Project Overview
The European Union (EU) implements a set of funding regulations under the Common Agricultural Policy (CAP), aiming at the sustainable development of the agricultural sector and the management of natural resources. Towards this direction EU and each state member offer also recovery assistance to disaster-affected farmers in the event of a natural disaster, i.e. fires, floods, etc. Implementation of the CAP and insurance coverage of farmers requires detailed and regular monitoring of crop types and the extent of the damage by carrying out frequent controls.
Nowadays, these controls are mainly performed through in-situ visits, which demand very high administrative costs. Moreover, the procedure is time-consuming and difficulties, such as adverse weather conditions, inaccessible areas, etc., can further delay subsidies/compensations. Although efforts have been made to use satellite data, certain factors obstructing their broad and automated exploitation. The limited availability and high cost of very high-resolution satellite images along with difficulties in their interpretation, which is highly subjective and requires a lot of time are some factors obstructing the use of satellite imagery.
The EU has recently launched Sentinel Satellites as part of the Copernicus Programme in cooperation with the European Space Agency (ESA). Sentinels enable monitoring of large agricultural fields and mapping floods/fire extend with high accuracy. In the field of processing time-series of satellite observations, research is still at an early stage and the development of automated techniques is limited.
To this end, the DiAS project will revise the existing knowledge on remote sensing methods for monitoring the agricultural land and will propose advancements were necessary, suitable for the Sentinels. Those methods will be implemented in a Decision Support System (DSS), which will be freely available and easy-to-use by non-experts. DiAS is expected to improve the efficiency of the decision-making process on agricultural aid and compensation. Exploiting free satellite data will reduce the number of in-situ visits, minimizing costs and delays of controls. The automation of the satellite image processing will contribute to the immediate decision making and to the sustainability of agriculture not only in Greece but also internationally.
Objectives
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to exploit Sentinel imagery in order to monitor agricultural activity and map natural disasters, such as fires and floods
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to promote scientific knowledge by evaluating existing remote sensing methods and to propose new, adapted to Sentinel
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to propose techniques which integrate data from different satellite systems to meet the needs of mapping and monitoring rural areas
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to develop a methodology for mapping and monitoring rural areas combining information on the state of crops before and after natural disasters, with emphasis in fires and floods
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to design a tool that incorporates the above methodology, to be easily used by the stakeholders (public entities)
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to improve both the speed and the quality of the control checks for timely payment of subsidies/compensations to farmers
