Georeferencing in Python has the advantage that it can be performed repeatedly without the need to define control points each time. It also allows you to add/remove control points and observe the impact on the transformation array. This tutorial demonstrates the complete georeferencing process of a national map using 3 points whose pixel coordinates have been extracted from the Paint utility in Windows. The tutorial also exports the raster while assigning a reference system.

Large amount of spatial data is indexed and delivered through files in Hierarchical Data Format (HDF). These files are compatible with desktop GIS software as QGIS but they are not so easy to open/read/process with standard Python libraries as Rasterio, or with dedicated libraries. On our research we found the spatial functionality on the powerful GDAL binaries and library for Python. 

If you want to determine the longest channel of a river network automatically this feature Hatari Utils might be of your interest. Hatari Utils is a toolbox for different analysis in water resources and beyond. On the “watershed delimitation” tool you can define the catchment, the river network and now you can define the main channel (longest succession of segments that connect a source to the outlet of the basin) automatically on the catchment delineation.

If you have a geological contact as a geospatial and you want to calculate/measure the strike and dip at a certain point, this tutorial might help you. The ThreePointMethod is a QGIS plugin that calculates a plane strike and dip direction using the three-point method. It works with a point shapefile and a digital elevation model.

This tutorial covers a simulation example of groundwater flow and groundwater discharge with the GroundwaterDupuitPercolator component of Landlab. Simulation is run on steady state over a one layer aquifer and results are plotted on charts and grids.

If you have a set of drone imagery and you want to know the location and direction of the camera, this tutorial might be interesting for you. We have done an applied example that retrieves the geospatial metadata from the drone camera for a group of images and makes a geostapatial repretacion on a map with the image name available as popup. The tutorial is done under a Jupyter notebook with Python and Folium.

Open lithology datasets are scarce and most times they come in certain exchange formats that can´t be easily coupled with other softwares. Python has the tools to read and extract data from those files and provide them in more friendly formats as csv or xlsx. With the use of spatial libraries as Fiona or 3D visualization libraries as Pyvistas we can go one step further and process our data as shapefiles or vtks.