Measuring, modelling and managing gully erosion at large scales: A state of the art
Soil erosion is generally recognized as the dominant process of land degradation. The
formation and expansion of gullies is often a highly significant process of soil erosion …
formation and expansion of gullies is often a highly significant process of soil erosion …
[HTML][HTML] A hybrid ensemble-based deep-learning framework for landslide susceptibility mapping
Landslides are highly hazardous geological disasters that can potentially threaten the safety
of human life and property. As a result, landslide susceptibility mapping (LSM) plays an …
of human life and property. As a result, landslide susceptibility mapping (LSM) plays an …
Development of different machine learning ensemble classifier for gully erosion susceptibility in Gandheswari Watershed of West Bengal, India
In various types of geo-environmental problems in the fringing area of Chhotanagpur
plateau in India, gully erosion is one of the vulnerable issue. In our current research, using …
plateau in India, gully erosion is one of the vulnerable issue. In our current research, using …
Landslide susceptibility modelling using GIS-based machine learning techniques for Chongren County, Jiangxi Province, China
The preparation of a landslide susceptibility map is considered to be the first step for
landslide hazard mitigation and risk assessment. However, these maps are accepted as end …
landslide hazard mitigation and risk assessment. However, these maps are accepted as end …
A GIS-based flood susceptibility assessment and its mapping in Iran: a comparison between frequency ratio and weights-of-evidence bivariate statistical models with …
K Khosravi, E Nohani, E Maroufinia, HR Pourghasemi - Natural hazards, 2016 - Springer
Flood is one of the most prevalent natural disasters that frequently occur in the northern part
of Iran reported in hot spots of flood occurrences. The main aim of the current study was to …
of Iran reported in hot spots of flood occurrences. The main aim of the current study was to …
GIS-based landslide susceptibility mapping and assessment using bivariate statistical methods in Simada area, northwestern Ethiopia
Simada area is found in the South Gondar Zone of Amhara National Regional State and it is
780Km far from Addis Ababa. Physiographically, it is part of the northwestern highlands of …
780Km far from Addis Ababa. Physiographically, it is part of the northwestern highlands of …
Spatial prediction of landslide hazard at the Yihuang area (China) using two-class kernel logistic regression, alternating decision tree and support vector machines
Preparation of landslide susceptibility map is the first step for landslide hazard mitigation
and risk assessment. The main aim of this study is to explore potential applications of two …
and risk assessment. The main aim of this study is to explore potential applications of two …
Landslide spatial modelling using novel bivariate statistical based Naïve Bayes, RBF Classifier, and RBF Network machine learning algorithms
Q He, H Shahabi, A Shirzadi, S Li, W Chen… - Science of the total …, 2019 - Elsevier
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 …
lives and infrastructure. Therefore, the main aim of the present study is to evaluate and …
Performance assessment of individual and ensemble data-mining techniques for gully erosion modeling
HR Pourghasemi, S Yousefi, A Kornejady… - Science of the Total …, 2017 - Elsevier
Gully erosion is identified as an important sediment source in a range of environments and
plays a conclusive role in redistribution of eroded soils on a slope. Hence, addressing …
plays a conclusive role in redistribution of eroded soils on a slope. Hence, addressing …
Machine learning ensemble modelling as a tool to improve landslide susceptibility mapping reliability
Statistical landslide susceptibility mapping is a topic in complete and constant evolution,
especially since the introduction of machine learning (ML) methods. A new methodological …
especially since the introduction of machine learning (ML) methods. A new methodological …