An integrated neural network method for landslide susceptibility assessment based on time-series InSAR deformation dynamic features
Author:
Affiliation:
1. Faculty of Geomatics, Lanzhou Jiaotong University, Lanzhou, People’s Republic of China
2. Faculty of Geosciences and Environmental Engineering, Southwest Jiaotong University, Chengdu, People’s Republic of China
Funder
National Natural Science Foundation of China
Gansu Science and Technology Program
Research and DevelopmentScience and Technology Project of Gansu Province
Publisher
Informa UK Limited
Subject
General Earth and Planetary Sciences,Computer Science Applications,Software
Link
https://www.tandfonline.com/doi/pdf/10.1080/17538947.2023.2295408
Reference62 articles.
1. Empirical characterization of random forest variable importance measures
2. A new algorithm for surface deformation monitoring based on small baseline differential SAR interferograms
3. A systematic review of landslide probability mapping using logistic regression
4. A ROC analysis-based classification method for landslide susceptibility maps
5. Landslide Susceptibility Zonation through ratings derived from Artificial Neural Network
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