| 摘要: |
| 健康城市和存量更新背景下，
功能照明作为保障公众夜晚活动和体验
的关键内容，对民众出行安全、情绪促
进、健康维护等具有积极意义。目前针
对城市中、宏观尺度的功能照明评价多
通过汇总微观节点结论得出，难以与城
市的空间布局、业态分布、公众行为需
求、场所潜能等进行充分衔接。相较于
复杂的城市环境，大学校园凭借其高度
内向化和自治化特征，能够为功能照明
评价提供相对理想和简化的研究环境。
研究以道路和开放空间为对象，通过网
络问卷、认知地图、指标实测、兴趣
点（POI）、无人机影像等多源数据，提
出传统照明评价方法的优化建议，在得
出校园功能照明整体不足、宿舍区在校
园夜晚生活发挥主导作用、开放空间潜
力未充分释放等结论同期，梳理了功能
照明品质评价、典型区域识别、夜晚热
力区校核、运维问题优化等的方法与建
议。研究实现了宏、微观结论的联系与
互校，提出了后续校园功能照明的更新
建议，证明了多源数据评价方法在（中、
宏观场景中）功能照明评价的适用性和
可行性，并就此方法的操作要点、完善
思路等提出建议。相关结论能够有效完
善传统评价方法的不足，并为后续中、
宏观尺度的照明评价及延伸研究提供流
程和方法参考。 |
| 关键词: 城市照明 功能照明评价 多
源数据 POI 无人机影像 |
| DOI：10.13791/j.cnki.hsfwest.20241113004 |
| 分类号: |
| 基金项目:云南省科技厅基础研究专项—面上项目（政策支持类）（KKLL202464021） |
|
| Functional lighting evaluation method optimization based on multi-source data |
|
FENG Kai,WANG Di
|
| Abstract: |
| Under the background of healthy cities and stock renewal, functional lighting plays an
important role in ensuring nighttime outdoor activities, promoting mood and health. Therefore, it is
necessary to explore the examination works and systematically sort out the evaluation methods of
functional lighting. At present, the evaluation of functional lighting at the medium and macro scales is
mostly based on summarizing micro node conclusions, which is difficult to fully connect with the spatial
layout, business distribution, public behavior needs, and potential of urban lighting. Compared to
complex urban environments (including multiple influencing variables), university campus, due to its
highly introverted and autonomous characteristics, could provide a relatively ideal and simplified
environment for the refinement of functional lighting evaluation methods, which could facilitate more
efficient discussions on optimizing evaluation methods and provide support for subsequent research on
functional lighting evaluation in complex urban environments.This study uses multi-source data methods
to evaluate roads and open spaces in campus by obtaining users’ cognition of the nighttime environment
through online questionnaires, creating a cognitive map based on campus night perception through
subjective evaluation and on-site interviews, measuring the minimum illuminance and illuminance
uniformity using a Konica Minolta T-10 illuminance meter to quantitatively evaluate the campus
functional lighting by comparing it with industry standards. And Perform Kernel density analysis using
Points of Interest (POI) were used to identify potential heat zones in campuses under different POI types,
then campus hot zone identification and verification were completed through drone (Dji air3) imaging.
Conclusions received are as follows. On an overall level, the campus functional lighting is insufficient
and difficult to meet the needs of daily outdoor activities. At the level of management and maintenance,
there are widespread problems such as roads without lights, lights not turning on, and light source
attenuation, corresponding maintenance work should be optimized. At the level of behavioral
characteristics, a. the dormitory area is an important factor affecting evening vitality, and there is an
urgent need to improve the activity path and venue lighting centered on the dormitory area in the future;
b. The student prefer open spaces with better lighting quality, and attention should be paid to the
improvement of functional lighting in such places. At the level of venue potential, a. Numerous open
spaces on campus have (varying degrees of) nighttime activity potential, but the current low-quality
lighting has had a negative impact on this. Improving lighting quality to promote campus nighttime
public life is an important aspect of future work; b. The insufficient functional lighting has led to the longterm
vacancy of open spaces and the neglect of such spaces during maintenance, resulting in significant
waste of public spaces in terms of site utilization and cultural promotion, which should be given attention
from both management and maintenance aspects. Regarding research methods Comparing traditional
methods (questionnaire + cognitive map + indicator measurement) with optimization methods (POI +
drone). In terms of basic problem analysis, both methods are applicable. The weak points in lighting
obtained by traditional methods can be effectively identified through optimization methods, indicating the
feasibility of identifying micro objects or features through optimization methods, which can more
efficiently complete the research and analysis of medium and large-scale objects. In terms of the
correlation between campus business formats and nighttime vitality, the advantage of traditional methods
lies in their ability to effectively identify detailed differences between different regions, while
optimization methods can establish spatial connections between regions (such as paths, scales, etc.),which is of great significance in subsequent mid and macro level researches. In the evaluation of micro objects, traditional methods can intuitively obtain the
lighting changes inside the field and the perceptual changes caused by them, which has advantages in micro research. Optimization methods are better at
discovering the distribution of similar problems within the scope and drawing common conclusions. This indicates that both methods are effective in
determining basic problems, typical objects, etc. However, in terms of spatial layout, path connections, and common problem sorting, the optimization method
can significantly improve work efficiency by leveraging its scale advantage to draw systematic conclusions simultaneously. In future similar evaluation work,
by combining the two, a multi-source data evaluation method that takes into account both macro and micro needs will be formed, which will provide effective
support for the development of lighting evaluation work. |
| Key words: urban lighting functional lighting evaluation multi-source data point of interest drone image |
