Mapping bamboo distribution in Eastern Nepal using random forest and SNIC classification with sentinel 2 imagery

Bamboo is a crucial resource for ecological sustainability and rural livelihoods, yet accurate spatial data on its distribution in Nepal is lacking, hindering effective management and conservation efforts. This study successfully mapped bamboo-growing areas in eastern Nepal using Sentinel-2 imagery and compared two classification methods, revealing that the Random Forest approach identified 148 km² of bamboo with an accuracy of 85%, outperforming the Simple Non-Iterative Clustering method, which mapped 132 km² with 68.9% accuracy.