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Bo-Cai Gao
Bo-Cai Gao
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Research Scientist in the Remote Sensing Division of the Naval Research Laboratory
Recent PACE-related Publications | See All ►
Space Station Image Captures a Red Tide Ciliate Bloom at High Spectral and Spatial Resolution (2015)
Atmospheric Correction for Global Mapping Spectroscopy: ATREM Advances for the Hyspiri Preparatory Campaign (2015)
Optimizing Irradiance Estimates for Coastal and Inland Water Imaging Spectroscopy (2015)
The Portable Remote Imaging Spectrometer (PRISM) Coastal Ocean Sensor: Characteristics and First Flight Results (2014)

Science Meeting Presentations (8)

PACE Atmospheric Correction Focusing on Adaptation of NASA’s Heritage Algorithm
Franz, B., Ibrahim, A., Ahmad, Z., Gao, B-C., and Zhai, P. (16-Jan-18)
Land and Ocean Versions of ATREM Codes for Processing Hyperspectral Imaging Data Sets
Gao, B-C. and Li, R-R. (16-Jan-18)
Land and Ocean Versions of ATREM Codes for Processing AVIRIS-Simulated PACE Proxy Data
Gao, B-C. and Li, R-R. (17-Jan-17). Click here to view this presentation with audio.
PACE Atmospheric Correction Focusing on Adaptation of NASA’s Heritage Algorithm
Franz, B., Ibrahim, A., Ahmad, Z., Healy, R., and Gao, B-C. (17-Jan-17)
PACE Science Team: Atmospheric Correction over Bright Water Targets with Non-negligible Radiances in the Near Infrared
Dierssen, H., Randolph, K., Garaba, S., Zhai, P., and Gao, B-C. (17-Jan-17)
Implementing Heritage AC Algorighm for Hyperspectral Rrs Retrieval
Ibraham, A., Franz, B., Ahmad, Z., Healy, R., and Gao, B-C. (21-Jan-16)
Hyperspectral and Multispectral Atmospheric Correction Algorithms for Supporting the NASA PACE Mission
Gao, B-C. and Li, R-R. (21-Jan-16)
Hyperspectral and Multispectral Atmospheric Correction Algorithms Supporting the NASA PACE Mission
Gao, B-C. (14-Jan-15)

ROSES Proposal

Hyperspectral and Multispectral Atmospheric Correction Algorithms for Supporting the NASA PACE Mission
At the core of the PACE mission is an advanced optical instrument, the Ocean Color Imager (OCI), designed to provide hyperspectral ultra violet (UV), to visible (VIS) and near-infrared (NIR) and multi-spectral short-wave infrared (SWIR 1.0 - 2.5 micron) observations of the earth ecosystems. We propose to join the PACE Atmospheric Correction team, to work together with other team members in developing hyperspectral and multispectral atmospheric correction algorithms to retrieve water leaving reflectances from OCI radiance measurements. We have extensive experience developing atmospheric correction algorithms. In early 1990s, we developed the first model-based land version of hyperspectral atmospheric correction algorithm (nicknamed ATREM) (Gao et al., RSE, 1993) to support the NASA HIRIS (High Resolution Imaging Spectrometer) Project. In late 1990s, we developed an ocean version of hyperspectral atmospheric correction algorithm for the Navy (Gao et al., Applied Optics, 2000), which was based on Robert Fraser's formulation (Fraser et al., JGR, 1997). In early 2000s, with funding support from the NASA SIMBIOS Project, we modified the ocean version of the hyperspectral atmospheric correction algorithm, and developed a MODIS version of multi-channel algorithm for remote sensing of water leaving reflectances over turbid coastal waters (Gao et al., IEEE TGRS, 2007) from a combination of MODIS land and ocean channels. A SWIR spectrum-matching technique using MODIS channels centered at 1.24, 1.64, and 2.13 micron was used to estimate aerosol models and optical depths. More recently we developed a VIIRS version of coastal water atmospheric correction algorithm. The VIIRS channels centered at 1.24, 1.61, and 2.25 micron with proper modeling of atmospheric CO2 and CH4 absorption effects and a SWIR spectrum-matching technique were used for atmospheric corrections. Over the past 6 years, we have supported the HICO (Hyperspectral Imager for Coastal Ocean) Project. We developed the L1B software for converting raw digital numbers to L1B radiances with proper consideration for instrument artifacts, such as spectral smear and second order light. We developed spectrum-matching algorithms for refining HICO wavelength calibrations and for monitoring the stability of the HICO instrument with time. We developed a functional version of atmospheric correction algorithm for processing HICO data. Here we propose to use our experience in hyperspectral and multi-channel algorithm development and in analysis of AVIRIS, MODIS, VIIRS, and HICO data, to help the development of atmospheric correction algorithms for processing PACE OCI data, and support the spectral and radiometric calibrations of the hyperspectral portion of the OCI instrument. We would work together with other PACE atmospheric correction team members for the design and implementation of a consensus OCI atmospheric correction algorithm.

Publications (30)

Dierssen, H.M., McManus, G., Chlus, A., Qiu, D., Gao, B.-C., and Lin, S. (2015). Space Station Image Captures a Red Tide Ciliate Bloom at High Spectral and Spatial Resolution, Proc. National Acad. Sci., 112 (48), 14783-14787.
Thompson, D.R., Gao, B.-C., Green, R.O., Roberts, D.A., Dennison, P.E., and Lundeen, S.R. (2015). Atmospheric Correction for Global Mapping Spectroscopy: ATREM Advances for the Hyspiri Preparatory Campaign, Remote Sens. Environ., 167, 64-77, doi: 10.1016/j.rse.2015.02.010.
Thompson, D.R., Seidel, F.C, Gao, B.-C., Gierach, M.M., Green, R.O., Kudela, R.M., and Mouroulis, P. (2015). Optimizing Irradiance Estimates for Coastal and Inland Water Imaging Spectroscopy, Geophys. Res. Lett., 42(10), 4116-4123, doi: 10.1002/2015GL063287.
Mouroulis, P., Gorp, B., Green, R., Dierssen, H., Wilson, D., Eastwood, M., Boardman, J., Gao, B., Cohen, C., Franklin, B., Loya, F., Lundeen, S., Mazer, A., McCubbin, I., Randall, D., Richardson, B., Rodriguez, J., Sarture, C., Urquiza, E., Vargas, R., White, V., and Yee, K. (2014). The Portable Remote Imaging Spectrometer (PRISM) Coastal Ocean Sensor: Characteristics and First Flight Results, Appl. Opt., 53(7), 1363-1380, doi: 10.1364/AO.53.001363.
Gao, B.-C. and Liu, M. (2013). A Fast Smoothing Algorithm for Post-Processing of Surface Reflectance Spectra Retrieved from Airborne Imaging Spectrometer Data, Sensors, 13(10), 13879-13891, doi: 10.3390/s131013879.
Gao, B.-C. and Chen, W. (2012). Multispectral Decomposition for the Removal of Out-Of-Band Effects of Visible/Infrared Imaging Radiometer Suite Visible and Near-Infrared Bands, Appl Opt., 51(18), 4078-4086, doi: 10.1364/AO.51.004078.
Gao, B.-C., Li, R.-R., Lucke, R.L., Davis, C.O., Bevilacqua, R.M., Korwan, D.R., Montes, M.J., Bowles, J.H., and Corson, M.R. (2012). Vicarious Calibrations of HICO Data Acquired from the International Space Station, Appl. Opt., 51(14), 2559-2567, doi: 10.1364/AO.51.002559.
Gao, B.-C. and Li, R.R. (2012). Removal of Thin Cirrus Scattering Effects for Remote Sensing of Ocean Color from Space, IEEE Geosci. Remote S., 9(5), 972-976, doi: 10.1109/LGRS.2012.2187876.
Li, R.-R., Lucke, R., Korwan, D., and Gao, B.-C. (2011). A Technique for Removing Second-Order Light Effects from Hyperspectral Imaging Data, IEEE Geosci. Remote S., 50(3), 824-830, doi: 10.1109/TGRS.2011.2163161.
Gitelson, A.A., Gao, B.-C., Li, R.-R., Berdnikov, S., and Saprygin, V. (2011). Estimation of Chlorophyll-A Concentration in Productive Turbid Waters Using a Hyperspectral Imager for the Coastal Ocean - The Azov Sea Case Study, Environ. Res. Lett., 6(2), 024023, doi: 10.1088/1748-9326/6/2/024023.
Lee, J., Yang, P., Dessler, A.E., Gao, B.-C., and Platnick, S. (2009). Distribution and Radiative Forcing of Tropical Thin Cirrus Clouds, J. Atmos. Sci., 66(12), 3721-3731, doi: 10.1175/2009JAS3183.1.
Gao, B.-C., Montes, M.J., Davis, C.O., and Goetz, A.F.H. (2009). Atmospheric Correction Algorithms for Hyperspectral Remote Sensing Data of Land and Ocean, Remote Sens. Environ., 113(1), S17-S24, doi: 10.1016/j.rse.2007.12.015.
Meyer, K., Platnick, S., Yang, P., and Gao, B.-C. (2009). Cirrus Cloud Optical Thickness from Reflectance Measurements in the MODIS 1.38__m Channel, AIP Conf. Proc., 1100, 404, doi: 10.1063/1.3117005.
Meyer, K., Yang, P., and Gao, B.-C. (2007). Tropical Ice Cloud Optical Depth, Ice Water Path, and Frequency Fields Inferred from the MODIS Level-3 Data, Atmos. Res., 85(2), 171-182, doi: 10.1016/j.atmosres.2006.09.009.
Gao, B.-C., Montes, M.J., Li, R.-R., Dierssen, H.M., and Davis, C.O. (2007). An Atmospheric Correction Algorithm for Remote Sensing of Bright Coastal Waters Using MODIS Land and Ocean Channels in the Solar Spectral Region, IEEE Geosci. Remote S., 45(6), 1835-1843, doi: 10.1109/TGRS.2007.895949.
Gao, B.-C., Montes, M.J., and Davis, C.O. (2004). Refinement of Wavelength Calibrations of Hyperspectral Imaging Data Using a Spectrum-Matching Technique, Remote Sens. Environ., 90(4), 424-433, doi: 10.1016/j.rse.2003.09.002.
Meyer, K., Yang, P., and Gao, B.-C. (2004). Optical Thickness of Tropical Cirrus Clouds Derived from the MODIS 0.66 and 1.375-mm Channels, IEEE Geosci. Remote S., 42(4), 833-841, doi: 10.1109/TGRS.2003.818939.
Gao, B.-C. and Kaufman, Y.J. (2003). Water Vapor Retrievals Using Moderate Resolution Imaging Spectrometer (MODIS) Near-IR Channels, J. Geophys. Res., 108(D13), 4389-4398, doi: 10.1029/2002JD003023.
Li, R.-R., Kaufman, Y.J., Gao, B.-C., and Davis, C.O. (2003). Remote Sensing of Suspended Sediments and Shallow Coastal Waters, IEEE Geosci. Remote S., 41(3), 559-566, doi: 10.1109/TGRS.2003.810227.
King, M.D., Menzel, W.P., Kaufman, Y.J., Tanré, D., Gao, B.-C., Platnick, S., Ackerman, S.A., Remer, L.A., Pincus, R., and Hubanks, P.A. (2003). Cloud and Aerosol Properties, Precipitable Water, and Profiles of Temperature and Water Vapor from MODIS, IEEE Geosci. Remote S., 41(2), 442-458, doi: 10.1109/TGRS.2002.808226.
Gao, B.-C., Kaufman, Y.J., Tanré, D., and Li, R.-R. (2002). Distinguishing Tropospheric Aerosols from Thin Cirrus Clouds for Improved Aerosol Retrievals Using the Ratio of 1.38-mm and 1.24-mm Channels, Geophys. Res. Lett., 29(18), 1890, doi: 10.1029/2002GL015475.
Gao, B.-C., Yang, P., Han, W., Li, R.-R., and Wiscombe, W.J. (2002). An Algorithm Using Visible and 1.38-Mm Channels to Retrieve Cirrus Cloud Reflectances from Aircraft and Satellite Data, IEEE Geosci. Remote S., 40(8), 1659-1668, doi: 10.1109/TGRS.2002.802454.
Gao, B.-C. and Li, R.-R. (2000). Quantitative Improvement in the Estimates of NDVI Values from Remotely Sensed Data by Correcting Thin Cirrus Scattering Effects, Remote Sens. Env., 74(3), 494-502, doi: 10.1016/S0034-4257(00)00141-3.
Gao, B.-C., Montes, M.J., Ahmad, Z. and Davis, C.O. (2000). Atmospheric Correction Algorithm for Hyperspectral Remote Sensing of Ocean Color from Space, Appl. Opt., 39(6), 887-896, doi: 10.1364/AO.39.000887.
Gao, B.-C., Kaufman, Y.J., Han, W., and Wiscombe, W.J. (1998). Correction of Thin Cirrus Path Radiance in the 0.4 - 1.0 µm Spectral Region Using the Sensitive 1.375-µm Cirrus Detecting Channel, J. Geophys. Res., 103(D24), 32169-32176, doi: 10.1029/98JD02006.
Gao, B.-C. (1996). NDWI - A Normalized Difference Water Index for Remote Sensing of Vegetation Liquid Water from Space, Remote Sens. Environ., 58(3), 257-266, doi: 10.1016/S0034-4257(96)00067-3.
Gao, B.-C. and Kaufman, Y.J. (1995). Selection of the 1.375-µm MODIS Channel for Remote Sensing of Cirrus Clouds and Stratospheric Aerosols from Space, J. Atm. Sci., 52, 4231-4237, doi: 10.1175/1520-0469(1995)052<4231:SOTMCF>2.0.CO;2.
Gao, B.-C., Heidebrecht, K.H.,and Goetz, A.F.H. (1993). Derivation of Scaled Surface Reflectances from AVIRIS Data, Remote Sens. Environ., 44(2-3), 165-178, doi: 10.1016/0034-4257(93)90014-O.
Gao, B.-C., Goetz, A.F.H., and Wiscombe, W.J. (1993). Cirrus Cloud Detection from Airborne Imaging Spectrometer Data Using the 1.38 µm Water Vapor Band, Geophys. Res. Lett., 20(4), 301-304, doi: 10.1029/93GL00106.
Gao, B.-C. and Goetz, A.F.H. (1990). Column Atmospheric Water Vapor and Vegetation Liquid Water Retrievals from Airborne Imaging Spectrometer Data, J. Geophys. Res., 95(D4), 3549-3564, doi: 10.1029/JD095iD04p03549.