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Natural Hazards GIS-Based Spatial Modeling Using Data Mining Techniques


Natural Hazards GIS-Based Spatial Modeling Using Data Mining Techniques
132.63 CHF
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Lieferzeit: 7-14 Werktage

  • 10463159


Beschreibung

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.

Eigenschaften

Breite: 156
Gewicht: 672 g
Höhe: 251
Länge: 21
Seiten: 296
Sprachen: Englisch
Autor: Hamid Reza Pourghasemi, Mauro Rossi

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