A curated community list of data, technology, and software resources for urban and regional planning professionals.
Urban & Regional Planning Resources is a community-curated GitHub repository that aggregates data, technology tools, software platforms, and educational materials for professionals working on built environment challenges. It serves as a centralized reference to discover public datasets, vendor data sources, open standards, coding libraries, and planning software across domains like transportation, housing, climate, and equity.
Urban and regional planners, GIS analysts, civic technologists, transportation engineers, researchers, and data scientists working on community development, infrastructure, or environmental projects.
It saves significant time by consolidating hundreds of specialized resources in one place, promotes the use of open standards and open-source tools, and fosters knowledge sharing across the planning community through its open, collaborative model.
Community list of data & technology resources concerning the built environment and communities. 🏙️🌳🚌🚦🗺️
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Centralizes hundreds of public and vendor datasets, tools, and specifications across domains like climate, demographics, and transportation, saving professionals significant research time. Evidence: Extensive sections like 'Public Data Resources' and 'Vendor Data Resources' list numerous sources.
Maintained by the APA Technology Division and open to contributions, ensuring the repository stays relevant and updated with community input. Evidence: README includes a 'Contributing' section and highlights it as 'community-maintained'.
Promotes interoperability by documenting key data specifications such as GTFS, CityGML, and CurbLR, which are essential for modern planning systems. Evidence: Dedicated 'Planning Data Specifications' section with detailed standards and links.
Caters to diverse roles by including coding libraries, software platforms, and educational materials, supporting planners, researchers, and technologists alike. Evidence: Sections like 'Coding Resources', 'Platforms and Software Resources', and 'Educational Resources' cover various needs.
Resources are manually curated and may become outdated, with no automatic verification of link validity or data freshness, requiring users to check currency independently. Evidence: Updates depend on GitHub commits and community contributions, without mentioned automation.
While it lists resources, it doesn't provide tutorials or best practices for integration, leaving users to figure out implementation on their own. Evidence: Sections are primarily descriptive lists with brief explanations, not step-by-step guides.
The vast breadth of resources across multiple categories can be difficult to navigate without prior knowledge, potentially leading to information overload. Evidence: Extensive table of contents with numerous sub-sections like 'Public Data Resources' and 'Vendor Data Resources'.