Multi-source remote sensing big data mining reveals cross-regional correlation between aquaculture and Enteromorpha disaster outbreaks-Reference-Cited by-同舟云学术

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Multi-source remote sensing big data mining reveals cross-regional correlation between aquaculture and Enteromorpha disaster outbreaks

Published:2024-05-17 Issue: Volume: Page:1-13
ISSN:1009-5020
Container-title:Geo-spatial Information Science
language:en
Short-container-title:Geo-spatial Information Science

Author:

Fan Jianchao¹^ORCID,Ma Yujuan²,Liang Tingting²,Cui Guangyan²³

Affiliation:

1. School of Control Science and Engineering, Dalian University of Technology, Dalian, China

2. Department of Ocean Remote Sensing, National Marine Environmental Monitoring Center, Dalian, China

3. School of Information, Shanghai Ocean University, Shanghai, China

Funder

National Natural Science Foundation of China

Research and Development

Publisher

Informa UK Limited

Link

https://www.tandfonline.com/doi/pdf/10.1080/10095020.2023.2282672

Reference42 articles.

1. Deep learning for change detection in remote sensing: a review

2. Environmental impact of aquaculture and countermeasures to aquaculture pollution in China

3. Extracting Raft Aquaculture Areas from Remote Sensing Images via an Improved U-Net with a PSE Structure

4. Fan, J., J. Chu, J. Geng, and F. Zhang. 2015. “Floating Raft Aquaculture Information Automatic Extraction Based on High Resolution SAR Images.” In 2015 IEEE International Geoscience and Remote Sensing Symposium (IGARSS), 92–98.

5. Marine Floating Raft Aquaculture Detection of GF-3 PolSAR Images Based on Collective Multikernel Fuzzy Clustering

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