Factors Affecting Landslide Susceptibility Mapping: Assessing the Influence of Different Machine Learning Approaches, Sampling Strategies and Data Splitting
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- Xiaolan Huang & Weicheng Wu & Tingting Shen & Lifeng Xie & Yaozu Qin & Shanling Peng & Xiaoting Zhou & Xiao Fu & Jie Li & Zhenjiang Zhang & Ming Zhang & Yixuan Liu & Jingheng Jiang & Penghui Ou & Wenc, 2021. "Estimating Forest Canopy Cover by Multiscale Remote Sensing in Northeast Jiangxi, China," Land, MDPI, vol. 10(4), pages 1-16, April.
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- Esteban Bravo-López & Tomás Fernández Del Castillo & Chester Sellers & Jorge Delgado-García, 2023. "Analysis of Conditioning Factors in Cuenca, Ecuador, for Landslide Susceptibility Maps Generation Employing Machine Learning Methods," Land, MDPI, vol. 12(6), pages 1-28, May.
- Thong Xuan Tran & Sihong Liu & Hang Ha & Quynh Duy Bui & Long Quoc Nguyen & Dinh Quoc Nguyen & Cong-Ty Trinh & Chinh Luu, 2024. "A Spatial Landslide Risk Assessment Based on Hazard, Vulnerability, Exposure, and Adaptive Capacity," Sustainability, MDPI, vol. 16(21), pages 1-37, November.
- Yang Yi & Chen Zhang & Jinqi Zhu & Yugang Zhang & Hao Sun & Hongzhang Kang, 2022. "Spatio-Temporal Evolution, Prediction and Optimization of LUCC Based on CA-Markov and InVEST Models: A Case Study of Mentougou District, Beijing," IJERPH, MDPI, vol. 19(4), pages 1-23, February.
- Enrico Miccadei & Cristiano Carabella & Giorgio Paglia, 2022. "Landslide Hazard and Environment Risk Assessment," Land, MDPI, vol. 11(3), pages 1-5, March.
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landslide; susceptibility; machine learning; GIS; Kerala;All these keywords.
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