Original Articles

GIS Based Space-time Simulation of GDP in Arid Regions: Taking the Northern Slope of Tianshan Mountains as an Example

  • 1. Xinjiang Institute of Ecology and Geography, CAS, Urumqi 830011, China;
    2. Graduate University of Chinese Academy of Sciences, Beijing 100049, China;
    3. West China Normal University, Nanchong 637002, China;
    4. College of Resources Science and Technology, Beijing Normal University, Beijing 100875, China

Online published: 2009-07-25


The traditional economic data expression is based on the administrative regions at county or province level, which conceals the inner difference of the calculation area. It cannot satisfy the requirement of the study of resources and environmental sciences.Land use data integrate lot of information of factors affecting economic distribution. A close spatial relation between land use and economic distribution can be established using the data of the nature of land, the production mode of primary industry, the input and output of industry, and the proportion of service in China. After analyzing the characteristics of the regional economic development, we consider the GDP of counties separately and constructed the model based on land use for three types of industries to simulate the difference of GDP in arid area using 1 km × 1 km grid-cells. To the primary industry, we considered the influence of land-use type and land quality, the area weightiness method is adopted, using linear equation to fit it; According to the influence of road on secondary industry, a road-based counter-distance weighted model is built to calculate the secondary industry output indices, and then the spatialization of the secondary industry output is implemented. For the output of tertiary industry, a power exponential model based on the scale of town and the distance from the center of town is derived from distance decay function. We take the GDP data in the northern piedmont of the Tianshan Mountains in Xinjiang in 1995, 2000, 2007 as a case. The results show that the precision of each simulation result is high both at industries and counties level, the relative errors between the simulation results and the statistical ones are all below 1%. From the distribution map, we can see that the high value areas are mainly distributed from Miquan to Shawan, and dispersed radially from Urumqi, Karamay and Shihezi to their surrounding areas. In city area, the GDP density is decreased from the inner city to the outskirts, and the downtown GDP density is much higher than the suburban one. This is highly matched the fact. The time series analysis reflected the process of regional economic development and fit the distribution characteristics of regional economy well. Compared with other models, the simulation method we used in this case is more practicable and effective.

Cite this article

HUANG Ying1|2, BAO Anming1|3, CHEN Xi1, LIU Hailong1,YANG Guanghua1|2 . GIS Based Space-time Simulation of GDP in Arid Regions: Taking the Northern Slope of Tianshan Mountains as an Example[J]. PROGRESS IN GEOGRAPHY, 2009 , 28(4) : 494 -502 . DOI: 10.11820/dlkxjz.2009.04.003


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