Research on house change detection algorithm based on satellite remote sensing and big data

Jie Xue; YanHui Yang; Rong Xing; YunMei Zheng

doi:10.1117/12.3049048

27 November 2024 Research on house change detection algorithm based on satellite remote sensing and big data

Jie Xue, YanHui Yang, Rong Xing, YunMei Zheng

Proceedings Volume 13402, International Conference on Remote Sensing, Mapping, and Geographic Information Systems (RSMG 2024); 134020W (2024) https://doi.org/10.1117/12.3049048
Event: International Conference on Remote Sensing, Mapping, and Geographic Information Systems (RSMG 2024), 2024, Zhengzhou, China

Abstract

In order to meet the monitoring needs of dynamic changes in housing under the background of rapid urbanization, a housing change detection algorithm that integrates deep learning and multi-scale features is proposed based on multi-source satellite remote sensing data. The study utilized an improved deep residual U-Net model, combined with Landsat 8 OLI, Sentinel-2 MSI, and Sentinel-1 SAR data, to achieve high-sensitivity detection of small-scale and subtle changes.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Jie Xue, YanHui Yang, Rong Xing, and YunMei Zheng "Research on house change detection algorithm based on satellite remote sensing and big data", Proc. SPIE 13402, International Conference on Remote Sensing, Mapping, and Geographic Information Systems (RSMG 2024), 134020W (27 November 2024); https://doi.org/10.1117/12.3049048

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