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

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.

[1]  W. Cohen,et al.  An improved strategy for regression of biophysical variables and Landsat ETM+ data. , 2003 .

[2]  Yong Zha,et al.  A landscape approach to quantifying land cover changes in Yulin, Northwest China , 2008, Environmental monitoring and assessment.

[3]  Wu Wen-bo.  Retrieval and analysis of vegetation cover in the Three-North Regions of China based on MODIS data , 2009 .

[4]  B. Markham,et al.  Summary of Current Radiometric Calibration Coefficients for Landsat MSS, TM, ETM+, and EO-1 ALI Sensors , 2009 .

[5]  H. Mooney,et al.  Human Domination of Earth’s Ecosystems , 1997, Renewable Energy.

[6]  B. E. L Aw,et al.  Disturbance and climate effects on carbon stocks and fluxes across Western Oregon USA , 2004 .

[7]  Chengquan Huang,et al.  Global characterization and monitoring of forest cover using Landsat data: opportunities and challenges , 2012, Int. J. Digit. Earth.

[8]  P. Caccetta,et al.  Continental Monitoring : 34 Years of Land Cover Change Using Landsat Imagery , 2007 .

[9]  J. J. Zhu,et al.  Environmental impacts of the shelter forests in Horqin Sandy land, northeast China. , 2011, Journal of environmental quality.

[10]  Darrel L. Williams,et al.  Landsat and Earth Systems Science : Development of terrestrial monitoring , 1997 .

[11]  S. Goward,et al.  An automated approach for reconstructing recent forest disturbance history using dense Landsat time series stacks , 2010 .

[12]  A. Savitzky,et al.  Smoothing and Differentiation of Data by Simplified Least Squares Procedures. , 1964 .

[13]  D. Schimel,et al.  CONTINENTAL SCALE VARIABILITY IN ECOSYSTEM PROCESSES: MODELS, DATA, AND THE ROLE OF DISTURBANCE , 1997 .

[14]  Jiali Xie,et al.  Assessing vegetation dynamics in the Three-North Shelter Forest region of China using AVHRR NDVI data , 2011 .

[15]  Eric A. Lehmann,et al.  Forest cover trends from time series Landsat data for the Australian continent , 2013, Int. J. Appl. Earth Obs. Geoinformation.

[16]  Zhibao Dong,et al.  Has the Three Norths Forest Shelterbelt Program solved the desertification and dust storm problems in arid and semiarid China , 2010 .

[17]  Frédéric Achard,et al.  Global Forest Monitoring from Earth Observation , 2012 .

[18]  Liangyun Liu,et al.  Analysis of the changes of vegetation coverage of western Beijing mountainous areas using remote sensing and GIS , 2009, Environmental monitoring and assessment.

[19]  Volker C. Radeloff,et al.  Using Landsat imagery to map forest change in southwest China in response to the national logging ban and ecotourism development , 2012 .

[20]  P. Teillet,et al.  On the Slope-Aspect Correction of Multispectral Scanner Data , 1982 .

[21]  C. Justice,et al.  Atmospheric correction of MODIS data in the visible to middle infrared: first results , 2002 .

[22]  Neal A. Scott,et al.  The net carbon flux due to deforestation and forest re‐growth in the Brazilian Amazon: analysis using a process‐based model , 2004 .

[23]  F. Chapin,et al.  Consequences of changing biodiversity , 2000, Nature.

[24]  Peter E. Thornton,et al.  Modeling and measuring the effects of disturbance history and climate on carbon and water budgets in evergreen needleleaf forests , 2002 .

[25]  Darrel L. Williams,et al.  Landsat: Yesterday, Today, and Tomorrow , 2006 .

[26]  Scott L. Powell,et al.  Forest Disturbance and North American Carbon Flux , 2008 .

[27]  S. Goward,et al.  Dynamics of national forests assessed using the Landsat record: Case studies in eastern United States , 2009 .

[28]  Chengquan Huang,et al.  Assessing rates of forest change and fragmentation in Alabama, USA, using the vegetation change tracker model , 2009 .

[29]  S. VAN TUY,et al.  Disturbance and climate effects on carbon stocks and fluxes across Western Oregon USA , 2004 .

[30]  Chengquan Huang,et al.  Use of remote sensing coupled with a vegetation change tracker model to assess rates of forest change and fragmentation in Mississippi, USA , 2009 .

[31]  Chengquan Huang,et al.  Development of time series stacks of Landsat images for reconstructing forest disturbance history , 2009, Int. J. Digit. Earth.

[32]  S. Carpenter,et al.  Global Consequences of Land Use , 2005, Science.

[33]  I. Gibson.  Statistics and Data Analysis in Geology , 1976, Mineralogical Magazine.

[34]  Martha C. Anderson,et al.  Free Access to Landsat Imagery , 2008, Science.

[35]  C. Woodcock,et al.  Continuous monitoring of forest disturbance using all available Landsat imagery , 2012 .

[36]  Richard H. Waring,et al.  Forest Ecosystems: Analysis at Multiple Scales , 1985 .