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 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.

Authors

Institutions

Publication Details

Journal
PLoS ONE
Published
2025-02-06
DOI
https://doi.org/10.1371/journal.pone.0310780
Citations
4
Primary Topic
Remote Sensing in Agriculture
Type
article
Field-Weighted Citation Impact
6.87

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Mapping forest cover change and estimating carbon stock using satellite-derived vegetation indices in Alemsaga forest, Ethiopia

Agenagnew A. Gessesse, Anbaw Tigabu
4 citations
PLoS ONE
Remote Sensing in Agriculture
6.87
article

Mapping forest cover change and estimating carbon stock using satellite-derived vegetation indices in Alemsaga forest, Ethiopia

Agenagnew A. Gessesse, Anbaw Tigabu
article en
4 citations

Abstract

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.

PLoS ONEVol. 20(2)
Amhara Agricultural Research Institute (ET), Ethiopian Space Science and Technology Institute (ET), University of Gondar (ET)
U.S. Geological Survey
Life in Land
Openalex Percentile: Top 4%
Remote Sensing in Agriculture
6.87
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.