A high‐accuracy vegetation restoration potential mapping model integrating similar habitat and machine learning-Reference-Cited by-同舟云学术

A high‐accuracy vegetation restoration potential mapping model integrating similar habitat and machine learning

Published:2022-11-30 Issue:4 Volume:34 Page:1208-1224
ISSN:1085-3278
Container-title:Land Degradation & Development
language:en
Short-container-title:Land Degrad Dev

Author:

Meng Xiaoyu¹^ORCID,Pi Huawei¹^ORCID,Gao Xin²,He Panxing³,Lei Jiaqiang²

Affiliation:

1. Key Research Institute of Yellow River Civilization and Sustainable Development & Collaborative Innovation Center on Yellow River Civilization of Henan Province Henan University Kaifeng PR China

2. State Key Laboratory of Desert and Oasis Ecology, Xinjiang Institute of Ecology and Geography Chinese Academy of Sciences Urumqi PR China

3. Ministry of Education Key Laboratory for Western Arid Region Grassland Resources and Ecology, College of Grassland Science Xinjiang Agricultural University Urumqi PR China

Funder

National Natural Science Foundation of China

Publisher

Wiley

Subject

Soil Science,General Environmental Science,Development,Environmental Chemistry

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/ldr.4527

Reference70 articles.

1. TerraClimate, a high-resolution global dataset of monthly climate and climatic water balance from 1958–2015

2. Estimation of fractional vegetation cover dynamics based on satellite remote sensing in pakistan: A comprehensive study on the FVC and its drivers

3. Evaluating Post-Fire Forest Resilience Using GIS and Multi-Criteria Analysis: An Example from Cape Sounion National Park, Greece