2024
DOI: 10.1038/s41598-024-64231-0
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Revolutionizing urban mapping: deep learning and data fusion strategies for accurate building footprint segmentation

P. Dabove,
M. Daud,
L. Olivotto

Abstract: In the dynamic urban landscape, understanding the distribution of buildings is paramount. Extracting and delineating building footprints from high-resolution images, captured by aerial platforms or satellites, is essential but challenging to accomplish manually, due to the abundance of high-resolution data. Automation becomes imperative, yet it introduces complexities related to handling diverse data sources and the computational demands of advanced algorithms. The innovative solution proposed in this paper ad… Show more

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