Flood susceptibility mapping using a novel ensemble weights-of-evidence and support vector machine models in GIS
about
Conveying Flood Hazard Risk Through Spatial Modeling: A Case Study for Hurricane Sandy-Affected Communities in Northern New Jersey.Flash flood susceptibility analysis and its mapping using different bivariate models in Iran: a comparison between Shannon's entropy, statistical index, and weighting factor models.Optimal Combinations of Non-Sequential Regressors for ARX-Based Typhoon Inundation Forecast Models Considering Multiple ObjectivesA Study on Coastal Flooding and Risk Assessment under Climate Change in the Mid-Western Coast of TaiwanCity Compactness: Assessing the Influence of the Growth of Residential Land UseAutomatic landslide detection using Dempster–Shafer theory from LiDAR-derived data and orthophotosComparison of four kernel functions used in support vector machines for landslide susceptibility mapping: a case study at Suichuan area (China)Ensemble machine-learning-based geospatial approach for flood risk assessment using multi-sensor remote-sensing data and GISFlash flood susceptibility assessment in Jeddah city (Kingdom of Saudi Arabia) using bivariate and multivariate statistical modelsSpatial prediction of landslide hazard at the Luxi area (China) using support vector machinesSustainable Brownfields Land Use Change Modeling Using GIS-based Weights-of-Evidence ApproachRemote sensing-based studies coupled with field data reveal urgent solutions to avert the risk of flash floods in the Wadi Qus (east of Jeddah) Kingdom of Saudi ArabiaSpatial landslide hazard assessment along the Jelapang Corridor of the North-South Expressway in Malaysia using high resolution airborne LiDAR dataSpatio-temporal Prediction of Urban Expansion Using Bivariate Statistical Models: Assessment of the Efficacy of Evidential Belief Functions and Frequency Ratio ModelsFlood susceptibility mapping using integrated bivariate and multivariate statistical modelsComparative analysis of product-level fusion, support vector machine, and artificial neural network approaches for land cover mappingAssessment of stream flood susceptibility: a cross-analysis between model results and flood lossesRapid flood inundation mapping using social media, remote sensing and topographic data
P2860
Q38848688-E0CDEEF7-158C-4C6F-88FF-6EB6BF9546BBQ51104455-4D3690E2-F56A-4C99-A9F4-1FBA36738327Q57527699-5F7C0628-88C3-4C70-AEFF-6676E2A7B8B4Q57527902-F1EC51F5-9D58-4C33-991B-7BC418927EF5Q57598039-CA34DF7C-0DF5-4D77-9D0C-FC4D34096CADQ57598045-5017D1CF-C321-4985-A80D-6B9D2F5E0C6EQ57598047-98983527-0C95-4EC7-BDD1-55E7FDD963BBQ57598050-F95DF929-1F72-4876-94B7-B25C095E96BAQ57598112-B5008663-E457-4C03-BCA0-ABB561F11D1FQ57598129-E0D54A12-9E31-4ED3-A34C-63F8CEF81D15Q57598135-98348928-2562-4F09-859F-0FCDEEE11EA7Q57598186-1534A845-FEE0-40EB-B539-C241FAD0BA8AQ57598202-C508C923-9169-493A-868A-B262D4435267Q57598209-FCCB43E4-89C2-4DC5-A99F-6CF6C219AE5AQ57598275-18A3F672-B31D-4E3A-BF82-7AD9AE1D2DC3Q57634427-BC8D085B-FC41-4CF0-B57A-B65F91E7DD7CQ57698441-9B6C1FB3-3363-4881-9FE3-ABE830C4F41EQ59256200-DBC2D92C-2F23-4DB3-914A-DB5CD514391D
P2860
Flood susceptibility mapping using a novel ensemble weights-of-evidence and support vector machine models in GIS
description
article
@en
wetenschappelijk artikel
@nl
наукова стаття, опублікована в травні 2014
@uk
name
Flood susceptibility mapping u ...... t vector machine models in GIS
@en
Flood susceptibility mapping u ...... t vector machine models in GIS
@nl
type
label
Flood susceptibility mapping u ...... t vector machine models in GIS
@en
Flood susceptibility mapping u ...... t vector machine models in GIS
@nl
prefLabel
Flood susceptibility mapping u ...... t vector machine models in GIS
@en
Flood susceptibility mapping u ...... t vector machine models in GIS
@nl
P1433
P1476
Flood susceptibility mapping u ...... t vector machine models in GIS
@en
P2093
Mustafa Neamah Jebur
P304
P356
10.1016/J.JHYDROL.2014.03.008
P577
2014-05-01T00:00:00Z