書誌情報 : The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
DOI: pending
MUSUBOU-AR: An Open-Source Geospatial AR Framework for Integrating Public GIS Data, Field Authoring, and Disaster Walking Tours
DOI:
https://doi.org/10.51094/jxiv.5764キーワード:
Augmented Reality、 Open-source GIS、 Mobile GIS、 Geovisualization、 Disaster Risk Communication、 Hazard Maps抄録
Conventional hazard maps, public GIS layers, and disaster education materials are essential resources for community disaster risk reduction, but they do not always support in-situ spatial understanding during field-based training. This paper presents MUSUBOU-AR, a publicly released open-source geospatial augmented reality framework that links public GIS resources, local scenario authoring, mobile AR visualization, and post-activity review for disaster walking tours. The system combines a map mode based on public and custom XYZ tiles, an AR mode for location-based visualization of hazards and disaster-related field resources, a web-based authoring environment for points, routes, and GIS layers, GPX-based field logging and review, and optional LiDAR-enhanced AR visualization for improving environmental alignment and ground-surface-aware rendering. As a representative field deployment, the framework was used in a joint disaster walking tour in the Hiro area of Kure City, Hiroshima Prefecture. In this paper, the case is used primarily to examine the field-deployment workflow of MUSUBOU-AR, including public hazard-map use, route and point authoring, AR scenario configuration, and on-site operation. A previously reported facilitator survey provides supplementary evidence that the activity supported situated geospatial interpretation among university student facilitators. Although the supporting survey evidence was limited by a small sample and no control group, the results suggest that MUSUBOU-AR can support reusable geospatial workflows for field-based disaster risk communication.
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The authors declare no conflicts of interest related to this manuscript.ダウンロード *前日までの集計結果を表示します
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投稿日時: 2026-07-28 01:32:53 UTC
公開日時: 2026-08-03 07:39:00 UTC
ライセンス
Copyright(c)2026
Yoshida, Daisuke
Thien Nguyen
Hirofumi Hayashi
Keiko Ishihara
この作品は、Creative Commons Attribution 4.0 International Licenseの下でライセンスされています。
