This is a collection of scripts and Jupyter notebooks that helps facilitate scalable and reproducible analysis of landscape data.
aoi-2-dataset.ipynb demonstrates how to search within an area of interest (AOI) in Google Earth Engine for topographic and multispectral data in the Arctic, download that data, and convert it to a format that can be used to create labels and training data for image segmentation via Doodleverse tools. For now this includes functions but in the future this tool may take the form of a package or functions/methods within a package. But for now you can run this notebook to collect your own data. Stay tuned!
imagery-dem-profiler uses geemap to load up a visual of a landscape and then you can draw multiple topographic profiles on that imagery. Great for exploring water tracks!
spectral-change-detector creates annual composite images to look at pixelwise changes in spectral indices over time. Great for exploring greening and browning of water tracks!