Web 2.0 geospatial visual analytics for improved urban flooding situational awareness and assessment

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.