HUBEI AGRICULTURAL SCIENCES ›› 2022, Vol. 61 ›› Issue (21): 244-251.doi: 10.14088/j.cnki.issn0439-8114.2022.21.045

• Economy & Management • Previous Articles     Next Articles

Research on GDP spatialization of urban agglomeration on the northern slope of Tianshan Mountains based on NPP-VIIRS data

YU Feng-tian, GAO Min-hua   

  1. College of Resource and Environment Sciences/Key Laboratory of Oasis Ecology of Ministry of Education, Xinjiang University, Urumqi 830046,China
  • Received:2021-04-01 Online:2022-11-10 Published:2022-12-10

Abstract: In order to meet the needs of spatial socio-economic data in the development of urban agglomerations, on the basis of analyzing and summarizing the spatial technical methods of socio-economic data, the urban agglomeration on the northern slope of the Tianshan Mountains was taken as the research object, the quantitative analysis was made on the night light data and GDP statistics of NPP-VIIRS in 2013 and 2019, and the spatial research was made on the regional GDP of 15 counties and cities. By analyzing the spatial correlation between the total output value, the first, second and third industry values, and the sum of the secondary and tertiary industry values of the urban agglomeration on the northern slope of the Tianshan Mountains and the light index extracted from the NPP-VIIRS night light data, the optimal light index was selected. Finally, the 500 m precision sub-industry GDP density map of the study area in 2013 and 2019 was simulated through the linear regression model. The results showed that there was a significant correlation between the two periods of night light data and the GDP of sub industry regions. The distribution of industrial output value of urban agglomeration was mainly concentrated in the main nodes of traffic lines between counties and cities, and the high-value areas were mainly concentrated in Urumqi, Changji, Shihezi and Karamay. The spatial distribution result of sub-industry GDP simulated by night light data was more credible,and the relative error between the simulation result and the statistical values was small, which could intuitively show the regional distribution difference of statistical data and the dynamic changes of regional economic development.

Key words: urban agglomeration on the northern slope of Tianshan Mountains, NPP-VIIRS night light data, statistical data spatialization, regression analysis

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