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

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Helmholz, P.; Bueschenfeld, T.; Breitkopf, U.; Mueller, S.; Rottensteiner, F.: Multitemporal quality assessment of grassland and cropland objects of a topographic dataset. In: International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences: [XXII ISPRS Congress, Technical Commission I] 39 (2012), Nr. B4, S. 67-72. DOI:

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Sum total of downloads: 138

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 usefulness 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. In 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 32m). 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.
License of this version: CC BY 3.0 Unported
Document Type: article
Publishing status: publishedVersion
Issue Date: 2012
Appears in Collections:Fakultät für Elektrotechnik und Informatik

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pos. country downloads
total perc.
1 image of flag of Germany Germany 111 80.43%
2 image of flag of United States United States 9 6.52%
3 image of flag of Russian Federation Russian Federation 4 2.90%
4 image of flag of Brazil Brazil 4 2.90%
5 image of flag of Korea, Republic of Korea, Republic of 2 1.45%
6 image of flag of India India 2 1.45%
7 image of flag of Saudi Arabia Saudi Arabia 1 0.72%
8 image of flag of Czech Republic Czech Republic 1 0.72%
9 image of flag of China China 1 0.72%
10 image of flag of Armenia Armenia 1 0.72%
    other countries 2 1.45%

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