Replication data for: Quantifying tourism booms and the increasing footprint in the Arctic with social media data (doi:10.18710/QEOFPY)

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Part 2: Study Description
Part 3: Data Files Description
Part 4: Variable Description
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Replication data for: Quantifying tourism booms and the increasing footprint in the Arctic with social media data

doi:10.18710/QEOFPY

DataverseNO

2020-02-06

1

Runge, Claire A.; Daigle, Remi M.; Hausner, Vera H., 2020, "Replication data for: Quantifying tourism booms and the increasing footprint in the Arctic with social media data", https://doi.org/10.18710/QEOFPY, DataverseNO, V1, UNF:6:czqP04pzsqnMiDPqDgKLpg== [fileUNF]

Replication data for: Quantifying tourism booms and the increasing footprint in the Arctic with social media data

doi:10.18710/QEOFPY

Runge, Claire A. (UiT The Arctic University of Norway)

Daigle, Remi M. (Département de biologie, Université Laval, Québec, Canada)

Hausner, Vera H. (UiT The Arctic University of Norway)

UiT The Arctic University of Norway

RConnected

CONNECT

247474

DataverseNO

UiT The Arctic University of Norway

Runge, Claire A.

Runge, Claire Alice

2019-03-22

https://doi.org/10.18710/QEOFPY

Earth and Environmental Sciences, Social Sciences, Arctic, tourism, tourism management, trend analysis, Flickr, geography, social media, passive crowdsourcing, spatiotemporal trends, environmental impacts

Arctic tourism has rapidly increased in the past two decades. We used social media data to examine localized tourism booms and quantify the spatial expansion of the Arctic tourism footprint. We extracted geotagged locations from over 800,000 photos on Flickr and mapped these across space and time. We critically examine the use of social media as a data source in data-poor regions, and find that while social media data is not suitable as an early warning system of tourism growth in less visited parts of the world, it can be used to map changes at large spatial scales. Our results show that the footprint of summer tourism quadrupled and winter tourism increased by over 600% between 2006 and 2016, although large areas of the Arctic remain untouched by tourism. This rapid increase in the tourism footprint raises concerns about the impacts and sustainability of tourism on Arctic ecosystems and communities. This boom is set to continue, as new parts of the Arctic are being opened to tourism by melting sea ice, new airports and continued promotion of the Arctic as a ‘last chance to see’ destination. Arctic societies face complex decisions about whether this ongoing growth is socially and environmentally sustainable.

2004-01-01-2017-12-31

2017-12-04-2018-05-07

Norway, Finland, Iceland, Faroe Islands, Russian Federation, Greenland, Svalbard and Jan Mayen, Canada, United States

Alaska

• West Bounding Longitude: 180
• East Bounding Longitude: -180
• South Bounding Latitude: 60
• North Bounding Latitude: 90

Datasets derived from geospatially tagged photographs

please see manuscript for full description of methods.

https://www.flickr.com

https://www.flickr.com/services/api/

Runge CA, Daigle RM, Hausner VH. 2020. Quantifying tourism booms and the increasing footprint in the Arctic with social media data. PLOS ONE 15:e0227189.

10.1371/journal.pone.0227189

Runge CA, Daigle RM, Hausner VH. 2020. Quantifying tourism booms and the increasing footprint in the Arctic with social media data. PLOS ONE 15:e0227189.

• Number of cases: 84

• No. of variables per record: 7

• Type of File: text/tab-separated-values

UNF:6:KBnYvwOlStVgdrbYH3B9Ig==

• Number of cases: 28

• No. of variables per record: 7

• Type of File: text/tab-separated-values

UNF:6:38kZzr3tTR4dOUV5Fgz+bQ==

• yearseason - yearseason
• year - year
• season - season
• type - type
• sample_size - sample_size
• footprint - footprint
• footprint_percent - footprint_percent
• yearseason - yearseason
• year - year
• season - season
• Total Flickr Photos - Total Flickr Photos
• Arctic photos - Arctic photos
• Global increase - Global increase
• Percent Traffic - Percent Traffic

f6940 Location:

Variable Format: character

Notes: UNF:6:Jtnp/lg+DtBjSyeSHESheg==

f6940 Location:

Summary Statistics: Mean 2010.5; Min. 2004.0; StDev 4.05534007606392; Max. 2017.0; Valid 84.0

Variable Format: numeric

Notes: UNF:6:6RV0/+mneSDKH8vPJ8NlCg==

f6940 Location:

Variable Format: character

Notes: UNF:6:qWCa8VIVYe3WyZ2Owtl/Og==

f6940 Location:

Variable Format: character

Notes: UNF:6:mMTK08Sl3t1rl06rTjepwA==

f6940 Location:

Summary Statistics: Max. 4807.0; Mean 1222.8214285714284; Valid 56.0; Min. 241.0; StDev 1117.265657464978;

Variable Format: numeric

Notes: UNF:6:7Tdc+COpISeNUflKj90dVQ==

f6940 Location:

Summary Statistics: Mean 6.887109487737075E-4; Valid 84.0; Min. 3.65709893097979E-5; StDev 8.721813547756617E-4; Max. 0.00384855881618991

Variable Format: numeric

Notes: UNF:6:EsPMk34ZTu/SPR6jEaErag==

f6940 Location:

Summary Statistics: Valid 84.0; Max. 0.384855881618991; Min. 0.00365709893097979; Mean 0.06887109487737075; StDev 0.08721813547756617

Variable Format: numeric

Notes: UNF:6:keBGaK1btB6/9Ana1Yub7g==

f6939 Location:

Variable Format: character

Notes: UNF:6:OZpXLVv+fpfiU7+mZ/wlLw==

f6939 Location:

Summary Statistics: Mean 2010.5; Valid 28.0; StDev 4.1051007115358145; Max. 2017.0; Min. 2004.0;

Variable Format: numeric

Notes: UNF:6:LDqwxGoNgLGmQOukBNZoJg==

f6939 Location:

Variable Format: character

Notes: UNF:6:vdwRZ/kGWG///mePOFM5Sw==

f6939 Location:

Summary Statistics: Max. 2.31337858E8; Mean 1.407351822142857E8; Valid 28.0; Min. 7827070.0; StDev 6.668535161780985E7

Variable Format: numeric

Notes: UNF:6:QFpYLXxyZpOeV+Vv8jeuZA==

f6939 Location:

Summary Statistics: Mean 28588.535714285714; StDev 25615.010435119286; Valid 28.0; Max. 81980.0; Min. 287.0

Variable Format: numeric

Notes: UNF:6:95L84OUhXeA7hPs6XXyauA==

f6939 Location:

Summary Statistics: Valid 28.0; Mean 14.488788808501166; Min. 1.0; StDev 6.818489352206656; Max. 23.0901279789244

Variable Format: numeric

Notes: UNF:6:6uLNk01Z+oQMaFS8X9ehgQ==

f6939 Location:

Summary Statistics: Mean 1.6510638053649526E-4; Max. 4.02021234086809E-4; Min. 3.08385811803383E-5; StDev 1.0786397099223014E-4; Valid 28.0

Variable Format: numeric

Notes: UNF:6:y8T2kN2K8ciG4GJ6lM5xhw==

Label:

00_Readme.txt

Text:

Contains descriptions of data files and column headers

text/plain

Label:

Flickr_density_mapping.r

Text:

R script to create rasters of Flickr PUD across the Arctic

type/x-r-syntax

Label:

Flickr_photos_per_year.R

Text:

R script to download global stats on number of photos submitted to Flickr

type/x-r-syntax

Label:

Flickr_PUDper100kmcell_summer.tif

Text:

Raster of tourism intensity in Arctic summer at 100km resolution

image/tiff

Label:

Flickr_PUDper100kmcell_winter.tif

Text:

Raster of tourism intensity in Arctic winter at 100km resolution

image/tiff

Label:

Flickr_PUDper10kmcell_summer.tif

Text:

Raster of tourism intensity in Arctic summer at 10km resolution

image/tiff

Label:

Flickr_PUDper10kmcell_winter.tif

Text:

Raster of tourism intensity in Arctic winter at 10km resolution

image/tiff

Label:

Flickr_spatialoverlaps_for_gams.r

Text:

R script to create hexagonal grids, spatial overlap grid with accessibility and protected area shapefiles to estimate coverage in each grid cell. Spatial overlap of each grid cell with Flickr data.

type/x-r-syntax

Label:

GAM_footprint.r

Text:

R script to calculate Arctic tourism footprint and make tables & figures for manuscript.

type/x-r-syntax

Label:

GAM_models.r

Text:

R script to make GAM models of accessibility vs presence/absence of tourists and make tables & figures for manuscript.

type/x-r-syntax

Label:

GAM_model_input.R

Text:

R script to calculate PUD (photo-unit-days) in each grid cell.

type/x-r-syntax

Label:

raw_data_download.r

Text:

R script to download Flickr data for the Arctic

type/x-r-syntax