Heterogeneous transfer learning considering feature representation and environmental consistency for landslide spatial prediction-Reference-Cited by-同舟云学术

Heterogeneous transfer learning considering feature representation and environmental consistency for landslide spatial prediction

Published:2024-05-09 Issue:1 Volume:61 Page:
ISSN:1548-1603
Container-title:GIScience & Remote Sensing
language:en
Short-container-title:GIScience & Remote Sensing

Author:

Zhao Zheng¹²,Wang Weihong³,Chen Jianhua⁴,Yao Jiaming⁵,Liao Yangyang⁴,Liu Jie¹²

Affiliation:

1. State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, China

2. University of Chinese Academy of Sciences, Beijing, China

3. College of Earth and Planetary Sciences, Chengdu University of Technology, Chengdu, China

4. College of Geophysics, Chengdu University of Technology, Chengdu, China

5. School of Earth and Space Sciences, Peking University, Beijing, China

Funder

Project of Sichuan Science and Technology Program

Publisher

Informa UK Limited

Link

https://www.tandfonline.com/doi/pdf/10.1080/15481603.2024.2349343

Reference77 articles.

1. Landslide susceptibility hazard map in southwest Sweden using artificial neural network

2. Construction of small sample seismic landslide susceptibility evaluation model based on Transfer Learning: a case study of Jiuzhaigou earthquake

3. Landslide Susceptibility Modeling: An Integrated Novel Method Based on Machine Learning Feature Transformation

4. A comparison of slope units and grid cells as mapping units for landslide susceptibility assessment

5. Mapping landslides through a temporal lens: an insight toward multi-temporal landslide mapping using the u-net deep learning model