Biomass and carbon estimation with remote sensing tools in tropical dry forests of Tolima, Colombia
DOI:
https://doi.org/10.4995/raet.2023.19242Keywords:
Sentinel-2A, climate change, vegetation index, allometric models, carbon stocksAbstract
Forests store a large amount of carbon in biomass, which constitutes an option for climate change mitigation. This research focused on the estimation of aboveground biomass and carbon using remote sensing and mathematical modeling tools in dry forests of the Centro Universitario Regional del Norte (CURDN) of the University of Tolima: gallery and riparian forest (152.2 ha) and secondary or transitional vegetation (329.1 ha). Fifty-nine temporary sampling plots were established and the aboveground biomass and carbon were estimated by measuring trees and using allometric models and a carbon fraction of 0.47. Four vegetation indexes (NDVI, EVI, SAVI and OSAVI) were estimated from two Sentinel 2A satellite images from rainy and dry season. The NDVI from the rainy season showed the best R2 (0.87), which allowed the development of a model for estimation of aboveground biomass. Biomass and carbon distribution mapping was generated in the study area, yielding an average value of 95.1 and 44.1 t/ha of aboveground biomass and carbon, respectively. These results made it possible to spatialize the biomass content and carbon sinks within the CURDN and serve as a first step to manage the territory and establish mechanisms for the preservation of the bs-T in the department of Tolima.
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