Building shadow extraction and height calculation using GF-2 remote sensing images

Yubin Xu; Rong Li; Chengrui Wang; Chuming Huang; Kun Qin; Kai Xu

doi:10.1117/12.3010394

15 November 2023 Building shadow extraction and height calculation using GF-2 remote sensing images

Yubin Xu, Rong Li, Chengrui Wang, Chuming Huang, Kun Qin, Kai Xu

Proceedings Volume 12815, International Conference on Remote Sensing, Mapping, and Geographic Systems (RSMG 2023); 1281503 (2023) https://doi.org/10.1117/12.3010394
Event: International Conference on Remote Sensing, Mapping, and Geographic Systems (RSMG 2023), 2023, Kaifeng, China

Abstract

This paper proposes a shadow extraction method for GF-2 remote sensing images based on Stacking. The method uses Multiple Linear Regression Model as the second layer model to fuse the results of shadow extraction obtained by NDUI, NIS and C3 which are used as the first-layer base learners of the model. The comparison experiments demonstrate that the proposed method is superior to these traditional shadow operators such as NDUI, NSI and C3 in the accuracy of building shadow extraction. Finally, the height of the buildings is estimated using the shadow lengths and the imaging geometry method. The experimental results show that the average error of the building's height estimated is less than 1m.

(2023) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Yubin Xu, Rong Li, Chengrui Wang, Chuming Huang, Kun Qin, and Kai Xu "Building shadow extraction and height calculation using GF-2 remote sensing images", Proc. SPIE 12815, International Conference on Remote Sensing, Mapping, and Geographic Systems (RSMG 2023), 1281503 (15 November 2023); https://doi.org/10.1117/12.3010394

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KEYWORDS

Shadows

Remote sensing

Satellites

Error analysis

Education and training

Image fusion

Single mode fibers

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