DLR-Logo -> http://www.dlr.de
DLR Portal Home | Imprint | Privacy Policy | Contact | Deutsch
Fontsize: [-] Text [+]

Detection of building structures from single polarized TerraSAR-X data

Schmidt, Martin and Esch, Thomas and Thiel, Michael and Dech, Stefan (2011) Detection of building structures from single polarized TerraSAR-X data. In: Proceedings of SPIE. SPIE 2011, 19.-22. Sep. 2011, Prag, Teschechische Republik.

Full text not available from this repository.


This study aims at an area-wide detection of the building structure of settlements from individual, single-polarized TerraSAR-X (TSX) intensity datasets recorded in stripmap mode. Due to SAR side-looking acquisition, the building-related information is located in areas which do spatially not exactly correspond with the true location of the buildings. To perform a supervised classification approach we at first create a mask of areas which are affected by scattering from the buildings based on reference datasets of the building footprints with their respective height by considering the viewing geometry of the TSX data. The generated mask is used in the following to randomly extract training samples in order to determine the relationships between the SAR data and the class membership. For the classification of the areas carrying the building-related information we utilize a random forest algorithm. As input features for classification we compare the suitability of the Grey Level Co-occurrence Matrix based textures measures according to Haralick, Mathematical Morphology and Spatial Autocorrelation texture measures. These features are calculated from TSX data using a pixel-based multiple-scale moving window approach. For each texture feature set and each moving window width the relationship to the class membership is modeled on the basis of the extracted training samples. The different models are used in the following to perform different classification runs of the entire TSX dataset. With the described approach we achieve overall classification accuracies of up to 78 %. The influence of the simultaneous usage of input texture features calculated with different window widths on the classification accuracy is of the same magnitude as the influence of the usage of the different texture feature sets.

Item URL in elib:https://elib.dlr.de/74214/
Document Type:Conference or Workshop Item (Speech, Paper)
Title:Detection of building structures from single polarized TerraSAR-X data
AuthorsInstitution or Email of AuthorsAuthor's ORCID iD
Schmidt, Martinmartin.schmidt (at) dlr.deUNSPECIFIED
Esch, Thomasthomas.esch (at) dlr.deUNSPECIFIED
Thiel, Michaelmichael.thiel (at) uni-wuerzburg.deUNSPECIFIED
Dech, Stefanstefan.dech (at) dlr.deUNSPECIFIED
Journal or Publication Title:Proceedings of SPIE
Refereed publication:No
Open Access:No
Gold Open Access:No
In ISI Web of Science:No
Keywords:High Resolution SAR, TerraSAR-X, building detection, random forest, Spatial Autocorrelation, GLCM, Mathematical Morphology
Event Title:SPIE 2011
Event Location:Prag, Teschechische Republik
Event Type:international Conference
Event Dates:19.-22. Sep. 2011
HGF - Research field:Aeronautics, Space and Transport
HGF - Program:Space
HGF - Program Themes:Earth Observation
DLR - Research area:Raumfahrt
DLR - Program:R EO - Earth Observation
DLR - Research theme (Project):R - Geoscientific remote sensing and GIS methods
Location: Oberpfaffenhofen
Institutes and Institutions:German Remote Sensing Data Center
Deposited By: Schmidt, Martin
Deposited On:24 Jan 2012 13:01
Last Modified:24 Jan 2012 13:01

Repository Staff Only: item control page

Help & Contact
electronic library is running on EPrints 3.3.12
Copyright © 2008-2017 German Aerospace Center (DLR). All rights reserved.