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| Content Provider | ACM Digital Library |
|---|---|
| Author | Hill, David Rodriguez, Alejandro Marini, Luigi Liu, Yong Myers, Jim Kooper, Rob |
| Abstract | Situational awareness of urban flooding during storm events is important for disaster and emergency management. However, no general purpose tools yet exist for rendering rainfall accumulations in real-time at the resolution of hydrologic units used for modeling. This demonstration will exhibit a novel web 2.0 visual analytical approach for understanding and adaptively managing urban flooding issues. The approach generates a geospatial-temporal map of rainfall within urban hydrologic units (sewer-sheds) in real-time. The polygon-averaged rainfall data is generated using virtual sensors which provide customized real-time data products derived from National Weather Service weather radar data using NCSA's workflow tools. Time-series KML (Keyhole Markup Language) layers are generated, where each KML layer represents a particular slice of the geospatial color-coded sewershed map. Such time-aware KML can be replayed as a movie in the web-based Google Earth environment. This geospatial visual analytic approach can provide decision markers and communities a powerful resource for assessment of neighborhood flooding issues. We will demonstrate our technology using historical and real-time rainfall data in the metropolitan Chicago area to show the effectiveness of such approach. Future work by combining additional ground-truth flooding data will allow us move towards real-time improved decision support for flooding and stormwater management. |
| Starting Page | 554 |
| Ending Page | 555 |
| Page Count | 2 |
| File Format | |
| ISBN | 9781605586496 |
| DOI | 10.1145/1653771.1653873 |
| Language | English |
| Publisher | Association for Computing Machinery (ACM) |
| Publisher Date | 2009-11-04 |
| Publisher Place | New York |
| Access Restriction | Subscribed |
| Subject Keyword | Geospatial visual analytics Web 2.0 Nexrad Keyhole markup language Rainfall Animation Workflow Virtual sensor |
| Content Type | Text |
| Resource Type | Article |
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