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

Download statistics - Document (COUNTER):

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: https://doi.org/10.5194/isprsarchives-XXXIX-B4-67-2012

Repository version

To cite the version in the repository, please use this identifier: https://doi.org/10.15488/1097

Selected time period:

year: 
month: 

Sum total of downloads: 108




Thumbnail
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.
License of this version: CC BY 3.0
Document Type: article
Publishing status: publishedVersion
Issue Date: 2012
Appears in Collections:Fakultät für Elektrotechnik und Informatik

distribution of downloads over the selected time period:

downloads by country:

pos. country downloads
total perc.
1 image of flag of Germany Germany 99 91.67%
2 image of flag of Brazil Brazil 4 3.70%
3 image of flag of United States United States 1 0.93%
4 image of flag of Korea, Republic of Korea, Republic of 1 0.93%
5 image of flag of Estonia Estonia 1 0.93%
6 image of flag of China China 1 0.93%
7 image of flag of Armenia Armenia 1 0.93%

Further download figures and rankings:


Hinweis

Zur Erhebung der Downloadstatistiken kommen entsprechend dem „COUNTER Code of Practice for e-Resources“ international anerkannte Regeln und Normen zur Anwendung. COUNTER ist eine internationale Non-Profit-Organisation, in der Bibliotheksverbände, Datenbankanbieter und Verlage gemeinsam an Standards zur Erhebung, Speicherung und Verarbeitung von Nutzungsdaten elektronischer Ressourcen arbeiten, welche so Objektivität und Vergleichbarkeit gewährleisten sollen. Es werden hierbei ausschließlich Zugriffe auf die entsprechenden Volltexte ausgewertet, keine Aufrufe der Website an sich.

Search the repository


Browse