Significance Analysis of Multi-temporal RapidEye Satellite Images in a Land-cover Classification

Michael Forster, Christian Schuster and Birgit Kleinschmit
Department of Geo information Processing for Landscape and Environmental Planning,Technische Universitaet Berlin,Berlin, Germany
{michael.foerster, christian.schuster, birgit.kleinschmit}@tu-berlin.de

Abstract: Multi-temporal satellite information can supply valuable information about changing patterns of land-cover, especially for vegetation species. As a contribution to evaluate the additional information content of intra-annual high spatial resolution satellite images the presented study assesses the significance of the classification accuracy for the identification of land-cover data. An Microarray Significance Analysis (MSA) was used to evaluate a sequence of nearest neighbor classifications (with training areas from field spectral measurements and existing geo-data) using image combinations of different dates and spectral bands for the utilized land cover classes. The resulting microarray of accuracy percentages of single classes and the overall classification was used for the subsequent MSA. The results from the MSA showed a higher significance when more images were included in the classification process. Especially the scene from September 2009 indicated a positive significance within the land-cover classification.

Keywords: Microarray Significance Analysis; RapidEye; object- based image analysis

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