Environmental Monitoring and Assessment

, Volume 185, Issue 12, pp 9949–9965 | Cite as

Mapping afforestation and deforestation from 1974 to 2012 using Landsat time-series stacks in Yulin District, a key region of the Three-North Shelter region, China

  • Liangyun Liu
  • Huan Tang
  • Peter Caccetta
  • Eric A. Lehmann
  • Yong Hu
  • Xiaoliang Wu


The Three-North Shelter Forest Program is the largest afforestation reconstruction project in the world. Remote sensing is a crucial tool to map land use and land cover change, but it is still challenging to accurately quantify the change in forest extent from time-series satellite images. In this paper, 30 Landsat MSS/TM/ETM+ epochs from 1974 to 2012 were collected, and the high-quality ground surface reflectance (GSR) time-series images were processed by integrating the 6S atmosphere transfer model and a relative reflectance normalization algorithm. Subsequently, we developed a vegetation change tracking method to reconstruct the forest change history (afforestation and deforestation) from the time-series Landsat GSR images based on the integrated forest z-score (IFZ) model by Huang et al. (2009a), which was improved by multi-phenological IFZ models and the smoothing processing of IFZ data for afforestation mapping. The mapping result showed a large increase in the extent of forest, from 380,394 ha (14.8 % of total district area) in 1974 to 1,128,380 ha (43.9 %) in 2010. Finally, the land cover and forest change map was validated with an overall accuracy of 89.1 % and a kappa coefficient of 0.858. The forest change time was also successfully retrieved, with 22.2 % and 86.5 % of the change pixels attributed to the correct epoch and within three epochs, respectively. The results confirmed a great achievement of the ecological revegetation projects in Yulin district over the last 40 years and also illustrated the potential of the time-series of Landsat images for detecting forest changes and estimating tree age for the artificial forest in a semi-arid zone strongly influenced by human activities.


Remote sensing Three-North Shelter Forest Program Forest change Time-series Afforestation Deforestation 



The authors gratefully acknowledge financial support provided for this research by the External Cooperation Program of the Chinese Academy of Sciences (GJH21123) and the National Natural Science Foundation of China (41222008, 91125003).


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Copyright information

© Springer Science+Business Media Dordrecht 2013

Authors and Affiliations

  • Liangyun Liu
    • 1
  • Huan Tang
    • 1
  • Peter Caccetta
    • 2
  • Eric A. Lehmann
    • 2
  • Yong Hu
    • 1
  • Xiaoliang Wu
    • 2
  1. 1.Key Laboratory of Digital Earth Science, Institute of Remote Sensing and Digital EarthChinese Academy of SciencesBeijingChina
  2. 2.Commonwealth Scientific and Industrial Research Organisation (CSIRO)Division of Mathematics, Informatics and Statistics (CMIS)WembleyAustralia

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