Local spectrum-trend similarity approach for detecting land-cover change by using SPOT-5 satellite images

Penglin Zhang, Zhiyong Lv, Wen Zhong Shi

Research output: Journal article publicationJournal articleAcademic researchpeer-review

33 Citations (Scopus)


Spectra-based change detection (CD) methods, such as image difference method and change vector analysis, have been widely used for land-cover CD using remote sensing data. However, the spectra-based approach suffers from a strict requirement of radiometric consistency in the multitemporal images. This letter proposes a new image feature named spectrum trend, which is explored from the spectral values of the image in a local geographic area (e.g., a 3 × 3 sliding window) through raster encoding and curve fitting techniques. The piecewise similarity between the paired local areas in the multitemporal images is calculated by using a sliding window centered at the pixel to generate the change magnitude image. Finally, CD is achieved by a threshold decision or a classified method. This proposed approach, called "local spectrum-trend similarity," is applied and validated by a case study of land-cover CD in Wuqin District, Tianjin City, China, by using SPOT-5 satellite images. Accuracies of "change" versus "no-change" detection are assessed. Experimental results confirm the feasibility and adaptability of the proposed approach in land-cover CD.
Original languageEnglish
Article number6605510
Pages (from-to)738-742
Number of pages5
JournalIEEE Geoscience and Remote Sensing Letters
Issue number4
Publication statusPublished - 1 Apr 2014


  • Change detection (CD)
  • land cover
  • local spectrum-trend similarity (LSTS)
  • remote sensing image

ASJC Scopus subject areas

  • Geotechnical Engineering and Engineering Geology
  • Electrical and Electronic Engineering


Dive into the research topics of 'Local spectrum-trend similarity approach for detecting land-cover change by using SPOT-5 satellite images'. Together they form a unique fingerprint.

Cite this