ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., III-7, 149-155, 2016
http://www.isprs-ann-photogramm-remote-sens-spatial-inf-sci.net/III-7/149/2016/
doi:10.5194/isprs-annals-III-7-149-2016
 
07 Jun 2016
BUILDING CHANGE DETECTION IN VERY HIGH RESOLUTION SATELLITE STEREO IMAGE TIME SERIES
J. Tian1, R. Qin2, D. Cerra1, and P. Reinartz1 1Dept. Photogrammetry and Image Analysis, Remote Sensing Technology Institute, German Aerospace Center (DLR), Germany
2Dept. Civil, Environmental and Geodetic Engineering, The Ohio State University, USA
Keywords: Building, DSM, Change detection, Satellite, Satellite image time series Abstract. There is an increasing demand for robust methods on urban sprawl monitoring. The steadily increasing number of high resolution and multi-view sensors allows producing datasets with high temporal and spatial resolution; however, less effort has been dedicated to employ very high resolution (VHR) satellite image time series (SITS) to monitor the changes in buildings with higher accuracy. In addition, these VHR data are often acquired from different sensors. The objective of this research is to propose a robust time-series data analysis method for VHR stereo imagery. Firstly, the spatial-temporal information of the stereo imagery and the Digital Surface Models (DSMs) generated from them are combined, and building probability maps (BPM) are calculated for all acquisition dates. In the second step, an object-based change analysis is performed based on the derivative features of the BPM sets. The change consistence between object-level and pixel-level are checked to remove any outlier pixels. Results are assessed on six pairs of VHR satellite images acquired within a time span of 7 years. The evaluation results have proved the efficiency of the proposed method.
Conference paper (PDF, 1070 KB)


Citation: Tian, J., Qin, R., Cerra, D., and Reinartz, P.: BUILDING CHANGE DETECTION IN VERY HIGH RESOLUTION SATELLITE STEREO IMAGE TIME SERIES, ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., III-7, 149-155, doi:10.5194/isprs-annals-III-7-149-2016, 2016.

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