Research on visual experience evaluation of fortress heritage landscape by integrating SBE–SD method and eye movement analysis

IF 2.6 1区 艺术学 Q2 CHEMISTRY, ANALYTICAL Heritage Science Pub Date : 2024-08-05 DOI:10.1186/s40494-024-01397-w
Xiang Xu, Rui Dong, Zhixing Li, Yuxiao Jiang, Paolo Vincenzo Genovese
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Abstract

Urbanization has led to homogenizing heritage site landscapes, and the protective measures have become disconnected from public needs. Additionally, the complex and diverse overall characteristics of heritage sites and the uneven distribution of values across different areas are related to the lack of landscape experience assessment. The “subjective + objective” cognitive evaluation and visual perception framework that adopts the Scenic Beauty Estimation Procedure-Semantic Differential (SBE–SD) method and eye-tracking analysis can compensate for the limitations of a single evaluation method by integrating quantitative and qualitative analysis. This research takes the Yi’an Fortress in Zhangpu County, Fujian Province, as the object and examines the visual experiences of different areas and types of landscapes within the Yi’an Fortress. The findings reveal several key insights: (1) Significant differences were found in the landscape experiences of different areas within the heritage site. The visual experience score of the core building area of Yi’an Fortress is (1.01) > the heritage entrance area (0.897) > the residential area (0.841) > the natural ecological area (0.784), indicating that the natural ecological area should be the focus of future protection and development efforts, with a particular emphasis on enhancing the ‘landscape aesthetic’ and ‘landscape cultural’ aspects. (2) The landscape experience scores can be used to understand the reasons for the differences in participants’ experiences of different landscapes. The architectural heritage landscape of the Yi’an Fortress scored highest in the experience evaluation due to its superior performance in terms of ‘landscape form’ factors. The cultural decorative landscape scored next, while the garden greening landscape scored the lowest, due to their poorer performance in terms of ‘landscape form’ and ‘landscape aesthetics’. (3) The eye-tracking data was consistent with the results of the subjective evaluation, validating the “subjective + objective” cognitive evaluation and visual perception framework, employing the SBE–SD method and eye-tracking analysis is a scientific and effective method for assessing the visual experience of heritage landscapes. These results provide a scientific basis for the heritage planners and managers of the Yi’an fortress to improve the landscape environment, better meet public needs, and preserve the unique character of this vital cultural resource. Furthermore, this study offers a new research method and approach for the protection of other heritage landscapes.

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结合 SBE-SD 方法和眼动分析法的要塞遗产景观视觉体验评价研究
城市化导致遗产地景观同质化,保护措施与公众需求脱节。此外,遗产地整体特征复杂多样,不同区域价值分布不均,也与景观体验评估的缺失有关。采用风景美学估算程序-语义差分法(SBE-SD)和眼动跟踪分析的 "主观+客观 "认知评价和视觉感知框架,通过定量分析和定性分析相结合的方法,可以弥补单一评价方法的局限性。本研究以福建省漳浦县义安堡为对象,考察了义安堡内不同区域、不同类型景观的视觉体验。研究结果揭示了以下几个重要启示:(1)遗产地内不同区域的景观体验存在显著差异。义安堡核心建筑区的视觉体验得分(1.01);遗产入口区的视觉体验得分(0.897);居住区的视觉体验得分(0.841);自然生态区的视觉体验得分(0.784)。(2) 通过景观体验得分可以了解参与者对不同景观体验差异的原因。义安堡的建筑遗产景观由于在 "景观形式 "方面表现出色,在体验评价中得分最高。文化装饰景观得分次之,园林绿化景观得分最低,这是因为它们在 "景观形式 "和 "景观美学 "方面表现较差。(3)眼动数据与主观评价结果一致,验证了 "主观+客观 "的认知评价和视觉感知框架,采用 SBE-SD 方法和眼动分析是评价遗产景观视觉感受的科学有效方法。这些结果为义安堡的遗产规划者和管理者改善景观环境、更好地满足公众需求、保护这一重要文化资源的独特性提供了科学依据。此外,这项研究还为其他遗产景观的保护提供了新的研究方法和途径。
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来源期刊
Heritage Science
Heritage Science Arts and Humanities-Conservation
CiteScore
4.00
自引率
20.00%
发文量
183
审稿时长
19 weeks
期刊介绍: Heritage Science is an open access journal publishing original peer-reviewed research covering: Understanding of the manufacturing processes, provenances, and environmental contexts of material types, objects, and buildings, of cultural significance including their historical significance. Understanding and prediction of physico-chemical and biological degradation processes of cultural artefacts, including climate change, and predictive heritage studies. Development and application of analytical and imaging methods or equipments for non-invasive, non-destructive or portable analysis of artwork and objects of cultural significance to identify component materials, degradation products and deterioration markers. Development and application of invasive and destructive methods for understanding the provenance of objects of cultural significance. Development and critical assessment of treatment materials and methods for artwork and objects of cultural significance. Development and application of statistical methods and algorithms for data analysis to further understanding of culturally significant objects. Publication of reference and corpus datasets as supplementary information to the statistical and analytical studies above. Description of novel technologies that can assist in the understanding of cultural heritage.
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