Search

https://nlnet.nl/news/2025/20250321-call-announcement-core.html

Notes

1. Projects meaningfully sharing two programming languages get 0.5 a point each, even if the split is not exactly half-half.
2. Two projects are listed under "Multi/Misc/Other" which is opinionated, and some may disagree with.
3. Three points (5 projects) are assigned to "Unaccounted/Not Available". Two of the projects have no code at all (related to the grant, or otherwise). One project with no published code is (charitably) listed under "Python", however, since the author mentions Python+QT as the choice for implementation.

9.5 (10 projects) Rust

https://git.joyofhardware.com/Products/FastWave2.0
https://github.com/slint-ui/slint
https://github.com/stalwartlabs/mail-server
https://github.com/dimforge
https://github.com/DioxusLabs/blitz
https://github.com/fdtshim
https://github.com/trynova/nova
https://github.com/yaws-rs
https://github.com/lycheeverse/lychee
https:/

repo: https://github.com/damienallen/urban-heat

cross-posted from: https://programming.dev/post/14939898

I wanted to share a small project I've been working on. The goal was to make the data from NASA's Landsat Thermal Infrared Sensor more accessible to the general public.

I worked with the raw temperature band data to general annual maximum surface temperature raster images for large urban areas covered by the Eurostat GISCO Urban Audit. In the browser, these images are transformed into easier to interpret isotherm contours with some adjustable settings.

I don't have a specific target audience in mind. The map could help identify areas of refuge for the warmer months, or overheated neighborhoods to avoid as we march towards a toasty future.

Feedback is welcome :)