Classifying vegetation communities karst wetland synergistic use of image fusion and object-based machine learning algorithm with Jilin-1 and UAV multispectral images

•Vegetation communities in the largest karst wetland of China achieved fine classifications.•Fusion of JL101K and UAV multispectral images improved classification accuracy (1.9%–4.0%)•Classification performance of LightGBM algorithm outperformed XGBoost (0.6%–2.5%) and RF algorithms (1.6%–3.5%).•UAV multispectral images produced the highest overall accuracy (87.8%) in three data sources.•Red-edge band and DSM provide great contributions to identify vegetation communities.