The itsdm is an R CRAN package, which calls isolation forest and variations such as SCiForest and EIF to model species distribution. It also uses a technique based on Shapley values for model explanation. Please check more details and tutorials on its online document.
This is a package that combines R and Python to ensemble existing land cover products, human and machine intelligence to do land cover mapping (chapter 1 in the dissertation project). The package has scripts to process satellite images, to build Random Forest gap-filling model, and to train U-Net model. Please check GitHub for details.
This package provides necessary steps at both level 2 and 3 to preprocess sentinel-1&2 images. Check its GitHub page to get details about its functions and how to use them.
Docker to run Orchestrate WASP (Weighted Average Synthesis Processor) to create monthly syntheses of cloud-free reflectance for sentinel-2 or Venus Level-2A products distributed by the Theia Land data centre. Check its GitHub page about how to use it.
Land cover map of Tanzania (4.77 m) and the training set are shared on OSF and Registry of Open Data on AWS. The interested users can go there to download them.