Satellite‐air‐ground integrated multi‐source earth observation and machine learning processing brain for tailings reservoir monitoring and rapid emergency response-Reference-Cited by-同舟云学术

Satellite‐air‐ground integrated multi‐source earth observation and machine learning processing brain for tailings reservoir monitoring and rapid emergency response

Published:2023-01-25 Issue:7 Volume:34 Page:1941-1959
ISSN:1085-3278
Container-title:Land Degradation & Development
language:en
Short-container-title:Land Degrad Dev

Author:

Wan Yuting¹²^ORCID,Zhong Yanfei¹²^ORCID,Ma Ailong¹²,Hu Xin¹,Wei Lifei³

Affiliation:

1. State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing Wuhan University Wuhan PR China

2. Collaborative Innovation Center of Geospatial Technology Wuhan University Wuhan PR China

3. School of Resources and Environmental Science Hubei University Wuhan PR China

Funder

National Natural Science Foundation of China

China Postdoctoral Science Foundation

Publisher

Wiley

Subject

Soil Science,General Environmental Science,Development,Environmental Chemistry

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/ldr.4580

Reference36 articles.

1. The environmental impact of gold mines: pollution by heavy metals

2. VERTICAL DISTRIBUTION AND POTENTIAL MOBILITY OF HEAVY METALS IN NEW AND OLD TAILINGS OF A LEAD/ZINC SULFIDE MINE

3. Fifty-year sedimentary record of heavy metal pollution (Cd, Zn, Cu, Pb) in the Lot River reservoirs (France)

4. Estimation of Heavy Metals in Tailings and Soils Using Hyperspectral Technology: A Case Study in a Tin-Polymetallic Mining Area

5. A new change-detection method in high-resolution remote sensing images based on a conditional random field model

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