Automating GIS Processes 2023
Automating GIS Processes 2023# Welcome to the Automating GIS processes course 2023! Through interactive lessons and hands-on exercises, this course introduces you to geographic data analysis using the Python programming language. If you are new to Python, we recommend you first start with the Geo-Python course (geo-python.readthedocs.io) before diving into using it for GIS analyses in this course.
GitHub - mapbox/robosat: Semantic segmentation on aerial and satellite imagery. Extracts features such as: buildings, parking lots, roads, water, clouds
RoboSat is an end-to-end pipeline written in Python 3 for feature extraction from aerial and satellite imagery. Features can be anything visually distinguishable in the imagery for example: buildings, parking lots, roads, or cars. Have a look at this OpenStreetMap diary post where we first introduced RoboSat and show some results this OpenStreetMap diary post where we extract building footprints b
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GitHub - geopython/pygeofilter: pygeofilter is a pure Python parser implementation of OGC filtering standards
Client Challenge
Build a geospatial dashboard in Python using Greppo | Towards Data Science
Remote Sensing: Deep Learning for Land Cover Classification of Satellite Imagery Using Python
GitHub - sat-utils/sat-search: A python client for sat-api
GitHub - stac-utils/stac-validator: Validator for the stac-spec
GitHub - opengeos/leafmap: A Python package for interactive mapping and geospatial analysis with minimal coding in a Jupyter environment
GitHub - geopy/geopy: Geocoding library for Python.
GitHub - WZBSocialScienceCenter/geovoronoi: a package to create and plot Voronoi regions within geographic boundaries
rio-stac
GitHub - stac-utils/pystac: Python library for working with any SpatioTemporal Asset Catalog (STAC)
GitHub - Toblerity/rtree: Rtree: spatial index for Python GIS