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FOREST RESOURCES WANAGEMENT ›› 2022, Vol. 0 ›› Issue (5): 7-14.doi: 10.13466/j.cnki.lyzygl.2022.05.002

• Integrated M lanagement and Administration • Previous Articles     Next Articles

Improving the Management Efficiency of Natural Parks Based on Big Data Technology:Taking Big Data for Human Activity as an Example

WANG Shanghui1(), WANG Taiqi2   

  1. 1. National Park(Natural Protected Area)Development Centre of National Forestry and Grassland Administration,Beijing 100714,China
    2. Aspire Information Technology(Beijing)Co.,Ltd.,Beijing 100071,China
  • Received:2022-07-27 Revised:2022-10-08 Online:2022-10-28 Published:2022-12-23

Abstract:

Improving the management efficiency of natural parks based on big data technology is of great practical significance for building a natural protected area system with national parks as the main body and ensuring effective coordination between the protection and rational utilization of natural parks.It is an important task for natural parks to innovate management mode continually and further improve management efficiency.This paper analyzed the current situation of the management of natural parks and the main problems faced with the use of big data,explored the path of using big data technology to improve the management efficiency of natural parks,and took the big data of human activities as an example to analyze and demonstrate the collection,analysis,processing and specific application of big data.It was believed that the use of big data technology to scientifically limit human activities was the key to improve the efficiency of natural park management.In view of the problems of using human activity big data to improve management efficiency,this paper put forward some suggestions on using human activity big data to improve management efficiency of natural parks from the aspects of improving top-level design,building monitoring system,broadening talent channels,using big data to solve management problems and focusing on data governance.

Key words: natural park, human activities, big data, management

CLC Number: