Spatio-Temporal Change of Land Use/Land Cover and Vegetation Using Multi-MODIS Satellite Data, Western Ethiopia
Land use and land cover (LULC) change and variability are some of the challenges to present-day water resource management. The purpose of this study was to determine LULC and Normalized Difference Vegetation Index (NDVI) fluctuations in western Ethiopia during the last 20 years. The first part of th...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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Hindawi Limited
2023-01-01
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| Series: | The Scientific World Journal |
| Online Access: | http://dx.doi.org/10.1155/2023/7454137 |
| _version_ | 1797634013123313664 |
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| author | Tesema Kebede Seifu Tekalegn Ayele Woldesenbet Taye Alemayehu Tenalem Ayenew |
| author_facet | Tesema Kebede Seifu Tekalegn Ayele Woldesenbet Taye Alemayehu Tenalem Ayenew |
| author_sort | Tesema Kebede Seifu |
| collection | DOAJ |
| description | Land use and land cover (LULC) change and variability are some of the challenges to present-day water resource management. The purpose of this study was to determine LULC and Normalized Difference Vegetation Index (NDVI) fluctuations in western Ethiopia during the last 20 years. The first part of the study used MODIS LULC data for the change analysis, change detection, and spatial and temporal coverage in the study region. In the second part, the study analyzes the NDVI change and its spatial and temporal coverage. In this study, The Moderate Resolution Imaging Spectroradiometer (MODIS) satellite data were applied to determine LULC and NDVI changes over four different periods. Evergreen broadleaf forests, deciduous broadleaf forests, mixed forests, woody savannas, savannas, grasslands, permanent wetlands, croplands, urban and built-up lands, and water bodies are the LULC in the period of analysis. The overall classification accuracy for the classified image from 2001 to 2020 was 85.4% and the overall kappa statistic was 81.2%. The results indicate a substantial increase in woody savannas, deciduous broadleaf, grasslands, permanent wetlands, and mixed forest areas by 119.6%, 57.7% 45.2%, 37%, and 21.3%, respectively, followed by reductions in croplands, water bodies, savannas, and evergreen broadleaf forest by 90.1%, 19.8%, 13.2%, and 4.8%, respectively, for the catchment between 2001 and 2020. The result also showed that the area’s vegetation cover increased by 64% from 2001 to 2022. This study could provide valuable information for water resource and environmental management as well as policy and decision-making. |
| first_indexed | 2024-03-11T12:02:48Z |
| format | Article |
| id | doaj.art-9184816f91614120ba36cbab81b385e0 |
| institution | Directory Open Access Journal |
| issn | 1537-744X |
| language | English |
| last_indexed | 2024-03-11T12:02:48Z |
| publishDate | 2023-01-01 |
| publisher | Hindawi Limited |
| record_format | Article |
| series | The Scientific World Journal |
| spelling | doaj.art-9184816f91614120ba36cbab81b385e02023-11-08T00:00:18ZengHindawi LimitedThe Scientific World Journal1537-744X2023-01-01202310.1155/2023/7454137Spatio-Temporal Change of Land Use/Land Cover and Vegetation Using Multi-MODIS Satellite Data, Western EthiopiaTesema Kebede Seifu0Tekalegn Ayele Woldesenbet1Taye Alemayehu2Tenalem Ayenew3Haramaya Institute of TechnologyEthiopian Institute of Water ResourcesEthiopian Institute of Water ResourcesSchool of Earth SciencesLand use and land cover (LULC) change and variability are some of the challenges to present-day water resource management. The purpose of this study was to determine LULC and Normalized Difference Vegetation Index (NDVI) fluctuations in western Ethiopia during the last 20 years. The first part of the study used MODIS LULC data for the change analysis, change detection, and spatial and temporal coverage in the study region. In the second part, the study analyzes the NDVI change and its spatial and temporal coverage. In this study, The Moderate Resolution Imaging Spectroradiometer (MODIS) satellite data were applied to determine LULC and NDVI changes over four different periods. Evergreen broadleaf forests, deciduous broadleaf forests, mixed forests, woody savannas, savannas, grasslands, permanent wetlands, croplands, urban and built-up lands, and water bodies are the LULC in the period of analysis. The overall classification accuracy for the classified image from 2001 to 2020 was 85.4% and the overall kappa statistic was 81.2%. The results indicate a substantial increase in woody savannas, deciduous broadleaf, grasslands, permanent wetlands, and mixed forest areas by 119.6%, 57.7% 45.2%, 37%, and 21.3%, respectively, followed by reductions in croplands, water bodies, savannas, and evergreen broadleaf forest by 90.1%, 19.8%, 13.2%, and 4.8%, respectively, for the catchment between 2001 and 2020. The result also showed that the area’s vegetation cover increased by 64% from 2001 to 2022. This study could provide valuable information for water resource and environmental management as well as policy and decision-making.http://dx.doi.org/10.1155/2023/7454137 |
| spellingShingle | Tesema Kebede Seifu Tekalegn Ayele Woldesenbet Taye Alemayehu Tenalem Ayenew Spatio-Temporal Change of Land Use/Land Cover and Vegetation Using Multi-MODIS Satellite Data, Western Ethiopia The Scientific World Journal |
| title | Spatio-Temporal Change of Land Use/Land Cover and Vegetation Using Multi-MODIS Satellite Data, Western Ethiopia |
| title_full | Spatio-Temporal Change of Land Use/Land Cover and Vegetation Using Multi-MODIS Satellite Data, Western Ethiopia |
| title_fullStr | Spatio-Temporal Change of Land Use/Land Cover and Vegetation Using Multi-MODIS Satellite Data, Western Ethiopia |
| title_full_unstemmed | Spatio-Temporal Change of Land Use/Land Cover and Vegetation Using Multi-MODIS Satellite Data, Western Ethiopia |
| title_short | Spatio-Temporal Change of Land Use/Land Cover and Vegetation Using Multi-MODIS Satellite Data, Western Ethiopia |
| title_sort | spatio temporal change of land use land cover and vegetation using multi modis satellite data western ethiopia |
| url | http://dx.doi.org/10.1155/2023/7454137 |
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