Jinzhu Wang
Biographic Data
| ID | 6272929 |
|---|---|
| NAME | Jinzhu Wang |
| GIVEN NAMES | Jinzhu |
| FAMILY NAME | Wang |
| SIGNATURE | WANG J |
| AFFILIATIONS | Deakin University |
| ORCID | 0000-0002-5602-7398 |
| VERIFIED | Yes |
| TOTAL WORKS | 6 |
| TOTAL CITATIONS | 14 |
| AUTHOR COUNT | 6 |
| EDITOR COUNT | 0 |
| FIRST PUBLICATION YEAR | 2022 |
| LATEST PUBLICATION YEAR | 2026 |
| H-INDEX | 1 |
Delineating urban development boundaries in urban agglomeration: Integrating flow-based approach and U-Net deep learning
Containing urban sprawl in China: A cross-city evaluation of urban development boundaries using U-Net deep learning
Nonlinear effects of urban and industrial forms on surface urban heat island: Evidence from 162 Chinese prefecture-level cities
Quantifying multiple effects of land finance on urban sprawl: Empirical study on 284 prefectural-level cities in China
Simulating large-scale urban land-use patterns and dynamics using the U-Net deep learning architecture
Complex regional telecoupling between people and nature revealed via quantification of trans‐boundary ecosystem service flows
Quantifying and mapping trans‐boundary ecosystem service (ES) flows can help identify dependencies and responsibilities for promoting economic development and environmental sustainability between nations, but few studies have focused on ES flows beyond national boundaries. Our case‐study region—Central Asia—hosts one of the largest dryland areas in the world, and this ecosystem is vulnerable to climate variability and anthropogenic impacts. Under…
Simulating large-scale urban land-use patterns and dynamics using the U-Net deep learning architecture
Complex regional telecoupling between people and nature revealed via quantification of trans‐boundary ecosystem service flows
Quantifying and mapping trans‐boundary ecosystem service (ES) flows can help identify dependencies and responsibilities for promoting economic development and environmental sustainability between nations, but few studies have focused on ES flows beyond national boundaries. Our case‐study region—Central Asia—hosts one of the largest dryland areas in the world, and this ecosystem is vulnerable to climate variability and anthropogenic impacts. Under…
Nonlinear effects of urban and industrial forms on surface urban heat island: Evidence from 162 Chinese prefecture-level cities
Quantifying multiple effects of land finance on urban sprawl: Empirical study on 284 prefectural-level cities in China
Containing urban sprawl in China: A cross-city evaluation of urban development boundaries using U-Net deep learning
Delineating urban development boundaries in urban agglomeration: Integrating flow-based approach and U-Net deep learning
Land Use and Ecosystem Services (6 works) · Geography (5 works) · Human Mobility and Location-Based Analysis (3 works) · Urban planning (3 works) · Cartography (2 works) · China (2 works) · Civil engineering (2 works) · Deep learning (2 works) · Ecology (2 works) · Economic geography (2 works)