SpaceSense’s library is structured with fusion of data at its core. The library is divided into the following sections:
The Client object enables users to directly interact with SpaceSense’s backend. This object is the main entry point to the library.
The Fusion Result object comes from the fusion of Search Result objects and custom data loaded using File Loaders objects, and contains the stacked data cube output.
Search Result objects are the results of queries to any SpaceSense satellite catalog. These objects contain the data and metadata necessary to download and fuse the exact observations you require. These objects possess Pandas dataframe attributes, which enable the refinement of the data by the user, as they would refine any other dataframe. More information on the filtering and manipulation of dataframes can be found here.
File Loaders are objects used to categorize and load user-provided files. Currently, both Raster and Vector data can be loaded using the associated Raster and Vector file loader objects.. With these objects, the files can be specified, and certain bands/fields/attributes can be identified as the information the user wants to fuse in the final result.
Job objects are used to initialize, view progress, retry, and download data resulting from a scaled workflow.
Finally, the Utilities objects and functions contain various useful functions for users to use. More utilties are planned to be added to aide and simplify processing and visualization for numerous domains and users.