DOI: 10.57760/sciencedb.30725
title: A Study on the Mechanism of How the Color Scheme of Lifestyle Streets Affects Residents' Mental Health study data
title: A Study on the Mechanism of How the Color Scheme of Lifestyle Streets Affects Residents' Mental Health study data

description: This study is situated within the macro-context of urban renewal shifting from expansion to optimization of existing resources. Within the specific setting of historic urban areas, lifestyle streets—as the public spaces most frequently encountered by residents in their daily lives—have environmental qualities that profoundly influence community vitality and cultural heritage. However, there remains a lack of systematic empirical analysis regarding how environmental colors, a key perceptual element, impact residents' mental health. Therefore, this study aims to precisely investigate the relationship between environmental colors of lifestyle streets in historic urban areas and residents' mental health, with the goal of providing theoretical support for human-oriented street renewal and the development of healthy communities, grounded in scientific evidence.The first research document aims to analyze the overall color characteristics of lifestyle streets. To achieve this objective, the study establishes a systematic quantitative analysis framework: first, Baidu Map street view images are adopted as an objective and traceable data foundation; subsequently, within the MATLAB environment, an algorithmic model is constructed to accurately calculate two core indicators that comprehensively reflect the holistic appearance of street colors—richness and harmony. This reusable research framework not only serves the specific analysis of this study but also provides a scientific research paradigm and practical reference for the preservation and inheritance of color landscape in the ancient city of Suzhou and other similar historic urban areas.To delve into the intrinsic mechanism of how the colors of livable streets influence residents' emotions, this study breaks it down to the level of specific constituent elements in the second document. Using semantic segmentation technology, we achieved precise extraction of elements such as building facades, storefront signs, greenery, signage, vehicular roads, pedestrian walkways, and street furniture. Subsequently, MATLAB was employed to conduct a comprehensive mapping of these elements, covering aspects such as the number of colors, proportion of dominant hues, types of color tones, chromaticity index, saturation index, brightness index, the proportion of warm and cool colors, as well as comparative indices for saturation, hue, and brightness. This refined approach aims to accurately reveal the color contribution and functional pathways of different elements, thereby laying an empirical foundation for the scientific construction and validation of a theoretical model for the color–psychological perception relationship in street environments.The third document constitutes the empirical database on residents' mental health for this study. Employing the internationally recognized Spielberger State-Trait Anxiety Inventory as the core instrument, the research accurately measured psychological changes in local residents before and after their exposure to livable streets by distributing 1,200 questionnaires. This pre-post experimental design successfully yielded paired data reflecting fluctuations in psychological states, thereby enabling effective capture and quantitative assessment of residents' real-time emotional dynamics in authentic street environments.The fourth document focuses on the correlation between environmental colors and mental health, with the ultimate goal of empowering design practices. By precisely quantifying the relationship between the two, the study successfully transforms perceptual color selection into a rational decision-making process. It provides clear guidance on how to configure colors in street renewal projects to achieve desired health benefits. This offers solid theoretical support and a clear practical roadmap for shifting away from the traditional design model reliant on subjective experience toward evidence-based healthy design.
description: This study is situated within the macro-context of urban renewal shifting from expansion to optimization of existing resources. Within the specific setting of historic urban areas, lifestyle streets—as the public spaces most frequently encountered by residents in their daily lives—have environmental qualities that profoundly influence community vitality and cultural heritage. However, there remains a lack of systematic empirical analysis regarding how environmental colors, a key perceptual element, impact residents' mental health. Therefore, this study aims to precisely investigate the relationship between environmental colors of lifestyle streets in historic urban areas and residents' mental health, with the goal of providing theoretical support for human-oriented street renewal and the development of healthy communities, grounded in scientific evidence.The first research document aims to analyze the overall color characteristics of lifestyle streets. To achieve this objective, the study establishes a systematic quantitative analysis framework: first, Baidu Map street view images are adopted as an objective and traceable data foundation; subsequently, within the MATLAB environment, an algorithmic model is constructed to accurately calculate two core indicators that comprehensively reflect the holistic appearance of street colors—richness and harmony. This reusable research framework not only serves the specific analysis of this study but also provides a scientific research paradigm and practical reference for the preservation and inheritance of color landscape in the ancient city of Suzhou and other similar historic urban areas.To delve into the intrinsic mechanism of how the colors of livable streets influence residents' emotions, this study breaks it down to the level of specific constituent elements in the second document. Using semantic segmentation technology, we achieved precise extraction of elements such as building facades, storefront signs, greenery, signage, vehicular roads, pedestrian walkways, and street furniture. Subsequently, MATLAB was employed to conduct a comprehensive mapping of these elements, covering aspects such as the number of colors, proportion of dominant hues, types of color tones, chromaticity index, saturation index, brightness index, the proportion of warm and cool colors, as well as comparative indices for saturation, hue, and brightness. This refined approach aims to accurately reveal the color contribution and functional pathways of different elements, thereby laying an empirical foundation for the scientific construction and validation of a theoretical model for the color–psychological perception relationship in street environments.The third document constitutes the empirical database on residents' mental health for this study. Employing the internationally recognized Spielberger State-Trait Anxiety Inventory as the core instrument, the research accurately measured psychological changes in local residents before and after their exposure to livable streets by distributing 1,200 questionnaires. This pre-post experimental design successfully yielded paired data reflecting fluctuations in psychological states, thereby enabling effective capture and quantitative assessment of residents' real-time emotional dynamics in authentic street environments.The fourth document focuses on the correlation between environmental colors and mental health, with the ultimate goal of empowering design practices. By precisely quantifying the relationship between the two, the study successfully transforms perceptual color selection into a rational decision-making process. It provides clear guidance on how to configure colors in street renewal projects to achieve desired health benefits. This offers solid theoretical support and a clear practical roadmap for shifting away from the traditional design model reliant on subjective experience toward evidence-based healthy design.