Posters and Spotlights
Enhancing WebGIS for Data Visualization: Tile Servers vs. Database Operations in the Era of Big Geospatial Data
Start Date
30-4-2025 11:30 AM
Document Type
Event
Description
Poster Presenter: A. N. Sahin
Research Team: A.N. Sahin, Y. Ozeren, L. Rébillout, M. Al-Hamdan, R. Bingner
Abstract: This study investigates how different data serving methods impact the performance and user experience of WebGIS applications, especially when dealing with massive geospatial datasets. Focusing on tile servers versus direct database operations, we assess their efficiency in visualizing complex geospatial data for informed decision-making. Our study focuses on nationwide dataset with over 35 million reaches and 85 million subwatersheds, generated by the TOPAGNPS topographic analysis tool for 4794 THUC regions (Figure 3). This data allows us to visualize topological relationships and model specific areas through a userfriendly interface. Central to this research is the Agricultural Integrated Management System (AIMS), a webbased decision support tool developed by the University of Mississippi, NCCHE, and USDA-ARS. AIMS automates input data preparation and utilizes the AnnAGNPS model for watershed simulations, relying on TOPAGNPS for terrain attribute extraction. Figure 2 illustrates the user sequence diagram for AIMS, highlighting the interaction between the user, AIMS, and the system database. After user login and project/scenario creation, the user interacts with AIMS to choose an outlet. This triggers AIMS to execute a series of SQL queries on the System DB (PostgreSQL PostGIS). While essential for data retrieval and storage, database connections in AIMS introduce potential challenges. Performance issues can arise from complex queries or large datasets, leading to slow response times. Security concerns necessitate robust measures to prevent unauthorized access and protect the data. Furthermore, scaling AIMS for numerous concurrent users may demand significant database optimization and infrastructure upgrades. Therefore, optimizing database interactions is necessary to ensure AIMS remains efficient and responsive, especially when handling extensive geospatial data.
Relational Format
poster
Recommended Citation
Sahin, A. N., "Enhancing WebGIS for Data Visualization: Tile Servers vs. Database Operations in the Era of Big Geospatial Data" (2025). Showcase of Research and Scholarly Activity. 50.
https://egrove.olemiss.edu/ored_showcase/2025/posters/50
Enhancing WebGIS for Data Visualization: Tile Servers vs. Database Operations in the Era of Big Geospatial Data
Poster Presenter: A. N. Sahin
Research Team: A.N. Sahin, Y. Ozeren, L. Rébillout, M. Al-Hamdan, R. Bingner
Abstract: This study investigates how different data serving methods impact the performance and user experience of WebGIS applications, especially when dealing with massive geospatial datasets. Focusing on tile servers versus direct database operations, we assess their efficiency in visualizing complex geospatial data for informed decision-making. Our study focuses on nationwide dataset with over 35 million reaches and 85 million subwatersheds, generated by the TOPAGNPS topographic analysis tool for 4794 THUC regions (Figure 3). This data allows us to visualize topological relationships and model specific areas through a userfriendly interface. Central to this research is the Agricultural Integrated Management System (AIMS), a webbased decision support tool developed by the University of Mississippi, NCCHE, and USDA-ARS. AIMS automates input data preparation and utilizes the AnnAGNPS model for watershed simulations, relying on TOPAGNPS for terrain attribute extraction. Figure 2 illustrates the user sequence diagram for AIMS, highlighting the interaction between the user, AIMS, and the system database. After user login and project/scenario creation, the user interacts with AIMS to choose an outlet. This triggers AIMS to execute a series of SQL queries on the System DB (PostgreSQL PostGIS). While essential for data retrieval and storage, database connections in AIMS introduce potential challenges. Performance issues can arise from complex queries or large datasets, leading to slow response times. Security concerns necessitate robust measures to prevent unauthorized access and protect the data. Furthermore, scaling AIMS for numerous concurrent users may demand significant database optimization and infrastructure upgrades. Therefore, optimizing database interactions is necessary to ensure AIMS remains efficient and responsive, especially when handling extensive geospatial data.