check out OpenEO (like GEE from ESA)

[bbest]

• OpenEO, About

Earth Observation data are becoming too large to be downloaded locally for analysis. Also, the way they are organised (as tiles, or granules: files containing the imagery for a small part of the Earth and a single observation date) makes it unnecessary complicated to analyse them. The solution to this is to store these data in the cloud, on compute back-ends, process them there, and browse the results or download resulting figures or numbers. But how do we do that?

openEO develops an open application programming interface (API) that connects clients like R, Python and JavaScript to big Earth observation cloud back-ends in a simple and unified way.

With such an API,

• each client can work with every back-end, and
• it becomes possible to compare back-ends in terms of capacity, cost, and results (validation, reproducibility)

• R client: openeo-r-client
• Python client: openeo

Datacubes | openEO

Filtering the sample datacube. It is displayed at the top with dimensions labels. Filtered results are shown at the bottom.

Spatial resampling. The geometry which the input cube is resampled to is displayed in the middle. The output cube then contains the same information, but in the resampled spatial layout.

When aggregating spatially, pixels are grouped (cut out) based on geometries, and then collapsed with a reducer function. A vector datacube is returned (as shown with dimensions names and labels). Please note that this visualization shows aggregation on a data cube with four dimensions, but aggregate_spatial specifically can only handle data cubes with three dimensions as of now.