Semi-Automatic System for Land Cover Change Detection Using Bi-Temporal Remote Sensing Images

ZhiYong Lv, WenZhong Shi, XiaoCheng Zhou, Jon Atli Benediktsson

Research output: Contribution to journalArticlepeer-review

19 Citations (Scopus)


Change detection is an increasingly important research topic in remote sensing application. Previous studies achieved land cover change detection (LCCD) using bi-temporal remote sensing images. However, many widely used methods detected change depending on a series of parameters, and determining parameters is time-consuming. Furthermore, numerous methods are data-dependent. Therefore, their degree of automation should be improved significantly. Three techniques, which consist of a semi-automatic change detection system, are proposed for LCCD to overcome the abovementioned drawbacks. The three techniques are as follows: (1) change magnitude image (CMI) noise reduction is based on Gaussian filter (GF), which is coupled with OTSU for reducing CMI noise automatically using an iterative optimization strategy; (2) a method based on histogram curve fitting is suggested to predict the threshold range for parameter determination; and (3) a modified region growing algorithm is built for iteratively constructing the final change detection map. The detection accuracies of the proposed system are investigated through four experiments with different bi-temporal image scenes. Compared with several widely used change detection methods, the proposed system can be applied to detect land cover change with high accuracy and flexibility. This work is an attempt to provide a change detection system that is compatible with remote sensing images with high and median-low spatial resolution
Original languageEnglish
Number of pages1112
JournalRemote Sensing
Issue number11
Publication statusPublished - 31 Oct 2017

Other keywords

  • Remote sensing images
  • Land cover change detection
  • Semi-automatic change detection system
  • Fjarkönnun


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