Volume XLI-B7
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLI-B7, 517-522, 2016
https://doi.org/10.5194/isprs-archives-XLI-B7-517-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLI-B7, 517-522, 2016
https://doi.org/10.5194/isprs-archives-XLI-B7-517-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.

  21 Jun 2016

21 Jun 2016

OBJECT-ORIENTED CHANGE DETECTION BASED ON MULTI-SCALE APPROACH

Yonghong Jia1, Mingting Zhou1, and Ye Jinshan2 Yonghong Jia et al.
  • 1Institute of Remote Sensing and Information Engineering, Wuhan University, Wuhan 430079, China
  • 2Institute of Remote Sensing and Digital Earth,Beijing 100101, China

Keywords: Optimal scale; multi-scale; CART tree; object-oriented techniques

Abstract. The change detection of remote sensing images means analysing the change information quantitatively and recognizing the change types of the surface coverage data in different time phases. With the appearance of high resolution remote sensing image, object-oriented change detection method arises at this historic moment. In this paper, we research multi-scale approach for high resolution images, which includes multi-scale segmentation, multi-scale feature selection and multi-scale classification. Experimental results show that this method has a stronger advantage than the traditional single-scale method of high resolution remote sensing image change detection.