, Volume 12, Issue 2, pp 279–297 | Cite as

Estimating Long-Term Changes in China’s Village Landscapes

  • Erle Christopher EllisEmail author
  • Nagaraj Neerchal
  • Kui Peng
  • Hong Sheng Xiao
  • Hongqing Wang
  • Yan Zhuang
  • Shou Cheng Li
  • Jun Xi Wu
  • Jia Guo Jiao
  • Hua Ouyang
  • Xu Cheng
  • Lin Zhang Yang


Over the past 50 years, China’s ancient agricultural village landscapes have been transformed by unprecedented social, technological, and ecological changes. Although these dense anthropogenic mosaics of croplands, settlements, and other used lands cover more than 2 million square kilometers across China, the nature of these changes and their environmental impacts remain poorly understood because their spatial scale is generally too small to measure accurately using conventional land-change methods. Here, we investigate the regional consequences of fine-scale landscape changes across China’s village regions from 1945 to 2002 using high-resolution, field-validated ecological mapping of a regionally stratified sample of village landscapes at five sites across China, with uncertainties estimated using model-based resampling and Monte Carlo methods. From 1945 to 2002, built surface areas increased by about 7% (90% credible interval = 2–17%) across China’s village regions, an increase equivalent to about three times the total urban area of China in 2000. Although this striking result is explained by a near doubling of already large village populations and by lower housing density per capita in rural areas, two unexpected changes were also observed: a 9% net increase (−4% to +21%) in regional cover by closed canopy trees and an 11% net decline (−30% to +3%) in annual crops. These major regional changes were driven primarily by intensive fine-scale land-transformation processes including tree planting and regrowth around new buildings, cropland abandonment, and by the adoption of perennial crops and improved forestry practices. Moreover, the fragmentation, heterogeneity, and complexity of village landscapes increased over time. By coupling regional sampling and upscaling with observations in the field, this study revealed that fine-scale land-change processes in anthropogenic landscapes have the potential for globally significant environmental consequences that are not anticipated, measured, or explained by conventional coarser resolution approaches to global and regional change measurement or modeling.


human dominated ecosystems land-use and land-cover change China anthropogenic biomes ecological history landscape ecology upscaling regional change ecotope mapping agriculture 



This material is based upon work supported by the U.S. National Science Foundation under Grant DEB-0075617 awarded to Erle C. Ellis in 2000. We are very grateful to Xin Ping Liu for research in Hunan, to Shi Ming Luo for supporting research in Guangdong, and to our local collaborators for field assistance across China. Peter Verburg developed our initial regionalization system. Thanks to Kevin Klingebiel, Kevin Sigwart, Jonathan Dandois, and Dominic Cilento for critical assistance in this project. Thanks to Jiyuan Liu for China land-cover data and to Yongzhong Tian for China population density data. Eric Lecoutre developed R code used in producing supplementary material—Appendix 5. Thanks to Michael Leonard and the National Archives and Records Administration for historical aerial photographs. SpaceImaging provided IKONOS imagery. Erle Ellis thanks Steve Gliessman of the Department of Environmental Studies at the University of California, Santa Cruz, and Chris Field of the Department of Global Ecology, Carnegie Institute of Washington at Stanford for graciously hosting his sabbatical. A final thanks to Greg Asner, Diann Prosser, Mutlu Ozdogan, and our anonymous reviewers for helpful comments on the manuscript. Any opinions, findings, conclusions, or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the National Science Foundation.

Supplementary material

10021_2008_9222_MOESM1_ESM.doc (2.1 mb)
(DOC 2163 kb)


  1. Achard, F., Eva, H.D., Stibig, H.-J., Mayaux, P., Gallego, J., Richards, T., Malingreau, J.-P., 2002. Determination of deforestation rates of the world’s humid tropical forests. Science 297, 999–1002.PubMedCrossRefGoogle Scholar
  2. Binford, M.W., Lee, T.J., Townsend, R.M., 2004. Sampling design for an integrated socioeconomic and ecological survey by using satellite remote sensing and ordination. PNAS 101, 11517–11522.PubMedCrossRefGoogle Scholar
  3. Brewer, K.R.W., 1999. Design-based or Prediction-based Inference? Stratified Random vs Stratified Balanced Sampling. International Statistical Review 67, 35–47.CrossRefGoogle Scholar
  4. Cochran, W.G., 1977. Sampling Techniques. John Wiley & Sons, New York, New York, USA.Google Scholar
  5. de Boor, C., 1978. A Practical Guide to Splines. Springer-Verlag, New York.Google Scholar
  6. Efron, B., Tibshirani, R., 1991. Statistical-data analysis in the Computer-Age. Science 253, 390–395.PubMedCrossRefGoogle Scholar
  7. Ellis, E.C., 2004. Long-term ecological changes in the densely populated rural landscapes of China. In: DeFries, R.S., Asner, G.P., Houghton, R.A. (Eds.), Ecosystems and Land Use Change. American Geophysical Union, Washington, DC, pp. 303–320.Google Scholar
  8. Ellis, E.C., Li, R.G., Yang, L.Z., Cheng, X., 2000. Long-term change in village-scale ecosystems in China using landscape and statistical methods. Ecol Appl 10, 1057–1073.CrossRefGoogle Scholar
  9. Ellis, E.C., Ramankutty, N., 2008. Putting people in the map: anthropogenic biomes of the world. Front. Ecol. Environ. 6, 439–447.CrossRefGoogle Scholar
  10. Ellis, E.C., Wang, H., 2006. Estimating area errors for fine-scale feature-based ecological mapping. Int J Remote Sens 27, 4731–4749.CrossRefGoogle Scholar
  11. Ellis, E.C., Wang, H., Xiao, H.S., Peng, K., Liu, X.P., Li, S.C., Ouyang, H., Cheng, X., Yang, L.Z., 2006. Measuring long-term ecological changes in densely populated landscapes using current and historical high resolution imagery. Remote Sens Environ 100, 457–473.CrossRefGoogle Scholar
  12. Fang, J., A. Chen, C. Peng, S. Zhao, and L. Ci. 2001. Changes in forest biomass carbon storage in China between 1949 and 1998. Science 292:2320–2322.PubMedCrossRefGoogle Scholar
  13. Fischer G, van Velthuizen H, Nachtergaele F, Medow S. 2000. Global agro-ecological zones – 2000. FAO Land and Water Digital Media Series Number 11. Food and Agriculture Organization of the United Nations, International Institute for Applied Systems Analysis, RomeGoogle Scholar
  14. Foley, J.A., DeFries, R., Asner, G.P., Barford, C., Bonan, G., Carpenter, S.R., Chapin, F.S., Coe, M.T., Daily, G.C., Gibbs, H.K., Helkowski, J.H., Holloway, T., Howard, E.A., Kucharik, C.J., Monfreda, C., Patz, J.A., Prentice, I.C., Ramankutty, N., Snyder, P.K., 2005. Global consequences of land use. Science 309, 570–574.PubMedCrossRefGoogle Scholar
  15. Frolking, S., Xiao, X.M., Zhuang, Y.H., Salas, W., Li, C.S., 1999. Agricultural land-use in China: a comparison of area estimates from ground-based census and satellite-borne remote sensing. Global Ecol Biogeogr 8, 407–416.CrossRefGoogle Scholar
  16. Fylstra, D., Lasdon, L., Watson, J., Waren, A., 1998. Design and Use of the Microsoft Excel Solver. Interfaces 28, 29–55.CrossRefGoogle Scholar
  17. Gallego, F.J., Delince, G., Carfugna, E., 1994. Two stage area frame on squared segments for farm surveys. Survey Methodology 20, 107–115.Google Scholar
  18. Gibbard S, Caldeira K, Bala G, Phillips TJ, Wickett M. 2005. Climate effects of global land cover change. Geophys Res Lett 32. doi: 10.1029/2005GL024550
  19. Grimm, N.B., Grove, J.M., Pickett, S.T.A., Redman, C.L., 2000. Integrated approaches to long-term studies of urban ecological systems. BioScience 50, 571–584.CrossRefGoogle Scholar
  20. Han, C.R., 1989. Recent changes in the rural environment in China. Journal of Applied Ecology 26, 803–812.CrossRefGoogle Scholar
  21. Heilig GK. 1997. Anthropogenic factors in land-use change in China. Popul Dev Rev 23:139CrossRefGoogle Scholar
  22. Houghton RA. 2002. Temporal patterns of land-use change and carbon storage in China and tropical Asia. Sci China C Life Sci 45:10CrossRefGoogle Scholar
  23. Houghton RA, Hackler JL. 2003. Sources and sinks of carbon from land-use change in China. Global Biogeochem Cycles 17Google Scholar
  24. Kauppi, P.E., Ausubel, J.H., Fang, J., Mather, A.S., Sedjo, R.A., Waggoner, P.E., 2006. Returning forests analyzed with the forest identity. PNAS 103, 17574–17579.PubMedCrossRefGoogle Scholar
  25. Liu, J., Diamond, J., 2005. China’s environment in a globalizing world. Nature 435, 1179–1186.PubMedCrossRefGoogle Scholar
  26. Liu, J., Dietz, T., Carpenter, S.R., Alberti, M., Folke, C., Moran, E., Pell, A.N., Deadman, P., Kratz, T., Lubchenco, J., Ostrom, E., Ouyang, Z., Provencher, W., Redman, C.L., Schneider, S.H., Taylor, W.W., 2007. Complexity of coupled human and natural systems. Science 317, 1513–1516.PubMedCrossRefGoogle Scholar
  27. Liu J, Liu M, Tian H, Zhuang D, Zhang Z, Zhang W, Tang X, Deng X. 2005a. Spatial and temporal patterns of China’s cropland during 1990–2000: an analysis based on Landsat TM data. Remote Sens Environ 98:442Google Scholar
  28. Liu J, Tian H, Liu M, Zhuang D, Melillo JM, Zhang Z. 2005b. China’s changing landscape during the 1990s: large-scale land transformations estimated with satellite data. Geophys Res Lett 32:1–5Google Scholar
  29. Liu, J.Y., Liu, M.L., Zhuang, D.F., Zhang, Z.X., Deng, X.Z., 2003. Study on spatial pattern of land-use change in China during 1995–2000. Science in China Series D-Earth Sciences 46, 373–384.Google Scholar
  30. National Geospatial-Intelligence Agency, 2004. Shuttle Radar Topography Mission DTED Level 1 (3 arcsecond). National Center for Earth Resources Observation and Science (EROS)Google Scholar
  31. Noss, R.F., 1990. Indicators for Monitoring Biodiversity: A Hierarchical Approach. Conservation Biology 4, 355–364.CrossRefGoogle Scholar
  32. Ozdogan, M., Woodcock, C.E., 2006. Resolution dependent errors in remote sensing of cultivated areas. Remote Sens Environ 103, 203.CrossRefGoogle Scholar
  33. Rindfuss, R.R., Walsh, S.J., Turner, B.L., II, Fox, J., Mishra, V., 2004. Developing a science of land change: Challenges and methodological issues. PNAS 101, 13976–13981.PubMedCrossRefGoogle Scholar
  34. Schreuder, H.T., Gregoire, T.G., Weyer, J.P., 2001. For What Applications Can Probability and Non-Probability Sampling Be Used? Environ Monit Assess 66, 281.PubMedCrossRefGoogle Scholar
  35. Seto, K.C., Fragkias, M., 2005. Quantifying Spatiotemporal Patterns of Urban Land-use Change in Four Cities of China with Time Series Landscape Metrics. Landscape Ecol 20, 871.CrossRefGoogle Scholar
  36. Tian, Y., Yue, T., Zhu, L., Clinton, N., 2005. Modeling population density using land cover data. Ecol. Model. 189, 72–88.CrossRefGoogle Scholar
  37. Turner II, B.L., Lambin, E.F., Reenberg, A., 2007. The emergence of land change science for global environmental change and sustainability. PNAS 104, 20666–20671.PubMedCrossRefGoogle Scholar
  38. Verburg, P.H., Chen, Y., 2000. Multiscale characterization of land-use patterns in China. Ecosystems 3, 369ΓÇô385.CrossRefGoogle Scholar
  39. Vitousek, P.M., Mooney, H.A., Lubchenco, J., Melillo, J.M., 1997. Human domination of Earth’s ecosystems. Science 277, 494–499.CrossRefGoogle Scholar
  40. Wang, H., Ellis, E.C., 2005. Spatial accuracy of orthorectified IKONOS imagery and historical aerial photographs across five sites in China. Int J Remote Sens 26, 1893–1911.CrossRefGoogle Scholar
  41. Willmott CJ, Matsuura K. 2001. Terrestrial air temperature and precipitation: monthly and annual climatologies (Version 3.02). Center for Climatic Research, Department of Geography, University of DelawareGoogle Scholar
  42. Wu J-X, Cheng X, Xiao H-S, Wang H, Yang L-Z, Ellis EC. 2009. Agricultural landscape change in China’s Yangtze Delta, 1942 to 2002: a case study. Agric Ecosyst Environ 129:523–33Google Scholar
  43. Wulder, M.A., Hall, R.J., Coops, N.C., Franklin, S.E., 2004. High spatial resolution remotely sensed data for ecosystem characterization. BioScience 54, 511.CrossRefGoogle Scholar
  44. Young, F., 1981. Quantitative analysis of qualitative data. Psychometrika 46, 357–388.CrossRefGoogle Scholar
  45. Young, F., de Leeuw, J., Takane, Y., 1976. Regression with qualitative and quantitative variables: An alternating least squares method with optimal scaling features. Psychometrika 41, 505–529.CrossRefGoogle Scholar
  46. Zhang, J.Y., Dong, W.J., Wu, L.Y., Wei, J.F., Chen, P.Y., Lee, D.K., 2005. Impact of land use changes on surface warming in China. Advances In Atmospheric Sciences 22, 343–348.CrossRefGoogle Scholar
  47. Zhang, W., Zhuang, D., Hu, W., 2000. Area summarization in establishing the national resources and environmental database. Journal of Remote Sensing (Beijing) 4, 304–310.Google Scholar
  48. Zhao, J., Sun, Y., Bai, G., Wu, G., Shao, G., 2003. Certainties and uncertainties of land cover statistics in China. Journal of Environmental Sciences (China) 15, 520–524.Google Scholar

Copyright information

© Springer Science+Business Media, LLC 2008

Authors and Affiliations

  • Erle Christopher Ellis
    • 1
    Email author
  • Nagaraj Neerchal
    • 2
  • Kui Peng
    • 3
    • 4
  • Hong Sheng Xiao
    • 5
  • Hongqing Wang
    • 1
    • 6
  • Yan Zhuang
    • 2
  • Shou Cheng Li
    • 7
  • Jun Xi Wu
    • 8
  • Jia Guo Jiao
    • 9
  • Hua Ouyang
    • 3
  • Xu Cheng
    • 8
  • Lin Zhang Yang
    • 9
  1. 1.Department of Geography & Environmental SystemsUniversity of Maryland, Baltimore CountyBaltimoreUSA
  2. 2.Department of Mathematics & StatisticsUniversity of Maryland, Baltimore CountyBaltimoreUSA
  3. 3.Institute of Geographic Sciences & Natural Resources ResearchChinese Academy of SciencesBeijingChina
  4. 4.Metallurgical and Ecological Engineering SchoolUniversity of Science and Technology BeijingBeijingChina
  5. 5.Institute of Tropical & Subtropical EcologySouth China Agricultural UniversityGuangzhouChina
  6. 6.Institute of Coastal Ecology and EngineeringUniversity of Louisiana at LafayetteLafayetteUSA
  7. 7.Agronomy CollegeSichuan Agricultural UniversityYaanChina
  8. 8.Department of Agronomy & AgroecologyChina Agricultural UniversityBeijingChina
  9. 9.Institute of Soil ScienceChinese Academy of SciencesNanjingChina

Personalised recommendations