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Assessing Experienced Tranquillity Through Natural Language Processing and Landscape Ecology Measures

Overview
Journal Landsc Ecol
Publisher Springer
Date 2021 Nov 1
PMID 34720411
Citations 2
Authors
Flurina M Wartmann
Olga Koblet
Ross S Purves
Affiliations
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Abstract

Context: Identifying tranquil areas is important for landscape planning and policy-making. Research demonstrated discrepancies between modelled potential tranquil areas and where people experience tranquillity based on field surveys. Because surveys are resource-intensive, user-generated text data offers potential for extracting where people experience tranquillity.

Objectives: We explore and model the relationship between landscape ecological measures and experienced tranquillity extracted from user-generated text descriptions.

Methods: Georeferenced, user-generated landscape descriptions from Geograph.UK were filtered using keywords related to tranquillity. We stratify resulting tranquil locations according to dominant land cover and quantify the influence of landscape characteristics including diversity and naturalness on explaining the presence of tranquillity. Finally, we apply natural language processing to identify terms linked to tranquillity keywords and compare the similarity of these terms across land cover classes.

Results: Evaluation of potential keywords yielded six keywords associated with experienced tranquillity, resulting in 15,350 extracted tranquillity descriptions. The two most common land cover classes associated with tranquillity were , and , followed by and . In the logistic regression model across all land cover classes, freshwater, elevation and naturalness were positive predictors of tranquillity. Built-up area was a negative predictor. Descriptions of tranquillity were most similar between and and most dissimilar between and

Conclusions: This study highlights the potential of applying natural language processing to extract experienced tranquillity from text, and demonstrates links between landscape ecological measures and tranquillity as a perceived landscape quality.

Supplementary Information: The online version of this article (10.1007/s10980-020-01181-8) contains supplementary material, which is available to authorized users.

Citing Articles

Past and future uses of text mining in ecology and evolution.

Farrell M, Brierley L, Willoughby A, Yates A, Mideo N Proc Biol Sci. 2022; 289(1975):20212721.

PMID: 35582795 PMC: 9114983. DOI: 10.1098/rspb.2021.2721.

Landscape ecology reaching out.

Kienast F, Walters G, Burgi M Landsc Ecol. 2021; 36(8):2189-2198.

PMID: 34334950 PMC: 8310730. DOI: 10.1007/s10980-021-01301-y.

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