Pramet Kaewmesri
Pramet Kaewmesri is a researcher in remote sensing, geospatial analysis, and environmental modelling. His work focuses on integrating satellite data, machine learning, and spatial analysis to monitor soil properties, ecosystems, and environmental change. He has experience working with multispectral satellite imagery and data-driven approaches for agricultural and environmental applications.
Session
09-02
16:00
30min
Estimation of Soil Organic Carbon and Total Nitrogen in Thailand's Rubber Plantations Using Multispectral Imagery and Machine Learning Algorithms
Pramet Kaewmesri
Soil organic carbon (SOC) and total nitrogen were estimated using Sentinel-2 vegetation indices and machine learning in northeastern Thailand. After outlier removal, Random Forest achieved R² = 0.63 for SOC and R² = 0.39 for total N, with BSI and BAEI as dominant predictors.
Conference Management Room5