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Financial Contributions
Top financial contributors
Organizations
$2,400 USD since Mar 2018
$820 USD since Nov 2019
$375 USD since Aug 2025
$350 USD since Dec 2021
$246 USD since Dec 2018
$200 USD since Mar 2018
$116 USD since Jul 2019
$102 USD since Feb 2023
$40 USD since Jul 2026
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Individuals
$4,600 USD since Sep 2022
$332 USD since Apr 2021
$308 USD since Dec 2017
$250 USD since Sep 2022
$208 USD since Mar 2018
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$170 USD since Apr 2022
$154 USD since Mar 2018
$110 USD since Dec 2017
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TurfJS is all of us
Our contributors 47
Thank you for supporting TurfJS.
Morgan Herlocker
$308 USD
Denis Carriere
$110 USD
Stefano Borghi
$44 USD
Tom MacWright
$24 USD
Rowan Winsemius
Tim Channell
Ashley
sponsor
$4,600 USD
Mapbox
$2,400 USD
Pozi
$820 USD
Torutek
$375 USD
2metz
$350 USD
Luis Ricardo
backer
$332 USD
CarbonReach
$250 USD
Intevation
backer
$246 USD
Budget
Transparent and open finances.
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$956.00 USD
About
About Turf.js
TurfJS is a modular geospatial analysis library designed for use in the browser as well as NodeJS. We provide almost 150 modules for people to use freely in their applications. Our most popular module is downloaded 50,000 times a week via npm.
Why we're looking for support
TurfJS is a community-driven project maintained by a small group of core contributors who work on the project in their spare time. Time is spent supporting users, improving documentation, fixing bugs as well as creating new modules. Your funding will directly go to development costs, marketing campaigns, promotional events & any other financial costs to operate & maintain TurfJS.
In particular, we're looking for corporate sponsors who use TurfJS in revenue-generating ways, either by creating applications for clients, or through use in an app used by customers. Of course individuals are welcome to support us as well if TurfJS has helped you :)
2017 Achievements
- Refactoring the codebase to support ES6 modules
- Adding approx 70 new modules/functions
- All new documentation
Development goals for Turf.js in the coming year
- Removing our largest dependency (JSTS) to significantly reduce the size of our compiled code
- Add new modules to bring us closer to feature parity with other geospatial libraries
Our team
Morgan Herlocker
Denis Carriere
Stefano Borghi
Tom MacWright
Rowan Winsemius
Tim Channell