Awesome-Mirrors
/
Awesome-Geospatial
mirror of https://github.com/sacridini/Awesome-Geospatial.git
1
0
Fork 0
Code Issues Packages Projects Releases Wiki Activity

Add "Lets-Plot" to Kotlin and Python sections.

This commit is contained in:
Igor Alshannikov 2023-04-20 15:55:08 -04:00
parent 6b2b87ae3f
commit 7a1d498ec4
1 changed files with 2 additions and 0 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

2
README.md
View File

@ -742,6 +742,7 @@ Long list of geospatial analysis tools. Geospatial analysis, or just spatial ana
## Kotlin
* [geospatial-messenger](https://github.com/sdeleuze/geospatial-messenger) - Geospatial messenger application written with Spring Boot + Kotlin + PostgreSQL.
* [Lets-Plot](https://github.com/JetBrains/lets-plot-kotlin/blob/master/docs/geotools.md) - An open-source plotting library. Together with GeoTools it allows you to visualize geospatial data in Jupyter notebooks or a JVM application.
## Lisp
* [cl-ewkb](https://github.com/filonenko-mikhail/cl-ewkb/) - Common Lisp PostGIS EWKB data model and encoder/decoder.
@ -841,6 +842,7 @@ Long list of geospatial analysis tools. Geospatial analysis, or just spatial ana
* [landsat7-errors](https://github.com/gena/landsat7-errors) - Identifies and correct errors in raw values of Landsat 7.
* [landsatxplore](https://github.com/yannforget/landsatxplore) - Search and download Landsat scenes from EarthExplorer.
* [leafmap](https://github.com/giswqs/leafmap) - A Python package for geospatial analysis and interactive mapping with minimal coding in a Jupyter environment.
* [Lets-Plot](https://lets-plot.org) - An open-source plotting library supporting visualization of geospatial data on static or interactive maps.
* [lidar](https://github.com/giswqs/lidar) - Terrain and hydrological analysis using digital elevation models (DEMs).
* [localtileserver](https://github.com/banesullivan/localtileserver) - A Python package for serving tiles from large raster files in the Slippy Maps standard (i.e., `/zoom/x/y.png`) for visualization in Jupyter with `ipyleaflet` or `folium`.
* [LT-ChangeDB](https://github.com/eMapR/LT-ChangeDB) - Scripts to extract spectral change information from LandTrendr data to a geodatabase.