ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
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Articles | Volume IV-2/W5
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., IV-2/W5, 239–243, 2019
https://doi.org/10.5194/isprs-annals-IV-2-W5-239-2019
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., IV-2/W5, 239–243, 2019
https://doi.org/10.5194/isprs-annals-IV-2-W5-239-2019

  29 May 2019

29 May 2019

A LAND COVER CHANGE DETECTION METHOD BASED ON CHANGE DIFFERENCE MAP FUSION

H. Xing1, D. Hou2, M. Lu3, and J. Chen1 H. Xing et al.
  • 1School of Surveying and Geo-informatics, Shandong Jianzhu University, Jinan, China
  • 2School of Geosciences and Info Physics, Central South University, Changsha, China
  • 3Key Laboratory of Agri-informatics, Ministry of Agriculture/Institute of Agricultural Resources and Regional Planning, Chinese Academy of Agricultural Sciences, Beijing, China

Keywords: Change Detection, Remote Sensing Image, Change Difference Map Fusion, Expectation Maximization

Abstract. Direct radiometric comparison-based change detection methods have been widely used for detecting land cover change areas. However, the traditional methods are usually developed by using a single change index, which may cause omission or commission of land cover change. To address this challenge, we propose a change difference map fusion-based land cover change detection approach. First, operators of change vector analysis (CVA) and spectral gradient difference (SGD) are used for constructing change difference map, respectively. Second, image product weighted fusion method is introduced to construct a comprehensive change difference map. Finally, the expectation maximization algorithm and Bayesian rule with minimum error rate are applied to get the change/unchanged area. Experimental results of Landsat5 TM in 2010 and Landsat8 OLI in 2015 in two test areas are conducted. The experimental results show that accuracy of the proposed method is superior to the traditional change detection methods.