Landslide detection, monitoring and prediction with remote-sensing techniques

N Casagli, E Intrieri, V Tofani, G Gigli… - Nature Reviews Earth & …, 2023 - nature.com
Landslides are widespread occurrences that can become catastrophic when they occur near
settlements and infrastructure. Detection, monitoring and prediction are fundamental to …

Review of satellite interferometry for landslide detection in Italy

L Solari, M Del Soldato, F Raspini, A Barra… - Remote Sensing, 2020 - mdpi.com
Landslides recurrently impact the Italian territory, producing huge economic losses and
casualties. Because of this, there is a large demand for monitoring tools to support landslide …

Detection and segmentation of loess landslides via satellite images: A two-phase framework

H Li, Y He, Q Xu, J Deng, W Li, Y Wei - Landslides, 2022 - Springer
Landslides are catastrophic natural hazards that often lead to loss of life, property damage,
and economic disruption. Image-based landslide investigations are crucial for determining …

Landslide detection from an open satellite imagery and digital elevation model dataset using attention boosted convolutional neural networks

S Ji, D Yu, C Shen, W Li, Q Xu - Landslides, 2020 - Springer
Convolution neural network (CNN) is an effective and popular deep learning method which
automatically learns complicated non-linear map** from original inputs to given labels or …

Integration of Sentinel-1 and ALOS/PALSAR-2 SAR datasets for map** active landslides along the **sha River corridor, China

X Liu, C Zhao, Q Zhang, Z Lu, Z Li, C Yang, W Zhu… - Engineering …, 2021 - Elsevier
Landslide hazards along the **sha River corridor pose serious threats to the lives and
property of local residents and can affect the safety of hydropower facilities because of the …

[HTML][HTML] Uncertainty pattern in landslide susceptibility prediction modelling: Effects of different landslide boundaries and spatial shape expressions

F Huang, J Yan, X Fan, C Yao, J Huang, W Chen… - Geoscience …, 2022 - Elsevier
In some studies on landslide susceptibility map** (LSM), landslide boundary and spatial
shape characteristics have been expressed in the form of points or circles in the landslide …

Interpretation and sensitivity analysis of the InSAR line of sight displacements in landslide measurements

K Dai, J Deng, Q Xu, Z Li, X Shi… - GIScience & Remote …, 2022 - Taylor & Francis
Landslides are major geological hazards and frequently occur in mountainous areas with
steep slopes, often causing significant loss. Interferometric Synthetic Aperture Radar …

[HTML][HTML] An updating of landslide susceptibility prediction from the perspective of space and time

Z Chang, F Huang, J Huang, SH Jiang, Y Liu… - Geoscience …, 2023 - Elsevier
Due to the similarity of conditioning factors, the aggregation feature of landslides and the
multi-temporal landslide inventory, the spatial and temporal effects of landslides need to be …

Modeling landslide susceptibility using LogitBoost alternating decision trees and forest by penalizing attributes with the bagging ensemble

H Hong, J Liu, AX Zhu - Science of the total environment, 2020 - Elsevier
The major target of this study is to design two novel hybrid integration artificial intelligent
models, which are denoted as LADT-Bagging and FPA-Bagging, for modeling landslide …

Landslide susceptibility modeling using integrated ensemble weights of evidence with logistic regression and random forest models

W Chen, Z Sun, J Han - Applied sciences, 2019 - mdpi.com
The main aim of this study was to compare the performances of the hybrid approaches of
traditional bivariate weights of evidence (WoE) with multivariate logistic regression (WoE …