AI-supported citizen science to monitor high-tide flooding in newport beach, California

Behzad Golparvar, Ruo Qian Wang

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Monitoring High-tide Flooding (HTF) is challenging because HTF usually spreads widely and forms localized water accumulations depending on the natural processes and infrastructure. Stationary monitoring systems and satellite imaging have their certain limitations. To date, citizen science is considered as the most promising means to monitor HTF, which provides wide and continuous coverage of the community and real-time first-hand witness of the flooding event. Here, we present a flexible Artificial Intelligence (AI)-supported citizen science platform for HTF monitoring. Flood extent is identified through standard photogrammetry algorithms and a Computer vision technique called monoplotting, and water depth can be estimated using reference objects. In this paper, monoplotting is employed to establish a correlation between photos and the corresponding digital elevation model (DEM) data, allowing to map the flood extent and water depth to the DEM map to minimize the data uncertainty and enhance the data credibility, resolution, and overall value.

Original languageEnglish (US)
Title of host publicationProceedings of the 3rd ACM SIGSPATIAL International Workshop on Advances in Resilient and Intelligent Cities, ARIC 2020
EditorsBandana Kar, Xinyue Ye, Shima Mohebbi, Guangtao Fu
PublisherAssociation for Computing Machinery, Inc
Pages66-69
Number of pages4
ISBN (Electronic)9781450381659
DOIs
StatePublished - Nov 3 2020
Externally publishedYes
Event3rd ACM SIGSPATIAL International Workshop on Advances in Resilient and Intelligent Cities, ARIC 2020 - Seattle. Virtual, United States
Duration: Nov 3 2020 → …

Publication series

NameProceedings of the 3rd ACM SIGSPATIAL International Workshop on Advances in Resilient and Intelligent Cities, ARIC 2020

Conference

Conference3rd ACM SIGSPATIAL International Workshop on Advances in Resilient and Intelligent Cities, ARIC 2020
Country/TerritoryUnited States
CitySeattle. Virtual
Period11/3/20 → …

All Science Journal Classification (ASJC) codes

  • Building and Construction
  • Computer Networks and Communications
  • Information Systems
  • Civil and Structural Engineering

Keywords

  • computer vision
  • flood extent estimation
  • high tide flooding
  • monoplotting

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