ARCADIA SIT is a partner in a European consortium for the supply of services in the field of GIS and remote sensing, under the framework contract Desis. The project is developed by CCR – IPSC – The Institute for the Protection and Security of the Citizen / MARS-Monitoring Agricultural Resources.
Development and execution, since 1992, of a system for forecasting agricultural crops in Europe.
The system provides annual estimates of harvest at European level by monitoring the growth of crops and vegetation analysis of weather effects in the short term. The geographical area covered is Throughout continental Europe in any detail and West Africa sub-regional level.
The input data used are:
- Scientific publications.
- 10 days composite raster images from the following systems of platform/sensors
- MODIS – TERRA, SPOT –VEGETATION , MSG – SEVIRI, METOP – AVHRR;
- Raster and vector file in the frame of land cover/land use Corine Land Cover;
- Meteorological data;
- Agronomical data;
- Modeled agronomic and agrometereological indicators;
- Statistical data;
- and reporting:
- Monthly bulletin of yield forecast in Europe;
- Commission reports on agricultural pattern .
AGRI4CAST project organizes various kinds of information and geographical data in a huge database:
- Meteorological data;
- Soil use;
- Pedologic data;
- Statistical data on agricultural production;
For the EU countries information are collected and organized to provide data for prediction models and to obtain results in terms of expected production for the different types of agricultural production.
From this information, we generate variable dimension vector grids required to create EU level cover that summarize input and output data.
The informationbehind AGRI4CAST projectare managedand processed withArcGISDesktopfor all phasesof analysisinvolvingthe intersection betweenthe various vector themes: CorineLand Cover, soil map, agricultural production data, weather, etc.. this aim to identifyhomogeneous areasforpotential
productions, which combine the information of the previous productions.
Information are transposed on regular grids of different sizes to calculate the indicators and thereby provide input data to the predictive models. Each stage of the process consists of an .mxd that haracterize the graphical representation of input themes and the results of the various procedural steps of data processing.
Projects layout are defined for printing and for the representation of statistics, showing the thematic areas aimed at the production of overview maps. Develop information infrastructures and systems (INSPIRE, SEIS, GEOSS, G M ES, RSDI) to share environmental observations, information and analytical models and promote interoperability and standard setting.
Many of the procedures for the production of statistics are made using ArcGIS Model Builder that allows to repeatedly produce data analysis for each EU country examined, ensuring uniqueness of analysis.
Model Builder is effective for the possibility of establishing schematic procedures which link geo-processing tools within a procedural flow of spatial analysis of the information, producing new layers or classify existing ones. Typically combination of geo-processing tools is set, according to a analysis scheme defined by user that simultaneously provide data analysis and classification of certain parameters: type of vegetation, event time, surface concerned, etc.
Model Builder was used in the project intensively for different types of activities:
accuracy verification of the input information:
- Completeness of descriptive information;
- Spatial coverage of information;
- Geometric and topological accuracy.
Information analysis and scenarios production:
- correlation of the different information depending on the location;
- calculation of indicators processing the original information and saving in the database.
The activities are based on expertise in crop modeling, agro-meteorology, sampling methods, environmental geo-spatial analysis, econometrics and using European and global data infrastructures. From this skill-set are generated evidence-based information and forecasts for the management of agricultural practices and early warnings on Food Security. The project foster the development of control systems, such as land parcel management and remote sensing checks, for efficient implementation of the Common Agriculture Policy, including the ‘greening’ aspects. We perform assessments of the effectiveness, efficiency, relevance and sustainability of policy measures according to their impacts on rural environment and on food security. This includes the issue of climate change adaptation and possible mitigation by agriculturally related policies, and specific attention to new measures promoting biodiversity, environmental quality and resource efficiency.
In view of providing support to the CAP and the Climate Change policy agenda of the European Commission, studies are being implemented in AGRI4CAST that assess the impact of a changing climate on crop yields in Europe, that identify vulnerabilities and resilience of crop production systems under a number of climate change scenarios, and evaluate different adaptation measures to mitigate the impacts identified. Agriculture has a dual role in terms of global change: It is an important emitter of greenhouse gases, while at the same time it is one of the main sectors to be impacted by climatic change, with local, regional and global implications for the stability and access of food supply. AGRI4CAST investigates impacts on agricultural yield levels with simulations of BioMA-based models forced by chosen climate change scenarios, concentrating on short-term and medium-term time horizons (e.g. 2020, 2050).
Climate change-related activities of AGRI4CAST also explore regional vulnerabilities in agricultural production and effects of selected adaptation strategies to mitigate climate change effects as well as impacts of selected soil organic carbon mitigation measures on agricultural production, thus supporting the Europe 2020 flagship of a Resource Efficient Europe.
Crossing the input data through, GIS, Data mining and ad-hoc routines in the appropriate IT language, to analyze data and produce in output:
- Analysis continental scale images of vegetation indicator such fAPAR (Gobron and Cyclops methods) and NDVI on agricultural and pasture land;
- Analysis of the meteo, agronomic and agrometereological indicators;
- Identification of the timing of the main agro-phenological events;
- Analysis of the behaviors of the vegetation indicators and the statistical data;
- Derivation of yield forecast for the main crops in Europe.
In this project various quality checks are performed on the input data quality and on the perimeter of the burned areas produced. These procedures have been implemented in ArcGIS Desktop advanced environment through Model builder and a deep usage of Python scripts and geo-processing libraries.
Conduct further testing, the correspondence between the elements territorial and statistical data of estimations. The verification concerns the geometric consistency (spike, undershoot, overshoot), topological (overlap) and the population of the attribute tables. Before loading in the database datasets on forest fires and matching of these with the areas taken from images are verified.
CustomerJoint Research Centre ISPRA - EU COMMISSION
- Quality Control Procedure
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