Paper
1 November 2005 Mapping of dispersion of urban air pollution using remote sensing and in-situ monitoring data
M. A. Zoran, L. F. V. Zoran
Author Affiliations +
Abstract
Urban air quality is of great interest from health points of view as well as for future planning and decision making. Mapping of dispersion of air pollution is very complex as it depends upon various factors including weather conditions, urban structural features and their topologies. Urban air pollution is quite dependent on the ventilation condition in traffic corridors which is influenced by the aerodynamic roughness parameters of the ground. Air pollution dispersion with a 3D distribution was mapped by using bio-optical mathematical models and interpolation methods, based on ground local measurements of meteorological parameters and aerosol optical thickness as well as satellite data. While SAR (Synthetic Aperture Radar) images with a time variability are very useful for morphological urban structures extraction, Landsat TM, ETM, SPOT, MODIS images data present a wide applicability for air pollution studies. In this paper, dispersion of urban air pollution in Bucharest town, Romania was mapped through establishing the relationship among optical thickness and ground local data for visible, near infrared and thermal infrared band of the Landsat TM, ETM. Dust particulates concentration and the apparent temperature from satellite data is highly correlated for Landsat TM6 (thermal infrared).A linear regression analysis was performed to establish the relationship between satellite and in-situ monitoring data. Optical thickness of green and red bands and difference of at-satellite temperature of thermal infrared band show statistically significant relationships with, particulate matter, black particles and carbon monoxide respectively. Such analysis is of great importance for urban micro-climate and environmental quality assessment.
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M. A. Zoran and L. F. V. Zoran "Mapping of dispersion of urban air pollution using remote sensing and in-situ monitoring data", Proc. SPIE 5979, Remote Sensing of Clouds and the Atmosphere X, 597914 (1 November 2005); https://doi.org/10.1117/12.627775
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KEYWORDS
Satellites

Air contamination

Atmospheric modeling

Aerosols

Earth observing sensors

3D modeling

Atmospheric particles

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