Qingfeng He's research while affiliated with Shaanxi University of Science and Technology and other places
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Publications (2)
Landslides are major hazards for human activities often causing great damage to human lives and infrastructure. Therefore, the main aim of the present study is to evaluate and compare three machine learning algorithms (MLAs) including Naïve Bayes (NB), radial basis function (RBF) Classifier, and RBF Network for landslide susceptibility mapping (LSM...
Landslides are a major geological hazard worldwide. Landslide susceptibility assessments are useful to mitigate human casualties, loss of property, and damage to natural resources, ecosystems, and infrastructures. This study aims to evaluate landslide susceptibility using a novel hybrid intelligence approach with the rotation forest-based credal de...
Citations
... To this aim, landslide susceptibility analyses can be carried out (Brabb 1984;Guzzetti et al. 2005;Reichenbach et al. 2018). Different landslide susceptibility methods have been proposed by numerous researchers classifying them into quantitative and qualitative (Glade et al. 2005;He et al. 2019). They differ a lot in terms of result accuracy (Chen et al. 2017). ...
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... (11,(16)(17)(18) In landslide studies, for decades, the landslide susceptibility model has been analyzed using the data derived from remote sensing platforms such as satellites and aircraft. (19)(20)(21) These previous landslide studies sampled landslides from 3D images derived from remote sensing technology, which were used for independent variables such as terrain, vegetation, and land use maps to classify landslide-susceptible areas from meter-class resolution images. Terrain variables consist of slopes, aspects, topographic wetness index (TWI), terrain roughness index (TRI), and curvatures related to the physical rainfall energy resulting in landslides. ...
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