Evaluating Multi-Sensors Spectral and Spatial Resolutions for Tree Species Diversity Prediction

Forests contribute significantly to terrestrial biodiversity conservation. Monitoring of tree species diversity is vital due climate change factors. Remote sensing imagery a means data collection for predicting species. Since various sensors have different spectral and spatial resolutions, it worth comparing them ascertain which could influence the accuracy prediction diversity. Hence, this study evaluated resolutions PlanetScope, RapidEye, Sentinel 2 Landsat 8 images in based on Shannon index (H′), Simpson Index (D1) Species richness (S). The Random Forest regression was applied using bands as variables. best image, producing highest coefficient determination (R2) under both (R2 = 0.926) 0.923). Both RapidEye produced comparable higher 0.917 R2 0.915, respectively). PlanetScope second-accurate 0.90), whiles least accurate three indices. outcomes suggest that accuracies satellite imagery.