Science China Earth Sciences

, Volume 53, Issue 11, pp 1689–1699 | Cite as

Accuracy assessment of global historical cropland datasets based on regional reconstructed historical data—A case study in Northeast China

Research Paper


Historical cropland datasets are fundamental for quantifying the effects of human land use activities on climatic change and the carbon cycle. Two representative global land-use datasets, the Global Land Use Database (termed SAGE dataset) and the Historical Database of the Global Environment (termed HYDE dataset) have been established and used widely. Despite improvement of data quality and methodologies for extracting historical land use information, certain dataset limitations exist that need to be quantified and communicated to users so that they can make informed decisions on whether and how these land-use products should be used. The Cropland data of Northeast China (CNEC) is based on calibrated historical data and a multi-sourced data conversion model, and reconstructs cropland cover change in Northeast China over the last 300 years. Using the CNEC as a reference, we evaluated the accuracy of cropland cover for SAGE and HYDE in Northeast China at spatial scales ranging from the entire Northeast China to provinces and even individual raster grid cells. Neither SAGE nor HYDE reflects real historical land reclamation. Cropland areas in SAGE are overestimated by 20.98 times in 1700 to 1.6 times in 1990. Although HYDE is better, there are significant disagreements in cropland area and distribution between HYDE and CNEC, especially in the 18th and 19th centuries. The proportion of total grid cells whose relative error was greater than 100% was 63.55% in 1700 and 53.27% in 1780. Global cropland dataset errors over Northeast China originate mainly from both the reverse calculation method for historical cropland data based on modern spatial patterns, and modern land-use outputs from satellite data.


LUCC dataset accuracy assessment Northeast China 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Vitousek P M, Mooney H A, Lubchenco J, et al. Human domination of the Earth’s ecosystems. Science, 1997, 277: 494–499CrossRefGoogle Scholar
  2. 2.
    Lambin E F, Turner B L, Geist H J, et al. The causes of land-use and land-cover change: Moving beyond the myths. Glob Environ Change, 2001, 11: 261–269CrossRefGoogle Scholar
  3. 3.
    Bolin B, Sukumar R. Global perspective. In: Watson R T, Noble I R, Bolin B, et al., eds. Land Use, Land-use Change, and Forestry. Cambridge: Cambridge University Press, 2000. 25–45Google Scholar
  4. 4.
    Hansen J E, Sato M, Lacis A, et al. Climate forcings in the Industrial era. Proc Natl Acad Sci USA, 1998, 95: 12753–12758CrossRefGoogle Scholar
  5. 5.
    Feddema J, Oleson K, Bonan G, et al. A comparison of a GCM response to historical anthropogenic land cover change and model sensitivity to uncertainty in present-day land cover representations. Climate Dyn, 2005, 25: 581–609CrossRefGoogle Scholar
  6. 6.
    IPCC. Climate Change 2007: The Physical Science Basis. Contribution of Working Group I to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge and New York: Cambridge University Press, 2007. 180–185, 512Google Scholar
  7. 7.
    Houghton R A. Revised estimates of the annual net flux of carbon to the atmosphere from changes in land use and land management 1850–2000. Tellus Ser B-Chem Phys Meteorol, 2003, 55: 378–390CrossRefGoogle Scholar
  8. 8.
    Betts R A, Falloon P D, Goldewijk K K, et al. Biogeophysical effects of land use on climate: Model simulations of radiative forcing and large-scale temperature change. Agric Forest Meteorol, 2007, 142: 216–233CrossRefGoogle Scholar
  9. 9.
    Zhen J Y, Lin S S, He F N. Recent progress in studies on land cover change and its regional climatic effects over China during historical times. Adv Atmos Sci, 2009, 26: 793–802CrossRefGoogle Scholar
  10. 10.
    Ge Q S, Dai J H, He F N, et al. Land use changes and their relations with carbon cycles over the past 300 a in China. Sci China Ser D-Earth Sci, 2008, 51: 871–884CrossRefGoogle Scholar
  11. 11.
    LUCC Scientific Steering Committee. Key findings of LUCC on its research questions. Glob Change Newsl, 2004, 63: 12–14Google Scholar
  12. 12.
    Goldewijk K K, Ramankutty N. Land cover change over the last three centuries due to human activities: The availability of new global data sets. Geo J, 2004, 61: 335–344Google Scholar
  13. 13.
    Ramankutty N, Foley J A. Estimating historical changes in global land cover: Croplands from 1700 to 1992. Glob Biogeochem Cycle, 1999, 13: 997–1027CrossRefGoogle Scholar
  14. 14.
    Goldewijk K K, Drecht G V. HYDE 3: Current and historical population and land cover. In: Bouwman A F, Kram T, Goldewijk K K, eds. Integrated Modelling of Global Environmental Change: An Overview of IMAGE 2.4. Bilthoven: Netherlands Environmental Assessment Agency (MNP), 2006Google Scholar
  15. 15.
    Tian H, Melillo J M, Kicklighterc D W, et al. Regional carbon dynamics in monsoon Asia and its implications for the global carbon cycle. Glob Planet Change, 2003, 37: 201–217Google Scholar
  16. 16.
    Brovkin V, Sitch S, Bloh W V, et al. Role of land cover changes for atmospheric CO2 increase and climate change during the last 150 years. Glob Change Biol, 2004, 10: 1253–1266CrossRefGoogle Scholar
  17. 17.
    Oost K V, Quine T A, Govers G, et al. The impact of agricultural soil erosion on the global carbon cycle. Science, 2007, 318: 626–629CrossRefGoogle Scholar
  18. 18.
    Matthews H D, Weaver A J, Eby M, et al. Radiative forcing of climate by historical land cover change. Geophys Res Lett, 2003, 30: 1055–1059CrossRefGoogle Scholar
  19. 19.
    Wang H, Pitman A J, Zhao M, et al. The impact of land-cover modification on the June meteorology of China since 1700, simulated using a regional climate model. Int J Climatol, 2003, 23: 511–527CrossRefGoogle Scholar
  20. 20.
    Chen X, Lei M, Tang J P. Simulating the effect of changed vegetation on the climate change in Eurasia (in Chinese). Adv Earth Sci, 2006, 21: 1075–1082Google Scholar
  21. 21.
    Li Q P, Ding Y H, Dong W J. A numerical simulation study of impacts of historical land-use changes on the regional climate in China since 1700. Acta Meteorol Sin, 2007, 21: 9–23Google Scholar
  22. 22.
    Ye Y, Fang X Q, Ren Y Y, et al. Cropland cover change in Northeast China during the past 300 years. Sci China Ser D-Earth Sci, 2009, 52: 1172–1182CrossRefGoogle Scholar
  23. 23.
    Goldewijk K K. Estimating global land use change over the past 300 years: The HYDE database. Glob Biogeochem Cycle, 2001, 15: 417–433CrossRefGoogle Scholar
  24. 24.
    Goldewijk K K. Three centuries of global population growth: A spatial referenced population density database for 1700–2000. Popul Environ, 2005, 26: 343–367CrossRefGoogle Scholar
  25. 25.
    Ye Y, Fang X Q, Dai Y J, et al. Calibration of cropland data and reconstruction of rate of reclamation in Northeast China during the period of Republic of China (in Chinese). Prog Nat Sci, 2006, 16: 1419–1427Google Scholar
  26. 26.
    Ramankutty N, Foley J A. Characterizing patterns of global land use: An analysis of global croplands data. Glob Biogeochem Cycles, 1998, 12: 667–685CrossRefGoogle Scholar
  27. 27.
    Scepan J. Thematic validation of high-resolution global land-cover data sets. Photogramm Eng Rem Sens, 1999, 65: 1051–1060Google Scholar
  28. 28.
    Goldewijk K K, Drecht G V, Bouwman A F. Mapping contemporary global cropland and grassland distributions on a 5×5 minute resolution. J Land Use Sci, 2007, 2: 167–190CrossRefGoogle Scholar
  29. 29.
    Mayaux P, Eva H, Gallego J, et al. Validation of the global land cover 2000 map. IEEE Trans Geosci Remote Sens, 2006, 44: 1728–1739CrossRefGoogle Scholar

Copyright information

© Science China Press and Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  1. 1.School of GeographyBeijing Normal UniversityBeijingChina
  2. 2.Institute of Geographic Sciences and Natural Resources ResearchChinese Academy of SciencesBeijingChina

Personalised recommendations