stplanr

Tools for transport planning with an emphasis on spatial transport data and non-motorized modes. The package was originally developed to support the 'Propensity to Cycle Tool', a publicly available strategic cycle network planning tool Lovelace et al. 2017, but has since been extended to support public transport routing and accessibility analysis Moreno-Monroy et al. 2017 and routing with locally hosted routing engines such as 'OSRM' Lowans et al. 2023. The main functions are for creating and manipulating geographic "desire lines" from origin-destination (OD) data (building on the 'od' package); calculating routes on the transport network locally and via interfaces to routing services such as https://cyclestreets.net/ Desjardins et al. 2021; and calculating route segment attributes such as bearing. The package implements the 'travel flow aggregration' method described in Morgan and Lovelace (2020) https://doi.org/10.1177%2F2399808320942779 and the 'OD jittering' method described in Lovelace et al. (2022) https://doi.org/10.32866%2F001c.33873. Further information on the package's aim and scope can be found in the vignettes and in a paper in the R Journal Lovelace and Ellison 2018, and in a paper outlining the landscape of open source software for geographic methods in transport planning Lovelace, 2021.

Last 30 days

This package has been downloaded 1,548 times in the last 30 days. That's enough downloads to impress a room full of undergrads. A commendable achievement indeed. The following heatmap shows the distribution of downloads per day. Yesterday, it was downloaded 49 times.

The following line graph shows the downloads per day. You can hover over the graph to see the exact number of downloads per day.

Last 365 days

This package has been downloaded 21,547 times in the last 365 days. The downloads are officially high enough to crash an underfunded departmental server. Quite an accomplishment! The day with the most downloads was Aug 22, 2024 with 238 downloads.

The following line graph shows the downloads per day. You can hover over the graph to see the exact number of downloads per day.