Recently, massive amounts of satellite images are becoming available. The automated and efficient management, knowledge extraction and visualisation of these big earth data can enable the timely and comprehensive decision making in a number of operational scenarios. In this work, we demonstrate DataCAP that combines the Open Data Cube (ODC) technology on Satellite Image Time-series (SITS), with Machine Learning (ML) pipelines and crowdsourced street-level images to assist in the monitoring of the Common Agricultural Policy (CAP). DataCAP offers a suit of processing tools to simply and intuitively search, store and analyse radar and optical satellite images, along with visualisation tools that combine satellite and street-level imagery for the visual verification of algorithmic decisions. * Supported by the ENVISION (No. 869366) and the CALLISTO (No. 101004152) projects, which have been funded by EU Horizon 2020 programs.