Abstract
Induced by high population density, rapid but uneven economic growth, and long-time resource exploitation, China's upper Yangtze basin has witnessed remarkable changes in land uses and covers, which have resulted in severe environmental consequences, such as flooding, soil erosion, and habitat loss. This paper examines the causes of the land use and land cover changes (LUCC) along the Jinsha River, one primary section of the upper Yangtze, aiming to better understand the human impact on the dynamic LUCC process and to provide necessary policy actions for sustainable land use and environmental protection. Using a panel dataset covering 31 counties over four time periods from 1975 to 2000, the study develops a fractional logit model to empirically determine the effects of socioeconomic and institutional factors on changes for cropland, forestland, and grassland. It is shown that population expansion, food self-sufficiency, and better market access drove cropland expansion, while industrial development contributed significantly to the increase of forestland and the decrease of other land uses. Similarly, stable tenure had a positive effect on forest protection. Moreover, past land use decisions were less significantly influenced by the distorted market signals. The policy implications of these findings and future directions of research are also discussed.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Notes
- 1.
The Chinese government initially defined the poverty line as per capita income below 200 yuan in 1985. Based on inflation and other considerations, the figure has been adjusted upwards over time, reaching 1067 yuan in 2007 (China State Statistics Bureau 2008). A national poverty county is declared if a majority, but not necessarily all, of the local population lives below the poverty line.
- 2.
Elevation will not be listed in the summary statistics of variables because it is a time-constant variable. It ranges from 295 meters (m) to 6109 m for the study region, with a mean of 3070 m.
References
Ahn, S., Plantinga, A. J., & Alig, R. J. (2000). Predicting future forestland area: A comparison of econometric approaches. Forest Sciences, 46(3), 363–376.
China State Statistics Bureau. (2008). China Statistics Yearbook. Beijing: China Statistics Press.
Chomitz, K. M., & Gray, D. A. (1996). Roads, land use, and deforestation: A spatial model applied to Belize. World Bank Economic Review, 10(3), 487–512.
Conservation International. (2002). Biodiversity hotspots. Retrieved from http://www.biodiversityhotspots.org/xp/hotspots/China
Du, S. F. (2001). Environmental economics. Beijing: Encyclopedia Press.
Fischer, G., & Sun, L. X. (2001). Model based analysis of future land-use development in China. Agriculture, Ecosystems and Environment, 85, 163–176.
Geoghegan, J., Villar, S. C., Klepeis, P., Mendoza, P. M., Himmelberger, Y. O., Chowdhury, R. R., et al. (2001). Modeling tropical deforestation in the southern Yucatán Peninsular region: Comparing survey and satellite data. Agriculture, Ecosystems and Environment, 85, 25–46.
Ji, C. Y., Liu, Q., Sun, D., Wang, S., Lin, P., & Li, X. (2001). Monitoring urban expansion with remote sensing in China. International Journal of Geographical Information System, 22(8), 1441–1455.
Kaimowitz, D., & Angelsen, A. (1998). Economic models of tropical deforestation: A review. Bogor, Indonesia: Center for International Forestry Research.
Li, X., Peterson, J. A., Liu, G., & Qian, L. (2001). Assessing regional sustainability: The case of land use and land cover change in the Middle Yiluo Catchment of the Yellow River Basin, China. Applied Geography, 21, 87–106.
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), 46(4), 373–384.
Loucks, C. J., Lü, Z., Dinerstein, E., Wang, H., Olson, D. M., Zhu, C. Q., et al. (2001). Giant pandas in a changing landscape. Science, 294, 1465.
Lu, X. X. (2005). Spatial variability and temporal change of water discharge and sediment flux in the lower Jinsha tributary: impact of environmental changes. River Research and Applications, 21(2–3), 229–243.
McCracken, S. D., Brondizio, E. S., Nelson, D., Moran, E. F., Siqueira, A. D., & Rodriguez-Pedraza, C. (1999). Remote sensing and GIS at farm property level: Demography an deforestation in the Brazilian Amazon. Photogrammetric Engineering and Remote Sensing, 65(11), 1311–1320.
Mertens, B., Sunderlin, W. D., Ndoye, O., & Lambin, E. F. (2000). Impact of macroeconomic change on deforestation in South Cameroon: Integration of household survey and remotely sensed data. World Development, 28(6), 983–999.
Miller, J. D., O., & Plantinga, J. A. (1999). Modeling land use decision with aggregated data. American Journal of Agricultural Economics, 81, 180–194.
Müller, D., & Zeller, M. (2002). Land use dynamics in the central highlands of Vietnam: A spatial model combining village survey data with satellite imagery interpretation. Agricultural Economics, 27, 333–354.
Munroe, D. K., & York, A. M. (2003). Jobs, houses and trees: Changing regional structure, local land-use patterns, and forest cover in Southern Indiana. Growth and Change, 34(3), 299–320.
Pan, J. G. (1999). The characteristics of water runoff and suspended sediment along the Jinsha River. Journal of Sediment Research, 2, 19–24.
Plantinga, A. J. (1996). The effects of agricultural policies on land use and environmental quality. American Journal of Agricultural Economics, 78, 1082–1091.
Ruttan, V. W. (2001). Technology, growth, and development: An induced innovation perspective. Oxford, UK: Oxford University Press.
Sichuan Statistics Yearbook. (2003). Chengdu, China: Sichuan Statistics Press.
Turner II, B. L., Lambin, E. F., & Reenberg, A. (2007). The emergence of land change science for global environmental change and sustainability. PNAS, 104(52), 20666–20671.
Turner II, B. L., Meyer, B. W., & Skole, D. L. (1994). Global land use/land cover change: towards an integrated study. AMBIO, 23(1), 91–94.
USGCRP. (2004). Land use/land cover change: USGCRP program element. Retrieved from http://www.usgcrp.gov/usgcrp/ProgramElements/land.htm.
Verburg, P. H., Veldkamp, W. S. A., Espaldon, R. L. V., & Mastura, S. S. A. (2002). Modeling the spatial dynamics of regional land use: the CLUE-S model. Environmental Management, 30(3), 391–405.
Wang, X. T. (2003). Building an ecological shield along the Upper Yangtze river: Priorities and measures. Beijing: China Agriculture Publishing House.
Wooldridge, J. M. (2002). Econometric analysis of cross section and panel data. Cambridge, MA: The MIT Press.
Xu, J. T., Katsigris, E., & White, A. (Eds.). (2002). Implementing the natural forest protection program and the sloping land conversion program: Lessons and policy recommendations. Beijing, China: China Forestry Press.
Xu, J., Yin, R. S., Li, Z., & Liu, C. (2007). China's ecological rehabilitation: Progress and challenges. Ecological Economics, 57(4), 595–607.
Yeh, A. G., & Li, X. (1998). Suitable land development model for rapid growth areas Using GIS. International Journal of Geographical Information System, 12(2), 169–189.
Yin, H., & Li, C. (2001). Human impact on floods and flood disasters on the Yangtze River, Geomorphology, 41(2–3), 105–109.
Yunnan Statistics Yearbook. (2003). Kunming, China: Yunnan Statistics Press.
Zhang, X., Mount, T. D., & Boisvert, R. N. (2003). Industrialization, urbanization and land use in China. IFPRI, Environment and Production Technology Division (Discussion Paper No. 58).
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2009 Springer Science+Business Media B.V.
About this chapter
Cite this chapter
Xiang, Q., Yin, R., Xu, J., Deng, X. (2009). Modeling the Driving Forces of the Land Use and Land Cover Changes Along the Upper Yangtze River. In: Yin, R. (eds) An Integrated Assessment of China's Ecological Restoration Programs. Springer, Dordrecht. https://doi.org/10.1007/978-90-481-2655-2_5
Download citation
DOI: https://doi.org/10.1007/978-90-481-2655-2_5
Published:
Publisher Name: Springer, Dordrecht
Print ISBN: 978-90-481-2654-5
Online ISBN: 978-90-481-2655-2
eBook Packages: Biomedical and Life SciencesBiomedical and Life Sciences (R0)