Natural Hazards GIS-Based Spatial Modeling Using Data Mining Techniques
-15%
portes grátis
Natural Hazards GIS-Based Spatial Modeling Using Data Mining Techniques
Rossi, Mauro; Pourghasemi, Hamid Reza
Springer International Publishing AG
01/2019
296
Dura
Inglês
9783319733821
15 a 20 dias
776
Descrição não disponível.
Gully erosion modeling using GIS-based data mining techniques in Northern Iran; a comparison between boosted regression tree and multivariate adaptive regression spline.- Concepts for Improving Machine Learning Based Landslide Assessment.- Multi-hazard assessment modeling using multi-criteria analysis and GIS: a case study.- Assessment of the contribution of geo-environmental factors to flood inundation in a semi-arid region of SW Iran: comparison of different advanced modeling approaches.- Land Subsidence modelling using data mining techniques. The case study of Western Thessaly, Greece.- Application of fuzzy analytical network process model for analyzing the gully erosion susceptibility.- Landslide susceptibility prediction maps: from blind-testing to uncertainty of class membership: a review of past and present developments.- Earthquake events modeling using multi-criteria decision analysis in Iran.- Prediction of Rainfall as One of the Main Variables in Several Natural Disasters.- Landslide Inventory, Sampling & Effect of Sampling Strategies on Landslide Susceptibility/Hazard Modelling at a Glance.- GIS-based landslide susceptibility evaluation using certainty factor and index of entropy ensembled with alternating decision tree models.- Evaluation of Sentinel-2 MSI and Pleiades 1B imagery in forest fire susceptibility assessment in temperate regions of Central and Eastern Europe. A case study of Romania.- Monitoring and Management of Land Subsidence induced by over-exploitation of groundwater.- A VEGETATED VARIATION MODEL FOR THE FLOODPLAIN OF LOWER MEKONG DELTA DERIVED FROM MULTI-TEMPORAL ERS-2 AND SENTINEL-1 DATA.
Este título pertence ao(s) assunto(s) indicados(s). Para ver outros títulos clique no assunto desejado.
Landslide susceptibility, hazard, and risk assessment;Flash flood modeling and zonation;Data mining techniques;GIS-based spatial modeling;Geo-spatial analysis;Gully erosion zonation;Forest fire susceptibility modeling;Seismic hazard;Land subsidence assessment;Multi-hazard risk assessment
Gully erosion modeling using GIS-based data mining techniques in Northern Iran; a comparison between boosted regression tree and multivariate adaptive regression spline.- Concepts for Improving Machine Learning Based Landslide Assessment.- Multi-hazard assessment modeling using multi-criteria analysis and GIS: a case study.- Assessment of the contribution of geo-environmental factors to flood inundation in a semi-arid region of SW Iran: comparison of different advanced modeling approaches.- Land Subsidence modelling using data mining techniques. The case study of Western Thessaly, Greece.- Application of fuzzy analytical network process model for analyzing the gully erosion susceptibility.- Landslide susceptibility prediction maps: from blind-testing to uncertainty of class membership: a review of past and present developments.- Earthquake events modeling using multi-criteria decision analysis in Iran.- Prediction of Rainfall as One of the Main Variables in Several Natural Disasters.- Landslide Inventory, Sampling & Effect of Sampling Strategies on Landslide Susceptibility/Hazard Modelling at a Glance.- GIS-based landslide susceptibility evaluation using certainty factor and index of entropy ensembled with alternating decision tree models.- Evaluation of Sentinel-2 MSI and Pleiades 1B imagery in forest fire susceptibility assessment in temperate regions of Central and Eastern Europe. A case study of Romania.- Monitoring and Management of Land Subsidence induced by over-exploitation of groundwater.- A VEGETATED VARIATION MODEL FOR THE FLOODPLAIN OF LOWER MEKONG DELTA DERIVED FROM MULTI-TEMPORAL ERS-2 AND SENTINEL-1 DATA.
Este título pertence ao(s) assunto(s) indicados(s). Para ver outros títulos clique no assunto desejado.
