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Spatial-temporal Dataset of Environmental Pressure in the Upper Reaches of Yangtze River (1998-2021)


HUANG Lei1,2
1 College of Economics and Management,Southwest University,Chongqing 400715,China2 China Institute of Development Strategy and Planning,Wuhan University,Wuhan 430072,China

DOI:10.3974/geodb.2024.05.03.V1

Published:May 2024

Visitors:177       Data Files Downloaded:28      
Data Downloaded:3.77 MB      Citations:

Key Words:

watershed economy,environmental pressure,ecological protection,regional disparity,spatial effect

Abstract:

The author focuses on the upper reaches of the Yangtze River, including 47 prefecture level cities of Yunnan, Guizhou, Sichuan provinces, and Chongqing City. The entropy method was employed to assess environmental stress in these regions, and the spatiotemporal patterns of environmental stress was analyzed through the Dagum Gini coefficient, Markov chain, and spatial convergence model, etc. The dataset includes the following data in the upper reaches of the Yangtze River from 1998 to 2021: (1) environmental pressure values for 47 prefecture level cities; (2) the Dagum Gini coefficient and its decomposition of environmental pressure; (3) probability matrixes of multi-period Markov chain transitions of environmental pressure; (4) five control variable values for the convergence analysis of environmental pressure, they are economic development level, industrial gradient level, industrial structure, consumption vitality, investment propensity; (5) a spatial weight matrix constructed based on adjacency relationships for the 47 prefecture level cities. The dataset is archived in .xlsx format, and consists of one file with data size of 138 KB. The analysis paper based on the dataset will be coordinated with Acta Geographica Sinica, Vol. 79, No. 5, 2024.

Foundation Item:

National Social Science Fund of China (20CJL021)

Data Citation:

HUANG Lei.Spatial-temporal Dataset of Environmental Pressure in the Upper Reaches of Yangtze River (1998-2021)[J/DB/OL]. Digital Journal of Global Change Data Repository, 2024. https://doi.org/10.3974/geodb.2024.05.03.V1.

References:


     [1] Wang, S. J., Gao, S., Huang, Y. Y., et al. Spatio-temporal evolution and trend prediction of urban carbon emission performance in China based on super-efficiency SBM model[J]. Acta Geographica Sinica, 2020, 75(6): 1316-1330.
     [2] Wang, S. H., Huang, L., Xu, X. L., et al. Spatio-temporal variation characteristics of ecological space and its ecological carrying status in mega-urban agglomerations [J]. Acta Geographica Sinica, 2022, 77(1): 164-181.
     [3] Dagum, C. A new approach to the decomposition of the Gini income inequality ratio [J]. Empirical Economics, 1997, 22(4): 515-531.
     [4] Dai, J. P., Khan, Y. A. Ecological environment pressure state and response system for coupling coordinate development: An application on China data [J]. Environmental Science and Pollution Research, 2023, 30(10): 25682-25690.
     [5] Hu, M. J., Li, Z. J., Ding, Z. S., et al. The evolution characteristics and threshold effects of the resource and environmental pressure in the Pan-Yangtze River Delta cities [J]. Scientia Geographica Sinica, 2020, 40(5): 701-709.
     [6] Dai, T. J., Wang, W. J., Liu, R. Spatio-temporal variation of resource and environmental pressure in China [J]. Resources Science, 2017, 39(10): 1942-1955.
     [7] Zhang, M., Yang, L. Y., Hu, Z. W., et al. Spatiotemporal differentiation and influencing mechanism of urban expansion in the Yangtze River Economic Belt, China [J]. Acta Geographica Sinica, 2024, 79(2): 439-461.
     [8] Zhang, Z. Q., Zhang, T., Feng, D. F. Study on regional differences, dynamic evolution and convergence of carbon emission intensity in China [J]. The Journal of Quantitative & Technological Economics, 2022, 39(4): 67-87.
     

Data Product:

ID Data Name Data Size Operation
1 EnvironPress_UR_YangtzeRiver1998-2021.xlsx 137.83KB
Co-Sponsors

Institute of Geographic Sciences and Natural Resources Research,Chinese Academy of Sciences

The Geographical Society of China

Parteners

Committee on Data for Science and Technology (CODATA) Task Group on Preservation of and Access to Scientific and Technical Data in/for/with Developing Countries (PASTD)

Jomo Kenyatta University of Agriculture and Technology

Digital Linchao GeoMuseum