How do I find the best Python GIS library in Awesome GIS?

Navigate to the 'Geospatial Library' section and look under 'Python' for a curated list of libraries like GDAL, GeoPandas, and Rasterio, but note that you'll need to research each one separately for suitability.

What's the difference between Awesome GIS and the GIS tools listed in Awesome Python?

Awesome GIS is a comprehensive, geospatial-specific directory covering software, data, and learning resources across all languages, while Awesome Python's GIS section is limited to Python tools and lacks broader categories like remote sensing or spatial databases.

How can I contribute a new tool to Awesome GIS?

Follow the Contributing Guidelines linked in the README, which involve submitting a pull request on GitHub with the resource added to the appropriate category, ensuring it meets the project's quality standards.

Are there free satellite imagery datasets in this list?

Yes, check the 'Data' section for open data sources, and the 'Deep Learning Datasets' subsection includes links to satellite imagery collections for machine learning, though availability and formats vary.

How often is Awesome GIS updated?

Updates depend on community contributions; the GitHub badge shows the last commit date, but there's no fixed schedule, so some sections may be more current than others.

Does Awesome GIS include mobile GIS SDKs for cross-platform development?

Yes, the 'Mobile Develop Tools' section lists SDKs for Android, iOS, and cross-platform frameworks like React Native, but you'll need to evaluate compatibility and features for your specific use case.

Open-Awesome

Awesome GIS

MIT

A curated collection of geospatial software, data, libraries, and resources for GIS developers and analysts.

GitHub

5.5k stars852 forks0 contributors

What is Awesome GIS?

Awesome GIS is a curated GitHub repository that aggregates geospatial software, libraries, data sources, and educational resources. It solves the problem of discovering and evaluating GIS tools by providing a categorized, community-maintained directory for developers and analysts.

Target Audience

Geospatial developers, GIS analysts, remote sensing researchers, and anyone needing a reference for geospatial tools and data across various programming languages and platforms.

Value Proposition

It saves significant research time by offering a single, trusted source for discovering geospatial resources, is frequently updated by the community, and covers a wider range of tools than commercial vendor lists.

Overview

😎Awesome GIS is a collection of geospatial related sources, including cartographic tools, geoanalysis tools, developer tools, data, conference & communities, news, massive open online course, some amazing map sites, and more.

Use Cases

Best For

Finding open-source alternatives to commercial GIS software like ArcGIS
Discovering geospatial libraries for a specific programming language (e.g., Python, JavaScript)
Locating spatial databases and web mapping frameworks for application development
Accessing free geospatial data sources and satellite imagery datasets
Learning GIS through MOOCs, conferences, and community resources
Evaluating tools for remote sensing, 3D mapping, or mobile geospatial development

Not Ideal For

Enterprises requiring integrated, vendor-supported GIS platforms with service-level agreements and dedicated support
Developers seeking hands-on tutorials, code samples, or implementation guidance for specific geospatial tools
Projects needing real-time, dynamic resource discovery or automated tool recommendations beyond a static list

Pros & Cons

Pros

Extensive Categorization

The README organizes resources into over 30 detailed sections—from GIS software and spatial databases to data formats and MOOCs—making it easy to navigate by topic.

Multi-Language Library Coverage

Lists geospatial libraries for numerous programming languages, including Python, JavaScript, Java, and R, as highlighted in the 'Geospatial Library' section with sub-sections for each language.

Community-Driven Freshness

Actively encourages contributions via GitHub, with badges showing stars, forks, and recent commits, ensuring the list stays updated with new tools and data sources.

Broad Resource Inclusion

Goes beyond software to include open data sources, learning materials, conferences, and standards, as seen in sections like 'Data' and 'Open Standards'.

Cons

No Quality Assessments

The list only provides names and links without reviews, ratings, or comparisons, forcing users to independently evaluate tool suitability and reliability.

Risk of Stale Entries

Relies on community contributions for updates, so some tools may be outdated or deprecated without clear warnings, as noted in the reliance on external issue reporting.

Lacks Implementation Guidance

Focuses on aggregation rather than offering tutorials or best practices, leaving users to figure out integration and usage on their own after discovery.

Frequently Asked Questions

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Community-curated · Updated weekly · 100% open source

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