Building Change Detection by Using Past Map Information and Optical Aerial Images

Motohiro TAKAGI  Kazuya HAYASE  Masaki KITAHARA  Jun SHIMAMURA  

Publication
IEICE TRANSACTIONS on Information and Systems   Vol.E104-D   No.6   pp.897-900
Publication Date: 2021/06/01
Publicized: 2021/03/23
Online ISSN: 1745-1361
DOI: 10.1587/transinf.2020EDL8129
Type of Manuscript: LETTER
Category: Artificial Intelligence, Data Mining
Keyword: 
neural networks,  change detection,  map information,  

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Summary: 
This paper proposes a change detection method for buildings based on convolutional neural networks. The proposed method detects building changes from pairs of optical aerial images and past map information concerning buildings. Using high-resolution image pair and past map information seamlessly, the proposed method can capture the building areas more precisely compared to a conventional method. Our experimental results show that the proposed method outperforms the conventional change detection method that uses optical aerial images to detect building changes.