DataCAP: A Satellite Datacube and Crowdsourced Street-level Images for the Monitoring of the Common Agricultural Policy
Creators
- 1. National Observatory of Athens
- 2. National Technical University of Athens
Description
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.
Files
DataCAP_mmm22.pdf
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Additional details
Related works
- Is published in
- Conference paper: 10.1007/978-3-030-98355-0_41 (DOI)
Funding
- ENVISION – Monitoring of Environmental Practices for Sustainable Agriculture Supported by Earth Observation 869366
- European Commission
- CALLISTO – Copernicus Artificial Intelligence Services and data fusion with other distributed data sources and processing at the edge to support DIAS and HPC infrastructures 101004152
- European Commission