Share Email Print
cover

Proceedings Paper

Object-based urban change detection analyzing high resolution optical satellite images
Author(s): Markus Boldt; Antje Thiele; Karsten Schulz
Format Member Price Non-Member Price
PDF $14.40 $18.00

Paper Abstract

Change detection in urban areas by investigating image data of remote sensing satellites is an important topic. Of special interest is, for example, the detection of changes in terms of monitoring and disaster management, where accurate information about dimension and category of changes are frequently requested. Hence, in this paper, a workflow for object-oriented multispectral classification is presented to differentiate between traffic infrastructure, water, vegetation and non-vegetation areas. Changes are detected by analyzing multi-temporal classification results. For this, multitemporal QuickBird images covering the city Karlsruhe and LiDAR data are investigated to detect urban change areas.

Paper Details

Date Published: 25 October 2012
PDF: 9 pages
Proc. SPIE 8538, Earth Resources and Environmental Remote Sensing/GIS Applications III, 85380E (25 October 2012); doi: 10.1117/12.973687
Show Author Affiliations
Markus Boldt, Fraunhofer-Institut für Optronik, Systemtechnik und Bildauswertung (Germany)
Antje Thiele, Fraunhofer-Institut für Optronik, Systemtechnik und Bildauswertung (Germany)
Karlsruher Institut für Technologie (Germany)
Karsten Schulz, Fraunhofer-Institut für Optronik, Systemtechnik und Bildauswertung (Germany)


Published in SPIE Proceedings Vol. 8538:
Earth Resources and Environmental Remote Sensing/GIS Applications III
Shahid Habib; David Messinger; Antonino Maltese; Ulrich Michel; Daniel L. Civco; Manfred Ehlers; Karsten Schulz; Konstantinos G. Nikolakopoulos, Editor(s)

© SPIE. Terms of Use
Back to Top