基于眼动的景观视觉质量评价——以大学生对宏村旅游景观图片的眼动实验为例

doi:10.18402/resci.2017.06.13

Abstract

Abstract:

Landscape visual quality assessment is the basis of rational planning,development,utilization and protection of tourism resources. Various assessment methods have their own advantages,but many deficiencies. Most existing evaluation methods are subjectively qualitative approaches. Here,we introduce eye-tracking analysis to landscape visual quality assessment using the rural tourism destination Hongcun as a case study. An eyetracker was used to record eye movement data while subjects looked at Hongcun landscape pictures. We combined SBE and SD to obtain the subjective evaluation of landscape visual quality,which were analyzed by correlation and regression analysis with eye movement index data. We found that subjects had different eye movement characteristics in four landscapes types,among which,there were significant differences in fixation frequency,average fixation duration and saccade frequency. The fixation points mainly focused on the main buildings,some prominent elements and the borders of landscape elements. The subjective evaluation of landscape visual quality was significantly correlated with fixation frequency,percentage of fixation duration, average fixation duration and percentage of saccade duration. The eye movement evaluation model of landscape visual quality was built. Visual quality values of four landscape types in Hongcun, settlement, ecology, agriculture and culture, calculated by the model, were 5.99, 5.98, 5.96 and 5.90. The model shows that a higher fixation frequency and a longer watching time（a lower percentage of fixation duration） produce a higher landscape visual quality assessment of tourism landscapes. Our method is a new tool to conduct landscape visual quality assessments.

Key words: landscape visual quality, eye movement experiments, tourism landscape, college students, Hongcun

Suling GUO, Ningxi ZHAO, Jianxin ZHANG, Ting XUE, Peixue LIU, Shuai XU, Dandan XU. Landscape visual quality assessment based on eye movement:college student eye-tracking experiments on tourism landscape pictures[J].Resources Science, 2017, 39(6): 1137-1147.

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眼动指标	简写	基本意义
注视频率/（次/s）	FF	注视次数与注视时间之比,反映评价区域受重视程度的指标,注视频率高则表示被试对图片感觉重要或较为感兴趣
注视时间比重	PFD	注视总时间与观察总时间的比值,注视时间比重越小,说明被试对图片的观察时间相对较长而注视总时间相对较短
平均注视时间/（ms）	AFD	被试对每个注视点停留的平均时间,被试对图片认知越努力,其在注视点停留的平均时间就越长。
眼跳频率/（次/s）	SF	单位时间内的眼跳次数,能够反映被试的搜素行为。在信息搜索过程中眼动频率高表明被试的搜索量大,其所观察的图片的特征不鲜明
眼跳时间比重	PSD	眼跳总时间与观察总时间的比值,反映被试在选取注视点上所用的时间
平均眼跳幅度/度	ASA	反映获取信息的范围。平均眼跳幅度越大表示图片特征越鲜明,被试能够直接到达目标区
平均眼跳速度/（度/s）	ASV	评价被试获取信息范围大小的指标,反映图片信息的鲜明特征

眼动指标	FF	PFD	AFD	SF	PSD	ASA	ASV
总体差异（sig.）	0.000*	0.981	0.034*	0.003*	0.470	0.111	0.747
景观类型间差异
聚落景观（a）	2.54^d	0.84	355.91	2.44^d	0.07	2.65	84.00
生态景观（b）	2.57^d	0.85	360.86	2.43^d	0.07	2.86	86.47
农业景观（c）	2.47^d	0.85	406.60	2.30^d	0.06	2.41	82.24
文化景观（d）	2.21^abc	0.85	424.48	2.08^abc	0.07	3.97	88.48

		FF	PFD	AFD	SF	PSD	ASA	ASV
VQ	Pearson相关性	0.105*	-0.127**	-0.113*	0.075	0.101*	0.033	0.072
	显著性	0.023	0.006	0.014	0.102	0.028	0.469	0.119
	N	472	472	472	472	472	472	472

		非标准化系数		标准系数	t	Sig.
		B	标准误差	试用版	t	Sig.
模型1	（常量）	6.899	0.347		19.889	0.000
	注视时间比重	-1.120	0.402	-0.127	-2.786	0.006
模型2	（常量）	6.455	0.383		16.851	0.000
	注视时间比重	-1.248	0.402	-0.142	-3.101	0.002
	注视频率	0.226	0.085	0.122	2.658	0.008

景观类型	主观评价得分	预测评价得分
聚落景观	5.85	6.01
生态景观	6.98	5.96
农业景观	5.81	5.96
文化景观	5.98	5.96

Landscape visual quality assessment based on eye movement:college student eye-tracking experiments on tourism landscape pictures

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