Abstract:

The importance of population and socioeconomic data and their spatial distributions to researches of natural resources, environment and natural disaster assessment has been widely recognized. It’s a worthy exploration to solve the problem by combining remote sensing and GIS technology. According to the statistical population, GDP and land use data in Dongjiang watershed, we built multiple linear regression models by taking the statistical population or GDP as the dependent variable and per unit of statistical data carrying capacity as independent variables. Meanwhile, based on the raster land use data and 100m×100m grid data, the constraint index layers of population and GDP’s spatial distribution were obtained. Furthermore, through the regression model and GIS interpolation, the spatialisation of the statistical population and GDP data of Dongjiang watershed in 2009 was completed. The simulated result was verified to be equal or superior in county-scale by comparing with the actual statistical data in the same scale. The result suggests that to combine remote sensing and GIS is an effective way to spatialising socioeconomic data.

Key words: statistical data, land use, spatialization, remote sensing, GIS