README.md
In gregorbj/Placetypes_USA: Place Type Analysis Using EPA's Smart Location Database
This project includes R scripts and a Shiny application for designating place types at the Census block group level using the Environment Protection Agency's (EPA) Smart Location Database (SLD). Place types are categories of land uses that are useful for describing development patterns and their relationship to human behavior (e.g. travel behavior) and well being (e.g. health). One of the objectives of developing place type designations at the block group level for the US is to be able to add land use attributes to the 2009 National Household Travel Survey in order to estimate travel demand models that are sensitive to land use attributes.
The R directory of this repository contains R scripts that process SLD and related data to be used in the Shiny application described below. The process_sld.R script processes the raw SLD data in a number of steps. Each step produces intermediary R datasets that are saved in the data directory. The raw SLD data is not included in this this repository and neither is the BlkGrp_shp.Rda file that is created by the script because their large file sizes are not consistent with GitHub policy. The misc.R script creates a correspondence table between state names and state FIPS codes, and a R file that contains initial parameter values for the Shiny application.
The app directory contains a Shiny application which designates place types based on various parameter settings. Users can adjust various parameter settings using the interface, see how the adjustments affect the place type designations, and save the results. The interface includes instructions about how to use the application and documentation of the methods used to designate place types. For more information about Shiny and how to start a Shiny application see http://shiny.rstudio.com/. In addition to R, you will need to have the shiny, leaflet, and RColorBrewer R packages installed in order to run the application.
gregorbj/Placetypes_USA documentation built on May 17, 2019, 8:36 a.m.
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This project includes R scripts and a Shiny application for designating place types at the Census block group level using the Environment Protection Agency's (EPA) Smart Location Database (SLD). Place types are categories of land uses that are useful for describing development patterns and their relationship to human behavior (e.g. travel behavior) and well being (e.g. health). One of the objectives of developing place type designations at the block group level for the US is to be able to add land use attributes to the 2009 National Household Travel Survey in order to estimate travel demand models that are sensitive to land use attributes.
The R directory of this repository contains R scripts that process SLD and related data to be used in the Shiny application described below. The process_sld.R script processes the raw SLD data in a number of steps. Each step produces intermediary R datasets that are saved in the data directory. The raw SLD data is not included in this this repository and neither is the BlkGrp_shp.Rda file that is created by the script because their large file sizes are not consistent with GitHub policy. The misc.R script creates a correspondence table between state names and state FIPS codes, and a R file that contains initial parameter values for the Shiny application.
The app directory contains a Shiny application which designates place types based on various parameter settings. Users can adjust various parameter settings using the interface, see how the adjustments affect the place type designations, and save the results. The interface includes instructions about how to use the application and documentation of the methods used to designate place types. For more information about Shiny and how to start a Shiny application see http://shiny.rstudio.com/. In addition to R, you will need to have the shiny, leaflet, and RColorBrewer R packages installed in order to run the application.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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