SpatialModelingTutorials was developed to demonstrate function modeling, batch processing, and raster_tools functionality, along with various other coding and modelling strategies.
This collection of Notebooks is meant to demonstrate spatial modeling techniques that use parallel processing and the newly developed Raster Tools package. All notebooks are designed to run within Google's Colab. However, they can also be used locally if Raster Tools in properly installed on the local machine.
To open a notebook within Colab, expand the Notebooks directory and click on a given notebook. After the notebook opens in GitHub, click on the “Open in Colab” link (top left). Once in Colab you can step through each notebook cell.
- ANF_ML – A short course notebook that demonstrates various vector, machine learning, and visualization techniques using the Raster_Tools package.
- DeliveredCost – A notebook that demonstrates the delivered cost routine described in New Geospatial Approaches for Efficiently Mapping Forest Biomass Logistics at High Resolution over Large Areas using Raster_Tools.
- EGAM_example – A notebook used to demonstrate the EGAM modeling procedure described in Estimating Forest Characteristics for Longleaf Pine Restoration Using Normalized Remotely Sensed Imagery in Florida USA.
- PODs_Integration – A notebook demonstrating 21st Century Planning Techniques for Creating Fire-Resilient Forests in the American West.
- Python_Automation_ANFS – A short course notebook that demonstrates python automation strategies and basic vector processing using Raster_Tools.
- Quick_example_in_R – A short notebook demonstrating how to create a R Colab notebook.
- Raster_tools_surface – A short notebook demonstrating the surface module within Raster Tools.
- Rumple_python – A short notebook demonstrating how to create fast for loops using Numba and automated parallelization through Dask.