Output for Probability of Rescue Requests from Twitter

Rescue requests during large-scale urban flood disasters can be difficult to validate and prioritize. High-resolution aerial imagery is often unavailable or lacks the necessary geographic extent, making it difficult to obtain real-time information about where flooding is occurring. In this paper, we present a novel approach to map the extent of urban flooding in Harris County, Texas during Hurricane Harvey (August 25–30, 2017) and identify where people were most likely to need immediate emergency assistance. Using Maximum Entropy, we predict the probability of flooding based on several spatially-distributed physical and socio-economic characteristics coupled with crowdsourced data.