Integrated Administration And Control System Research Articles

Analysing Data of the Integrated Administration and Control System (IACS) to Detect Patterns of Agricultural Land-Use Change at Municipality Level

European landscapes have featured considerable changes towards intensification and marginalisation. These major trends are expected to continue in the future. Besides, the cultivation of bioenergy crops has become an important factor in agricultural land use. A thorough understanding of land-use processes for management purposes is needed. In this study, the spatial and temporal pattern of agricultural land use and land-use change was classified at the scale of municipalities from 2005 to 2010. The study region was the German federal state Hesse. By using data of the Integrated Administration and Control System (IACS) of the European Union and with the help of k-means cluster analysis, five types of agricultural land-use patterns and dynamics (TLPDs) were detected. These TLPDs represent different sub-regions. Sub-regions with favourable physical conditions for cultivation are dominated by arable land. A progressive land-use change occurred by conversion of grassland to arable land. In sub-regions, where physical conditions are rather unfavourable, especially in mountainous areas, grassland is the predominant land use. But on the remaining arable land, there is a slight change in favour of maize. The knowledge of sub-regions with spatially and temporally different agricultural land use could be utilised to develop land management instruments like site-specific agri-environmental schemes.

The dynamic effects of government-supported farm-investment activities on structural change in Austrian agriculture

The objective of our paper is to analyse the effects of government-supported farm-investment activities on structural change in agriculture. Our method comprises combining direct covariate matching with a difference-in-difference (DiD) estimator. In order to capture the dynamics and the heterogeneity of structural effects, we have developed time and farm-group specific models. We apply our model in Austria, where we analyse the Integrated Administration and Control System (IACS) data of 98,000 farms within the time period of 2000–2011. Our results show that farms adapt their numbers of livestock very quickly, whereas, the increase in agricultural area seems to be fairly decoupled from the investment activity itself. Effects tend to be farm-group specific; e.g. farm size initially increases (and drops) on pig farms to a greater extent than on cattle farms. Furthermore, government-supported farm-investment activities not only influence structural change but also tend to increase production intensity and reduce diversification on arable land – perhaps counteracting, therefore, the goals of agri-environmental schemes. However, our results indicate that investing (cattle) farmers are more likely to enter the organic farming programme and tend rather to remain in animal husbandry.

Estimation of olive oil production based on the use of administrative data

Italy is one of the most relevant countries in the European Union as regards crops and, in particular, olive oil production. Actually, statistical data on olive oil are provided by the 20 Italian Regions to ISTAT through estimates supplied by experts and / or local panels of influent farmers and category associations. However, more precise estimates may be derived from the administrative data collected by AGEA, which is the Italian acronym for Integrated Administration and Control System (IACS). IACS is in charge of receiving from farmers declarations of production, on the basis of which they receive subsidies. The main goals of the work are the following ones: 1) to transform the administrative IACS database into a statistical one; 2) to compare different methodologies for producing monthly estimates of olive oil productions in presence of missing declarations; 3) to aggregate the IACS yearly olive oil production, comparing these estimates with those supplied by experts estimates. The paper analyses the main outcomes concerning the Region Apulia (South Italy), where the 40.1% of Italian olive oil is produced.

Possible influence factors of technical tolerance

Legitimate users of agricultural areas can receive land-based payments based on the area of either the cultivated plants or the uncultivated land kept, in line with the provisions of community and national legislation, in condition eligible for support. Furthermore, land-based support can be received via other rural development measures as well.According to European Commission regulation the appropriate and eligible claim of the land-based supports shall be controlled by the member states. The most robust technique of this process is the remote sensing control. The observed discrepancies shall be sanctioned based on their extent and intentional nature. A measurement tolerance interval shall be set in case of remote sensing operations so that the extent of discrepancy is to be determined in the most objective way possible. As far as the measurement tolerance interval is concerned the goal is to minimise the cumulative faults appearing during the measurements (such as the scale of agricultural activities, the inaccuracy of farmers’ drawings necessary for the claiming of support and the inaccuracy of control materials and methods).The establishment of the measurement tolerance interval is based on the fact that the reference parcels selected by the validation protocol are made by several operators in iterations. As a result of this process the following conclusions can be drawn:The validation method of multi-level tests required by the Joint Research Centre (JRC) properly detects the measurement results strongly affected by faults. Although this method is to be used exclusively to determine the technical tolerance in the Control with Remote Sensing (CwRS) process of the Integrated Administration and Control System (IACS), as independent validation process it does not take the further imagery and other vector references into account. In our examination we assessed the possible inclusion of the smallest identification unit of the Land Parcel Identification System (LPIS) – i.e. the physical block – as well as its impact on the value of technical tolerance.

Cross compliance and the protection of grassland – Illustrative analyses of land use transitions between permanent grassland and arable land in German regions

Permanent grassland combines various ecological functions in terms of nature, soil, water and climate protection. Conversion of grassland to arable land is accompanied by a diminution of these functions. Various developments have led to increased pressure on the EU grassland area. With cross compliance, the EU sets minimum standards for the protection of the ratio of permanent grassland. However, this requirement alone does not ensure the preservation of grassland on sensitive sites, such as water or nature conservation areas or land on organic soils or on steep hills. This paper deals with land use changes between grassland and arable land. For this purpose we analyse data of the EU's Integrated Administration and Control System (IACS) from four German federal states. The described methodology allows to identify gross changes of land use and to distinguish between conversion of permanent grassland and “loss” due to “deactivation” at a highly disaggregated level. Merging IACS-data with further spatially explicit data provides a picture of land use transitions in ecologically sensitive areas and enables conclusions to be drawn about the effectiveness of protection measures.

Data model for the collaboration between land administration systems and agricultural land parcel identification systems

The Common Agricultural Policy (CAP) of the European Union (EU) has dramatically changed after 1992, and from then on the CAP focused on the management of direct income subsidies instead of production-based subsidies. For this focus, Member States (MS) are expected to establish Integrated Administration and Control System (IACS), including a Land Parcel Identification System (LPIS) as the spatial part of IACS. Different MS have chosen different solutions for their LPIS. Currently, some MS based their IACS/LPIS on data from their Land Administration Systems (LAS), and many others use purpose built special systems for their IACS/LPIS. The issue with these different IACS/LPIS is that they do not have standardized structures; rather, each represents a unique design in each MS, both in the case of LAS based or special systems. In this study, we aim at designing a core data model for those IACS/LPIS based on LAS. For this purpose, we make use of the ongoing standardization initiatives for LAS (Land Administration Domain Model: LADM) and IACS/LPIS (LPIS Core Model: LCM). The data model we propose in this study implies the collaboration between LADM and LCM and includes some extensions. Some basic issues with the collaboration model are discussed within this study: registration of farmers, land use rights and farming limitations, geometry/topology, temporal data management etc. For further explanation of the model structure, sample instance level diagrams illustrating some typical situations are also included.

Integration of bio-physical and economic models to analyze management intensity and landscape structure effects at farm and landscape level

We present an integrated spatially explicit land use modeling framework, which integrates two key components of agricultural systems, the bio-physical production system and the management system, by coupling the bio-economic farm optimization model FAMOS[space], the crop rotation model CropRota, and the bio-physical process model EPIC (Environmental Policy Integrated Climate). The integrated modeling framework has been developed to analyze the cost-effectiveness of selected agri-environmental program (AEP) measures. We also focus on the landscape development and therefore include a detailed representation of landscape elements such as fields or orchard meadows in our analysis. An indicator set represents all main environmental AEP objectives, i.e. preservation of water and soil resources, mitigation of climate change, protection of biodiversity, maintenance of cultural landscapes as well as farm income support. The integrated modeling framework is applied to 20 farms in the Austrian ‘Mostviertel’ region, which are selected from the Integrated Administration and Control System (IACS) of the European Union. The cost-effectiveness of AEP measures is assessed under different premium levels. The implementation of the AEP clearly affects environmental quality in a positive way. Nitrogen rates are reduced, landscape elements can be sustained, and the landscape becomes more diverse. The program also increases farm gross margins on average. However, the cost-effectiveness ratios (CER) are declining with increasing premium levels. The results indicate that the cost-effectiveness of AEP measures can be improved by spatial targeting.

Rule-based classification of multi-temporal satellite imagery for habitat and agricultural land cover mapping

Aim To evaluate the use of time-series of Landsat sensor data acquired over an annual cycle for mapping semi-natural habitats and agricultural land cover. Location Berwyn Mountains, North Wales, United Kingdom. Methods Using eCognition Expert, segmentation of the Landsat sensor data was undertaken for actively managed agricultural land based on Integrated Administration and Control System (IACS) land parcel boundaries, whilst a per-pixel level segmentation was undertaken for all remaining areas. Numerical decision rules based on fuzzy logic that coupled knowledge of ecology and the information content of single and multi-date remotely sensed data and derived products (e.g., vegetation indices) were developed to discriminate vegetation types based primarily on inferred differences in phenology, structure, wetness and productivity. Results The rule-based classification gave a good representation of the distribution of habitats and agricultural land. The more extensive, contiguous and homogeneous habitats could be mapped with accuracies exceeding 80%, although accuracies were lower for more complex environments (e.g., upland mosaics) or those with broad definition (e.g., semi-improved grasslands). Main conclusions The application of a rule-based classification to temporal imagery acquired over selected periods within an annual cycle provides a viable approach for mapping and monitoring of habitats and agricultural land in the United Kingdom that could be employed operationally.

An approach to optimise the establishment of grassy headlands in the Belgian Walloon region: A tool for agri-environmental schemes

Farming in Europe is constantly changing as environmental concerns have increasingly been taken into account since the mid 1980s and emphasis has been put on agri-environmental matters throughout all European countries. For instance, in Wallonia (Belgium), as a result of the provisions of the Government Decree on agri-environmental measures, farmers are increasingly encouraged to adopt environmentally friendly practices such as the creation of grassy headlands in their fields. As European agriculture is changing, tools are needed to monitor the evolution of agricultural practices, to control policy application and to advise farmers. In this framework, we present a new approach to optimise the establishment of grassy headlands in cultivated fields. Using a Geographic Information System (GIS), we identify exact locations where farmers can introduce grassy headlands in accordance with legal specifications and environmental concerns and calculate the total length of grassy headland that farmers can establish considering the features of their farm and parcels and for which they can receive subsidies. It indicates a potential, which could serve as a calculation baseline for an indicator. Wallonia was chosen as study area because a digitised parcel plan has been available from the Integrated Administration and Control System (IACS) since 1997. The methodological approach proposes a new valorisation of this spatial information layer and can be considered as an example of application providing relevant information for several intervention levels: national or regional decision-makers, advisors and individual farmers. Since all EU Member States had to set up their own GIS-based land parcel system starting in 2005, our approach may be useful as is or in similar applications in other countries.