Use case: Computing the bikability of the Santa Barbara County
Use case: Computing the bikability of the Santa Barbara County
Our goal is to develop a bikability index to estimate how bike-friendly a specific area is. Here, we will focus on computing one component of this index by estimating the steepness of a specific area.
Workflow overview
- Download a Digital Elevation Model (DEM) Covering Santa Barbara County
- Compute the slope deom this DEM
- Calculate zonal statistics on the slope using the US Census Group Blocks for the area
- Create a Map showing the median slope for each area
- Share our project on GitHub
Data
- DEM: we will get this dataset using the STAC API from data catalog of the Microsoft Planetary Computer https://planetarycomputer.microsoft.com/catalog#DEMs
- US Census group block: the dataset is provided as zipped shapefile
Ask
- Work with your coding agent to refine the various steps you will need to complete your task
- Set up your project file structure organizing data (raw and processed), code, and visual outputs
- Remember that geospatial datasets can come in different projections
- Use Python or R to implement this workflow.
- When using Python, favor geopandas and pangeo libraries (https://pangeo.io/#ecosystem)
- When using R, favor recent geospatial packages such as
sfandterraand the tidyverse style guide
- Make sure to document your work well
References
- Codina O, Maciejewska M, Nadal J, Marquet O. Built environment bikeability as a predictor of cycling frequency: Lessons from Barcelona. Transportation Research Interdisciplinary Perspectives. 2022;16: 100725. doi:10.1016/j.trip.2022.100725
- Reading Data from the STAC API https://planetarycomputer.microsoft.com/docs/quickstarts/reading-stac/