an essential alternative to traditional methods.
Dragan, M., Sahsuvaroglu, T., Gitas, I. and Feoli, E. (2005), "Application and validation of a desertification risk index using data for Lebanon", Management of Environmental Quality, Vol. 16 No. 4, pp. 309-326. https://doi.org/10.1108/14777830510601190
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