Scripts used to create environmental exposure estimates based on GPS time activity patterns
Author: Andrew Larkin
Affiliation: Oregon State University, College of Public Health and Human Sciences
Principal Investigator: Laurel Kincl
Date last modified: September 23rd, 2018
Summary
The practicum folder contains functions written in python and R as part of a practicum project to satisfy
the requirements for a masters in public health through George Washington University. The site preceptor was Laurel Kincl. Resources for completing the scripts were contributed by Perry Hystad.
The purpose of the practicum project was to develop GIS-based exposure measures to environmental conditions that may alter respiratory lung function. Time activity patterns, collected by smartphone GPS, were combined with georeferenced data sets to create time-weighted exposure measures for multiple types of vegetation, major and minor roads, toxic release inventory sites, and air monitor networks.
In the practicum folder, each subfolder contains a single python or R script, along with example input and output files. Descriptions and directions for running the scripts are found within commented blocks at the start of each script.
Data sources
- National Land Cover Database - https://explorer.earthengine.google.com/#detail/USGS%2FNLCD
- Landsat 8 NDVI - https://explorer.earthengine.google.com/#detail/LANDSAT%2FLC8_L1T_TOA
- Road Data - http://wiki.openstreetmap.org/wiki/Downloading_data
- Major and minor road classifications - http://wiki.openstreetmap.org/wiki/United_States_Road_Classification.
Note: major roads are "primary" and "secondary" roads. Minor roads are all other roads - Air Monitor data - https://aqs.epa.gov/aqsweb/documents/data_mart_welcome.html
- TRI Sites and emissions - https://www.epa.gov/toxics-release-inventory-tri-program/tri-data-and-tools