Understanding information about agricultural land. An evaluation of the extent of data modification in the Land Parcel Identification System for the needs of area-based payments - a case study

摘要

The development the GIS technology and growing access to spatial data encourage greater use of information for various purposes. Users may not be aware that data pertaining to the same fragment of land (in aspect of geometry or description attributes), but acquired from different sources do not always adequately reflect reality. After Poland's accession to the European Union, the EU Member States have undertaken to develop a Land Parcel Identification System (LPIS) as part of the Integrated Administration and Control System in every country. The information aggregated by that system supports the payment of area-based subsidies, monitoring farmers' cross-compliance with selected environmental rules and the implementation of rural development programs. The LPIS was developed by compiling data from various sources, including the Cadastral Register (CR). The LPIS database is continuously modified to account for changes in the use of agricultural land. However, not all users are aware of these changes, and they regard LPIS data as identical to CR data. The above can breed conflict and legal complications. The aim of this study was to evaluate the extent to which the reference data from the CR are modified in the LPIS. The CR was selected for this analysis because it is widely used for various purposes, including urban planning, calculation of taxes and public statistics. Geographic and descriptive data were analyzed, and the relationships between both data bases were determined (more than 12,000 elements were measured). The extent to which primary data were modified was expressed with the use of an indicator describing the percentage change in cadastral data. The study concerned geometry (I-g), described parameters (I-d) and the cumulative index (I-c) of the examined objects. The results of the analysis indicate that the extent of changes in primary data varies across different locations. In more than 50 % of the analyzed objects, the relevant changes (cumulated index - I-C) exceeded 50 %. These observations constitute valuable information for individuals, researchers or institutions who rely on LPIS resources.