About

Called Web Crop Phenology Metrics Service (WCPMS) the software extracts phenological metrics from big EO image collections, modeled as multidimensional data cubes, produced by the BDC project of INPE.

It allows analysts to calculate phenological metrics on cloud. The opposite of the on-premises established algorithms, so with no need to download big EO data sets on their personal computers.

We created the wcpms.py library from scratch to facilitate phenology extraction operations. This library was developed to be interoperable with other Python libraries, thus enabling users to integrate established libraries into their own workflows for pre- or post-processing and analysis. The wcpms.py library has a group of functions, the main ones are:

• get_collections: returns in list format the unique identifier of each of the data cubes available in the BDC’s SpatioTemporal Asset Catalogs (STAC).

• get_description: returns in dictionary format the information on each of the phenology metrics, such as code, name, description and method.

• get_phenometrics: returns in dictionary form all the phenological metrics calculated for the given spatial location.

• get_phenometrics_region: returns in list format the phenological metrics calculated for each pixel centers within the boundaries of the given region using satellite images time series.

Installation

See Installation.

Changes

See Changes.

Documentation

See https://wcpms.readthedocs.io/en/latest.

References

Sansigolo, G., Reis Ferreira, K., De Queiroz, G. R., Körting, T., Pereira Garcia Leão, L., & Adami, M. (2026). A tool for crop phenology metrics analysis from big Earth observation data. Big Earth Data, 1–24. https://doi.org/10.1080/20964471.2026.2641272

License