Assessment of the effects of training data selection on the landslide susceptibility mapping: a comparison between support vector machine (SVM), logistic regression …
B Kalantar, B Pradhan, SA Naghibi… - … , Natural Hazards and …, 2018 - Taylor & Francis
Landslide is a natural hazard that results in many economic damages and human losses
every year. Numerous researchers have studied landslide susceptibility mapping (LSM), each …
every year. Numerous researchers have studied landslide susceptibility mapping (LSM), each …
Landslide susceptibility mapping: Machine and ensemble learning based on remote sensing big data
Predicting landslide occurrences can be difficult. However, failure to do so can be catastrophic,
causing unwanted tragedies such as property damage, community displacement, and …
causing unwanted tragedies such as property damage, community displacement, and …
A comparative assessment of GIS-based data mining models and a novel ensemble model in groundwater well potential mapping
In recent years, application of ensemble models has been increased tremendously in various
types of natural hazard assessment such as landslides and floods. However, application of …
types of natural hazard assessment such as landslides and floods. However, application of …
Deep neural network utilizing remote sensing datasets for flood hazard susceptibility mapping in Brisbane, Australia
Large damages and losses resulting from floods are widely reported across the globe. Thus,
the identification of the flood-prone zones on a flood susceptibility map is very essential. To …
the identification of the flood-prone zones on a flood susceptibility map is very essential. To …
Fire‐Net: A Deep Learning Framework for Active Forest Fire Detection
Forest conservation is crucial for the maintenance of a healthy and thriving ecosystem. The
field of remote sensing (RS) has been integral with the wide adoption of computer vision and …
field of remote sensing (RS) has been integral with the wide adoption of computer vision and …
Groundwater potential mapping using C5. 0, random forest, and multivariate adaptive regression spline models in GIS
A Golkarian, SA Naghibi, B Kalantar… - Environmental monitoring …, 2018 - Springer
Ever increasing demand for water resources for different purposes makes it essential to
have better understanding and knowledge about water resources. As known, groundwater …
have better understanding and knowledge about water resources. As known, groundwater …
Land cover classification from fused DSM and UAV images using convolutional neural networks
In recent years, remote sensing researchers have investigated the use of different modalities
(or combinations of modalities) for classification tasks. Such modalities can be extracted via …
(or combinations of modalities) for classification tasks. Such modalities can be extracted via …
Forest fire susceptibility prediction based on machine learning models with resampling algorithms on remote sensing data
This study predicts forest fire susceptibility in Chaloos Rood watershed in Iran using three
machine learning (ML) models—multivariate adaptive regression splines (MARS), support …
machine learning (ML) models—multivariate adaptive regression splines (MARS), support …
Groundwater potential mapping using a novel data-mining ensemble model
… Mojtaba Dolat Kordestani1, Seyed Amir Naghibi2*, Hossein Hashemi2, Kourosh
Ahmadi3, 3 Bahareh Kalantar4, Biswajeet Pradhan5, 6 4 … 2016; Hong et al. 2017; …
Ahmadi3, 3 Bahareh Kalantar4, Biswajeet Pradhan5, 6 4 … 2016; Hong et al. 2017; …
Potential of hybrid evolutionary approaches for assessment of geo-hazard landslide susceptibility mapping
H Nguyen, M Mehrabi, B Kalantar… - … , Natural Hazards and …, 2019 - Taylor & Francis
As a prevalent disaster, landslides cause severe loss of property and human life worldwide.
The specific objective of this study is to evaluate the capability of artificial neural network (…
The specific objective of this study is to evaluate the capability of artificial neural network (…
