NDLI: Prediction of gully erosion susceptibility mapping using novel ensemble machine learning algorithms

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Prediction of gully erosion susceptibility mapping using novel ensemble machine learning algorithms

Content Provider	Directory of Open Access Journals (DOAJ)
Author	Alireza Arabameri Subodh Chandra Pal Romulus Costache Asish Saha Fatemeh Rezaie Amir Seyed Danesh Biswajeet Pradhan Saro Lee Nhat-Duc Hoang
Abstract	Spatial modelling of gully erosion at regional level is very relevant for local authorities to establish successful counter-measures and to change land-use planning. This work is exploring and researching the potential of a genetic algorithm-extreme gradient boosting (GE-XGBoost) hybrid computer education solution for spatial mapping of the susceptibility of gully erosion. The new machine learning approach is to combine the extreme gradient boosting machine (XGBoost) and the genetic algorithm (GA). The GA metaheuristic is being used to improve the efficiency of the XGBoost classification approach. A GIS database has been developed that contains recorded instances of gully erosion incidents and 18 conditioning variables. These parameters are used as predictive variables used to assess the condition of non-erosion or erosion in a given region within the Kohpayeh-Sagzi River Watershed research area in Iran. Exploratory results indicate that the proposed GE-XGBoost model is superior to the other benchmark solution with the desired predictive precision (89.56%). Therefore, the newly built model may be a promising method for large-scale mapping of gully erosion susceptibility.
Related Links	http://dx.doi.org/10.1080/19475705.2021.1880977
ISSN	19475705
e-ISSN	19475713
DOI	10.1080/19475705.2021.1880977
Journal	Geomatics, Natural Hazards & Risk
Issue Number	1
Volume Number	12
Language	English
Publisher	Taylor & Francis Group
Publisher Date	2021-01-01
Publisher Place	United Kingdom
Access Restriction	Open
Subject Keyword	Environmental technology. Sanitary engineering Environmental sciences Risk in industry. Risk management Gully Erosion Spatial Modelling Ensemble Learning Extreme Gradient Boosting Machine Gis Genetic Algorithm
Content Type	Text
Resource Type	Article
Subject	Earth and Planetary Sciences Environmental Science

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