Monitoring and Modeling Land- Use Change in the Pearl River Delta, China, Using Satellite Imagery and Socioeconomic Data Robert K. Kaufmann Harvard University January 29,

Modeling and Forecasting Effects of Land-Use Change in China Based on Socioeconomic Drivers Boston University Department of Geography Principal Investigator: Robert K. Kaufmann Co-Investigators:Curtis E. Woodcock Dennis G. Dye Karen C. Seto Chinese Collaborators:Lu Jinfa, Institute of Geography CAS Li Xiaowen, IRSA Wang Tongsan, Economic Forecasting Center Huang Xiuhua, IRSA Liang Youcai, State Information Center Funded by NASA LCLUC-NAG5-6214

Why Pearl River Delta, Guangdong Province? real GDP growth: % Major agricultural region and national leader in production of: lychees, bananas, pond fish, sugar cane Special Economic Zones Geographic proximity to Hong Kong Cultural ties to overseas Chinese investors

China Study Area: Pearl River Delta

30 December 1995 TM

10 December 1988 TM March 1996 TM 432 Land-Use Change Map water natural vegetation agriculture urban natural to urban agriculture to urban 5 km

10 December 1988 TM 4323 March 1996 TM 432 Land-Use Change Map water natural vegetation agriculture urban water to ag ag to urban natural to urban 5 km

10 December 1988 TM March 1996 TM 432 Land-Use Change Map water natural vegetation agriculture urban natural to urban agriculture to urban 5 km agriculture to water

Official Estimates vs. Satellite-Derived Estimates of Agricultural Land Seto, K.C., R.K. Kaufmann, and C.E. Woodcock Agricultural land conversion in southern China. Nature 406: 121.

Land Use and Land Use Change: Made in conjunction with NASA Goddard Space Flight Center

% % % Real GDP Growth 25 km

Percent Land-Use Change of Counties High: % Medium: % Low: 0 - 9% 25 km

Modeling Socioeconomic Drivers of LUC Y it =  i +  i x it +  it i = 1,…, N t = 1,…, T Dependent variables: - agriculture  urban - natural vegetation/water  urban Examples of independent variables: - GDP - Demography (m/f/rural/urban) - Gross output value in industry & agriculture - Wages by sector

Agriculture to Urban = [-5.0] *Relative land productivity [1.97] *Ag labor productivity [-4.58] *Investment in capital construction [2.74] *Average wage [5.98] Natural to Urban = [3.13] *Relative land productivity [3.55] *Relative labor productivity [-3.37] *Investment in capital construction [3.27] Drivers of Land-Use Change Seto, K.C. and R.K. Kaufmann, In press, Modeling the drivers of urban land-use change in the Pearl River Delta, China: Integrating remote sensing with socioeconomic data. Land Economics

Evaluation of Results *Panel cointegration--variables share the stochastic trend *Hendry forecast test--Regression results stable over space and time *Moran’s I--No spatial autocorrelation *Granger causality--Some evidence that RHS variables “Granger cause” land use change no evidence for opposite effect

Results Successful mapping of land-use change with high accuracy (93.5%) Amount of developed land has increase by 319% between 1988 and 1996 Developed new method to evaluate change in series of images using time series techniques Identified and quantified major drivers of urbanization