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[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 …
Suitability estimation for urban development using multi-hazard assessment map
Preparation of natural hazards maps are vital and essential for urban development. The
main scope of this study is to synthesize natural hazard maps in a single multi-hazard map …
main scope of this study is to synthesize natural hazard maps in a single multi-hazard map …
Multi-hazard assessment modeling via multi-criteria analysis and GIS: a case study
Multi-hazard assessment modeling comprises an essential tool in any plan that aims to
mitigate the impact of future natural disasters. For a particular area they can be generated by …
mitigate the impact of future natural disasters. For a particular area they can be generated by …
Evaluation of multi-hazard map produced using MaxEnt machine learning technique
Natural hazards are diverse and uneven in time and space, therefore, understanding its
complexity is key to save human lives and conserve natural ecosystems. Reducing the …
complexity is key to save human lives and conserve natural ecosystems. Reducing the …
Landslide causative factors evaluation using GIS in the tectonically active Glafkos River area, northwestern Peloponnese, Greece
Landslide events are a common geohazard and cause significant damage to urban facilities.
Understanding landslides' effects involves determining the relationship between landslides …
Understanding landslides' effects involves determining the relationship between landslides …
A geospatial analysis of multi-hazard risk in Dharan, Nepal
Natural hazard risk assessment generally focuses on a single hazard type, such as
earthquakes, landslides, or floods. This emphasis tends to consider physical processes in …
earthquakes, landslides, or floods. This emphasis tends to consider physical processes in …
A novel hybrid artificial intelligence approach based on the rotation forest ensemble and naïve Bayes tree classifiers for a landslide susceptibility assessment in …
The main objective of this study was to produce landslide susceptibility maps for Langao
County, China, using a novel hybrid artificial intelligence method based on rotation forest …
County, China, using a novel hybrid artificial intelligence method based on rotation forest …
Physical and anthropogenic factors related to landslide activity in the Northern Peloponnese, Greece
The geological, geomorphic conditions of a mountainous environment along with
precipitation and human activities influence landslide occurrences. In many cases, their …
precipitation and human activities influence landslide occurrences. In many cases, their …
Comparative study of convolutional neural network (CNN) and support vector machine (SVM) for flood susceptibility map**: a case study at Ras Gharib, Red Sea …
Geohazard risk is high in Arab countries due to ineffective disaster preparedness measures,
mismanagement, lack of public awareness, inadequate funding and lack of stakeholder …
mismanagement, lack of public awareness, inadequate funding and lack of stakeholder …
Hazard zonation map** of earthquake-induced secondary effects using spatial multi-criteria analysis
The present study aims to suggest an approach that allows the simultaneous hazard
zonation map** of earthquake-induced secondary effects. The modeling process of the …
zonation map** of earthquake-induced secondary effects. The modeling process of the …