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      Using data derived from cellular phone locations to estimate visitation to natural areas: An application to water recreation in New England, USA

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          Abstract

          We introduce and validate the use of commercially available human mobility datasets based on cell phone locations to estimate visitation to natural areas. By combining this data with on-the-ground observations of visitation to water recreation areas in New England, we fit a model to estimate daily visitation for four months to more than 500 sites. The results show the potential for this new big data source of human mobility to overcome limitations in traditional methods of estimating visitation and to provide consistent information at policy-relevant scales. However, the data providers’ opaque and rapidly developing methods for processing locational information required a calibration and validation against data collected by traditional means to confidently reproduce the desired estimates of visitation. We found that with this calibration, the high-resolution information in both space and time provided by cell phone location-derived data creates opportunities for developing next-generation models of human interactions with the natural environment.

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          A study of cross-validation and bootstrap for accuracy estimation and model selection in

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            Using social media to quantify nature-based tourism and recreation

            Scientists have traditionally studied recreation in nature by conducting surveys at entrances to major attractions such as national parks. This method is expensive and provides limited spatial and temporal coverage. A new source of information is available from online social media websites such as flickr. Here, we test whether this source of “big data” can be used to approximate visitation rates. We use the locations of photographs in flickr to estimate visitation rates at 836 recreational sites around the world, and use information from the profiles of the photographers to derive travelers' origins. We compare these estimates to empirical data at each site and conclude that the crowd-sourced information can indeed serve as a reliable proxy for empirical visitation rates. This new approach offers opportunities to understand which elements of nature attract people to locations around the globe, and whether changes in ecosystems will alter visitation rates.
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              A survey of results on mobile phone datasets analysis

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                Author and article information

                Contributors
                Role: ConceptualizationRole: Data curationRole: Formal analysisRole: InvestigationRole: MethodologyRole: Project administrationRole: SoftwareRole: SupervisionRole: ValidationRole: VisualizationRole: Writing – original draftRole: Writing – review & editing
                Role: ConceptualizationRole: Data curationRole: Formal analysisRole: MethodologyRole: ValidationRole: Writing – original draftRole: Writing – review & editing
                Role: ConceptualizationRole: Data curationRole: Formal analysisRole: InvestigationRole: MethodologyRole: ResourcesRole: ValidationRole: VisualizationRole: Writing – original draftRole: Writing – review & editing
                Role: ConceptualizationRole: SupervisionRole: Writing – original draftRole: Writing – review & editing
                Role: ConceptualizationRole: Data curationRole: Formal analysisRole: InvestigationRole: MethodologyRole: SoftwareRole: ValidationRole: VisualizationRole: Writing – original draftRole: Writing – review & editing
                Role: Editor
                Journal
                PLoS One
                PLoS ONE
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, CA USA )
                1932-6203
                30 April 2020
                2020
                : 15
                : 4
                : e0231863
                Affiliations
                [1 ] Atlantic Coastal Environmental Sciences Division, U.S. Environmental Protection Agency, Office of Research and Development, Center for Environmental Measurement and Modeling, Narragansett, Rhode Island, United States of America
                [2 ] Cooperative Institute for Marine & Atmospheric Studies, Rosenstiel School of Marine & Atmospheric Science, University of Miami, Miami, Florida, United States of America
                [3 ] Gulf Ecosystem Measurement and Modeling Division, U.S. Environmental Protection Agency, Office of Research and Development, Center for Environmental Measurement and Modeling, Gulf Breeze, Florida, United States of America
                University of Wisconsin Madison, UNITED STATES
                Author notes

                Competing Interests: The authors have declared that no competing interests exist.

                Author information
                http://orcid.org/0000-0003-3891-2833
                http://orcid.org/0000-0002-4776-0774
                Article
                PONE-D-19-32712
                10.1371/journal.pone.0231863
                7192446
                32352978
                e0a921e4-f25b-44a9-a687-4cc1b33d398b

                This is an open access article, free of all copyright, and may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose. The work is made available under the Creative Commons CC0 public domain dedication.

                History
                : 25 November 2019
                : 2 April 2020
                Page count
                Figures: 6, Tables: 3, Pages: 19
                Funding
                The author(s) received no specific funding for this work.
                Categories
                Research Article
                Biology and Life Sciences
                Psychology
                Behavior
                Recreation
                Social Sciences
                Psychology
                Behavior
                Recreation
                Engineering and Technology
                Equipment
                Communication Equipment
                Cell Phones
                Research and Analysis Methods
                Research Design
                Survey Research
                Census
                Computer and Information Sciences
                Geoinformatics
                Earth Sciences
                Geography
                Geoinformatics
                Computer and Information Sciences
                Information Technology
                Data Processing
                Computer and Information Sciences
                Data Management
                Earth Sciences
                Geography
                Human Geography
                Behavioral Geography
                Social Sciences
                Human Geography
                Behavioral Geography
                Earth Sciences
                Geography
                Human Geography
                Human Mobility
                Social Sciences
                Human Geography
                Human Mobility
                Custom metadata
                All relevant data are available at https://github.com/USEPA/Recreation_Benefits.git.

                Uncategorized
                Uncategorized

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