A Minnesota Legacy research project
Understanding visitation to Minnesota’s parks and trails is essential for planning, programming, and investment decisions. Visitation estimates generally rely on methods such as intercept surveys, in-field visitation counts, and automated trail counters. Visitation estimates using passively generated data sources may offer opportunities to complement existing strategies.
This project used aggregated and anonymized location-based services (LBS) data to estimate and evaluate visitation to Minnesota parks and trails. LBS data gives information about when and where people travel. This approach provides unprecedented detail about how visitors use parks and trails and broadly describes who those visitors are. Visitation and use patterns can be analyzed at annual, monthly, weekly, and hourly time intervals. This data makes it possible to understand how people travel to parks and trails and where they are coming from. This data is intended to supplement, but not replace existing data used for decision making.
This project was funded with Legacy Partnership Research Funds from the State of Minnesota Parks and Trails Legacy Fund. The joint research project was conducted in collaboration with the Minnesota Department of Natural Resources, the Greater Minnesota Regional Parks and Trails Commission, and the Metropolitan Council. We thank staff from across the different organizations and cooperating implementing agencies for their cooperation in sharing data and providing feedback.
This repository contains R code, tabular and spatial data files, and documentation behind this research project.
The code used to conduct primary analyses are located in three folders:
/parks, /trails, and /visitors. Each folder contains a tutorial
document (park_tutorial.Rmd, trail_tutorial.Rmd, and
visitor_tutorial.Rmd, respectively) which calls additional scripts to
conduct each step of the analysis. These scripts are numbered in the
order in which they are called.
Complete technical documentation is generated via
legacy-LBS-parktrail-research-documentation.Rmd; higher level summary
texts are generated in the documentation folder.
The /data-raw folder contains data obtained from external sources;
/data-intermediate contains partially processed data, individual
StreetLight (LBS) analysis downloads, or other internally-produced data;
/data-processed contains the final products of this research.
The /figures folder contains two sub-folders: storymap and
factsheets. storymap contains individual plots and images used for
online StoryMaps. factsheets contains single-page PDF reports for each
park and trail with information like weekly total annual visits, weekly
visit trends, mode share, hourly use, visitor home locations,
generalized visitor demographics, and unit geography, organized by
agency and unit type. Data is generally available from 2019 to April
2022.
To re-render plots and factsheets properly, ensure you have the Avenir font installed on your machine. Avenir is available for free in various places online.
Before running any code, be sure to open R/_load_packages.R and ensure
you have all necessary packages installed.
This project uses
streetlightR
to conduct LBS analyses and
councilR for
plotting. Users will additionally require a StreetLight API key (request
via StreetLight Support Team) and a Census API
Key.
Initially, you will need to save some parameters to your machine.
require(keyring)
require(usethis)
keyring::key_set(service = "StreetLightAPI")
usethis::edit_r_environ()
# When the `.Renviron` file comes up in the editor, save the following parameters:
# `STREETLIGHT_LOGIN` = "your email"
# `STREETLIHT_API_KEY` = "your API key"
# `CENSUS_API_KEY` = "your API key"
#
# Save and close the `.Renviron` file and Restart R.General contact: research@metc.state.mn.us.
- Contributing Before contributing to this repository, please review the contribution guide.
- Code of Conduct Please note that this repository is released with a Contributor Code of Conduct. By contributing to this project, you agree to abide by its terms.
- License Code is released with an MIT license. Data provided is for informational purposes. Please open an issue if you have any questions regarding licensing.
- Thanks to our contributors.
- Raven McKnight @ravenmcknight
- Ellen Esch @ehesch
- Liz Roten @eroten
- Senior Manager, Joel Huting @joelhuting