Three-dimensional Visualization of Particulate Matter Data Focused on Metropolitan and Gangnam Station Areas in South Korea
Source abstract
Abstract
In this paper, we propose a method of effectively visualizing particulate matter data based on a 3D spatial grid system to overcome the limitations of 2D spatial information. The metropolitan area in Korea was set as the demonstration site for the regional scope, whereas the Gangnam Station area in Seoul, South Korea, was set for the local scope. The particulate matter data were collected from the Korean Air Quality Forecasting System (KAQFS), public data, and private corporations. The 3D data were created by applying the GRS80 coordinate transformation and GIS spatial interpolation according to the data attribute. Moreover, the grid size was determined according to the spatial scope, and the data were structuralized for a library application. For the empirical analysis, the 3D particulate matter data were visualized by building an open-sourcebased 3D Geospatial Grid Library. The results demonstrated that the 3D spatial distribution of particulate matter data for each time series can be visualized, which can be used as scientific evidence for establishing policies related to particulate matter.
Source: openalex_inverted_index · Quality: baseline
Research context
OpenAlex topics: Air Quality Monitoring and Forecasting · Atmospheric chemistry and aerosols · Vehicle emissions and performance
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
References
Reference metadata was not supplied for this record.