Measuring Physical Profile and Use of PCN with Deep Learning and MM Data Analytics
Project Name: Measuring Physical Profile and Use of Park Connector Network(PCN) with Deep Learning and Multi-Source Multi-Modal Data Analytics
Project Sponsor: Ministry of Education
Grant Amount: S$175,000
Duration: 2 Years
Description: This project is devoted to developing an innovative method that can effectively harness people’s perception, use, and experience of street spaces and objectively measure their relationships with different attributes of the settings from social media. This method will enable an accurate understanding of people’s interactions with the surrounding street environment in their everyday life. On this basis, we further develop an evidence-based approach to evaluating and designing a human-scale street environment. This project will
- create a full image dataset and 3D digital model that can describe and visualize in high-resolution the physical environment of the entire PCN,
- map out how the park connectors are used by different groups of people in their everyday life at a fine-grained spatial and temporal scale, and
- develop new data analytics that can accurately capture and measure specific qualities of the physical environment of PCN and effectively assess their relationships with observed people’s activity patterns.
The analytical methods will then be used to design tools and research outcomes to create guidelines that enable more informed decision-making in future PCN development.