1. Estimating carbon stock using vegetation indices and empirical data in the upper awash river basin.
- Author
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Legesse, Fekadu, Degefa, Sileshi, and Soromessa, Teshome
- Abstract
The Awash River Basin is essential in combating climate change by absorbing atmospheric carbon. The goal of this study was to determine carbon stocks using the linear correlation between field inventory and remote sensing data in the basin. The regression model was created using each plot studied from field inventory and the corresponding vegetation indices (VI) values obtained from ArcGIS software in the basin's study area. The linear correlation values for estimated carbon stock with Normalized Difference Vegetation Index (NDVI) and Enhanced Vegetation Index (EVI) were R
2 = 0.36, R = 0.60, and R2 = 0.52, R = 0.72, respectively. In contrast, the values for the Soil-Adjusted Vegetation Index (SAVI) were R2 = 0.36 and R = 0.60. The results show that the relationship between carbon stock and EVI is stronger for estimating carbon stock than other indices (NDVI and SAVI). The linear regression model or equation developed for NDVI, EVI, SAVI, and field-level carbon stock was Y = 16.25x–1.093, Y = 8.935x–1.1254, and Y = 12.988x–1.0895, respectively. The estimated carbon stock from the EVI linear regression model was 15,904,158.24 tons, with an average carbon stock value of 111.96 tons per hectare. The findings concluded that EVI has a stronger correlation with carbon stock stand estimation than NDVI and SAVI. This study could serve as a baseline for the estimation of carbon stock using vegetation indices in different and large-scale land use land cover types. High-resolution multispectral imagery and cloud-based geospatial analysis platforms could provide more accurate results. [ABSTRACT FROM AUTHOR]- Published
- 2024
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