Remote sensing analysis of desert sensitive areas using MEDALUS model and GIS in the Niger River Basin
Environmental degradation is a dynamic issue that requires ongoing monitoring to ensure ecological repair and environmental management for sustainable development. This study employed remote sensing techniques to ascertain the desertification sensitivity areas in the Niger River Basin (NRB) using th...
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| Format: | Article |
| Language: | English |
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Elsevier
2024-01-01
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| Series: | Ecological Indicators |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S1470160X23015467 |
| _version_ | 1827583843524149248 |
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| author | Chukwuka Ogbue Emeka Igboeli Chukwuedozie Ajaero Friday Uchenna Ochege Ibrahim Inuwa Yahaya Fenetahun Yeneayehu Yuan You Yongdong Wang |
| author_facet | Chukwuka Ogbue Emeka Igboeli Chukwuedozie Ajaero Friday Uchenna Ochege Ibrahim Inuwa Yahaya Fenetahun Yeneayehu Yuan You Yongdong Wang |
| author_sort | Chukwuka Ogbue |
| collection | DOAJ |
| description | Environmental degradation is a dynamic issue that requires ongoing monitoring to ensure ecological repair and environmental management for sustainable development. This study employed remote sensing techniques to ascertain the desertification sensitivity areas in the Niger River Basin (NRB) using the MEDALUS Model. The indicators for the model were divided into three categories: vegetation quality, climate quality, and soil quality index. The net primary productivity, estimated by the Carnegie Ames Stanford Approach model was substituted in the vegetation quality index. Each quality index was computed by calculating the geometric mean of selected sub-indices, while the geometric mean of the three quality indicators was utilized to determine the Environmental sensitivity to desertification in the study area. A total of 26.10% of the study area had low soil quality, while 26.16% and 17.41% of the study area had low vegetation and climate indicators, respectively. The study revealed that about 36.56% of the study area is highly sensitive while 27.65% and 35.78% are moderately and less sensitive respectively, to desertification in the NRB. The desertification-sensitivity index map shows that the northern part of the study area is highly susceptible to desertification and is encroaching southwards. The findings reveal that climate variables are major influencers in the study area. Our research is of importance to the Niger Basin Authority, planners, and other government agencies in charge of protecting the environment, to ascertain the sensitive areas to desertification, and to help cushion the effect of land degradation in the NRB. |
| first_indexed | 2024-03-08T23:13:33Z |
| format | Article |
| id | doaj.art-837ebe736590423b9641796171091f8f |
| institution | Directory Open Access Journal |
| issn | 1470-160X |
| language | English |
| last_indexed | 2024-03-08T23:13:33Z |
| publishDate | 2024-01-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Ecological Indicators |
| spelling | doaj.art-837ebe736590423b9641796171091f8f2023-12-15T07:23:05ZengElsevierEcological Indicators1470-160X2024-01-01158111404Remote sensing analysis of desert sensitive areas using MEDALUS model and GIS in the Niger River BasinChukwuka Ogbue0Emeka Igboeli1Chukwuedozie Ajaero2Friday Uchenna Ochege3Ibrahim Inuwa Yahaya4Fenetahun Yeneayehu5Yuan You6Yongdong Wang7National Engineering Technology Research Center for Desert and Oasis Ecological Construction, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, 818 South Beijing Road Urumqi 830011, Xinjiang, China; University of Chinese Academy of Sciences, Beijing 100049, ChinaNational Engineering Technology Research Center for Desert and Oasis Ecological Construction, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, 818 South Beijing Road Urumqi 830011, Xinjiang, China; University of Chinese Academy of Sciences, Beijing 100049, ChinaUniversity of Nigeria, Nsukka, NigeriaNational Engineering Technology Research Center for Desert and Oasis Ecological Construction, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, 818 South Beijing Road Urumqi 830011, Xinjiang, China; University of Chinese Academy of Sciences, Beijing 100049, ChinaNational Engineering Technology Research Center for Desert and Oasis Ecological Construction, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, 818 South Beijing Road Urumqi 830011, Xinjiang, China; University of Chinese Academy of Sciences, Beijing 100049, ChinaNational Engineering Technology Research Center for Desert and Oasis Ecological Construction, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, 818 South Beijing Road Urumqi 830011, Xinjiang, China; University of Chinese Academy of Sciences, Beijing 100049, ChinaNational Engineering Technology Research Center for Desert and Oasis Ecological Construction, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, 818 South Beijing Road Urumqi 830011, Xinjiang, ChinaNational Engineering Technology Research Center for Desert and Oasis Ecological Construction, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, 818 South Beijing Road Urumqi 830011, Xinjiang, China; Corresponding author.Environmental degradation is a dynamic issue that requires ongoing monitoring to ensure ecological repair and environmental management for sustainable development. This study employed remote sensing techniques to ascertain the desertification sensitivity areas in the Niger River Basin (NRB) using the MEDALUS Model. The indicators for the model were divided into three categories: vegetation quality, climate quality, and soil quality index. The net primary productivity, estimated by the Carnegie Ames Stanford Approach model was substituted in the vegetation quality index. Each quality index was computed by calculating the geometric mean of selected sub-indices, while the geometric mean of the three quality indicators was utilized to determine the Environmental sensitivity to desertification in the study area. A total of 26.10% of the study area had low soil quality, while 26.16% and 17.41% of the study area had low vegetation and climate indicators, respectively. The study revealed that about 36.56% of the study area is highly sensitive while 27.65% and 35.78% are moderately and less sensitive respectively, to desertification in the NRB. The desertification-sensitivity index map shows that the northern part of the study area is highly susceptible to desertification and is encroaching southwards. The findings reveal that climate variables are major influencers in the study area. Our research is of importance to the Niger Basin Authority, planners, and other government agencies in charge of protecting the environment, to ascertain the sensitive areas to desertification, and to help cushion the effect of land degradation in the NRB.http://www.sciencedirect.com/science/article/pii/S1470160X23015467Niger River BasinCASA modelNet primary productivityClimateLand degradation |
| spellingShingle | Chukwuka Ogbue Emeka Igboeli Chukwuedozie Ajaero Friday Uchenna Ochege Ibrahim Inuwa Yahaya Fenetahun Yeneayehu Yuan You Yongdong Wang Remote sensing analysis of desert sensitive areas using MEDALUS model and GIS in the Niger River Basin Ecological Indicators Niger River Basin CASA model Net primary productivity Climate Land degradation |
| title | Remote sensing analysis of desert sensitive areas using MEDALUS model and GIS in the Niger River Basin |
| title_full | Remote sensing analysis of desert sensitive areas using MEDALUS model and GIS in the Niger River Basin |
| title_fullStr | Remote sensing analysis of desert sensitive areas using MEDALUS model and GIS in the Niger River Basin |
| title_full_unstemmed | Remote sensing analysis of desert sensitive areas using MEDALUS model and GIS in the Niger River Basin |
| title_short | Remote sensing analysis of desert sensitive areas using MEDALUS model and GIS in the Niger River Basin |
| title_sort | remote sensing analysis of desert sensitive areas using medalus model and gis in the niger river basin |
| topic | Niger River Basin CASA model Net primary productivity Climate Land degradation |
| url | http://www.sciencedirect.com/science/article/pii/S1470160X23015467 |
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