Introduction to Geospatial Computing Open Data Science Conference 2022

Software

PySal: Python Spatial Analysis Library
GeoPandas: Geospatial Extension of Pandas Python Library
sf: Simple Features for R
spdep: Spatial Dependence Weighting Schemes and Statistics
stars: Spatiotemporal Arrays Raster and Vector Datacubes mapview: Interactive viewing of spatial data in R
rasterVis: Raster Visualization in R
Rayshader: 3D Maps in R
QGIS: Free and Open Source Geographic Information System
PostGIS: Spatial and Geographic objects for PostgreSQL
Apache Sedona: Spatial Extension of Apache Spark

Books

Spatial Data Science with applications in R
Geocomputation in R
Intro to GIS and Spatial Analysis
Geospatial Data Science With R: Applications in Environmental Geography
Spatial Data Science with R and “terra”
Spatio-Temporal Statistics with R
Analyzing US Census Data: Methods, Maps, and Models in R
Displaying time series, spatial and space-time data with R
The Geography of Transportation Systems

Other learning resources

Resources for Deep Learning with satellite & Aerial Imagery
Dani Arribas-Bel's Geographic Data Science Course Material
NSF's National Ecological Observatory Network (NEON) Tutorials on Spatial Data Processing
GIS&T Body of Knowledge
Common GIS File Fornmat

Data

Multi-Resolution Land Characteristics (MRLC) Consortium
Resourcewatch

extra need to format and organize

https://kepler.gl/

https://training.datapolitan.com/qgis-training/Introduction_to_GIS_Fundamentals

https://training.datapolitan.com/qgis-training/Intermediate_GIS/