📒 Introduction

Are you new to Ann Arbor, Detroit, Michigan and don’t know where to find urban data that can be mapped? Are you frustrated by spending hours to find data that can be downloaded for analysis? Are you trying to dig through piles of data to find out which one can help with your specific topic of interest or planning purpose? Do you want to find out cool, local datasets that researchers in Michigan had developed?

This data guide is an informal effort, as Prof. Xiaofan Liang from University of Michigan Taubman College of Architecture and Urban Planning learn and explore the data landscape in Michigan for her research and teaching. It is designed for students, researchers, and interested citizens who are looking for open (free) urban data, that can be mapped or used in urban or geospatial analytics, with a particular focus in Michigan contexts.

This guide contains two parts:

• A (👈🏻 to open) that documents publicly available urban datasets relevant to urban planning topics. These datasets include ones that are unique and local to cities in Michigan as well as ones that have spatial coverage up to the world.
• A User Guide (👈🏻 to open) that shows how to filter and combine modularized datasets for specific purpose.

What the database includes

We only include datasets that are:

• publicly accessible as vectors, rasters, or tables, either through a direct download or free-tier API or by request
• with geospatial information and thus can be mapped or used for geospatial analytics (either being GIS data, or tables that have coordinates, address, or administrative divisions that can be geocoded, such as census geographical units).
• helpful to answer urban planning and urban studies questions
• with geographic coverage (but not limited to) in Ann Arbor, Detroit, and Michigan.
• published by a reliable source (e.g., by municipal governments rather than Kaggle) with trackable metadata (e.g., date and the source of data)

What the database does not include

We exclude the following dataset types from the tabular database, which may be helpful to understand the spatial contexts and create arguments, but could not be downloaded or mapped. We may reference them in the context of other relevant datasets.

• Web applications and visualization tools that allow data exploration on the web but does not allow a direct download of the data (e.g., SEMCOG Maps and Apps Gallery)
• ESRI GIS layers that can only be open in map viewer but not downloadable
• Tabulated statistics that do not have spatial information (e.g., household income levels by age levels)
• PDF maps (e.g., zoning maps) or PDF reports
• General purpose data platforms (e.g., The Humanitarian Data Exchange) where only some datasets are relevant to planning topics. We prefer citing specific planning-related datasets published in these platforms and features these platforms in the Portal column.