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The scale effects of landscape variables on landscape experiences: a multi-scale spatial analysis of social media data in an urban nature park context

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Abstract

Context

The roles of landscape variables regarding the recreational services provided by nature parks have been widely studied. However, the potential scale effects of the relationships between landscape variables and categorized nature experiences have not been adequately studied from an experimental perspective.

Objectives

This article demonstrates multiscale geographically weighted regression (MGWR) as a new method to quantify the relationship between experiences and landscape variables and aims to answer the following questions: (1) Which dimensions of landscape experiences can be interpreted from geocoded social media data, and how are these experiences associated with specific landscape variables? (2) At what spatial scale and relative magnitude can landscape variables mediate landscape experiences?

Methods

Social media data (Flickr photos) from Amager Nature Park were categorized into different dimensions of landscape experience. Estimated parameter surfaces resulted from the MGWR were generated to show the patterns of the relationship between the landscape variables and the categorized experiences.

Results

All considered landscape variables were identified as relating to certain landscape experiences (nature, animals, scenery, engagement, and culture). Scale effects were observed in all relationships. This highlights the realities of context- and place-specific relationships as well as the limited applicability of simple approaches that are incapable of accounting for spatial heterogeneity and scale.

Conclusions

The spatial effect of landscape variables on landscape experiences was clarified and demonstrated to be important for understanding the spatial patterns of landscape experiences. The demonstrated modelling method may be used to further the study of the value of natural landscapes to human wellbeing.

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Fig. 1

source: Open Street Map, Styrelsen for Dataforsyning og Effektivisering, Basemap of Denmark, 2018)

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Data availability

The datasets generated during and/or analyzed during the current study are available from the corresponding author on reasonable request.

Code availability

The Python scripts used to produce dataset in the study is available from the corresponding author on reasonable request.

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Acknowledgements

We are grateful to the anonymous reviewers for their valuable comments on the manuscript of this paper. PC gratefully acknowledges the funding from China Scholarship Council.

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PC is funded by China Scholarship Council.

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Both authors contributed to the conceptualization and methodology of the study and manuscript writing and reviewing. PC performed formal analysis, investigation, visualization, and software. ASO provided resources and supervision.

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Correspondence to Ping Chang.

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Chang, P., Olafsson, A.S. The scale effects of landscape variables on landscape experiences: a multi-scale spatial analysis of social media data in an urban nature park context. Landsc Ecol 37, 1271–1291 (2022). https://doi.org/10.1007/s10980-022-01402-2

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