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Fine scale disaster response and recovery data suitable for spatial analysis are still relatively rare. This is unfortunate as insight into spatial patterns of recovery could be invaluable in predicting the reestablishment of homes, streets and neighborhoods. The purpose of this paper is to show how fine scale geographic data can be collected in near real-time for the intermediate phase between response...
In recent years, station-level ridership forecasting models have been developed based on Geographic Information Systems (GIS) and multiple regression analysis. These models estimate the number of passengers boarding at each station as a function of the station characteristics and the areas that they serve. These models have considerable advantages over the traditional four-step model, including simplicity...
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