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

Abstract

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 O 3 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.

Mapping of Traffic-Related Air Pollution Using GIS Techniques in Ijebu-Ode, Nigeria

“…Geographical Information System (GIS) is a powerful tool that facilitates linking spatial data to non-spatial information [Matejicek, 2005]. This study involved incorporating traffic related air pollution data from field measurements into digital map layers for illustrating the application of spatial analysis to Ijebu-ode area.…”

“…GIS-based pollution mapping, using interpolation techniques, such as inverse distance weighting and kriging have proved efficient in the assessment of urban air pollution [van der Kassteele , 2006;ESRI, 2007;Chattopadhyay et al, 2010]. Air pollution maps are potentially powerful tools particularly for urban areas for use in epidemiological studies and in identifying the "hot-spots" in need of special investigation or monitoring [Matejicek, 2005;Ettouney et al, 2009;Banja et al, 2010;Sampson et al, 2011;Sameen et al, 2014]. Integrating spatial analysis in GIS and statistical modelling can help the researcher to expand the understanding concerning the distribution of the pollutants in some locations or areas and to understand the factors that influence the trends and significance [Rahman et al, 2015].…”

The Effect of the Industrial Activities on Air Pollution at Baiji and Its Surrounding Areas, Iraq

“…Industrial activities will be more hazardous in highly populated areas (e.g. highly populated cities) [1]. Such activities have great impact on the ecology and agriculture as well as health and safety effects.…”

Stochastic Prediction of Wind Generating Resources Using the Enhanced Ensemble Model for Jeju Island’s Wind Farms in South Korea

“…It is widely used in various fields such as Geographic Information System (GIS), ecology, energy, and engineering [13][14][15][16]. Spatial modeling can estimate the value of the specific site without the accumulation of historical data.…”