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 …

[HTML][HTML] Landslide failures detection and map** using Synthetic Aperture Radar: Past, present and future

AC Mondini, F Guzzetti, KT Chang, O Monserrat… - Earth-Science …, 2021 - Elsevier
Landslides are geomorphological processes that shape the landscapes of all continents,
dismantling mountains and contributing sediments to the river networks. Caused by …

Performance evaluation of the GIS-based data mining techniques of best-first decision tree, random forest, and naïve Bayes tree for landslide susceptibility modeling

W Chen, S Zhang, R Li, H Shahabi - Science of the total environment, 2018 - Elsevier
The main aim of the present study is to explore and compare three state-of-the art data
mining techniques, best-first decision tree, random forest, and naïve Bayes tree, for landslide …

Remote sensing of photovoltaic scenarios: Techniques, applications and future directions

Q Chen, X Li, Z Zhang, C Zhou, Z Guo, Z Liu, H Zhang - Applied Energy, 2023 - Elsevier
Develo** solar photovoltaic (PV) systems is an effective way to address the problems of
limited fossil fuel reserves, soaring world energy demand and global climate change. The …

[HTML][HTML] Optimizing landslide susceptibility map** using machine learning and geospatial techniques

G Agboola, LH Beni, T Elbayoumi, G Thompson - Ecological Informatics, 2024 - Elsevier
Landslides present a substantial risk to human lives, the environment, and infrastructure.
Consequently, it is crucial to highlight the regions prone to future landslides by examining …

MFFSP: Multi-scale feature fusion scene parsing network for landslides detection based on high-resolution satellite images

P Li, Y Wang, T Si, K Ullah, W Han, L Wang - Engineering Applications of …, 2024 - Elsevier
Fast and efficient landslide detection plays an important role in post-disaster rescue and risk
assessment. Existing convolution neural network (CNN) based landslide detection methods …

CAS landslide dataset: a large-scale and multisensor dataset for deep learning-based landslide detection

Y Xu, C Ouyang, Q Xu, D Wang, B Zhao, Y Luo - Scientific Data, 2024 - nature.com
In this work, we present the CAS Landslide Dataset, a large-scale and multisensor dataset
for deep learning-based landslide detection, developed by the Artificial Intelligence Group at …

Landslide detection of hyperspectral remote sensing data based on deep learning with constrains

C Ye, Y Li, P Cui, L Liang, S Pirasteh… - IEEE Journal of …, 2019 - ieeexplore.ieee.org
Detecting and monitoring landslides are hot topics in remote sensing community, particularly
with the development of remote sensing technologies and the significant progress of …

Landslide detection and susceptibility map** by airsar data using support vector machine and index of entropy models in cameron highlands, malaysia

D Tien Bui, H Shahabi, A Shirzadi, K Chapi… - Remote Sensing, 2018 - mdpi.com
Since landslide detection using the combination of AIRSAR data and GIS-based
susceptibility map** has been rarely conducted in tropical environments, the aim of this …