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

Compare commits

base: Awesome-Mirrors:50e0a376d2d4b023a7a9467b048e25d11d906b85
Branches Tags
Awesome-Mirrors:master
...
compare: Awesome-Mirrors:e5a4a8cd9a3a66e06dc3ef88b07deccd97bc43b7
Branches Tags
Awesome-Mirrors:master

2 Commits
50e0a376d2 ... e5a4a8cd9a

Author SHA1 Message Date
Eduardo Lacerda e5a4a8cd9a
Update README.md 2023-04-15 20:19:38 -03:00
Eduardo Lacerda 01bf46662c
Update README.md 2023-04-15 20:16:56 -03:00
1 changed files with 2 additions and 0 deletions
Show Stats Expand all files Collapse all files

2
README.md
View File

@ -1150,6 +1150,7 @@ Long list of geospatial analysis tools. Geospatial analysis, or just spatial ana
* [SpatialPosition](https://cran.r-project.org/web/packages/SpatialPosition/index.html) - Computes spatial position models: Stewart potentials, Reilly catchment areas, Huff catchment areas.
* [spatialprobit](https://cran.r-project.org/web/packages/spatialprobit/index.html) - Bayesian Estimation of Spatial Probit and Tobit Models.
* [spatialRF](https://github.com/BlasBenito/spatialRF) - R package to fit spatial models with Random Forest.
* [SpatialRDD](https://github.com/axlehner/SpatialRDD) - R package to work spatialy with RDD files.
* [spatialsegregation](https://cran.r-project.org/web/packages/spatialsegregation/index.html) - Summaries for measuring segregation/mingling in multitype spatial point patterns with graph based neighbourhood description.
* [SpatialTools](https://cran.r-project.org/web/packages/SpatialTools/index.html) - Tools for spatial data analysis. Emphasis on kriging. Provides functions for prediction and simulation.
* [spatstat](https://cran.r-project.org/web/packages/spatstat/index.html) - Spatial Point Pattern Analysis, Model-Fitting, Simulation, Tests.
@ -1278,6 +1279,7 @@ Long list of geospatial analysis tools. Geospatial analysis, or just spatial ana
## Geospatial Big Data
* [Apache Sedona](https://sedona.apache.org/latest-snapshot/) - Cluster computing system for processing large-scale spatial data
* [geobeam](https://github.com/GoogleCloudPlatform/dataflow-geobeam) - geobeam adds GIS capabilities to your Apache Beam pipelines and enables you to ingest and analyze massive amounts of geospatial data in parallel using Dataflow.
* [GeoMesa](https://github.com/locationtech/geomesa) - GeoMesa is a suite of tools for working with big geo-spatial data in a distributed fashion.
* [GeoTrellis](https://github.com/locationtech/geotrellis) - GeoTrellis is a geographic data processing engine for high performance applications.