Spatial modelling of air pollution in urban areas with GIS: a case study on integrated database development

Abstract. A wide range of data collected by monitoring systems and by mathematical and physical modelling can be managed in the frame of spatial models developed in GIS. In addition to data management and standard environmental analysis of air pollution, data from remote sensing (aerial and satellite images) can ehance all data sets. In spite of the fact that simulation of air pollutant distribution is carried out by standalone computer systems, the spatial database in the framework of the GIS is used to support decision-making processes in a more efficient way. Mostly, data are included in the map layers as attributes. Other map layers are carried out by the methods of spatial interpolation, raster algebra, and case oriented analysis. A series of extensions is built into the GIS to adapt its functionality. As examples, the spatial models of a flat urban area and a street canyon with extensive traffic polluted with NO_x are constructed. Different scales of the spatial models require variable methods of construction, data management, and spatial data sources. The measurement of NO_x and O₃ by an automatic monitoring system and data from the differential absorption LIDAR are used for investigation of air pollution. Spatial data contain digital maps of both areas, complemented by digital elevation models. Environmental analyses represent spatial interpolations of air pollution that are displayed in horizontal and vertical planes. Case oriented analyses are mostly focused on risk assessment methods. Finally, the LIDAR monitoring results and the results obtained by modelling and spatial analyses are discussed in the context of environmental management of the urban areas. The spatial models and their extensions are developed in the framework of the ESRI's ArcGIS and ArcView programming tools. Aerial and satellite images preprocessed by the ERDAS Imagine represent areas of Prague.