1 / 16

Monitoring and Modeling Land-Use Change in the Pearl River Delta, China, Using Satellite Imagery and Socioeconomic Data

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, 2003. http://www.bu.edu/cees/readmoreRK.html.

howie
Download Presentation

Monitoring and Modeling Land-Use Change in the Pearl River Delta, China, Using Satellite Imagery and Socioeconomic Data

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. 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, 2003 http://www.bu.edu/cees/readmoreRK.html

  2. 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

  3. 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

  4. China Study Area: Pearl River Delta

  5. 30 December 1995 TM 432 3 1 2

  6. 3 March 1996 TM 432 10 December 1988 TM 432 Land-Use Change Map water natural vegetation agriculture urban natural to urban agriculture to urban 5 km

  7. 10 December 1988 TM 432 3 March 1996 TM 432 Land-Use Change Map water agriculture water to ag ag to urban 5 km urban natural vegetation natural to urban

  8. 10 December 1988 TM 432 3 March 1996 TM 432 Land-Use Change Map water natural vegetation agriculture urban agriculture to water natural to urban agriculture to urban 5 km

  9. Official Estimates vs. Satellite-Derived Estimatesof Agricultural Land Seto, K.C., R.K. Kaufmann, and C.E. Woodcock. 2000. Agricultural land conversion in southern China. Nature 406: 121.

  10. Land Use and Land Use Change:1988 -1996 Made in conjunction with NASA Goddard Space Flight Center

  11. 350 - 550% 200 - 300% 100 - 190% 1988 - 1996 Real GDP Growth 25 km

  12. 1988 - 1996 Percent Land-Use Change of Counties High: 17 - 23% Medium: 14 - 15% Low: 0 - 9% 25 km

  13. Modeling Socioeconomic Drivers of LUC Yit = ai + bixit + mit 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

  14. Drivers of Land-Use Change 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] 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

  15. 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

  16. 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

More Related