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Article . 2023
License: CC BY
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Article . 2023
License: CC BY
Data sources: Datacite
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Article . 2023
License: CC BY
Data sources: Datacite
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Global Academic Frontiers
Article . 2023 . Peer-reviewed
License: CC BY
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Enhancing Management Efficiency in Natural Parks Globally through Big Data Technologies

Authors: Dong, Hongyi;

Enhancing Management Efficiency in Natural Parks Globally through Big Data Technologies

Abstract

The adoption of big data technologies offers significant potential for enhancing the management efficiency of natural parks worldwide, a critical component in the establishment and upkeep of international conservation systems. Innovating management techniques and improving efficiency have become urgent tasks for global natural park authorities. This study examines the present landscape of natural park management and highlights primary challenges faced when incorporating big data. Using human activity data as a model, the paper discusses the processes of data collection, analysis, treatment, and deployment, arguing that leveraging big data technologies to scientifically regulate human activities is essential for boosting natural park management efficiency. In addressing challenges related to the use of human activity data for enhancing management efficacy, recommendations are provided, focusing on refining overarching strategies, creating monitoring systems, broadening talent acquisition, utilizing big data to resolve management challenges, and emphasizing data governance.

Related Organizations
Keywords

Big Data, Natural Parks, Human Activity, Management

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    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
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    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
hybrid