spatial-data

The PyEarthScience repository created by DKRZ (German Climate Computing Center) provides Python scripts and Jupyter notebooks in particular for scientific data processing and visualization used in climate science. It contains scripts for visualization, I/O, and analysis using PyNGL, PyNIO, xarray, cfgrib, xesmf, cartopy, and others.

Jupyter notebooks for the workshop *Introduction to Python language and Google Colab for spatial data visualization and analysis*

A collection of code notebooks designed to support researchers, analysts, and data enthusiasts create reproducible spatial workflows in R. Designed in collaboration with IPUMS and the NSF I-GUIDE.

Jupyter notebooks related to NITheCS micro school series.

01.12.18 - Notebook provides basic introduction to spatial data science in python for UMN Day of Data 2018

This repo provides multiple notebooks from a master degree course called 'Temporal and Spatial Data Mining' of University of Kassel, Germany.

This project demonstrates how to extract geospatial features (e.g., fire hydrants) from OpenStreetMap (OSM) and convert them to ArcGIS-compatible formats (ESRI Shapefiles). It includes an automated Jupyter Notebook workflow for reading OSM data, filtering objects, and exporting to .shp.

e plot_socib_rv_trajectories is a python notebook developed at SOCIB to plot the trajectiories from data collected by a VM-ADCP, thermosalinometer, GPS and weather station mounted onboard the RV-SOCIB. They are able to plot the trajectories of the main variables stored into the SOCIB netcdf files and plot them on a map

An AI-native spatial computing platform: a headless spatial kernel, designed so that the UI, CLI, notebooks and AI are all clients of it. v0.1.0 is a Windows prototype — open a GeoParquet, filter it in SQL, style it, publish a static interactive bundle. AGPL-3.0-or-later core; the SKP protocol and file formats are open.