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Published in:
2014 | OriginalPaper | Chapter
16. Digital Land Cover Model for Germany – DLM-DE
Authors : Michael Hovenbitzer, Friederike Emig, Christine Wende, Stephan Arnold, Michael Bock, Stefan Feigenspan
Published in: Land Use and Land Cover Mapping in Europe
Publisher: Springer Netherlands
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Abstract
National land monitoring activities are moving towards a harmonized integration of national datasets with pan-European LC/LU initiatives. A growing number of European countries derive their contributions to pan-European land cover and land use datasets following the principles of a bottom-up approach. In the case of Germany this concept is put into practice by using the topographic reference data of the Federal Stateś land surveying authorities (ATKIS ® Basis-DLM) as the main input to create a homogeneous LC/LU dataset for the entire country, supported by remote sensing methods. For the reason of temporal consistency the reference year of DLM-DE production has been synchronized with the Corine Land cover (CLC) phase 2012.
DLM-DE is a cooperative project between the Federal Environment Agency (UBA) in the role of the National Reference Center for land cover (NRC) and the Federal Agency for Cartography and Geodesy (BKG) as the data producer. A key criterion in the DLM-DE update procedure is the separated mapping of land cover and land use information. Through a semantic transformation the ATKIS feature types are translated to a preliminary coding of land cover and land use. This intermediate classification distinction between land cover and land use is assigned to the polygon features of Basis-DLM as LC and LU codes. During the update process these codes are verified or changed through semi-automated analysis and interpretation of multi-temporal satellite imagery, which is used as the main source of information.
The result of the DLM-DE is a high resolution vector data set describing LC and LU with a minimum mapping unit of 1 ha. The intermediate description is applied in a bidirectional way. On the one hand, it serves for deriving CLC classes by combining the encoded LC and LU information. On the other hand, it is also flexible enough to partly transform the updating results back to the original vector data source of Basis-DLM. On the long-term run the aim is to promote further applications of DLM-DE in the field of land monitoring and beyond.