Paul is an official at the Paying Agency. He is working in the control department. His job is to control the correct subsidy payments and provide consultations to farmers and access to their support related data. Paul also manages the maintenance of LPIS. Since recently, he has been managing projects aimed at developing an innovative monitoring process and a system that produces the indexes for the impact of agriculture in the Climate Change mitigation efforts. He experiences slow adoption of novel ICT tools by the departments doing operations.
1Scenario #1
Paul receives the automatically imported DIONE products: Crop types, EFAs, Permanent pastures, Biophysical parameters of crops and Soil data from spectrometers into the PA software. He opens that data to be provided to the farmers through the PA portal.
2Scenario #2
Paul receives the automatically imported DIONE very high ortho-imagery generated from drones into the PA software where he checks and updates the LPIS.
3Scenario #3
Paul receives the automatically imported DIONE geo-tagged photos recorded by farmers, soil data from miniaturized spectrometers and continuous soil properties maps into the PA software. He uses the data as in-situ to train the models and produce agro-environmental and climate change mitigation indices.
4Scenario #4
Paul logs in to DIONE environmental performance tool. He is provided with the menu of generated environmental performance indicators and other relevant datasets for the area of interest. He chooses the data layer to be displayed on the map and the geographic region. He picks on the map and the temporal changes of the parameter is displayed on the graph. Paul then picks on the other location and the related temporal changes are superimposed on the graph so he can compare the two locations. By setting the parameters of relevance, Paul triggers calculation of statistical data (e.g. environmental impact in comparison to certain crops). He exports the generated information to be used for the regular reporting he conducts.