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1、毕业设计(论文)文献翻译 利用ArcGIS研究城市地区 题 目 空气污染综合数据库开发 学 院 专 业 班 级 学 生 学 号 指导教师 二一一年六月七日Spatial Modelling of Air Pollution in Urban Areas withGIS: A Case Study on Integrated Database DevelopmentL. MatejicekInstitute for Environmental Studies, Charles University, Prague, 128 01, Czech Republic(lmatejicmbox.cesn
2、et.cz)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 the GIS. In addition to data management and standard environmental analysis of air pollution, data from remote sensing (aerial an
3、d satellite images) can extend all the data sets. In spite of that simulation of air pollutant distribution is carried out by standalone computer systems, the spatial database in the frame of the GIS is used to support decision-making processes in a more efficient way. Mostly, data are included in t
4、he 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 in the GIS to adapt its functionality. As examples, the spatial models of the flat urban area and the street canyon with e
5、xtensive traffic polluted with NOx are constructed. Different scales of the spatial models require variant methods of construction, data management and spatial data sources. The measurement of NOx and O3 by the automatic monitoring system and data from the differential absorption LIDAR are used for
6、investigation of air pollution. Spatial data contain digital maps of both the areas complemented by digital elevation models. Environmental analyses represent spatial interpolations of air pollution that are displayed in horizontal and vertical plains. Case oriented analyses are mostly focused on ri
7、sk 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 frame of the ESRIs ArcGIS and ArcView prog
8、ramming tools. Aerial and satellite images preprocessed by the ERDAS Imagine represent areas of Prague.Keywords: spatial modelling; GIS; air pollution; Lidar1. INTRODUCTIONThe recent development of spatial data management in the frame of geographic information systems (GISs) has created the new era
9、of environmental modelling. More powerful computers have made running air quality models at global and locale spatial scales possible. In order to understand the function of more complex models, the modelling system should consist of other subsystems (point and area sources of pollution, spatial des
10、cription of terrain elevations, meteorological data, air quality monitoring networks). Obviously, the use of the GIS has become essential in providing boundary conditions to the air quality models. Certainly, the use of the GIS in air pollution modelling can be extended moreover to processing the su
11、rface data. Many models have been coupled with the GIS in the past decade to simulate various environmental processes as described in the book written by Longley et al. 2001. Due to the four-dimensional nature of distribution of atmospheric pollutants, the concept of the GIS should be extended to in
12、clude temporal variations of three-dimensional spatial data. Considering to a huge volume of numerical calculations, two-dimensional interpolations into the horizontal layers are used to interpolate threedimensional atmospheric data onto a model grid system. The interpolations, integrations of land
13、cover surface data and the GIS analyses focused on small scale spatial models carried out in the kilometer grid are discussed by Lee in the book published by Goodchild 1996. In case of large scale air quality modelling, more detailed spatial data are needed to include the impact of buildings and oth
14、er man-made barriers on distribution of air pollutants, Janour, 1999; Civis 2001. Apart from this approach, the statistical theory is also used to indicate spatio-temporal interactions as described by Briggs et al. 2000.2. METHODS OF INTEGRATION AIR QUALITY MODELS INTO THE GISA few scenarios can be
15、established to integrate air quality models into the GIS. The basic level is represented by the standalone software application for simulation of air quality models (ISCST3, ISCPRIME), which is accompanied by data inputs and other software systems (GIS, RDBMS, Surfer, WWW-presentations). The individual programs form heterogeneous data structures that require the transport of data into various data formats. Figure 1 illustrates an example of steps carried out during the simulation of air quality models.Figure 1. The standalone simulation of air quality models,which i
