Using Python to script GIS workflows has several advantages:
Python is a fundamental scripting language in GIS and is known to GIS users as the chosen scripting language for ArcGIS and QGIS. Experienced GIS users likely know of the ArcPy and PyQGIS Python libraries, but there are a growing number of standalone GIS libraries in Python.
Users can take advantage of these libraries for a wide range of use cases ranging from efficient data acquisition to full-analysis workflows utilizing vector and raster data, in which case Python's powerful machine learning and visualization capabilities can be leveraged.
The following Python example scripts can get you started:
The scripts are hosted on Google Colab. If you are new to using Colab you access information here: https://colab.research.google.com/#scrollTo=GJBs_flRovLc
Example Python GIS Packages
GeoPandas working with vector-based geospatial data
GDAL a translator library for a wide variety of raster and vector data formats.
PyProj interface to the PROJ cartographic projections and coordinate transformations library.
PySAL provides tools for spatial data analysis
RSGISLib the Remote Sensing and GIS Software library for working with remote sensing and imagery data.
Open streetmap (OSMNX) a library to work with the Open street maps dataset and produce street networks
Rasterio working with raster data
GeoWombat working with multiband imagery
Other Useful resources and tutorials
https://automating-gis-processes.github.io/2016/Lesson1-Intro-Python-GIS.html
https://gisgeography.com/python-libraries-gis-mapping/
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