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 arable and horticulture, and improved grassland, followed by urban and suburban. 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 improved grassland and arable and horticulture, and most dissimilar between arable and horticulture and urban.

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.

中文翻译：

---

通过自然语言处理和景观生态措施评估体验的宁静

语境

确定宁静的区域对于景观规划和政策制定非常重要。研究表明，根据实地调查，模拟的潜在宁静区域与人们体验宁静的区域之间存在差异。由于调查是资源密集型的，用户生成的文本数据提供了提取人们体验安宁的地方的潜力。

目标

我们探索和建模从用户生成的文本描述中提取的景观生态措施与体验的宁静之间的关系。

方法

使用与宁静相关的关键字过滤来自 Geograph.UK 的地理参考、用户生成的景观描述。我们根据主要土地覆盖对产生的宁静位置进行分层，并量化景观特征（包括多样性和自然性）对解释宁静存在的影响。最后，我们应用自然语言处理来识别与宁静关键词相关的术语，并比较这些术语在土地覆盖类别中的相似性。

结果

对潜在关键词的评估产生了六个与体验宁静相关的关键词，从而提取了 15,350 个宁静描述。与宁静相关的两个最常见的土地覆盖类别是耕地和园艺，以及改良的草地，其次是城市和郊区。在所有土地覆盖类别的逻辑回归模型中，淡水、海拔和自然度是宁静的积极预测因素。建筑面积是一个负面预测因素。改良草地与耕地和园艺之间的宁静描述最相似，而耕地与园艺和城市的。

结论

本研究强调了应用自然语言处理从文本中提取体验的宁静的潜力，并展示了景观生态措施与作为感知景观质量的宁静之间的联系。