Assessment of Post-Harvest Rice Crop Biomass and Carbon Stock using Remote Sensing Data in Google Earth Engine

Abstract

This study is motivated in response to persistent seasonal burning of rice crop-residues in various parts of Thailand. The major aims are to assess dry above ground biomass (dry-AGB) and estimate carbon stock in the rice-crop area of Buak Kang and Chae Chang subdistricts, San Kamphaeng district, Chiang Mai using Google Earth Engine (GEE), as well as develop a web platform for visualization and monitoring. The methodology includes satellite imagery and field-data acquisition, factor identification, model development, accuracy assessment, and launching an open-access web platform. The dry weight and carbon content of the sample rice plants collected during fieldwork were analyzed in a science laboratory. The study establishes a robust model for estimating dry-AGB by correlating the results from the laboratory with the backscatter coefficients of various parameters derived from Sentinel-1 imagery captured on 24.09.2023 (Ascending). The best fit model has R² value of 0.852, which estimated total 16019.13 Tons dry-AGB and 3524.21 Tons carbon stock in the total identified rice-crop area of 34.61 km². The GEE apps based web platform facilitates calculation and visualization of dry-AGB and carbon stock supporting effective monitoring and management of rice-crop in the study area.