Details
| Original language | English |
|---|---|
| Pages (from-to) | 67-72 |
| Number of pages | 6 |
| Journal | International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives |
| Volume | 39 |
| Publication status | Published - 27 Jul 2012 |
| Event | 22nd Congress of the International Society for Photogrammetry and Remote Sensing, ISPRS 2012 - Melbourne, Australia Duration: 25 Aug 2012 → 1 Sept 2012 |
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 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.
Keywords
- Automation, Classification, Crop, GIS, Inspection, Multitemporal, Quality, Updating
ASJC Scopus subject areas
- Computer Science(all)
- Information Systems
- Social Sciences(all)
- Geography, Planning and Development
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In: International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives, Vol. 39, 27.07.2012, p. 67-72.
Research output: Contribution to journal › Conference article › Research › peer review
}
TY - JOUR
T1 - Multitemporal quality assessment of grassland and cropland objects of a topographic dataset
AU - Helmholz, P.
AU - Büschenfeld, T.
AU - Breitkopf, U.
AU - Müller, S.
AU - Rottensteiner, F.
PY - 2012/7/27
Y1 - 2012/7/27
N2 - 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.
AB - 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.
KW - Automation
KW - Classification
KW - Crop
KW - GIS
KW - Inspection
KW - Multitemporal
KW - Quality
KW - Updating
UR - http://www.scopus.com/inward/record.url?scp=84924292273&partnerID=8YFLogxK
U2 - 10.5194/isprsarchives-XXXIX-B4-67-2012
DO - 10.5194/isprsarchives-XXXIX-B4-67-2012
M3 - Conference article
AN - SCOPUS:84924292273
VL - 39
SP - 67
EP - 72
JO - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives
JF - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives
SN - 1682-1750
T2 - 22nd Congress of the International Society for Photogrammetry and Remote Sensing, ISPRS 2012
Y2 - 25 August 2012 through 1 September 2012
ER -