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Measurement of Forest Ecological Benefits Based on Big Data

Author

Listed:
  • Hua Li

    (Department of Biomedicine and Health Sciences, Shanghai Vocational College of Agriculture and Forestry, Shanghai 201699, China)

  • Shuo Liu

    (Heilongjiang Institute of Construction Technology, Harbin 150025, China
    College of Wildlife and Protected Area, Northeast Forestry University, Harbin 150040, China)

  • Tijiu Cai

    (College of Forestry, Northeast Forestry University, Harbin 150040, China)

Abstract

Socioeconomic development combined with the development and utilization of forest resources have resulted in the forest ecological environment becoming more and more valuable, and its impact on the national economy has also increased. Firstly, based on a modern statistical model, the dependent variable and independent variable set of standardized forest ecological benefits were determined, and the seemingly unrelated forest ecological benefit model was established. According to the alternative market method and market approximation theory, the first and second monetary models of forest ecological benefit value were constructed using the market approximation coefficient, the effective area coefficient, and the physical quantity conversion coefficient. Next, the concept of “whole diffusion” was introduced into the establishment of the forest ecological benefit model, and the whole diffusion model was established to estimate the physical amount of forest ecological benefits. The concepts of classical forest ecological benefit and generalized forest ecological benefit were proposed. Forest management survey data were used to measure forest ecological benefit, and classic ecological benefit and generalized forest benefit were integrated into one system for the first time. The economic value is 94.31 million RMB ¥.

Suggested Citation

  • Hua Li & Shuo Liu & Tijiu Cai, 2022. "Measurement of Forest Ecological Benefits Based on Big Data," Sustainability, MDPI, vol. 14(12), pages 1-14, June.
    • Handle: RePEc:gam:jsusta:v:14:y:2022:i:12:p:7248-:d:837952
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    References listed on IDEAS

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