Feature-Fusion Segmentation Network for Landslide Detection Using High-Resolution Remote Sensing Images and Digital Elevation Model Data

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Journal:IEEE Trans. Geoscience and Remote Sensing

Funded by:国家重点研发项目

Key Words:意义分割； 高分遥感；孪生网络；滑坡识别

Abstract:Landslide is one of the most dangerous and frequently occurred natural disasters. The semantic segmentation technique is efficient for wide area landslide identification from high-resolution remote sensing images (HRSIs). However, considerable challenges exist because the effects of sediments, vegetation, and human activities over long periods of time make visually blurred old landslides very challenging to detect based upon HRSIs. Moreover, for terrain features like slopes, aspect and altitude variations cannot be sufficiently extracted from 2-D HRSIs but can be from DEM data.

Indexed by:Journal paper

Document Code:doi: 10.1109/TGRS.2022.3233637

Discipline:Engineering

First-Level Discipline:信息与通信工程* Information and communication engineering

Document Type:J

Issue:61

Page Number:1-14

Translation or Not:no

Date of Publication:2023-01-03

Included Journals:SCI

Links to published journals:https://ieeexplore.ieee.org/document/10004996