DCPMS
A Large-Scale Raster Layer Serving Method for Custom Online Calculation and Rendering
Bibliographic Data
| ID | 22031474 |
|---|---|
| Authors | Anbang Yang (0000-0002-2180-0125, Zhejiang University), Feng Zhang (0000-0002-7444-1103, Zhejiang University), Jie Feng (0000-0002-3988-9148, Zhejiang University), Luoqi Wang (Zhejiang University), Enjiang Yue (Zhejiang University), Xinhua FAN (Zhejiang University), Jingyi Zhang (0000-0002-3147-8838, Zhejiang University), Linshu Hu (0000-0003-0015-0570, Zhejiang University, corresponding author), Sensen Wu (0000-0002-2476-8087, Zhejiang University) |
| Year | 2024 |
| Volume | 13 |
| Issue | 8 |
| Pages | 276 |
| Publication date | 2024-08-01 |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | ISPRS International Journal of Geo-Information (JOURNAL) |
| Journal identifiers | ISSN: 2220-9964 • E-ISSN: 2220-9964 |
| Publisher | MDPI AG (PUBLISHER • IT) |
| DOI | 10.3390/ijgi13080276 |
| OpenAlex | W4401206735 |
| Language | EN |
| References cited | 20 |
Raster data represent one of the fundamental data formats utilized in GIS. As the technology used to observe the Earth continues to evolve, the spatial and temporal resolution of raster data is becoming increasingly refined, while the data scale is expanding. One of the key issues in the development of GIS technology is to determine how to make large-scale raster data better to provide computation, visualization, and analysis services in the Internet environment. This paper proposes a decentralized COG-pyramid-based map service method (DCPMS). In comparison to traditional raster data online service technology, such as GIS servers and static tiles, DCPMS employs virtual mapping to reduce data storage costs and combines tile technology with a cloud-native storage scheme to enhance the concurrency of supportable requests. Furthermore, the band calculation process is shifted to the client, thereby effectively resolving the issue of efficient customized band calculation and data rendering in the context of a large-scale raster data online service. The results indicate DCPMS delivers commendable performance. Its decentralized architecture significantly enhances performance in high concurrency scenarios. With a thousand concurrent requests, the response time of DCPMS is reduced by 74% compared to the GIS server. Moreover, this service exhibits considerable strengths in data preprocessing and storage, suggesting a novel pathway for future technical improvement of large-scale raster data map services
Database · Distributed computing · Operating system · Raster data · Raster graphics · Remote sensing · Server · Spatial analysis · 3D Modeling in Geospatial Applications · Computer Science · Data Management and Algorithms · Geographic Information Systems Studies
| Highly cited | No |
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