Understanding the states of spatiotemporal flux in cities is critical for risk-informed decision making in disaster situations, resulting in crucial influences on physical, environmental, and social systems of cities. This paper presents a new framework to better understand dynamic spatiotemporal fluctuations related to the vulnerability of cities. We first leverage crowdsourced visual data to automatically identify and localize potential risks associated with vulnerable objects in cities before/during/after disasters. Then we bring multimodal sensing-based reality information into a 3D city model and an interactive computer-aided virtual environment (CAVE), which facilitates to interact the spatial information of vulnerable objects at the intersection of reality-virtuality of cities. For evaluation, case studies were conducted on Houston, TX. The resulting digital twin city reflecting multimodal sensing-based vulnerability information of cities has the potential to be used as a basis for simulating what-if scenarios for risk-informed decision making in disaster situations with enhanced reliability of analytics.
|Title of host publication||Computing in Civil Engineering 2019|
|Subtitle of host publication||Smart Cities, Sustainability, and Resilience - Selected Papers from the ASCE International Conference on Computing in Civil Engineering 2019|
|Editors||Yong K. Cho, Fernanda Leite, Amir Behzadan, Chao Wang|
|Publisher||American Society of Civil Engineers (ASCE)|
|Number of pages||8|
|Publication status||Published - 2019|
|Event||ASCE International Conference on Computing in Civil Engineering 2019: Smart Cities, Sustainability, and Resilience, i3CE 2019 - Atlanta, United States|
Duration: 2019 Jun 17 → 2019 Jun 19
|Name||Computing in Civil Engineering 2019: Smart Cities, Sustainability, and Resilience - Selected Papers from the ASCE International Conference on Computing in Civil Engineering 2019|
|Conference||ASCE International Conference on Computing in Civil Engineering 2019: Smart Cities, Sustainability, and Resilience, i3CE 2019|
|Period||19/6/17 → 19/6/19|
Bibliographical noteFunding Information:
This material is in part based upon work supported by the National Science Foundation (NSF) under CMMI Award #1832187. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the NSF.
© 2019 American Society of Civil Engineers.
All Science Journal Classification (ASJC) codes
- Computer Science(all)
- Civil and Structural Engineering