Study on the Influence Mechanism of Machine-Learning-Based Built Environment on Urban Vitality in Macau Peninsula
Abstract
1. Introduction
2. Literature Review
2.1. Research on the Relationship Between Urban Vitality and Built Environment
2.2. Application of Nonlinear Models and Complex Systems Approache
3. Study Area and Data Sources
3.1. Study Area
3.2. Variables and Data
3.2.1. Vitality Measurement
3.2.2. Measurement of the Built Environment
3.3. Data Sources and Preprocessing
3.3.1. Basic Geographic Data
3.3.2. Open-Source Data
- (1)
- Baidu Heat Population Data
- (2)
- Macau Property Price Data
- (3)
- POI data
- (4)
- Weibo check-in data
- (5)
- Street View Image
4. Research Methodology
4.1. Calculation of Projection Pursuit Model Based on Real-Coded Genetic Algorithm
4.1.1. Projection Pursuit Model (PPM)
4.1.2. Accelerated Genetic Algorithm Based on Real-Coded Encoding (RAGA)
4.1.3. Projection Pursuit Model Optimized by Accelerated Genetic Algorithm with Real-Coded Encoding (RAGA-PPM)
4.2. Machine Learning Models and SHAP Interpretability Method
5. Results and Analysis
5.1. Spatial Distribution Analysis of Unidimensional Activity
5.2. Comprehensive Vitality Space Analysis
5.3. Analysis of Spatial Differences in Vitality Using RAGA-PPM and EWM
5.4. The Impact of the Built Environment on Urban Vitality
5.4.1. Relative Importance of Built Environment Elements
5.4.2. Nonlinear Relationship Between Built Environment Elements and Urban Vitality
6. Conclusions and Discussion
6.1. Conclusions
- (1)
- There are certain spatial distribution differences in the urban vitality across the three dimensions—crowd activity, network interaction, and the built environment—on the Macau Peninsula. However, a common feature across all dimensions is that they exhibit high values at the center, with urban vitality values gradually decreasing toward the periphery. The vitality of crowd activities is concentrated around tourism, commerce, entertainment, and cultural functions, with a high value at the center and secondary vitality clusters in each district. The vitality of network interactions is centered around the New Port and Hac-Sa Bay, presenting a spatial pattern of “moderate vitality as the dominant feature, with scattered areas of low vitality”. The spatial distribution of built environment vitality shows clear hierarchical patterns, closely related to the regional functional layout, land use patterns, and transportation conditions, with high-vitality areas primarily concentrated around the Outer Harbor, Nanhai, Senado Square, and the area surrounding the Ruins of St. Paul’s.
- (2)
- The spatial distribution of overall vitality on the Macau Peninsula is like that of the individual dimensions. Specifically, the largest vitality center is located around the historic district, with vitality decreasing as it moves outward, and the lower vitality areas are distributed at the urban periphery. The RAGA-PPM method used in this study provided a more accurate identification of vitality areas, revealing more potential vitality centers. Each district contains a vitality center, with the historic district—comprising the Ruins of St. Paul’s, New Road, A-Ma Temple, and Senado Square—serving as the main vitality hub for the entire Macau Peninsula. The areas around New Road and Nanhai exhibited the highest vitality, while the areas around Lower Harbor and Taishan showed the lowest vitality. The spatial distribution of urban vitality on the Macau Peninsula is influenced by various factors, showing heterogeneity in distribution.
- (3)
- This study reveals that, at the neighborhood level, the six built environment factors most significantly influencing urban vitality in the Macau Peninsula are, in order of importance, street network density, spatial fractal dimension, sky openness, public facility density, functional mix, and building density. These factors were ranked based on their relative significance to urban vitality and form a key set of built environment indicators that impact the urban vitality of the Macau Peninsula.
- (4)
- The built environment on the Macau Peninsula has a nonlinear effect on urban vitality. Regarding the key factors that influence the vitality of streets and blocks, road network density, spatial fractal dimension, and sky openness had similar threshold values, with all demonstrating a positive impact on vitality when the value was below 0.2.
6.2. Discussion
Author Contributions
Funding
Data Availability Statement
Conflicts of Interest
References
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Variable | Detection Metric | Calculation Formula | Formula Description |
---|---|---|---|
Urban Vitality | Population Density | R represents the density value of a specific neighborhood unit; H denotes the kernel density value of a particular neighborhood unit; A is the area of a given neighborhood unit. | |
Weibo Check-in Density | |||
Spatial Configuration | Spatial Compactness | C represents the compactness of a block, which is determined by the area of the land parcel within the block unit and the lengths of the boundaries of the parcel. | |
Fractal Dimension | D value typically ranges between 1.0 and 2.0, with a higher D value indicating greater complexity in the spatial configuration of land parcels within the region. | ||
Functional Attribute | Functional Density | represents the total number of Points of Interest (POI) within the i-th urban block, refers to the area of the i-th category of urban blocks. | |
Functional Mix | represents the functional mix of the block, “i” denotes the number of POIs within the i-th block unit, and “Pi” signifies the ratio of the i-th category of POIs to the total number of POIs within the block unit. | ||
Socio-Economic Environment | Cultural Facility Density | D represents the ratio of the total number of cultural facilities, public facilities, and commercial facilities within a specific region to the total area of that region. | |
Public Facility Density | |||
Psychological Perception | Building Density | P represents the building density, i denotes the identification number of different buildings, refers to the base area of the building with the i-th identification number, and s stands for the usable area. | |
Hydrophilic index | WI denotes the hydrophilicity index of spatial blocks, while K is a constant term representing the search radius value for neighborhood analysis. | ||
Transportation Accessibility | Road Network Densit | D represents the ratio of the total number of commercial facilities and bus stops to the total area within the study region. | |
Bus Stop Density | |||
Street Quality | Green View Index | The visibility of vegetation as perceived by the human eye was measured to assess the level of greenery on urban streets. | |
sky view factor | The term refers to the proportion of the sky visible within the field of view at a specific location, typically expressed as a value ranging from 0 to 1. | ||
Enclosure | The sense of enclosure measures the extent to which an individual feels surrounded by the surrounding environment within a space. | ||
Walkability | Refers to the level of pedestrian-friendliness of a street or urban area. |
Data Type | Data Name | Data Source | Time | Preprocessing |
---|---|---|---|---|
Fundamental Geospatial Data | Macau Road Network | Tianditu (https://www.tianditu.gov.cn/ accessed on 3 April 2024) | 2024 | The data were uniformly projected onto the WGS84 coordinate system to classify road and building categories, and metrics such as road density, building area, and water system area were subsequently calculated. |
Macau Architectural Structures | ||||
Hydrological Data | ||||
Open-source Web Data | Baidu Heatmap Population Data | Baidu Map Smart Eye Population Big Data Platform (https://huiyan.baidu.com/ accessed on 3 April 2024) | 2024 | The Kernel Density analysis tool within ArcGIS was employed to convert the data into a continuous raster density map. |
Macau Housing Price Data | Estate Information Network of Macau (https://www.malimalihome.net/ accessed on 3 April 2024) | 2023 | The core fields, including unit price, total price, gross floor area, and property type, were collected to calculate key metrics such as price per square meter and average housing prices by region. | |
Points of Interest (POI) Data | GaoDe Map | 2024 | The dataset underwent comprehensive data cleaning, including the handling of missing values and outliers. Classification and standardization processes were implemented to ensure field uniformity across all 45,708 records. | |
Weibo Check-in Data | Sina Weibo (https://weibo.com/ accessed on 3 April 2024) | 2020 | The data cleaning process involved handling missing values and outliers, followed by categorizing the data based on check-in locations. The total number of Weibo check-ins processed was 145,370. | |
Street View Imagery | Baidu Street View Map Open Platform (https://lbs.baidu.com/ accessed on 3 April 2024) | 2023 | Sampling points were generated at 100 m intervals based on road network data. Utilizing the Baidu API endpoint with a pitch angle of 0 degrees, images were captured at four different azimuth angles: 0°, 90°, 180°, and 270°. A total of 10,442 images were collected. |
Dataset | MAE | RMSE | R2 |
---|---|---|---|
Training Set Results | 0.0256 | 0.0375 | 0.8170 |
Test Set Results | 0.0650 | 0.0817 | 0.5548 |
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Pan, C.; Guo, J.; Li, H.; Wu, J.; Qiu, N.; Wu, S. Study on the Influence Mechanism of Machine-Learning-Based Built Environment on Urban Vitality in Macau Peninsula. Buildings 2025, 15, 1557. https://doi.org/10.3390/buildings15091557
Pan C, Guo J, Li H, Wu J, Qiu N, Wu S. Study on the Influence Mechanism of Machine-Learning-Based Built Environment on Urban Vitality in Macau Peninsula. Buildings. 2025; 15(9):1557. https://doi.org/10.3390/buildings15091557
Chicago/Turabian StylePan, Chen, Jiaming Guo, Haibo Li, Jiawei Wu, Nengjie Qiu, and Shengzhen Wu. 2025. "Study on the Influence Mechanism of Machine-Learning-Based Built Environment on Urban Vitality in Macau Peninsula" Buildings 15, no. 9: 1557. https://doi.org/10.3390/buildings15091557
APA StylePan, C., Guo, J., Li, H., Wu, J., Qiu, N., & Wu, S. (2025). Study on the Influence Mechanism of Machine-Learning-Based Built Environment on Urban Vitality in Macau Peninsula. Buildings, 15(9), 1557. https://doi.org/10.3390/buildings15091557