
TurfJS
Advanced geospatial analysis for browsers and Node.js

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Top financial contributors
Individuals
$176 USD since Dec 2017
$100 USD since Oct 2018
$100 USD since Jan 2019
$100 USD since Jan 2019
$80 USD since Oct 2019
$76 USD since Dec 2017
$76 USD since Mar 2018
$76 USD since Mar 2018
$76 USD since Mar 2018
$76 USD since Mar 2018
Organizations
$2k USD since Mar 2018
$260 USD since Dec 2018
$200 USD since Mar 2018
$170 USD since Nov 2019
$108 USD since Dec 2018
$80 USD since Oct 2019
$44 USD since Jul 2019
TurfJS is all of us
Our contributors 38
Thank you for supporting TurfJS.

Budget
Transparent and open finances.
Monthly financial contribution to TurfJS (backer)
from Moacir de Sá Pereira •
Monthly financial contribution to TurfJS (backer)
from Luis Ricardo •
Monthly financial contribution to TurfJS (backer)
from Intevation GmbH •
$2,468.25 USD
$3,505.55 USD
$1,037.30 USD
$281.50 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