Bridging Assessment and Planning Intervention: An Eye-Tracking-Enabled Decision Support Framework for Enhancing Streetscape Visual Esthetic Quality

Although urban streetscape visual esthetic quality (VAQ) assessment has progressed markedly, its findings are rarely operationalized in urban planning policy-making. The resulting discontinuity in the assessment–policy linkage is a critical impediment to streetscape VAQ enhancement. We propose an eye-tracking-enabled, end-to-end decision support framework that links evidence acquisition, intervention prioritization, design strategy formulation, and outcome feedback. Eye tracking is integrated to establish a three-dimensional assessment system spanning spatial, psychological, and physiological dimensions. Within this integrated system, we construct a three-level eye-tracking-based visual characteristics (ET-VC) framework across streetscape elements, formal characteristics, and public esthetic perception (PAP). Together, the three-dimensional system provides a theoretical basis for acquiring the multi-modal data required for VAQ enhancement. Building on this integrated assessment, we embed scenario planning theory to construct a planning facing decision model with PAP as the core outcome. The model combines importance-performance analysis (IPA) with the coupling coordination degree model (CCDM) to guide resource allocation decisions and intervention prioritization, and further uses eye-tracking evidence to support the development of refined, actionable enhancement strategies. A case study in Wudadao validates the framework’s robustness and feasibility. The ET-VC results provide additional evidence for interpreting esthetic perception: (1) ET-VC indicators differ significantly across streetscape elements, and “being viewed more” does not necessarily correspond to higher esthetic ratings; (2) four groups of key formal characteristic indicators—color configuration, naturalness, historicity and planning/regulatory control, and visual scale—systematically reshape fixation onset and maintenance patterns; and (3) PAP appears to involve partially nonlinear relationships between material landscape features and additional top-down influences (e.g., historical narratives and individual experience), rather than being fully explained by linear associations alone. Overall, this study provides both a theoretical basis and an applied demonstration for evidence-based streetscape VAQ enhancement.

Authors

Institutions

Publication Details

Journal
Land
Published
2026-04-02
DOI
https://doi.org/10.3390/land15040587
Primary Topic
Urban Green Space and Health
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Bridging Assessment and Planning Intervention: An Eye-Tracking-Enabled Decision Support Framework for Enhancing Streetscape Visual Esthetic Quality

Aihemaiti Namaiti, Libo Qiao, Ya’nan Fang, Bin Yao
Land
Urban Green Space and Health
article

Bridging Assessment and Planning Intervention: An Eye-Tracking-Enabled Decision Support Framework for Enhancing Streetscape Visual Esthetic Quality

Aihemaiti Namaiti, Libo Qiao, Ya’nan Fang, Bin Yao
article en

Abstract

Although urban streetscape visual esthetic quality (VAQ) assessment has progressed markedly, its findings are rarely operationalized in urban planning policy-making. The resulting discontinuity in the assessment–policy linkage is a critical impediment to streetscape VAQ enhancement. We propose an eye-tracking-enabled, end-to-end decision support framework that links evidence acquisition, intervention prioritization, design strategy formulation, and outcome feedback. Eye tracking is integrated to establish a three-dimensional assessment system spanning spatial, psychological, and physiological dimensions. Within this integrated system, we construct a three-level eye-tracking-based visual characteristics (ET-VC) framework across streetscape elements, formal characteristics, and public esthetic perception (PAP). Together, the three-dimensional system provides a theoretical basis for acquiring the multi-modal data required for VAQ enhancement. Building on this integrated assessment, we embed scenario planning theory to construct a planning facing decision model with PAP as the core outcome. The model combines importance-performance analysis (IPA) with the coupling coordination degree model (CCDM) to guide resource allocation decisions and intervention prioritization, and further uses eye-tracking evidence to support the development of refined, actionable enhancement strategies. A case study in Wudadao validates the framework’s robustness and feasibility. The ET-VC results provide additional evidence for interpreting esthetic perception: (1) ET-VC indicators differ significantly across streetscape elements, and “being viewed more” does not necessarily correspond to higher esthetic ratings; (2) four groups of key formal characteristic indicators—color configuration, naturalness, historicity and planning/regulatory control, and visual scale—systematically reshape fixation onset and maintenance patterns; and (3) PAP appears to involve partially nonlinear relationships between material landscape features and additional top-down influences (e.g., historical narratives and individual experience), rather than being fully explained by linear associations alone. Overall, this study provides both a theoretical basis and an applied demonstration for evidence-based streetscape VAQ enhancement.

LandVol. 15(4)
Tianjin Normal University (CN), Tianjin University (CN), Central China Normal University (CN)
Jilin Office of Philosophy and Social Science
Sustainable cities and communities
Openalex Percentile: Top 31%
Urban Green Space and Health
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.