Crowdsourcing indicators for cultural ecosystem services: A geographically weighted approach for mountain landscapes

Tenerelli, Patrizia; Demšar, Urška; Luque, Sandra

doi:10.1016/j.ecolind.2015.12.042

Cited by 233 publications

(167 citation statements)

References 77 publications

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“…al 2010, Casalegno et al 2013, Tenerelli et al 2016). The analysis involved several photo-sharing websites to overcome the limitations of a study focused on just one community and one online service.…”

Section: Discussionmentioning

confidence: 99%

“…In contrast to Kisilevich et al's (2010) study, which focused on temporal patterns, we examined spatial patterns. After a preliminary analysis of data, we decided to focus on the number of users (as did Girardin et al 2008, Kisilevich et al 2010, Casalegno et al 2013, rather than the numbers of pictures (as did Antoniou et al 2010, Richards and Freiss 2015, and Tenerelli et al 2016. Some individuals share many pictures of an area in relation to a specific interest that is not related to the natural environment; therefore, an approach based on the density of pictures can be misleading in drawing conclusions.…”

Section: Methodsmentioning

confidence: 99%

“…Urban centrality was the target of another qualitative evaluation based on the density of pictures shared online (Hollenstein and Purves 2010). http://www.ecologyandsociety.org/vol21/iss3/art6/ Casalegno et al (2013), Richards and Friess (2015), and Tenerelli et al (2016) made the only attempts at explicitly targeting the detection of CES through a photo-sharing application. We therefore conclude that there is a rising number of studies that use photo-sharing applications to detect spatial preferences.…”

Section: Georeferenced Crowdsourced Information and Placesmentioning

confidence: 99%

“…In another use of Flickr, Richards and Friess (2015) focused on a small-scale analysis in a park, developing the spatial analysis further to include the analysis of environments and focal points. Tenerelli et al (2016) used the number of pictures shared on Panoramio and Flickr to apply a geographical weighted regression to derive CES. Kachkaev and Wood (unpublished manuscripts) created a leisure pedestrian navigation system eliciting people's preferences from a blend of four online photosharing services.…”

Section: Actions As Proxies Of Preferencesmentioning

confidence: 99%

See 3 more Smart Citations

Using crowdsourced imagery to detect cultural ecosystem services: a case study in South Wales, UK

Gliozzo¹,

Pettorelli²,

Haklay³

2016

E&S

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ABSTRACT. Within ecological research and environmental management, there is currently a focus on demonstrating the links between human well-being and wildlife conservation. Within this framework, there is a clear interest in better understanding how and why people value certain places over others. We introduce a new method that measures cultural preferences by exploring the potential of multiple online georeferenced digital photograph collections. Using ecological and social considerations, our study contributes to the detection of places that provide cultural ecosystem services. The degree of appreciation of a specific place is derived from the number of people taking and sharing pictures of it. The sequence of decisions and actions taken to share a digital picture of a given place includes the effort to travel to the place, the willingness to take a picture, the decision to geolocate the picture, and the action of sharing it through the Internet. Hence, the social activity of sharing pictures leaves digital proxies of spatial preferences, with people sharing specific photos considering the depicted place not only "worth visiting" but also "worth sharing visually." Using South Wales as a case study, we demonstrate how the proposed methodology can help identify key geographic features of high cultural value. These results highlight how the inclusion of geographical user-generated content, also known as volunteered geographic information, can be very effective in addressing some of the current priorities in conservation. Indeed, the detection of the most appreciated nonurban areas could be used for better prioritization, planning, and management.

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Section: Discussionmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Georeferenced Crowdsourced Information and Placesmentioning

confidence: 99%

Section: Actions As Proxies Of Preferencesmentioning

confidence: 99%

See 2 more Smart Citations

Using crowdsourced imagery to detect cultural ecosystem services: a case study in South Wales, UK

Gliozzo¹,

Pettorelli²,

Haklay³

2016

E&S

View full text Add to dashboard Cite

show abstract

“…The study's confirmation of the similarity of maps from different social media platforms (Panoramio, Flickr, and Instagram) indicates that crowdsourcing this type of data provides a reliable indicator of landscape perceptions. Additional efforts have reiterated the applicability of social media for understanding tourism appreciation [75,76], cultural ecosystem services [77,78], and other perceived landscape values [79]. The geographic locations represented in these data, and the photos and commentary volunteered on platforms like Instagram, provide valuable information about intensity of use at specific locations and the objects being appreciated (e.g.…”

Section: Mapping With Volunteered Geographic Informationmentioning

confidence: 99%

Integrating Spatially Explicit Representations of Landscape Perceptions into Land Change Research

Dorning

Berkel

Semmens

2017

Curr Landscape Ecol Rep

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Purpose of Review Human perceptions of the landscape can influence land-use and land-management decisions. Recognizing the diversity of landscape perceptions across space and time is essential to understanding land change processes and emergent landscape patterns. We summarize the role of landscape perceptions in the land change process, demonstrate advances in quantifying and mapping landscape perceptions, and describe how these spatially explicit techniques have and may benefit land change research. Recent Findings Mapping landscape perceptions is becoming increasingly common, particularly in research focused on quantifying ecosystem services provision. Spatial representations of landscape perceptions, often measured in terms of landscape values and functions, provide an avenue for matching social and environmental data in land change studies. Integrating these data can provide new insights into land change processes, contribute to landscape planning strategies, and guide the design and implementation of land change models. Summary Challenges remain in creating spatial representations of human perceptions. Maps must be accompanied by descriptions of whose perceptions are being represented and the validity and uncertainty of those representations across space. With these considerations, rapid advancements in mapping landscape perceptions hold great promise for improving representation of human dimensions in landscape ecology and land change research.

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Crowd‐sourced data reveal social–ecological mismatches in phenology driven by climate

Breckheimer

Theobald

Cristea

et al. 2019

Frontiers in Ecol & Environ

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Shifts in phenology that are driven by climate change have substantial impacts on ecosystems, but the effects of these ecological shifts on coupled social–ecological systems remain largely unexplored. Using a large database of crowd‐sourced photographs from the image‐hosting website Flickr, we show that early snow disappearance conditions similar to those expected by the late 21st century cause the seasonal peak of human visitation at Mount Rainier National Park (NP) to become mismatched from the seasonal peak of wildflower displays, a key visitor draw. Our work indicates that these mismatches between social and ecological systems were a product of both visitor behavior and management constraints, and could fundamentally alter visitor experiences in iconic natural areas like Mount Rainier NP. Recent dramatic growth in the volume of georeferenced citizen‐based observations and the increased availability of high‐resolution climate data will soon make it feasible to examine how climate affects social–ecological mismatches at very large spatial scales.

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Crowdsourcing indicators for cultural ecosystem services: A geographically weighted approach for mountain landscapes

Cited by 233 publications

References 77 publications

Using crowdsourced imagery to detect cultural ecosystem services: a case study in South Wales, UK

Using crowdsourced imagery to detect cultural ecosystem services: a case study in South Wales, UK

Integrating Spatially Explicit Representations of Landscape Perceptions into Land Change Research

Crowd‐sourced data reveal social–ecological mismatches in phenology driven by climate

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