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Boundary Dataset Based on Two Algorithms of the Hierarchical Solar Radiation Zones in China

HOU Jiang1
1 State Key Laboratory of Resource and Environmental Information Systems,Institute of Geographical Sciences and Resources Research,Chinese Academy of Sciences,Beijing 100101,China


Published:Jul. 2023

Visitors:444       Data Files Downloaded:18      
Data Downloaded:35.80 MB      Citations:

Key Words:

Solar radiation,Zoning boundary,Gaussian Mixture Model,Solar energy utilization


Solar radiation zoning is the foundation for guiding solar energy utilization and formulating regional development plans. An automatic zoning algorithm based on Gaussian mixture model is used to identify the solar radiation zones, whose number is adaptively determined by Bayesian inference. We use the ground observations of solar radiation at 98 stations of China from 2007 to 2020 for Gaussian mixture model fitting, and then puts spatially continuous solar radiation products from remote sensing images into the fitted model to identify the boundaries of adjacent zones. The zoning results are validated using sunshine-based solar radiation products at 716 weather stations of China. It is revealed that the zoning algorithm can divide stations with different solar radiation characteristics into plausible zones with an accuracy rate of approximately 90%. In addition, most inaccurate stations are located within the zone rather than near the boundaries, which further proves the reliability of the algorithm and identified boundaries. The dataset includes: (1) boundaries of 5 zones based on the total solar radiation; (2) boundaries of 10 zones based on the total and seasonal solar radiation. The dataset is archived in .shp data format, and consists of 14 data files with data size of 3.10 MB (Compressed into one file with 1.98 MB).

Foundation Item:

State Key Laboratory of Remote Sensing Science (OFSLRSS202204); National Natural Science Foundation of China (42201382)

Data Citation:

HOU Jiang. Boundary Dataset Based on Two Algorithms of the Hierarchical Solar Radiation Zones in China[J/DB/OL]. Digital Journal of Global Change Data Repository, 2023.


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Data Product:

ID Data Name Data Size Operation
1 SolarRadiationZones.rar 2036.74KB