PEERANAT PRASONGSUK
Sessions
In today's rapidly evolving field of map data visualization, the use of vector tiles is increasingly prevalent. Vector tiles offer flexible and efficient data display, but they require JSON Style data to define their visual representation. JSON Style plays a crucial role in formatting data, ensuring that presentations are both diverse and user-friendly.
Geospatial Topology, a fundamental concept in geographic information systems, focuses on the analysis and characterization of spatial relationships between geographic entities without alteration of their intrinsic properties. This presentation examines the implementation of Geospatial Topology rules utilizing Python programming language, facilitating execution in both client-side and server-side environments.
We present an empirical case study from the PWA GIS Department of Thailand, which employs a comprehensive set of over 30 topology rule-based validations to ensure data integrity and consistency across national cartographic operations. The research investigates two primary platforms: QGIS Desktop and Web Applications, both serving as client-side interfaces capable of executing topology scripts and generating inconsistency reports for subsequent rectification.
A critical distinction between QGIS Desktop and Web Application lies in their respective execution paradigms: QGIS Desktop operates within a local environment, while the Web Application leverages server-side processing capabilities.
This presentation will elucidate methodologies for developing custom topology rules and demonstrate techniques for accessing single-algorithm Python scripts across both Desktop and Web Application environments. By bridging the technological gap between these platforms, we aim to enhance the efficacy of geospatial data quality control processes and optimize GIS workflows.
The findings of this research contribute to the broader understanding of cross-platform geospatial topology implementation and offer practical insights for GIS professionals and developers seeking to improve data validation processes in diverse computational environments.