Geospatial analysis of desertification vulnerability using Mediterranean desertification and land use (MEDALUS) model in Kebbi State, Nigeria
| Autor: | Alias Mohd Sood, Muhammad Mansur Aliero, Mohamad Azani Alias, Mohd Hasmadi Ismail |
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| Rok vydání: | 2021 |
| Předmět: |
Mediterranean climate
021110 strategic defence & security studies Geospatial analysis Land use business.industry media_common.quotation_subject Geography Planning and Development 0211 other engineering and technologies Vulnerability Distribution (economics) 02 engineering and technology Environmental Science (miscellaneous) computer.software_genre Geography United Nations Convention to Combat Desertification Desertification Agricultural land Earth and Planetary Sciences (miscellaneous) Water resource management business Engineering (miscellaneous) computer 021101 geological & geomatics engineering media_common |
| Zdroj: | Applied Geomatics. 13:527-536 |
| ISSN: | 1866-928X 1866-9298 |
| Popis: | Desertification has been a global concern long ago. However, it has never been as severe as it is in the present day. According to the United Nations Convention to Combat Desertification (UNCCD), almost one-third of the world’s agricultural land is facing one form of degradation or another. Assessment of desertification using GIS nowadays presents an efficient means for identifying desertification vulnerable areas. Henceforth, this study aimed to assess desertification vulnerability in Kebbi State, Nigeria, by using Mediterranean desertification and land use-environmental sensitivity area index (MEDALUS-ESAI) approach. The approach is based on biophysical and human indicators. The characteristics and intensity of these indicators contribute to the evolution of different levels of desertification. For the desertification sensitivity index (DSI), quality indexes, and the corresponding individual indicators, a weighted sensitivity score was assigned from 1 to 2. The resultant index layers were merged for generating the DSI theme. The distribution of the DSI indicated that 36% of the area is not affected, and 17% and 30% fall into low and moderately sensitive classes, while 15% and 1% of the area are classified as sensitive and highly sensitive respectively. The result, therefore, indicated that the area is moderately sensitive to desertification. DSI is essentially useful for determining desertification severity. The theme will contribute significantly to the decision-making process most importantly in the selection of priority zones in combating the desertification phenomenon in the area. This study delineates the potential desertification vulnerable areas that need urgent action; the model is thus recommendable for its flexibility and accuracy. |
| Databáze: | OpenAIRE |
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