Unspecified Chris C. Schmidt Profile

Chris C. Schmidt

SPIE Involvement:

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Proceedings Article | 22 August 2020 Presentation

Investigation of GOES-R ABI cold pixels around fire

Xiangqian Wu, Chris Schmidt, Fangfang Yu, Zhipeng Wang

Proceedings Volume 11501, 1150118 (2020) https://doi.org/10.1117/12.2571067

KEYWORDS: Imaging systems, Satellite imaging, Satellites, Calibration, Image restoration, Image registration

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SPIE Journal Paper | 6 November 2014 Open Access

Geostationary Operational Environmental Satellite Imager infrared channel-to-channel co-registration characterization algorithm and its implementation in the ground system

Zhenping Li, Michael Grotenhuis, Xiangqian Wu, Timothy Schmit, Christopher Schmidt, Anthony Schreiner, James Nelson, Fangfang Yu, Hyre Bysal

JARS, Vol. 8, Issue 01, 083530, (November 2014) https://doi.org/10.1117/12.10.1117/1.JRS.8.083530

KEYWORDS: Infrared imaging, Imaging systems, Satellites, Satellite imaging, Earth observing sensors, Infrared radiation, Environmental sensing, Clouds, Infrared sensors, Fiber optic gyroscopes

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Channel-to-channel co-registration is an important performance metric for the Geostationary Operational Environmental Satellite (GOES) Imager, and large co-registration errors can have a significant impact on the reliability of derived products that rely on combinations of multiple infrared (IR) channels. Affected products include the cloud mask, fog and fire detection. This is especially the case for GOES-13, in which the co-registration error between channels 2 (3.9 μm) and 4 (10.7 μm) can be as large as 1 pixel (or ∼4 km) in the east-west direction. The GOES Imager IR channel-to-channel co-registration characterization (GII4C) algorithm is presented, which allows a systematic calculation of the co-registration error between GOES IR channel image pairs. The procedure for determining the co-registration error as a function of time is presented. The algorithm characterizes the co-registration error between corresponding images from two channels by spatially transforming one image using the fast Fourier transformation resampling algorithm and determining the distance of the transformation that yields the maximum correlation in brightness temperature. The GII4C algorithm is an area-based approach which does not depend on a fixed set of control points that may be impacted by the presence of clouds. In fact, clouds are a feature that enhances the correlations. The results presented show very large correlations over the majority of Earth-viewing pixels, with stable algorithm results. Verification of the algorithm output is discussed, and a global spatial-spectral gradient asymmetry parameter is defined. The results show that the spatial-spectral gradient asymmetry is strongly correlated to the co-registration error and can be an effective global metric for the quality of the channel-to-channel co-registration characterization algorithm. Implementation of the algorithm in the GOES ground system is presented. This includes an offline component to determine the time dependence of the co-registration errors and a real-time component to correct the co-registration errors based on the inputs from the offline component.

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SPIE Journal Paper | 16 December 2013 Open Access

Geostationary Operational Environmental Satellite (GOES)-14 super rapid scan operations to prepare for GOES-R

Timothy Schmit, Steven Goodman, Daniel Lindsey, Robert Rabin, Kristopher Bedka, Mathew Gunshor, John Cintineo, Christopher Velden, A. Scott Bachmeier, Scott Lindstrom, Christopher Schmidt

JARS, Vol. 7, Issue 01, 073462, (December 2013) https://doi.org/10.1117/12.10.1117/1.JRS.7.073462

KEYWORDS: Satellites, Imaging systems, Clouds, Convection, Video, Environmental sensing, Radar, Infrared imaging, Data centers, Meteorological satellites

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Proceedings Article | 2 October 2007 Paper

An improved atmospheric profile retrieval system for GOES sounder and SEVIRI data

Xin Jin, Jun Li, James Nelson, Christopher Schmidt, Zhenglong Li, Timothy Schmit, Mitchell Goldberg

Proceedings Volume 6684, 66840K (2007) https://doi.org/10.1117/12.732683

KEYWORDS: Lithium, Satellites, Atmospheric physics, Databases, Imaging systems, Infrared imaging, Infrared radiation, Humidity, Absorption, Algorithm development

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Proceedings Article | 20 October 1999 Paper

Retrieval of total atmospheric ozone from GOES

James Nelson, Jun Li, Christopher Schmidt, Timothy Schmit, W. Paul Menzel

Proceedings Volume 3756, (1999) https://doi.org/10.1117/12.366394

KEYWORDS: Ozone, Satellites, Computer simulations, Ultraviolet radiation, Meteorological satellites, Atmospheric physics, Earth's atmosphere, Radiative transfer, Atmospheric modeling, Transmittance

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Proceedings Article | 18 August 1998 Paper

Retrieval of total atmospheric ozone from GOES sounder radiance measurements with high spatial and temporal resolution

Jun Li, James Nelson, Timothy Schmit, W. Paul Menzel, Christopher Schmidt, Hung-Lung Huang

Proceedings Volume 3501, (1998) https://doi.org/10.1117/12.317758

KEYWORDS: Ozone, Satellites, Ultraviolet radiation, Temporal resolution, Atmospheric physics, Computer simulations, Resolution enhancement technologies, Radiative transfer, Atmospheric modeling, Transmittance

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Showing 5 of 6 publications

Conference Committee Involvement (1)

Optical Trapping and Optical Micromanipulation IX

12 August 2012 | San Diego, California, United States

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