Spatial indicators for nature conservation from European to local scale

The paper presents an overview of the objectives and exemplary results of the FP 5 project “Spatial Indicators for European Nature Conservation” (SPIN). The SPIN project is focused on the development and testing of advanced classification methods and spatial indicators based on multisensor satellite data and GIS to accomplish monitoring and management tasks in the context of Natura 2000 and nature conservation. A representative selection of eight regional test areas covers a pan-European network and allows comparative investigations to provide accepted recommendations for regional and European nature conservation. The selected results of four case studies are presented and discussed. The range of work covers the production of regional and local habitat maps by object-oriented classification, a case-based reasoning method for change detection as a management support tool for planning and regulating local land use, the selection and application of structural indicators for the monitoring of Natura 2000 habitats and the downscaling and disaggregation of soil information. Results and the further implementation of presented methods are discussed in the conclusions.

[1]  Christel Lingnau,et al.  OBJECT ORIENTED ANALYSIS AND SEMANTIC NETWORK FOR HIGH RESOLUTION IMAGE CLASSIFICATION , 2003 .

[2]  R. O'Neill,et al.  A factor analysis of landscape pattern and structure metrics , 1995, Landscape Ecology.

[3]  R. Haines-Young,et al.  Quantifying landscape structure: a review of landscape indices and their application to forested landscapes , 1996 .

[4]  H. Jenny,et al.  The Soil Resource , 1982, Ecological Studies.

[5]  R. B. Slocum,et al.  Manual of procedures , 1959 .

[6]  Thomas Blaschke Environmental monitoring and management of protected areas through integrated ecological information systems — an EU perspective , 2001 .

[7]  David W. Aha,et al.  The omnipresence of case-based reasoning in science and application , 1998, Knowl. Based Syst..

[8]  Thomas Blaschke,et al.  An Object-based Methodology for Mapping Mires Using High Resolution Imagery , 2003 .

[9]  H. Jenny,et al.  Factors of Soil Formation , 1941 .

[10]  Stefan Dech,et al.  Object-oriented classification of Landsat 7 data for regional planning purposes , 2003 .

[11]  T. Blaschke,et al.  Hierarchical object representation –Comparative multi-scale mapping of anthropogenic and natural features , 2003 .

[12]  Claus Rautenstrauch,et al.  Environmental information systems in industry and public administration , 2001 .

[13]  C. Burnett,et al.  A multi-scale segmentation/object relationship modelling methodology for landscape analysis , 2003 .

[14]  John Gerrard,et al.  Soil geomorphology : an integration of pedology and geomorphology , 1992 .

[15]  Jack Major,et al.  Factors of Soil Formation , 1981 .

[16]  R. A. MacMillan,et al.  A generic procedure for automatically segmenting landforms into landform elements using DEMs, heuristic rules and fuzzy logic , 2000, Fuzzy Sets Syst..

[17]  D. Maktav,et al.  Remote sensing of urban areas , 2005 .

[18]  I. Dav The Omnipresence of Case-based Reasoning in Science and Application 1 Case-based Reasoning , 1998 .

[19]  Monitoring von Verbuschungs- und Verwaldungsstadien im Natura-2000 Gebiet Wenger Moor: objektbasierte Bildanalyse und GIS , 2004 .

[20]  K. Remm Case-based predictions for species and habitat mapping , 2004 .

[21]  Tobias Langanke,et al.  IDEFIX - Integration einer Indikatorendatenbank für landscape metrics in ArcGIS 8.x , 2003 .

[22]  Thomas Blaschke,et al.  A comparison of three image-object methods for the multiscale analysis of landscape structure , 2003 .

[23]  Jasper Becker,et al.  Joint Research Centre , 1982, Nature.

[24]  K. McGarigal,et al.  FRAGSTATS: spatial pattern analysis program for quantifying landscape structure. , 1995 .