Aerosol retrieval over urban areas using spatial regression between V/NIR and MIR Hyperion channels

Barry Gross; Oluwatosin Ogunwuyi; Fred Moshary; Samir Ahmed; Brian Cairns

doi:10.1117/12.560097

15 September 2004 Aerosol retrieval over urban areas using spatial regression between V/NIR and MIR Hyperion channels

Barry Gross, Oluwatosin Ogunwuyi, Fred Moshary, Samir Ahmed, Brian Cairns

Proceedings Volume 5547, Remote Sensing in Atmospheric Pollution Monitoring and Control; (2004) https://doi.org/10.1117/12.560097
Event: Optical Science and Technology, the SPIE 49th Annual Meeting, 2004, Denver, Colorado, United States

Abstract

Determination of aerosol optical depth from satellite remote sensing measurements is extremely complex due to the large variability of aerosol optical properties. Significant simplification occurs when measurements are taken over water since the ocean reflection signal can be taken as negligible in the NIR.. Unfortunately, over land, most of the signal can be attributed to ground reflectance. While conventional approaches look for “dark” pixels in an image to isolate aerosols, these pixels are subjected to increased noise. In this paper, we explore the feasibility of a regression approach utilizing correlations between the VNIR and MIR channels to extract the aerosol reflection signal over urban areas. This approach is applied to hyperspectral high resolution Hyperion data where the aerosol reflectance signal is shown to agree very well with coincident Aeronet derived reflectance spectra. Comparisons between the regression technique and dark pixel thresholding clearly exhibit the improvement using regression methods. Finally, practical spatial resolution concerns are explored and specifications of the GOES-R imager are assessed.

Citation Download Citation

Barry Gross, Oluwatosin Ogunwuyi, Fred Moshary, Samir Ahmed, and Brian Cairns "Aerosol retrieval over urban areas using spatial regression between V/NIR and MIR Hyperion channels", Proc. SPIE 5547, Remote Sensing in Atmospheric Pollution Monitoring and Control, (15 September 2004); https://doi.org/10.1117/12.560097

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