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A survey of machine learning and deep learning in remote sensing of geological environment: Challenges, advances, and opportunities
Due to limited resources and environmental pollution, monitoring the geological
environment has become essential for many countries' sustainable development. As various …
environment has become essential for many countries' sustainable development. As various …
[HTML][HTML] Multi-hazard susceptibility map** based on Convolutional Neural Networks
Multi-hazard susceptibility prediction is an important component of disasters risk
management plan. An effective multi-hazard risk mitigation strategy includes assessing …
management plan. An effective multi-hazard risk mitigation strategy includes assessing …
[HTML][HTML] DEM resolution effects on machine learning performance for flood probability map**
Floods are among the devastating natural disasters that occurred very frequently in arid
regions during the last decades. Accurate assessment of the flood susceptibility map** is …
regions during the last decades. Accurate assessment of the flood susceptibility map** is …
Flood, landslides, forest fire, and earthquake susceptibility maps using machine learning techniques and their combination
HR Pourghasemi, S Pouyan, M Bordbar, F Golkar… - Natural Hazards, 2023 - Springer
Protection against natural hazards (ie, floods, landslides, forest fires, and earthquakes) is
vital in land-use planning, especially in high-risk areas. Multi-hazard susceptibility maps can …
vital in land-use planning, especially in high-risk areas. Multi-hazard susceptibility maps can …
Landslide and wildfire susceptibility assessment in Southeast Asia using ensemble machine learning methods
Q He, Z Jiang, M Wang, K Liu - Remote Sensing, 2021 - mdpi.com
Southeast Asia (SEA) is a region affected by landslide and wildfire; however, few studies on
susceptibility modeling for the two hazards together have been conducted for this region …
susceptibility modeling for the two hazards together have been conducted for this region …
Explainable step-wise binary classification for the susceptibility assessment of geo-hydrological hazards
Ö Ekmekcioğlu, K Koc - Catena, 2022 - Elsevier
This research proposes a novel step-wise binary prediction framework for the susceptibility
assessment of geo-hydrological hazards specific to floods and landslides. The framework of …
assessment of geo-hydrological hazards specific to floods and landslides. The framework of …
Machine learning-enabled regional multi-hazards risk assessment considering social vulnerability
The regional multi-hazards risk assessment poses difficulties due to data access challenges,
and the potential interactions between multi-hazards and social vulnerability. For better …
and the potential interactions between multi-hazards and social vulnerability. For better …
GIS-based comparative study of Bayes network, Hoeffding tree and logistic model tree for landslide susceptibility modeling
W Chen, S Zhang - Catena, 2021 - Elsevier
Landslides, one of the most common hazards around the world, have brought about severe
damage to life and property of human. To prevent and mitigate landslides, various models …
damage to life and property of human. To prevent and mitigate landslides, various models …
Forest fire susceptibility assessment using google earth engine in Gangwon-do, Republic of Korea
Forest fires are one of the most frequently occurring natural hazards, causing substantial
economic loss and destruction of forest cover. As the Gangwon-do region in Korea has …
economic loss and destruction of forest cover. As the Gangwon-do region in Korea has …
Wildfire hazard map** in the eastern Mediterranean landscape
A Trucchia, G Meschi, P Fiorucci… - … journal of wildland …, 2023 - CSIRO Publishing
Background Wildfires are a growing threat to many ecosystems, bringing devastation to
human safety and health, infrastructure, the environment and wildlife. Aims A thorough …
human safety and health, infrastructure, the environment and wildlife. Aims A thorough …