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Arid Land Geography ›› 2023, Vol. 46 ›› Issue (2): 305-315.doi: 10.12118/j.issn.1000-6060.2022.176

• Regional Development • Previous Articles     Next Articles

Spatiotemporal evolution and driving factors of the green development efficiency in Gansu Province

LU Chenyu1,2(),HUANG Ping1,ZHANG Tong1,LIU Xiaowan2,CHENG Wei1   

  1. 1. College of Geography and Environmental Science, Northwest Normal University, Lanzhou 730070, Gansu, China
    2. School of Architecture and Urban Planning, Lanzhou Jiaotong University, Lanzhou 730070, Gansu, China
  • Received:2022-04-25 Revised:2022-05-20 Online:2023-02-25 Published:2023-03-14

Abstract:

Improving the green development efficiency (GDE) is crucial for constructing ecological civilization and high-quality development in Gansu Province, China. Based on the Super-SBM model, hotspot analysis and the geographic detector model, Gansu Province from 2005 to 2019 was analyzed for the spatiotemporal evolution characteristics and driving factors of the GDE in 14 cities and prefectures. The following results are obtained: (1) Temporally, the GDE shows a pattern of “M”-shaped fluctuated growth, and the regional relative difference demonstrates a corresponding trend of fluctuation. (2) Spatially, the spatial heterogeneity of the GDE is significant, and the gradient difference in the north-south direction is significantly greater than that in the east-west direction. However, the degree of spatial agglomeration of the GDE is weak, dominated by low hot-spots, middle hot-spots, and low cold-spots. Additionally, the GDE displays a characteristic of spatial club convergence. (3) Marketization level, innovation ability, government regulation, and urbanization level are the driving factors of GDE. The GDE in Gansu Province is the result of the multifactor interaction. The results not only enrich the index system and case study of GDE but also can provide references for the green transformation development of Gansu Province and other less developed areas.

Key words: green development efficiency, the Super-SBM model, the geographic detector model, Gansu Province