GEDI–Sentinel Model Maps Northeast Thai Rubber at 82.63% Accuracy but Struggles With Young Plantations
This study mapped 2024 rubber distribution and age structure across Northeast Thailand using Random Forest in Google Earth Engine, combining Sentinel-1, Sentinel-2, vegetation indices, and a GEDI-trained canopy-height model. Three-class rubber mapping reached 82.63% overall accuracy and about 0.84 F1; three-group age classification reached 83.39%. Plantations older than seven years dominated and were classified more reliably than young stands. The output is a regional monitoring baseline, not an error-free parcel-level decision map.
Thai researchersSavittri Ratanopad Suwanlee · Muhammad Hanif · Surasak Keawsomsee · Kemin Kasa · Narissara Nuthammachot · Sarawut Ninsawat · Jantima Polpinij · Jaturong Som-Ard