Shijia Lin
Biographic Data
| ID | 9452632 |
|---|---|
| NAME | Shijia Lin |
| GIVEN NAMES | Shijia |
| FAMILY NAME | Lin |
| SIGNATURE | LIN S |
| AFFILIATIONS | Tongji University |
| ORCID | 0009-0005-0087-6162 |
| VERIFIED | Yes |
| TOTAL WORKS | 2 |
| TOTAL CITATIONS | 0 |
| WORKS AS AUTHOR | 2 |
| WORKS AS EDITOR | 0 |
| FIRST PUBLICATION YEAR | 2024 |
| LATEST PUBLICATION YEAR | 2025 |
| H-INDEX | 0 |
Street walkability inference with street view imagery through fine-tuning and prompting pre-trained large models
Large-scale assessment of street walkability using street view imagery is essential for supporting urban spatial governance and achieving sustainable development goals. This study proposes a walkability inference framework based on pre-trained multimodal large models, which integrates domain-specific knowledge of the hierarchy of walking needs through fine-tuning and prompt engineering. This framework consists of three sequential steps: filtratio…
A longitudinal study of evolving polycentric pattern in Shanghai
In the context of technological progress and economic transition, the urban spatial structure has consistently undergone dynamic evolution. However, the trajectories of polycentric patterns display significant national and regional variations. It is crucial to examine the dynamic evolution of spatial structures within Chinese metropolitan areas amidst economic transitions. Focusing on the Shanghai Metropolitan Area (SMA), this study investigates …
No prominent works on this page.
A longitudinal study of evolving polycentric pattern in Shanghai
In the context of technological progress and economic transition, the urban spatial structure has consistently undergone dynamic evolution. However, the trajectories of polycentric patterns display significant national and regional variations. It is crucial to examine the dynamic evolution of spatial structures within Chinese metropolitan areas amidst economic transitions. Focusing on the Shanghai Metropolitan Area (SMA), this study investigates …
Street walkability inference with street view imagery through fine-tuning and prompting pre-trained large models
Large-scale assessment of street walkability using street view imagery is essential for supporting urban spatial governance and achieving sustainable development goals. This study proposes a walkability inference framework based on pre-trained multimodal large models, which integrates domain-specific knowledge of the hierarchy of walking needs through fine-tuning and prompt engineering. This framework consists of three sequential steps: filtratio…
Affordance (1 work) · Economic geography (1 work) · Geography (1 work) · Hierarchy (1 work) · Inference (1 work) · Interpretability (1 work) · Pedestrian (1 work) · Regional Economic and Spatial Analysis (1 work) · Regional Economics and Spatial Analysis (1 work) · Regional science (1 work)