Carbon Sequestration Assessment Using Satellite Data and GIS at Chiang Mai Rajabhat University

Abstract

This study conducted a project to assess carbon sequestration in the forest area of Chiang Mai Rajabhat University, Mae Rim Campus, covering a total area of approximately 5,600 rai, with about 75% consisting of dry dipterocarp forest. The Sentinel-2 satellite data from 2019 to 2023 were used to analyze and classify forest density using the Normalized Difference Vegetation Index (NDVI). It was classified into four NDVI levels: highest, high, moderate, and low. Then, eight sample plots were distributed across all density levels to collect field data on tree species, number of trees, height, and diameter. The biomass and carbon sequestration in the sample plots showed a strong correlation with vegetation density, with the highest average correlation in February, particularly on February 13, 2023, showing the highest correlation coefficient of 0.817. This relationship is described by the equation y=78.601x‒25.726, indicating that this model is effective for estimating carbon sequestration. The analysis revealed that the area with the highest NDVI level of dry dipterocarp forest had the highest above-ground carbon sequestration rate of 16.25 tons per rai, whereas the forest with the lowest NDVI level had an above-ground carbon sequestration rate of 0.21 tons per rai. In total, the above-ground carbon sequestration for the trees amounted to 50,907.35 tons. This preliminary assessment serves as a promising foundation for future efforts the conservation and restoration of the university’s forest area, contributing to sustainable strategies for mitigating global warming.

Keywords

• carbon sequestration
• ndvi vegetation index
• sentinel-2
• geographic information systems (gis)