Ninghua Chen
Biographic Data
| ID | 9965916 |
|---|---|
| NAME | Ninghua Chen |
| GIVEN NAMES | Ninghua |
| FAMILY NAME | Chen |
| SIGNATURE | CHEN N |
| AFFILIATIONS | Zhejiang University |
| ORCID | 0000-0001-9401-9711 |
| VERIFIED | Yes |
| TOTAL WORKS | 2 |
| TOTAL CITATIONS | 0 |
| WORKS AS AUTHOR | 2 |
| WORKS AS EDITOR | 0 |
| FIRST PUBLICATION YEAR | 2021 |
| LATEST PUBLICATION YEAR | 2024 |
| H-INDEX | 0 |
A Novel and Extensible Remote Sensing Collaboration Platform
Geospatial data, especially remote sensing (RS) data, are of significant importance for public services and production activities. Expertise is critical in processing raw data, generating geospatial information, and acquiring domain knowledge and other remote sensing applications. However, existing geospatial service platforms are more oriented towards the professional users in the implementation process and final application. Building appropriat…
Deep Understanding of Urban Dynamics from Imprint Urban Toponymic Data Using a Spatial–Temporal–Semantic Analysis Approach
Urban land use is constantly changing via human activities. These changes are recorded by imprint data. Traditionally, urban dynamics studies focus on two-dimensional spatiotemporal analysis. Based on our best knowledge, there is no study in the literature that uses imprint data for better understanding urban dynamics. In this research, we propose a spatial–temporal–semantic triple analytical framework to better understand urban dynamics by makin…
No prominent works on this page.
Deep Understanding of Urban Dynamics from Imprint Urban Toponymic Data Using a Spatial–Temporal–Semantic Analysis Approach
Urban land use is constantly changing via human activities. These changes are recorded by imprint data. Traditionally, urban dynamics studies focus on two-dimensional spatiotemporal analysis. Based on our best knowledge, there is no study in the literature that uses imprint data for better understanding urban dynamics. In this research, we propose a spatial–temporal–semantic triple analytical framework to better understand urban dynamics by makin…
A Novel and Extensible Remote Sensing Collaboration Platform
Geospatial data, especially remote sensing (RS) data, are of significant importance for public services and production activities. Expertise is critical in processing raw data, generating geospatial information, and acquiring domain knowledge and other remote sensing applications. However, existing geospatial service platforms are more oriented towards the professional users in the implementation process and final application. Building appropriat…
Computer Science (2 works) · Geographic Information Systems Studies (2 works) · Geography (2 works) · Advanced Computational Techniques and Applications (1 work) · Archaeology (1 work) · Architecture (1 work) · Cartography (1 work) · Civil engineering (1 work) · Computer architecture (1 work) · Data science (1 work)