1.2 Learning objectives

1.2 Learning objectives#

By the end of this book, you will be familiar with and have seen examples demonstrating the following concepts and operations:

Data cubes and array data structures#

  • Understanding fundamental structures of data cubes and how to organize earth observation datasets within this data model

  • Using Xarray label-based indexing and selection to manipulate and organize multi-dimensional data objects

  • Performing dimensional computations and visualizations with Xarray

  • Visualizing and querying vector datasets with GeoPandas

  • Using Xvec to create and use vector datasets, combining the functionality of Xarray and GeoPandas

  • Aligning and comparing two objects with different spatial resolutions

Working with large datasets#

  • How to read very large local data into memory using GDAL virtual format files (VRT)

  • Parallelizing local data reads with Xarray open_mfdataset()

  • Using Dask to parallelize workflows in order to work with larger-than-memory data

Reading and writing data#

  • Reading raster data from cloud object storage

  • Handling geospatial metadata and geospatial operations involving array data using Xarray and RioXarray

  • Understanding STAC metadata specification and how to use it to query and read data from cloud object storage

  • Reading and writing Zarr data cubes with Xarray

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