Building Cultural Heritage Resilience through Remote Sensing: An Integrated Approach Using Multi-Temporal Site Monitoring, Datafication, and Web-GL Visualization

In the American West, wildfires and earthquakes are increasingly threatening the archaeological, historical, and tribal resources that define the collective identity and connection with the past for millions of Americans. The loss of said resources diminishes societal understanding of the role cultural heritage plays in shaping our present and future. This paper examines the viability of employing stationary and SLAM-based terrestrial laser scanning, close-range photogrammetry, automated surface change detection, GIS, and WebGL visualization techniques to enhance the preservation of cultural resources in California. Our datafication approach combines multi-temporal remote sensing monitoring of historic features with legacy data and collaborative visualization to document and evaluate how environmental threats affect built heritage. We tested our methodology in response to recent environmental threats from wildfire and earthquakes at Bodie, an iconic Gold Rush-era boom town located on the California and Nevada border. Our multi-scale results show that the proposed approach effectively integrates highly accurate 3D snapshots of Bodie’s historic buildings before/after disturbance, or post-restoration, with surface change detection and online collaborative visualization of 3D geospatial data to monitor and preserve important cultural resources at the site. This study concludes that the proposed workflow enhances the monitoring of at-risk California’s cultural heritage and makes a call to action to employ remote sensing as a pathway to advanced planning.This research was funded by the California Department of Parks and Recreation via Work Order #13-203732-00 and supplement Work Order #13-203732-00R3, by the Resources Legacy Fund, California State Parks Initiative (RLF Grant #2013-0387), and by the University of California Office of the President via a CITRIS Seed Grant 2016. The APC was funded by the University of California, Merced. Arianna Campiani's research was funded by the European Union's Horizon 2020 research and innovation program under the Marie Skłodowska-Curie grant agreement No 839602