Mapping forest cover change and estimating carbon stock using satellite-derived vegetation indices in Alemsaga forest, Ethiopia.
Deforestation and forest degradation are significant threats, leading to a decline in forest cover change, biomass and carbon storage, a crucial factor in mitigating climate change. Remote sensing techniques using satellite imagery offer a valuable tool for efficiently monitoring forest cover and bi...
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| Format: | Article |
| Language: | English |
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Public Library of Science (PLoS)
2025-01-01
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| Series: | PLoS ONE |
| Online Access: | https://doi.org/10.1371/journal.pone.0310780 |
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| author | Anbaw Tigabu Agenagnew A Gessesse |
| author_facet | Anbaw Tigabu Agenagnew A Gessesse |
| author_sort | Anbaw Tigabu |
| collection | DOAJ |
| description | Deforestation and forest degradation are significant threats, leading to a decline in forest cover change, biomass and carbon storage, a crucial factor in mitigating climate change. Remote sensing techniques using satellite imagery offer a valuable tool for efficiently monitoring forest cover and biomass over different areas. This study aimed to map and quantify the forest cover change, biomass and carbon stored in the Alemsaga forest, Ethiopia. The study employed Landsat satellite images from four different periods (1992, 2003, 2013, and 2022) to track changes in forest cover and construct carbon storage maps for the Alemsaga forest. The findings from this study can be used to develop better forest conservation and management strategies. The study revealed a significant increase in dense forest cover in Alemsaga (35.34%) between 1992 and 2022, now encompassing 48.25% of the total forest area. Notably, satellite-derived vegetation indices (NDVI & DVI) exhibited a strong correlation with ground observations (R2 = 0.80), and statistical analysis confirmed this relation with above-ground carbon levels (R2 = 0.84). This enabled the creation of carbon storage maps, revealing a substantial increase from 159.31 t/ha in 1992 to 323.84 t/ha by 2022. It's important to acknowledge that while NDVI/DVI proved effective, other factors might influence carbon storage. However, the study clearly shows that satellite imaging has the capacity to map forest cover change, biomass and estimating carbon stock accurately, which is an important first step toward a better understanding of how forests contribute to climate change. |
| format | Article |
| id | doaj-art-06b39b30d4804c23b5bc480d182f1ea1 |
| institution | Kabale University |
| issn | 1932-6203 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | Public Library of Science (PLoS) |
| record_format | Article |
| series | PLoS ONE |
| spelling | doaj-art-06b39b30d4804c23b5bc480d182f1ea12025-02-12T05:30:53ZengPublic Library of Science (PLoS)PLoS ONE1932-62032025-01-01202e031078010.1371/journal.pone.0310780Mapping forest cover change and estimating carbon stock using satellite-derived vegetation indices in Alemsaga forest, Ethiopia.Anbaw TigabuAgenagnew A GessesseDeforestation and forest degradation are significant threats, leading to a decline in forest cover change, biomass and carbon storage, a crucial factor in mitigating climate change. Remote sensing techniques using satellite imagery offer a valuable tool for efficiently monitoring forest cover and biomass over different areas. This study aimed to map and quantify the forest cover change, biomass and carbon stored in the Alemsaga forest, Ethiopia. The study employed Landsat satellite images from four different periods (1992, 2003, 2013, and 2022) to track changes in forest cover and construct carbon storage maps for the Alemsaga forest. The findings from this study can be used to develop better forest conservation and management strategies. The study revealed a significant increase in dense forest cover in Alemsaga (35.34%) between 1992 and 2022, now encompassing 48.25% of the total forest area. Notably, satellite-derived vegetation indices (NDVI & DVI) exhibited a strong correlation with ground observations (R2 = 0.80), and statistical analysis confirmed this relation with above-ground carbon levels (R2 = 0.84). This enabled the creation of carbon storage maps, revealing a substantial increase from 159.31 t/ha in 1992 to 323.84 t/ha by 2022. It's important to acknowledge that while NDVI/DVI proved effective, other factors might influence carbon storage. However, the study clearly shows that satellite imaging has the capacity to map forest cover change, biomass and estimating carbon stock accurately, which is an important first step toward a better understanding of how forests contribute to climate change.https://doi.org/10.1371/journal.pone.0310780 |
| spellingShingle | Anbaw Tigabu Agenagnew A Gessesse Mapping forest cover change and estimating carbon stock using satellite-derived vegetation indices in Alemsaga forest, Ethiopia. PLoS ONE |
| title | Mapping forest cover change and estimating carbon stock using satellite-derived vegetation indices in Alemsaga forest, Ethiopia. |
| title_full | Mapping forest cover change and estimating carbon stock using satellite-derived vegetation indices in Alemsaga forest, Ethiopia. |
| title_fullStr | Mapping forest cover change and estimating carbon stock using satellite-derived vegetation indices in Alemsaga forest, Ethiopia. |
| title_full_unstemmed | Mapping forest cover change and estimating carbon stock using satellite-derived vegetation indices in Alemsaga forest, Ethiopia. |
| title_short | Mapping forest cover change and estimating carbon stock using satellite-derived vegetation indices in Alemsaga forest, Ethiopia. |
| title_sort | mapping forest cover change and estimating carbon stock using satellite derived vegetation indices in alemsaga forest ethiopia |
| url | https://doi.org/10.1371/journal.pone.0310780 |
| work_keys_str_mv | AT anbawtigabu mappingforestcoverchangeandestimatingcarbonstockusingsatellitederivedvegetationindicesinalemsagaforestethiopia AT agenagnewagessesse mappingforestcoverchangeandestimatingcarbonstockusingsatellitederivedvegetationindicesinalemsagaforestethiopia |