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    Multitemporal quality assessment of grassland and cropland objects of a topographic dataset

    Access Status
    Fulltext not available
    Authors
    Helmholz, Petra
    Büschenfeld, T.
    Breitkopf, U.
    Müller, S.
    Rottensteiner, F.
    Date
    2012
    Type
    Conference Paper
    
    Metadata
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    Citation
    Helmholz, P. and Büschenfeld, T. and Breitkopf, U. and Müller, S. and Rottensteiner, F. 2012. Multitemporal quality assessment of grassland and cropland objects of a topographic dataset, in XXII ISPRS Congress, Aug 25 – Sep 01 2012, pp. 67-72. Melbourne, Australia: International Society for Photogrammetry and Remote Sensing.
    Source Title
    International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives
    ISSN
    1682-1750
    School
    Department of Spatial Sciences
    URI
    http://hdl.handle.net/20.500.11937/13588
    Collection
    • Curtin Research Publications
    Abstract

    As a consequence of the wide-spread application of digital geo-data in geographic information systems (GIS), quality control has become increasingly important to enhance the useful ness of the data. For economic reasons a high degree of automation is required for the quality control process. This goal can be achieved by automatic image analysis techniques. An example of how this can be achieved in the context of quality assessment of cropland and grassland GIS objects is given in this paper. The quality assessment of these objects of a topographic dataset is carried out based on multi-temporal information. The multi-temporal approach combines the channels of all available images as a multilayer image and applies a pixel-based SVM-classification. I n this way multispectral as well as multi-temporal information is processed in parallel. The features used for the classification consist of spectral, textural (Haralick features) and structural (features derived from a semi-variogram) features. After the SVM-classification, the pixel-based result is mapped to the GIS-objects. Finally, a simple ruled- based approach is used in order to verify the objects of a GIS database. The approach was tested using a multi-temporal data set consisting of one 5-channel RapidEye image (GSD 5m) and two 3-channel Disaster Monitoring Constellation (DMC) images (GSD 3 2m). All images were taken within one year. The results show that by using our approach, quality control of GIS- cropland and grassland objects is possible and the human operator saves time using our approach compared to a completely manual quality assessment.

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