LANDSLIDE DETECTION IN CENTRAL AMERICA USING THE DIFFERENTIAL BARE SOIL INDEX

9 citations as recorded by crossref.

1. Landslide extraction using a novel empirical method and binary semantic segmentation U-NET framework using sentinel-2 imagery M. Devara et al. https://doi.org/10.1080/2150704X.2024.2320178
2. ML-CASCADE: A machine learning and cloud computing-based tool for rapid and automated mapping of landslides using earth observation data N. Sharma & M. Saharia https://doi.org/10.1007/s10346-024-02360-3
3. Geographic object-based image analysis for landslide identification using machine learning on google earth engine D. Khadka et al. https://doi.org/10.1007/s12665-024-12045-8
4. Detecting Landslides Beyond Hydrology: Spectral Indices and Geochemical Controls M. Gentilucci et al. https://doi.org/10.1007/s41748-026-01188-2
5. Combination of optical images and SAR images for detecting landslide scars, using a classification and regression tree S. Phakdimek et al. https://doi.org/10.1080/01431161.2023.2224096
6. Rapid Landslide Detection Following an Extreme Rainfall Event Using Remote Sensing Indices, Synthetic Aperture Radar Imagery, and Probabilistic Methods A. Chrysafi et al. https://doi.org/10.3390/land14010021
7. Bare ground classification using a spectral index ensemble and machine learning models optimized across 12 international study sites S. Becker et al. https://doi.org/10.1080/10106049.2025.2465452
8. Detecting Coseismic Landslides in GEE Using Machine Learning Algorithms on Combined Optical and Radar Imagery S. Peters et al. https://doi.org/10.3390/rs16101722
9. Rock control on evolution of Khorat Cuesta, Khorat UNESCO Geopark, Northeastern Thailand P. Tepnarong et al. https://doi.org/10.1515/geo-2025-0896