Merging Various Types of Remote Sensing Data and Social Participation GIS with AI to Map the Objects Affected by Light Occlusion

Merging Various Types of Remote Sensing Data and Social Participation GIS with AI to Map the Objects Affected by Light Occlusion

This study proposes a practical integration of an existing deep learning model (YOLOv9-E) and social participation GIS using multi-source remote sensing data to identify asbestos-containing materials located on the side of a building affected by light occlusions. These objects are often undetectable...

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Bibliographic Details
Main Authors: Yen-Chun Lin, Teng-To Yu, Yu-En Yang, Jo-Chi Lin, Guang-Wen Lien, Shyh-Chin Lan
Format: Article
Language:English
Published: MDPI AG 2025-06-01
Series:Remote Sensing
Subjects:
asbestos tile
building side
deep learning
social participation
cellular phone photo
Google Street View
Online Access:https://www.mdpi.com/2072-4292/17/13/2131
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