To date, the Land Parcel Identification System (LPIS) has often been proposed as the foundation for effective spatial management of agriculture and the environment and many land managers have suggested incorporating it in most of the instruments for sustainable agriculture. The LPIS is originally used for registration of agricultural reference parcels considered eligible for annual payments of European Common Agricultural Policy (CAP) subsidies to farmers. Its intrinsic quality depends on the frequency and magnitude of the discrepancies in area, since some parcels can be under- or over-declared by farmers compared with reference registered within the LPIS. General application of the LPIS therefore depends on our capacity to ¿ first identify and explain the causes of these area discrepancies perceived as anomalies by national CAP payment agencies ¿second, to propose future improvements in its overall quality.
From a set of images used during the 2005 Control with Remote Sensing (CwRS) campaign, using the geographic information system (GIS) and ecological methodologies we assessed the quality of the LPIS by identifying the diversity of the existing anomalies. To that end, the ecological sampling method was adapted to the specific case of image-based detection of anomalies. The observed anomalies assemblages obtained from a set of European Member States representing the four types of LPIS were analysed to establish the spatial pattern of the anomalies.
We showed that the twelve zones surveyed can be grouped into four different clusters, each individually correlated with the presence of certain categories of LPIS anomaly. Some clusters were more particularly related to the presence of natural and anthropogenic landscape features, whereas others were typified by anomalies which stemmed from the process for creating and updating the LPIS, which accounted for 20% of the anomalies detected. Finally, we also showed that, even if useful for establishing procedures to manage the LPIS, the LPIS typology used in the European Union had no effect on the anomalies assemblage or on the spatial pattern; consequently, the type of LPIS no longer needs to be considered and LPIS anomalies assemblages could be pooled across Europe.
In the light of the results obtained, different proposals are made to improve LPIS quality by:
¿ identifying the critical points along the LPIS management chain;
¿ using landscape ecological methodologies to explain the causes of the clusters observed; and
¿ extrapolating the whole results in the CwRS risk analysis to perform ex-ante LPIS anomalies risk map.
Keywords: Land Parcel Identification System, Control with Remote Sensing, orthophoto, quality assessment, diversity, spatial pattern, landscape structureJRC.G.3-Agricultur
