Feasibility study and optimization of image tasking in the context of the European Union CAP CwRS

Abstract

CwRS (Control with Remote Sensing) is a control method foreseen by the CAP (Common Agricultural Policy) of the European Union (EU) which is used to check if agriculture area-based subsidies are correctly granted to EU farmers. A series of Very High Resolution (VHR) and High Resolution (HR) satellite sensors participate in the acquisition program. Imagery is collected in specific multi-temporal, short time-windows and used for parcel area determination, for crop identification and for control of Good Agricultural and Environmental Conditions (GAECs). In the 2003 Campaign 37 VHR zones with an overall area of 12.500 km2 were checked with the CwRS technique; in the 2011 Campaign 426 VHR control zones were acquired covering an overall area of 242.000 km2, with a total expenditure of 7.1 M euro. This is an enormous increase due to the success of the methodology which needs pointing out. Of interest is also the increasing requirements put on the imagery quality (higher elevation angle, better resolution and better radiometry.). One of the crucial features requested by EU Member States (MS) is window length, for VHR this is usually quite short (6-8 weeks). A feasibility analysis for all zones is therefore done before each VHR Campaign starts to ensure a maximal statistical success rate. This paper describes the complexity of the technical and competitive feasibility assessment taking into account parameters such as satellite characteristics (revisit capacity, number of passes), zone size, shape and latitude; elevation angle, acquisition window length, programming priority level, weather forecast and competitive conflicting tasking. To increase the efficiency of the image acquisition a real local tasking with the use of a Direct Access Facility (DAF) can be compared to a tasking performed through an Imaging and Processing Facility (IPF). Both approaches allow the integration of last minute information into the collection plan and yield for instance better chances of avoiding cloud cover. Illustrative examples are presented.