Next Article in Journal
Content-Based High-Resolution Remote Sensing Image Retrieval via Unsupervised Feature Learning and Collaborative Affinity Metric Fusion
Previous Article in Journal
Ocean Wave Parameters Retrieval from Sentinel-1 SAR Imagery
Article Menu
Issue 9 (September) cover image

Export Article

Open AccessArticle
Remote Sens. 2016, 8(9), 708;

Individual Building Extraction from TerraSAR-X Images Based on Ontological Semantic Analysis

School of Electronic Information, Wuhan University, Wuhan 430072, China
Collaborative Innovation Center of Geospatial Technology, Wuhan University, Wuhan 430079, China
Author to whom correspondence should be addressed.
Academic Editors: Nicola Masini, Soe Myint and Prasad S. Thenkabail
Received: 24 April 2016 / Revised: 20 August 2016 / Accepted: 23 August 2016 / Published: 27 August 2016
Full-Text   |   PDF [18843 KB, uploaded 27 August 2016]   |  


Accurate building information plays a crucial role for urban planning, human settlements and environmental management. Synthetic aperture radar (SAR) images, which deliver images with metric resolution, allow for analyzing and extracting detailed information on urban areas. In this paper, we consider the problem of extracting individual buildings from SAR images based on domain ontology. By analyzing a building scattering model with different orientations and structures, the building ontology model is set up to express multiple characteristics of individual buildings. Under this semantic expression framework, an object-based SAR image segmentation method is adopted to provide homogeneous image objects, and three categories of image object features are extracted. Semantic rules are implemented by organizing image object features, and the individual building objects expression based on an ontological semantic description is formed. Finally, the building primitives are used to detect buildings among the available image objects. Experiments on TerraSAR-X images of Foshan city, China, with a spatial resolution of 1.25 m × 1.25 m, have shown the total extraction rates are above 84%. The results indicate the ontological semantic method can exactly extract flat-roof and gable-roof buildings larger than 250 pixels with different orientations. View Full-Text
Keywords: building extraction; ontological semantics; object-based; high resolution SAR image building extraction; ontological semantics; object-based; high resolution SAR image

Graphical abstract

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

Share & Cite This Article

MDPI and ACS Style

Gui, R.; Xu, X.; Dong, H.; Song, C.; Pu, F. Individual Building Extraction from TerraSAR-X Images Based on Ontological Semantic Analysis. Remote Sens. 2016, 8, 708.

Show more citation formats Show less citations formats

Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Related Articles

Article Metrics

Article Access Statistics



[Return to top]
Remote Sens. EISSN 2072-4292 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top