Landslide detection by deep learning of non-nadiral and crowdsourced optical images
Sign Up to like & getrecommendations! Published in 2020 at "Landslides"
DOI: 10.1007/s10346-020-01513-4
Abstract: The recent development of mobile surveying platforms and crowdsourced geoinformation has produced a huge amount of non-validated data that are now available for research and application. In the field of risk analysis, with particular reference… read more here.
Keywords: learning; landslide detection; non nadiral; detection deep ... See more keywords
A comprehensive transferability evaluation of U-Net and ResU-Net for landslide detection from Sentinel-2 data (case study areas from Taiwan, China, and Japan)
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DOI: 10.1038/s41598-021-94190-9
Abstract: Earthquakes and heavy rainfalls are the two leading causes of landslides around the world. Since they often occur across large areas, landslide detection requires rapid and reliable automatic detection approaches. Currently, deep learning (DL) approaches,… read more here.
Keywords: detection; resu net; case; landslide detection ... See more keywords
Relict landslide detection using deep-learning architectures for image segmentation in rainforest areas: a new framework
Sign Up to like & getrecommendations! Published in 2022 at "International Journal of Remote Sensing"
DOI: 10.1080/01431161.2023.2197130
Abstract: ABSTRACT Landslides are destructive and recurrent natural disasters on steep slopes and represent a risk to lives and properties. Knowledge of relict landslides’ location is vital to understand their mechanisms, update inventory maps and improve… read more here.
Keywords: relict landslide; cnn; landslide detection; framework ... See more keywords
Landslide Detection Using Residual Networks and the Fusion of Spectral and Topographic Information
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DOI: 10.1109/access.2019.2935761
Abstract: Landslide inventories are in high demand for risk assessment of this natural hazard, particularly in tropical mountainous regions. This research designed residual networks for landslide detection using spectral (RGB bands) and topographic information (altitude, slope,… read more here.
Keywords: landslide detection; fusion; topographic information; residual networks ... See more keywords
A New Mask R-CNN-Based Method for Improved Landslide Detection
Sign Up to like & getrecommendations! Published in 2021 at "IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing"
DOI: 10.1109/jstars.2021.3064981
Abstract: This article presents a novel method of landslide detection by exploiting the Mask R-CNN capability of identifying an object layout by using a pixel-based segmentation, along with transfer learning used to train the proposed model.… read more here.
Keywords: mask cnn; landslide detection; detection; method ... See more keywords
Landslide Detection Using Densely Connected Convolutional Networks and Environmental Conditions
Sign Up to like & getrecommendations! Published in 2021 at "IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing"
DOI: 10.1109/jstars.2021.3079196
Abstract: A complete and accurate landslide map is necessary for landslide susceptibility and risk assessment. Currently, deep learning faces the dilemma of insufficient application, scarce samples, and poor efficiency in landslide recognition. This article utilizes the… read more here.
Keywords: landslide detection; convolutional networks; detection using; using densely ... See more keywords
The Outcome of the 2022 Landslide4Sense Competition: Advanced Landslide Detection From Multisource Satellite Imagery
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing"
DOI: 10.1109/jstars.2022.3220845
Abstract: The scientific outcomes of the 2022 Landslide4Sense (L4S) competition organized by the Institute of Advanced Research in Artificial Intelligence are presented here. The objective of the competition is to automatically detect landslides based on large-scale… read more here.
Keywords: satellite imagery; competition; 2022 landslide4sense; landslide detection ... See more keywords
Susceptibility-Guided Landslide Detection Using Fully Convolutional Neural Network
Sign Up to like & getrecommendations! Published in 2023 at "IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing"
DOI: 10.1109/jstars.2022.3233043
Abstract: Automatic landslide detection based on very high spatial resolution remote sensing images is crucial for disaster prevention and mitigation applications. With the rapid development of deep-learning techniques, state-of-the-art semantic segmentation methods based on fully convolutional… read more here.
Keywords: susceptibility guided; landslide detection; detection; guided landslide ... See more keywords
ShapeFormer: A Shape-Enhanced Vision Transformer Model for Optical Remote Sensing Image Landslide Detection
Sign Up to like & getrecommendations! Published in 2023 at "IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing"
DOI: 10.1109/jstars.2023.3253769
Abstract: Landslides pose a serious threat to human life, safety, and natural resources. Remote sensing images can be used to effectively monitor landslides at a large scale, which is of great significance for pre-disaster warning and… read more here.
Keywords: vision transformer; remote sensing; landslide detection; model ... See more keywords
DCI-PGCN: Dual-Channel Interaction Portable Graph Convolutional Network for Landslide Detection
Sign Up to like & getrecommendations! Published in 2023 at "IEEE Transactions on Geoscience and Remote Sensing"
DOI: 10.1109/tgrs.2023.3273623
Abstract: Landslide, a kind of destructive natural disaster, often occurs in the mountainous areas of China. Landslide information instant collection plays an important role in taking appropriate remedial measures and personnel evacuation. In recent years, the… read more here.
Keywords: graph convolutional; network; landslide detection; detection ... See more keywords