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Related Experiment Video

Updated: Aug 20, 2025

Measuring the Structure, Composition, and Change of Underwater Environments with Large-area Imaging
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Valuing Protected Area Tourism Ecosystem Services Using Big Data.

Adam Loch1, Glen Scholz2, Christopher Auricht3

  • 1Centre for Global Food and Resources, School of Economics and Public Policy, Level 6 - 10 Pulteney Street, The University of Adelaide, Adelaide, SA, Australia. adam.loch@adelaide.edu.au.

Environmental Management
|November 17, 2022
PubMed
Summary
This summary is machine-generated.

Protected areas in South Australia generated AU$373.8 million in economic value in 2018-19. This study utilized big data from booking systems to provide a comprehensive estimate of tourism expenditure, improving conservation and funding decisions.

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Area of Science:

  • Environmental Economics
  • Conservation Science
  • Tourism Management

Background:

  • Protected areas are crucial for biodiversity conservation and provide significant visitor benefits.
  • Accurate economic valuation of protected areas aids governments in resource allocation for conservation efforts.
  • Traditional survey methods often have limitations in capturing the full economic impact of protected areas.

Purpose of the Study:

  • To estimate the tourism ecosystem service expenditure values for a regional protected area network in South Australia.
  • To demonstrate the advantage of using big data from booking systems over traditional survey data.
  • To provide a comprehensive expenditure estimate for funding narratives and protected area expansion.

Main Methods:

  • Utilized direct transactional data, travel costs, and economic multipliers for value estimation.
  • Leveraged a comprehensive booking system dataset to overcome limitations of survey data.
  • Applied combined estimation methods to big datasets for a full area network expenditure estimate.

Main Results:

  • South Australian protected areas generated AU$373.8 million in economic value in the 2018-19 base year.
  • Big data approaches provided a unique, full area network expenditure estimate, improving upon typical survey methods.
  • The study highlighted the value of investing in big data for protected area management.

Conclusions:

  • Combined estimation methods with big data sets offer valuable baseline expenditure information for conservation and tourism sites.
  • Protected area managers benefit from investing in big data for comprehensive economic impact assessments.
  • The findings support funding narratives and protected area expansion, aligning with global conservation targets.