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Journal of Applied Remote Sensing

Comparative analyses of the ultraviolet-B flux over the continental United State based on the NASA total ozone mapping spectrometer data and USDA ground-based measurements
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Paper Abstract

In recent years, the risk of health effects caused by the increased exposure to Ultraviolet-B (UVB) due to stratospheric ozone depletion has received wide attention. In the US, there are two ways to accurately measure the UVB. They include: 1) the National Aeronautical and Space Administration (NASA) Nimbus-7 total ozone mapping spectrometer (TOMS), and 2) the United State Department of Agriculture (USDA) ground-based network. This paper compares these two sensors' data for the ultraviolet index (UVI) nationally and regionally to support possible public health, agricultural, and ecological analyses in the future. The major findings of our study are: 1) although there are discrepancies between these two data sets, the temporal correlation coefficients can be as high as 98%. 2) Both types of data sources depict the macroscopic spatial pattern of the UVI across the continental US.indicating a strong spatial correlation; 3) The two data sources are generally consistent though the UVI of the NASA TOMS data are often about 0.13-1.05 units larger than those of the USDA ground-based measurements; and 4) Varying differences can be seen between the Midwest and two coastal regions. While the level of the UVI on the west coast has shown a decreasing trend in the past few years, its counterpart on the east coast showed an opposite trend in between 2000 and 2005. It is hard to conclude that the changes are due to variations of total ozone concentrations in this study period. The USDA ground-based measurements may be better applied for time series analysis for public health, ecological, and agricultural applications due to their ability to provide intensive calibrated point measurements.

Paper Details

Date Published: 1 October 2010
PDF: 19 pages
J. Appl. Rem. Sens. 4(1) 043547 doi: 10.1117/1.3507249
Published in: Journal of Applied Remote Sensing Volume 4, Issue 1
Show Author Affiliations
Zhiqiang Gao, Colorado State Univ. (United States)
Wei Gao, Colorado State Univ. (United States)
Ni-Bin Chang, Univ. of Central Florida (United States)

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