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ATMOSPHERIC SMOG MODELLING, USING EOS SATELLITE ASTER IMAGE SENSOR, WITH FEATURE EXTRACTION FOR PATTERN RECOGNITION TECHNIQUES AND ITS ANALYSIS OF VARIANCE WITH IN-SITU GROUND SENSOR DATA

By Parthasarathi Roy, Paul Beaty, J. O. Brumfield, Ralph Oberly, Anita Walz, John Pollard and Jeff DooleyPaul Kennedy and Jeff Dooley

Abstract

Atmospheric pollution was previously considered as a 'Brown Cloud ’ phenomenon restricted to industrialized urban regions. Studies in field stations and satellite observations made since the last decade revealed that it now spans continents and ocean basins world wide. Anthropogenic activities are considered to be the primary cause of pollution in the atmosphere. The appearance of a smog layer with more absorption and scattering of solar radiations, particularly long-wave infrared radiations, decreases the atmospheric transmission factor, significantly perturbing the atmospheric absorption of solar radiation. The objective of this research is to create a geo-spatial model based on probability density of common atmospheric pollutants in the troposphere by using feature extraction and pattern recognition technique with high-spectral and spatial resolution Earth Observation System (EOS) satellite imaging sensor Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) data, US Environmental Protection Agency (EPA) ground sensor data and “Analysis of Variance ” of satellite pixel value with EPA ground sensor observations. This research investigated three locations: 1. San Francisco Bay area, in California has a unique land feature having maritime climate surrounded by coastal ranges. 2. Los Angeles, in California (a maritime climate) and, 3. Charleston, in West Virginia which has humid continental climate in the mountain ranges in Kanawha Valley. Polluting industries data and Tapered Element Oscillating Microbalance (TEOM) ground sensor data are collected from the US-EPA. Spectral signatures of common atmospheric pollutant

Topics: KEY WORDS, Smog, Absorption Bands, Satellite-Imagery, Spectral Signature, Sensors, and ASTER
Year: 2011
OAI identifier: oai:CiteSeerX.psu:10.1.1.184.3512
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