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

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.  

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Publication Details

Journal
International Journal of Geoinformatics
Published
2024-08-29
DOI
https://doi.org/10.52939/ijg.v20i8.3459
Primary Topic
Agricultural Development and Management
Type
article
Field-Weighted Citation Impact
0.00

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article

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

International Journal of Geoinformatics
Agricultural Development and Management
article

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

article en

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.  

International Journal of Geoinformatics
University of Salzburg (AT), Chiang Mai University (TH)
European Commission, Chiang Mai University, Universität Salzburg, Erasmus+
Zero hunger
Openalex Percentile: Top 75%
Agricultural Development and Management
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