Assessment of land degradation using machine‐learning techniques: A case of declining rangelands-Reference-Cited by-同舟云学术

Assessment of land degradation using machine‐learning techniques: A case of declining rangelands

Published:2020-11-17 Issue:3 Volume:32 Page:1452-1466
ISSN:1085-3278
Container-title:Land Degradation & Development
language:en
Short-container-title:Land Degrad Dev

Author:

Yousefi Saleh¹^ORCID,Pourghasemi Hamid Reza²^ORCID,Avand Mohammadtaghi³,Janizadeh Saeid³,Tavangar Shahla³,Santosh M.⁴⁵

Affiliation:

1. Soil Conservation and Watershed Management Research Department Chaharmahal and Bakhtiari Agricultural and Natural Resources Research and Education Center, AREEO Shahrekord Iran

2. Department of Natural Resources and Environmental Engineering, College of Agriculture Shiraz University Shiraz Iran

3. Department of Watershed Management Engineering, College of Natural Resources Tarbiat Modares University Tehran Iran

4. School of Earth Sciences and Resources China University of Geosciences Beijing Beijing PR China

5. Department of Earth Sciences University of Adelaide Adelaide South Australia Australia

Funder

Shiraz University

Publisher

Wiley

Subject

Soil Science,General Environmental Science,Development,Environmental Chemistry

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/ldr.3794

Reference127 articles.

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2. Livestock, medicinal plants and rangeland viability in Jordan’s Badia: through the lens of traditional and local knowledge

3. Assessment of the importance of gully erosion effective factors using Boruta algorithm and its spatial modeling and mapping using three machine learning algorithms

4. Comparison of machine learning models for gully erosion susceptibility mapping

5. A comparative assessment of random forest and k‐nearest neighbor classifiers for gully erosion susceptibility mapping;Avand M.;Water (Switzerland),2019

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