Analysis of image color and effective bandwidth as a tool for assessing air pollution at urban spatiotemporal scale

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review


Size and concentration of airborne particulate matter (PM) are important indicators of air pollution events and public health risks. It is therefore important to monitor size resolved PM concentrations in the ambient air. This task, however, is hindered by the highly dynamic spatiotemporal variations of the PM concentrations. Satellite remote sensing is a common approach for gathering spatiotemporal data regarding aerosol events but its current spatial resolution is limited to a large grid that does not fit high varying urban areas. Moreover, satellite-borne remote sensing has limited revisit periods and it measures along vertical atmospheric columns. Thus, linking satellite-borne aerosol products to ground PM measurements is extremely challenging. In the last two decades visibility analysis is used by the US Environmental Protection Agency (US-EPA) to obtain quantitative representation of air quality in rural areas by horizontal imaging. However, significantly fewer efforts have been given to utilize the acquired scene characteristics (color, contrast, etc.) for quantitative parametric modeling of PM concentrations. We suggest utilizing the image effective bandwidth, a quantitative measure of image characteristics, for predicting PM concentrations. For validating the suggested method, we have assembled a large dataset that consists of time series imaging as well as measurements from air quality monitoring stations located in the study area that report PM concentrations and meteorological data (wind direction and velocity, relative humidity, etc.). Quantitative and qualitative statistical evaluation of the suggested method shows that dynamic changes of PM concentrations can be inferred from the acquired images.

Original languageEnglish
Title of host publicationProceedings of SPIE-IS and T Electronic Imaging - Computational Imaging XI
StatePublished - 2013
EventComputational Imaging XI - Burlingame, CA, United States
Duration: 5 Feb 20137 Feb 2013

Publication series

NameProceedings of SPIE - The International Society for Optical Engineering


ConferenceComputational Imaging XI
Country/TerritoryUnited States
CityBurlingame, CA


  • Enviromatics
  • environmental monitoring
  • image effective bandwidth
  • image quantitative characteristics
  • particulate matter (PM)
  • remote sensing

All Science Journal Classification (ASJC) codes

  • Electronic, Optical and Magnetic Materials
  • Condensed Matter Physics
  • Computer Science Applications
  • Applied Mathematics
  • Electrical and Electronic Engineering


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