Content area
Strengthening the multi-dimensional vitality of industrial parks is crucial for fostering social cohesion. However, previous researches mainly focused on the vitality of various functions, lacking detailed insights for the specific planning of industrial parks. To address this issue, this study combines the spatial regression and multi-scale geographically weighted regression models to systematically analyze the spatial and temporal variations of multidimensional vitality in industrial parks of Shenzhen city. Both real and virtual indicators are employed to measure the physical and digital vitality of the industry parks, distinguishing vitality variations across weekdays and weekends. Additionally, the study further investigates the relationships between the vitality and the other influencing factors. The findings reveal that the spatial distribution of real vitality and weekend vitality follows a polycentric clustering pattern, while weekday vitality exhibits a relatively uniform spatial distribution. Virtual vitality, characterized by the lowest vitality level, spreads outward from a core of the highest values to the periphery. Weekday vitality reaches its peak in the morning, while weekend vitality demonstrates a more balanced distribution throughout the day. NDVI, diversified land use, motor vehicle diversity, enclosure and image quality contribute to increased vitality across all commercial areas, whereas the intersection density, subway stop and openness are associated with decreased vitality in these areas. The impact of building acreage, subway stop, enclosure and openness on weekend vitality is weaker and more variable. For the future development of industrial parks, efforts should focus not only on enhancing the NDVI and creating enclosed environment within the parks but also on improving the accessibility of public facilities between the eastern and western urban belts, as well as ensuring the convenience and safety of road connections. These measures will help establish a “15-minute residential circle”. Ultimately, implementing refined planning strategies tailored to the spatial and temporal differentiation of demand play a crucial role in boosting the vitality of industrial parks.
Details
Public spaces;
Spatial distribution;
Industrial areas;
Collaboration;
Industrial development;
Sustainable development;
Regression analysis;
Suburban areas;
Land use;
Temporal variations;
Gross Domestic Product--GDP;
Research & development--R&D;
Industrial plants;
Economic growth;
Cities;
Motor vehicles;
Industrial parks;
Parks & recreation areas
1 Faculty of Fine Arts and Design, Guangdong Vocational College of Art, 528000, Foshan, China; College of Electronics and Information Engineering, Shenzhen University, 518060, Shenzhen, China (ROR: https://ror.org/01vy4gh70) (GRID: grid.263488.3) (ISNI: 0000 0001 0472 9649)
2 College of Foreign Studies, Guilin University of Technology, 541004, Guilin, China (ROR: https://ror.org/03z391397) (GRID: grid.440725.0) (ISNI: 0000 0000 9050 0527)
3 Faculty of Architecture and Art Design, Ningxia College of Construction, 750000, Yinchuan, China
4 College of Electronics and Information Engineering, Shenzhen University, 518060, Shenzhen, China (ROR: https://ror.org/01vy4gh70) (GRID: grid.263488.3) (ISNI: 0000 0001 0472 9649); State Key Laboratory of Radio Frequency Heterogeneous Integration (Shenzhen University), 518060, Shenzhen, China (ROR: https://ror.org/01vy4gh70) (GRID: grid.263488.3) (ISNI: 0000 0001 0472 9649)