9 citations as recorded by crossref.

1. Hierarchy Clustering for Cloud Detection Assisted by Spectral Features of Ground Covers W. Song et al. https://doi.org/10.3390/rs18050698
2. A hierarchical-modular ecosystem mapping framework for high-intensity human activity zones J. Xin et al. https://doi.org/10.1080/17538947.2025.2564468
3. Mapping interannual changes of evergreen forests in Beijing, China at 30-m spatial resolution during 1990–2023 Z. Li et al. https://doi.org/10.1080/10106049.2026.2685918
4. Annual maps of forest and evergreen forest in the contiguous United States during 2015–2017 from analyses of PALSAR-2 and Landsat images J. Wang et al. https://doi.org/10.5194/essd-16-4619-2024
5. Automatic Mapping of 10 m Tropical Evergreen Forest Cover in Central African Republic with Sentinel-2 Dynamic World Dataset W. Zhao et al. https://doi.org/10.3390/rs17040722
6. Photon-Counting Lidar Remote Sensing: Current progress and future trends L. Wu et al. https://doi.org/10.1109/MGRS.2026.3660928
7. Monitoring vegetation degradation using remote sensing and machine learning over India – a multi-sensor, multi-temporal and multi-scale approach K. Sur et al. https://doi.org/10.3389/ffgc.2024.1382557
8. EMLARDE tree: ensemble machine learning based random de-correlated extra decision tree for the forest cover type prediction T. Guhan & N. Revathy https://doi.org/10.1007/s11760-024-03470-0
9. Time-series reconstruction and mapping of forest aboveground biomass in the Great Xing’an Mountains of China using GEDI, MODIS, and machine learning C. Yang et al. https://doi.org/10.1016/j.ecolind.2025.114375