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Landslide detection, monitoring and prediction with remote-sensing techniques
Landslides are widespread occurrences that can become catastrophic when they occur near
settlements and infrastructure. Detection, monitoring and prediction are fundamental to …
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
Landslides are geomorphological processes that shape the landscapes of all continents,
dismantling mountains and contributing sediments to the river networks. Caused by …
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
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 …
mining techniques, best-first decision tree, random forest, and naïve Bayes tree, for landslide …
Remote sensing of photovoltaic scenarios: Techniques, applications and future directions
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 …
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
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 …
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
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 …
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
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 …
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 …
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
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 …
susceptibility map** has been rarely conducted in tropical environments, the aim of this …