Applying tegon, the elementary physical land cover feature, for data interoperability

Most land cover mapping initiatives have been biased towards optimized data capture and cartographic quality. Interoperability of the resulting data has proven difficult due to the semantic ambiguity embedded in the classification and methodology of each initiative, which often does not correctly reflect and account for the complexity and specificity of the landscape under observation. This chapter describes how the tegon concept can model land cover as a real world phenomenon. Tegons are instances of the elementary physical components behind any existing mapping unit or legend class, expressed in the Land Cover Meta Language, specified in ISO 19144-2. Two large scale examples from an agricultural context show how the concept has been used for demarcating the land cover universe of discourse and for harmonization efforts. The tegon concept was developed by the Monitoring of Agriculture ResourceS (MARS) Unit of the Joint Research Centre of the European Commission and first applied during 2010 quality assessment of the Land Parcel Identification Systems (LPIS). This exercise required a full description of the European agriculture land cover types of all Member States (MS), based on the FAO Land Cover Classification System (LCCS). Later, its application has been expanded towards cross-border land monitoring initiatives, such as the project SPATIAL involving Bulgaria and Romania, where the tegon concept became the key methodological instrument for the land cover inventory and spatial data harmonization to cover the entire cross-border area representing a major part of Lower Danube Basin. Both application experiences demonstrate the high potential of the concept, in particular for addressing complex land cover phenomena and for insuring interoperability between existing classifications and their data sets. This potential is most evident at large scale data. Automation of the tegon modeling will be required to verify the claim of exhaustiveness and universality at these scales. Application of tegon conceptualization during the inception of new classifications or data sets should introduce the correct semantics in those initiatives. However, as tegon modeling in itself does not address the limitations of current data capture methodologies, impact for ongoing inventories will be limited to improving semantic interoperability.

JRC.H.4 - Monitoring Agricultural Resources