[HTML][HTML] Application of artificial intelligence and remote sensing for landslide detection and prediction: systematic review

S Akosah, I Gratchev, DH Kim, SY Ohn - Remote Sensing, 2024 - mdpi.com
This paper systematically reviews remote sensing technology and learning algorithms in
exploring landslides. The work is categorized into four key components:(1) literature search …

Machine learning approaches to landsat change detection analysis

G Richardson, A Knudby, MA Crowley… - Canadian Journal of …, 2025 - Taylor & Francis
The Landsat mission has captured images of the Earth's surface for over 50 years, and the
data have enabled researchers to investigate a vast array of different change phenomena …

Detecting small-scale landslides along electrical lines using robust satellite-based techniques

M Kazemi Garajeh, A Guariglia, P Paridad… - … , Natural Hazards and …, 2024 - Taylor & Francis
Abstract Robust Satellite Technique (RST) was applied to detect small-scale landslides
along electrical lines in Sicily, Italy. To this end, electrical poles were selected as targets …

[HTML][HTML] MB-Net: A network for accurately identifying cree** landslides from wrapped interferograms

R Zhang, W Zhu, B Fan, Q He, J Zhan, C Wang… - International Journal of …, 2024 - Elsevier
The efficient and automated identification of landslide hazards is essential for socio-
economic development and human safety. Integrating the feature extraction capabilities of …

[PDF][PDF] THE USE OF RECURRENT NEURAL NETWORKS (S-RNN, LSTM, GRU) FOR FLOOD FORECASTING BASED ON DATA EXTRACTED FROM CLASSICAL …

AM Rugină - Modelling in Civil and Environmental Engineering, 2023 - sciendo.com
Floods are natural disasters that have a significant impact on everyday human life, both
through material losses and loss of life. In the context of climate change, these events may …