Assessing the performance of GIS- based machine learning models with different accuracy measures for determining susceptibility to gully erosion-Reference-Cited by-同舟云学术

Assessing the performance of GIS- based machine learning models with different accuracy measures for determining susceptibility to gully erosion

Published:2019-05 Issue: Volume:664 Page:1117-1132
ISSN:0048-9697
Container-title:Science of The Total Environment
language:en
Short-container-title:Science of The Total Environment

Author:

Garosi Younes,Sheklabadi Mohsen^ORCID,Conoscenti Christian^ORCID,Pourghasemi Hamid Reza^ORCID,Van Oost Kristof

Funder

FNRS

Publisher

Elsevier BV

Subject

Pollution,Waste Management and Disposal,Environmental Chemistry,Environmental Engineering

Reference144 articles.

1. Prioritization of effective factors in the occurrence of land subsidence and its susceptibility mapping using an SVM model and their different kernel functions;Abdollahi;Bull. Eng. Geol. Environ.,2018

2. Comparisons of Boosted Regression Tree, GLM, and GAM Performance in the Standardization of Yellowfin Tuna Catch Rate Data From the Gulf of Mexico Longline Fishery;Abeare,2009

3. Multi-parametric GIS analysis to assess gully erosion susceptibility: a test in southern Sicily, Italy;Agnesi;Landf. Anal.,2011

4. Fit-for-purpose: species distribution model performance depends on evaluation criteria - Dutch hoverflies as a case study;Aguirre-Gutiérrez;PLoS ONE,2013

5. Mapping erosion susceptibility by a multivariate statistical method: a case study from the Ayvalık region, NW Turkey;Akgün;Comput. Geosci.,2011

Cited by 158 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Gully erosion susceptibility assessment using three machine learning models in the black soil region of Northeast China;CATENA;2024-10

2. Simulation and Spatio-Temporal Analysis of Soil Erosion in the Source Region of the Yellow River Using Machine Learning Method;Land;2024-09-07

3. Site‐scale drivers of post‐fire vegetation regrowth in gullies: A case study in Mediterranean Europe;Earth Surface Processes and Landforms;2024-09-03

4. Using algorithmic game theory to improve supervised machine learning: A novel applicability approach in flood susceptibility mapping;Environmental Science and Pollution Research;2024-08-19

5. Integrated machine learning and geospatial analysis enhanced gully erosion susceptibility modeling in the Erer watershed in Eastern Ethiopia;Frontiers in Environmental Science;2024-08-06