Monitoring and Modeling Monitoring and Modeling

Land-Use Change in the Land-Use Change in the

Pearl River Delta, China, Pearl River Delta, China,

Using Satellite Imagery and Using Satellite Imagery and

Socioeconomic DataSocioeconomic DataRobert K. Kaufmann

Harvard University

January 29, 2003

http://www.bu.edu/cees/readmoreRK.html

Modeling and Forecasting Effects of Land-Use Modeling and Forecasting Effects of Land-Use Change in China Based on Socioeconomic DriversChange 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?Why Pearl River Delta, Guangdong Province?

• 1988 - 1996 real GDP growth: 350-550%

• 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 432

12

3

10 December 1988 TM 432 3 March 1996 TM 432

Land-Use Change Map

waternatural vegetationagricultureurbannatural to urbanagriculture to urban

5 km

10 December 1988 TM 432 3 March 1996 TM 432 Land-Use Change Map

waternatural vegetation

agricultureurban

water to ag ag to urbannatural to urban5 km

10 December 1988 TM 432 3 March 1996 TM 432

Land-Use Change Map

waternatural vegetationagricultureurban

natural to urbanagriculture to urban

5 km

agriculture to water

Official Estimates vs. Official Estimates vs. Satellite-Derived EstimatesSatellite-Derived Estimates

of Agricultural Land of Agricultural Land

Seto, K.C., R.K. Kaufmann, and C.E. Woodcock. 2000. Agricultural land conversion in southern China. Nature 406: 121.

Land Use and Land Use Change:Land Use and Land Use Change:1988 -19961988 -1996

Made in conjunction with NASA Goddard Space Flight Center

QuickTime™ and aCinepak decompressor

are needed to see this picture.

350 - 550%

200 - 300%

100 - 190%

1988 - 1996 Real GDP Growth

25 km

1988 - 1996 Percent Land-Use Change of Counties

High: 17 - 23%

Medium: 14 - 15%

Low: 0 - 9%

25 km

Modeling Socioeconomic Drivers of LUCModeling Socioeconomic Drivers of LUC

Yit = i + ixit + it i = 1,…, Nt = 1,…, T

• Dependent variables:- agricultureurban- natural vegetation/waterurban

• Examples of independent variables:- GDP- Demography (m/f/rural/urban)- Gross output value in industry & agriculture- Wages by sector

Agriculture to Urban = -0.11 [-5.0]

+ 1.50 *Relative land productivity [1.97]

- 3.97 *Ag labor productivity [-4.58]

+ 1.24 *Investment in capital construction [2.74]

+ 0.03 *Average wage [5.98]

Natural to Urban = 0.028 [3.13]

+ 6.53*Relative land productivity [3.55]

- 1.39 *Relative labor productivity [-3.37]

+ 2.85*Investment in capital construction [3.27]

Drivers of Land-Use ChangeDrivers 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 ResultsEvaluation of Results

* Panel cointegration--variables share the stochastic trend

* Hendry forecast test--Regression results stable overspace and time

* Moran’s I--No spatial autocorrelation* Granger causality--Some evidence that RHS

variables “Granger cause” land use changeno evidence for opposite effect

ResultsResults

• 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