Comparative study of Landsat 9 and Sentinel-2 satellite data for above-ground carbon sequestration estimation at Mae Moh mine reforestation site, Lampang province, Thailand

Abstract

Importance of the work: Remote sensing techniques can help to estimate forest carbon sequestration, especially for large areas.
Objectives: To compare satellite image data from two different satellites for estimating above-ground carbon (AGC) sequestration.
Materials & Methods: Tree data were collected and allometric equations were used to calculate the AGC sequestration. The relationship between the AGC sequestration and each of six vegetation indices (VIs) from satellite data was determined based on linear regression. The model having the highest coefficient of determination (R²) was chosen.
Results: The Sentinel-2 data had greater potential to estimate the AGC sequestration than the Landsat 9 data. The relationship between the ratio vegetation index (RVI) and the amount of AGC sequestration had the highest R² value (0.71). The model with the form y = - 79.56 + 63.88x was created, which was significant at the 95% confidence level. Furthermore, the estimated AGC sequestration from the model and the AGC sequestration from the allometric equation were not significantly different at the 95% confidence level.
Main finding: Although Landsat 9 is a new satellite, the relationship between AGC sequestration and VIs using its data was poorer than for the Sentinel-2 data. Therefore, the spatial resolution may have affected the estimation of AGC sequestration.