[HTML][HTML] Identification of Landslide Precursors for Early Warning of Hazards with Remote Sensing

K Strząbała, P Ćwiąkała, E Puniach - Remote Sensing, 2024 - mdpi.com
Landslides are a widely recognized phenomenon, causing huge economic and human
losses worldwide. The detection of spatial and temporal landslide deformation, together with …

GIS-based data-driven bivariate statistical models for landslide susceptibility prediction in Upper Tista Basin, India

J Das, P Saha, R Mitra, A Alam, M Kamruzzaman - Heliyon, 2023 - cell.com
Predicting landslides is becoming a crucial global challenge for sustainable development in
mountainous areas. This research compares the landslide susceptibility maps (LSMs) …

Deep learning based landslide detection using open-source resources: Opportunities and challenges

S Das, P Sharma, A Pain, DP Kanungo… - Earth Science …, 2023 - Springer
Landslide inventories are important for hazard and risk analysis, as well as in facilitating
post-event recovery efforts. However, preparing these inventories is a time-consuming and …

Supervised change detection using prechange optical-SAR and postchange SAR data

S Saha, M Shahzad, P Ebel… - IEEE Journal of Selected …, 2022 - ieeexplore.ieee.org
Change detection using satellite/aerial images is used to quantify the impacts of many
natural and man-made disasters. At the occurrence of such events, both prechange optical …

Co‐seismic landslides in the Sikkim Himalaya during the 2011 Sikkim Earthquake: Lesson learned from the past and inference for the future

M Joshi - Geological Journal, 2022 - Wiley Online Library
Sikkim, a north‐eastern state of India, has a very specific and unique place in the tourism
map of India. Every year, lakhs of people visit the state. To accommodate such floating …

Limitations in the use of Sentinel-1 data for morphological change detection in rivers

G Marchetti, A Manconi, F Comiti - International Journal of Remote …, 2023 - Taylor & Francis
The identification of morphological changes occurring along river channels is essential to
support river process understanding, assess sediment budgets and evaluate the …

Statistical time-series analysis of interferometric coherence from sentinel-1 sensors for landslide detection and early warning

M Tzouvaras - Sensors, 2021 - mdpi.com
Landslides are one of the most destructive natural hazards worldwide, affecting greatly built-
up areas and critical infrastructure, causing loss of human lives, injuries, destruction of …

Detecting Coseismic Landslides in GEE Using Machine Learning Algorithms on Combined Optical and Radar Imagery

S Peters, J Liu, G Keppel, A Wendleder, P Xu - Remote Sensing, 2024 - mdpi.com
Landslides, resulting from disturbances in slope equilibrium, pose a significant threat to
landscapes, infrastructure, and human life. Triggered by factors such as intense …

A deep neural network framework for landslide susceptibility mapping by considering time-series rainfall

B Gao, Y He, X Chen, H Chen, W Yang… - IEEE Journal of …, 2024 - ieeexplore.ieee.org
Landslide susceptibility mapping (LSM) is of great significance in geohazard early warning
and prevention. The existing LSM methods mostly used traditional static landslide …

[HTML][HTML] How erosion shapes dynamic Quaternary mountain environments: A review

A Chakraborty - Quaternary Science Advances, 2023 - Elsevier
Erosion is a key driver of mountain topography and landform/landscape heterogeneity in the
Quaternary. While uncertainty persists on the precise relationship between erosion and …