Mapping plant communities in a local Arctic landscape applying a scanned infrared aerial photograph in a geographical information system

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Abstract
The vegetation of a 5km2 area in front of the Midtre Lovenbreen glacier, Northwest Spitsbergen, Svalbard, was mapped on the scale 1 10000. The main aim of the study was to develop a new method of vegetation classification based on a probability model, and apply the method on a digitized aerial colour infrared (CIR) photograph with a better ground resolution than provided by the Landsat and SPOT satellites. Large-scale data from different sources such as the CIR-aerial photograph, information layers derived from a digital elevation model (DEM) and vegetation sampling in the field have been integrated in a GIS. Probability models build the links between GIS data layers and plant communities resulting from classification of field data. Eight plant communities were defined by means of vegetation data and mapped automatically by classification of the CIR-photograph. Based on the probability model, maps were produced showing the actual and potential distribution of plant communities. The accuracy of the vegetation map was improved by including additional information from the DEM.

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