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Activity Number: 151 - Beyond the VAR: Advances in Spatial and Spatio-Temporal Modeling for Climate and Environmental Data
Type: Invited
Date/Time: Monday, July 29, 2019 : 10:30 AM to 12:20 PM
Sponsor: Section on Statistics and the Environment
Abstract #300553 Presentation
Title: Understanding Urban Pollution Through Spatial-Temporal Modeling
Author(s): Katherine Ensor* and Julia Schedler
Companies: Rice University and Rice University
Keywords: urban analytics; Hausdorff distance

Spatial-temporal modeling of pollution in an urban environment is key to helping city and community officials manage the impact of pollution. In this talk we will explore the dynamic structure of groundwater pollution after the historical flood of Houston caused by Hurricane Harvey in 2017. The statisical innovation incorporates a distant metric that encompasses the geography of the region. Using Hausdorff distance we establish an exposure index from this historical flood for residents in Houston. The index values will be published through the Kinder Institute Urban Data Platform ( Further, linking our index to the socio-economic data available on this platform we are able to quantify differential population exposure, pinpointing those residents at highest risk. This information is then used by city and community officials to mitigate the consequences of the aberrant pollution.

Authors who are presenting talks have a * after their name.

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