Integrating light and structure: Smarter mapping for fragile wetland ecosystems
Accurate classification of wetland vegetation is essential for biodiversity conservation and carbon cycle monitoring. This study developed an adaptive ensemble learning (AEL-Stacking) framework that combines hyperspectral and light detection and ranging (LiDAR) data captured by UAVs to precisely identify vegetation species in karst wetlands. The approach achieved up to 92.77% accuracy—substantially outperforming traditional models—and revealed how spectral and structural features jointly improve ecosystem mapping and restoration strategies.
Karst wetlands are globally significant ecosystems that regulate ...