An Object-Oriented Semi-Supervised Land-Use/Land-Cover Change Detection Method Based on Siamese Autoencoder Graph Attention Network-Reference-Cited by-同舟云学术

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An Object-Oriented Semi-Supervised Land-Use/Land-Cover Change Detection Method Based on Siamese Autoencoder Graph Attention Network

Published:2024 Issue: Volume:17 Page:6478-6500
ISSN:1939-1404
Container-title:IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
language:
Short-container-title:IEEE J. Sel. Top. Appl. Earth Observations Remote Sensing

Author:

Wu Yifan¹^ORCID,Xie Zhiwei¹^ORCID,Ma Zaiyang²^ORCID,Chen Min²^ORCID,Zhang Fengyuan³^ORCID,Shi Zhenguo¹^ORCID,Li Wengang¹^ORCID,Zhai Shuaizhi¹^ORCID

Affiliation:

1. School of Transportation and Geomatics Engineering, Shenyang Jianzhu University, Shenyang, China

2. Key Laboratory of Virtual Geographic Environment (Ministry of Education of PRC), Nanjing Normal University, Nanjing, China

3. School of Environment, Nanjing Normal University, Nanjing, China

Funder

National Natural Science Foundation of China

Ministry of Education of the People's Republic of China

Basic Research Programs of the Educational Department of Liaoning Province of China

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/4609443/10330207/10461037.pdf?arnumber=10461037

Reference101 articles.

1. Change detection from multi-temporal remote sensing images by integrating multiple features

2. AFSNet: attention-guided full-scale feature aggregation network for high-resolution remote sensing image change detection

3. Object-based change detection for vegetation disturbance and recovery using Landsat time series

4. Change detection techniques

5. Object-based change detection

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