Tian Yao

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Tian Yao

  • RESEARCH SCIENTIST
  • 617.834.6575
  • NASA/GSFC
  • Mail Code: 619
  • LANHAM , MD 20706
  • Employer: SCIENCE SYSTEMS AND APPLICATIONS INC
  • Brief Bio

    Dr. Yao received her B.S. degree in in Natural Resources and Environmental Science from Beijing Normal University, China, in 2003. Dr. Yao obtained her Ph.D. in Geography from Boston University in 2012. Her PhD work was focusing on measuring forest structure and biomass using lidar and optical remote sensing. She joined NASA Goddard through GESTAR/USRA in September 2013 as a Scientist. Her work is focusing on producing and evaluating the fAPARchl remote sensing product; developing methods for sustained implementation of remote sensing product into ecosystem models; developing methods to improve the estimations of carbon stocks with remote sensing products and ecosystem models such as the Community Land Model; and developing parallel computing approaches to speed up the process of satellite images for radiative transfer model development and remote sensing product testing.

    Education
    Ph.D. in Geography, May 2012, Boston University, Boston, MA, USA
    B.S. in Natural Resources and Environmental Science, May 2003, Beijing Normal University, Beijing, China

    Research Interest
    • Terrestrial Carbon Cycle Modeling
    • Monitoring and Modeling Vegetation Dynamics in Response to Climate Change
    • Optical and Lidar Remote Sensing
    • Applications of remote sensing in ecosystems science and natural resources

    Computer programming language and related skills
    • Proficient in Windows and Linux operating systems;
    • Proficient in Matlab;
    • Proficient in image processing software (ENVI and ESRI ArcGIS);
    • Intermediate knowledge in C, FORTRAN, R and Shell Script.
    • Experience working with scientific data formats including NetCDF and HDF.

    Academic Service
    • Invited Peer Reviewer: Remote Sensing of Environment; IEEE Transactions on Geosciences and Remote Sensing; IEEE Geoscience and Remote Sensing Letters; IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing; International Journal of Digital Earth; Remote Sensing; European Journal of Forest Research; Forest Ecosystems; Journal of Ecology and the Natural Environment; Journal of Forestry Research; The International Journal of Remote Sensing; Sensors; Climate; Forests; Land; Sustainability.
    • Proposal Reviewer: NASA Postdoctoral Program.
    • International Conference Reviewer: 2018 and 2017 IEEE International Geoscience & Remote Sensing Symposium
    • Conference Session Chair: Mapping and Monitoring Terrestrial Vegetation Carbon Stocks and Fluxes: Inventories, Modeling, and Policy Support, 2015 American Geophysical Union (AGU) Fall Meeting, San Francisco, USA.


    Field/Lab Experience
    • Smithsonian Environmental Research Center, MD – Field ground calibration for airborne remote sensing flights in summer 2017.
    • Cornfield stands, MD - Measuring leaf fluorescence, leaf chlorophyll content, soil moisture and vegetation height in summer 2014, 2015 and 2017.
    • New England Forest Stands, MA, ME and NH - Measuring forest structure parameters, such as tree diameters, tree height, tree species, tree crown size and LAI in summer 2007, 2009 - 2011.
    • Sierra Nevada Stands, CA - Measuring forest structure parameters, such as tree diameters, tree height, tree species, tree crown size, crown shape and LAI in July 2008.
    • Agricultural ecological station, Hebei, China - Measuring leaf reflectance, LAI and LAD of agricultural crops in summer 2003.

    Selected Peer Reviewed Journal Papers

    In Review Yao, T., Zhang, Q., Middleton, E., Lyapustin, A., Wang, Y., Shuai, Y. & Selkirk, H. (2018). Improving the Estimation of Gross Primary Production (GPP) Using MODIS data in the Community Land Model. Submitted to Agricultural and Forest Meteorology.
    In Review Campana, P. E., Zhang, J., Yao, T., Zhang, Y., Lundblad, A. & Yan, J. (2018). Managing agricultural drought in Sweden using a novel spatially-explicit model from the perspective of water-food-energy nexus. Submitted to Journal of Cleaner Production.
    2017 Campana, P. E., Zhang, J., Yao, T., Zhang, Y., Lundblad, A. & Yan, J. (2017). The water-food-energy nexus optimization approach to combat agricultural drought: a case study in the United States. Applied Energy (In Press), Doi:10.1016/j.apenergy.2017.07.036.
    2017 Franks, S., Neigh, C.S.R., Campbell, P.K., Sun, G., Yao, T., Zhang, Q., Huemmrich, K.F., Middleton, E.M., Ungar, S.G., Frye, S.W. (2017). EO-1 Data Quality and Sensor Stability with Changing Orbital Precession at the End of a 16 Year Mission. Remote Sens. 2017, 9, 412-430.
    2016 Zhang, Q., Middleton, E., Cheng, Y., Huemmrich, K., Cook, B., Corp, L., Kustas, W., Russ, A., Prueger, J., Yao, T. (2016), Integrating chlorophyll fAPAR and nadir photochemical reflectance index from EO-1/Hyperion to predict cornfield daily gross primary production, Remote sensing of Environment, 186(1), 311-321.
    2013 Zhao, F., Yang, X., Strahler, A. H., Schaaf, C., Yao, T., Wang, W. and etc., A comparison of foliage profiles in the Sierra National Forest obtained with a full-waveform under-canopy EVI lidar system with the foliage profiles obtained with an airborne full-waveform LVIS lidar system, Remote Sensing of Environment, 136, 330-341.
    2013 Yang, X., Strahler, A.H., Schaaf, C., Jupp, D., Yao, T., Zhao, F., Wang, Z. Culveno, D., Newnham, G., Lovell, J., Dubayah, R., Woodcock, C., Ni-Meister, W. (2013). Three-dimensional forest reconstruction and structural parameter retrievals using a terrestrial full-waveform lidar instrument (Echidna®), Remote Sensing of Environment, 135, 36-51
    2012 Zhao, F., Strahler, A.H., Schaaf, C.L., Yao, T., Yang, X.Y., Wang, Z., Schull, M.A., Roman, M.O. Woodcock, C.E., Olofsson, P., Ni-Meister, W., Jupp, D.L.,Lovell, J.L., Culvenor, D.S., Newnham, G.J., (2012), Measuring gap fraction, element clumping index and LAI in Sierra Forest stands using a full-waveform ground-based lidar, Remote Sensing of Environment, 125, 73-79.
    2011 Yao, T., Yang, X., Zhao, F., Wang, Z., Zhang, Q., Jupp, D.L.B., Culvenor, D.S., Newnham, G.J., Ni-Meister, W., Schaaf, C.B., Woodcock, C.E., Strahler, A.H. (2011), Measuring forest structure and biomass in New England forest stands using Echidna® ground-based lidar, Remote sensing of Environment, 115(11), 2965-2974.
    2011 Zhao, F., Yang, X., Schull, M., Roman-Colon, M., Yao, T., Wang, Z., Zhang, Q., Jupp, D., Culvenor, D., Newnham, G.,Ni-Meister, W., Schaff, C., Woodcock, C., Strahler, A. & Richardsone, A. (2011), Measuring effective leaf area index, foliage profile, and stand height in New England forest stands using Echidna® Validation Instrument (EVI) ground-Based lidar. Remote Sensing of Environment, 115(11), 2954-2964.
    2011 Wang, Z., Schaaf, C., Philip, L., Knyazikhin, Y., Schull, M., Strahler, A., Yao, T., Myneni, R.B., Chopping, M. (2011). Retrieval of canopy height using moderate-resolution imaging spectroradiometer (MODIS) data, Remote sensing of Environment, 115(6), 1595-1601.
    2010 Ni-Meister, W., S. Lee, A. H. Strahler, C. E. Woodcock, C. Schaaf, T. Yao, K. J. Ranson, G. Sun, and J. B. Blair, (2010), Assessing general relationships between aboveground biomass and vegetation structure parameters for improved carbon estimate from lidar remote sensing, J. Geophys. Res., 115(G00E11).
    2008 Ni-Meister, W., Strahler, A., Woodcock, C.E., Schaaf, C.B., Jupp, L.B.D., Yao, T., Zhao, F., and Yang, X., (2008), Modeling the hemispherical scanning, below-canopy lidar and vegetation structure characteristics with a geometric-optical and radiative-transfer model, Canadian Journal of Remote Sensing, 34(2), 385-S397.
    2008 Strahler, A.H., Jupp, D.L.B., Woodcock, C.E., Schaaf, C. B., Yao, T., Zhao, F., Yang, X., Lovell, J.L., Culvenor, D.S., Newnham, G.J, Ni-Meister, W., and Boykin-Morris, W. (2008), Retrieval of forest structure parameters using a ground based laser Instrument (Echidna®), Special issue for Canadian Journal of Remote Sensing. 34(2), 426-440.

    Brief Bio

    Dr. Yao received her B.S. degree in in Natural Resources and Environmental Science from Beijing Normal University, China, in 2003. Dr. Yao obtained her Ph.D. in Geography from Boston University in 2012. Her PhD work was focusing on measuring forest structure and biomass using lidar and optical remote sensing. She joined NASA Goddard through GESTAR/USRA in September 2013 as a Scientist. Her work is focusing on producing and evaluating the fAPARchl remote sensing product; developing methods for sustained implementation of remote sensing product into ecosystem models; developing methods to improve the estimations of carbon stocks with remote sensing products and ecosystem models such as the Community Land Model; and developing parallel computing approaches to speed up the process of satellite images for radiative transfer model development and remote sensing product testing.

    Education
    Ph.D. in Geography, May 2012, Boston University, Boston, MA, USA
    B.S. in Natural Resources and Environmental Science, May 2003, Beijing Normal University, Beijing, China

    Research Interest
    • Terrestrial Carbon Cycle Modeling
    • Monitoring and Modeling Vegetation Dynamics in Response to Climate Change
    • Optical and Lidar Remote Sensing
    • Applications of remote sensing in ecosystems science and natural resources

    Computer programming language and related skills
    • Proficient in Windows and Linux operating systems;
    • Proficient in Matlab;
    • Proficient in image processing software (ENVI and ESRI ArcGIS);
    • Intermediate knowledge in C, FORTRAN, R and Shell Script.
    • Experience working with scientific data formats including NetCDF and HDF.

    Academic Service
    • Invited Peer Reviewer: Remote Sensing of Environment; IEEE Transactions on Geosciences and Remote Sensing; IEEE Geoscience and Remote Sensing Letters; IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing; International Journal of Digital Earth; Remote Sensing; European Journal of Forest Research; Forest Ecosystems; Journal of Ecology and the Natural Environment; Journal of Forestry Research; The International Journal of Remote Sensing; Sensors; Climate; Forests; Land; Sustainability.
    • Proposal Reviewer: NASA Postdoctoral Program.
    • International Conference Reviewer: 2018 and 2017 IEEE International Geoscience & Remote Sensing Symposium
    • Conference Session Chair: Mapping and Monitoring Terrestrial Vegetation Carbon Stocks and Fluxes: Inventories, Modeling, and Policy Support, 2015 American Geophysical Union (AGU) Fall Meeting, San Francisco, USA.


    Field/Lab Experience
    • Smithsonian Environmental Research Center, MD – Field ground calibration for airborne remote sensing flights in summer 2017.
    • Cornfield stands, MD - Measuring leaf fluorescence, leaf chlorophyll content, soil moisture and vegetation height in summer 2014, 2015 and 2017.
    • New England Forest Stands, MA, ME and NH - Measuring forest structure parameters, such as tree diameters, tree height, tree species, tree crown size and LAI in summer 2007, 2009 - 2011.
    • Sierra Nevada Stands, CA - Measuring forest structure parameters, such as tree diameters, tree height, tree species, tree crown size, crown shape and LAI in July 2008.
    • Agricultural ecological station, Hebei, China - Measuring leaf reflectance, LAI and LAD of agricultural crops in summer 2003.

    Selected Peer Reviewed Journal Papers

    In Review Yao, T., Zhang, Q., Middleton, E., Lyapustin, A., Wang, Y., Shuai, Y. & Selkirk, H. (2018). Improving the Estimation of Gross Primary Production (GPP) Using MODIS data in the Community Land Model. Submitted to Agricultural and Forest Meteorology.
    In Review Campana, P. E., Zhang, J., Yao, T., Zhang, Y., Lundblad, A. & Yan, J. (2018). Managing agricultural drought in Sweden using a novel spatially-explicit model from the perspective of water-food-energy nexus. Submitted to Journal of Cleaner Production.
    2017 Campana, P. E., Zhang, J., Yao, T., Zhang, Y., Lundblad, A. & Yan, J. (2017). The water-food-energy nexus optimization approach to combat agricultural drought: a case study in the United States. Applied Energy (In Press), Doi:10.1016/j.apenergy.2017.07.036.
    2017 Franks, S., Neigh, C.S.R., Campbell, P.K., Sun, G., Yao, T., Zhang, Q., Huemmrich, K.F., Middleton, E.M., Ungar, S.G., Frye, S.W. (2017). EO-1 Data Quality and Sensor Stability with Changing Orbital Precession at the End of a 16 Year Mission. Remote Sens. 2017, 9, 412-430.
    2016 Zhang, Q., Middleton, E., Cheng, Y., Huemmrich, K., Cook, B., Corp, L., Kustas, W., Russ, A., Prueger, J., Yao, T. (2016), Integrating chlorophyll fAPAR and nadir photochemical reflectance index from EO-1/Hyperion to predict cornfield daily gross primary production, Remote sensing of Environment, 186(1), 311-321.
    2013 Zhao, F., Yang, X., Strahler, A. H., Schaaf, C., Yao, T., Wang, W. and etc., A comparison of foliage profiles in the Sierra National Forest obtained with a full-waveform under-canopy EVI lidar system with the foliage profiles obtained with an airborne full-waveform LVIS lidar system, Remote Sensing of Environment, 136, 330-341.
    2013 Yang, X., Strahler, A.H., Schaaf, C., Jupp, D., Yao, T., Zhao, F., Wang, Z. Culveno, D., Newnham, G., Lovell, J., Dubayah, R., Woodcock, C., Ni-Meister, W. (2013). Three-dimensional forest reconstruction and structural parameter retrievals using a terrestrial full-waveform lidar instrument (Echidna®), Remote Sensing of Environment, 135, 36-51
    2012 Zhao, F., Strahler, A.H., Schaaf, C.L., Yao, T., Yang, X.Y., Wang, Z., Schull, M.A., Roman, M.O. Woodcock, C.E., Olofsson, P., Ni-Meister, W., Jupp, D.L.,Lovell, J.L., Culvenor, D.S., Newnham, G.J., (2012), Measuring gap fraction, element clumping index and LAI in Sierra Forest stands using a full-waveform ground-based lidar, Remote Sensing of Environment, 125, 73-79.
    2011 Yao, T., Yang, X., Zhao, F., Wang, Z., Zhang, Q., Jupp, D.L.B., Culvenor, D.S., Newnham, G.J., Ni-Meister, W., Schaaf, C.B., Woodcock, C.E., Strahler, A.H. (2011), Measuring forest structure and biomass in New England forest stands using Echidna® ground-based lidar, Remote sensing of Environment, 115(11), 2965-2974.
    2011 Zhao, F., Yang, X., Schull, M., Roman-Colon, M., Yao, T., Wang, Z., Zhang, Q., Jupp, D., Culvenor, D., Newnham, G.,Ni-Meister, W., Schaff, C., Woodcock, C., Strahler, A. & Richardsone, A. (2011), Measuring effective leaf area index, foliage profile, and stand height in New England forest stands using Echidna® Validation Instrument (EVI) ground-Based lidar. Remote Sensing of Environment, 115(11), 2954-2964.
    2011 Wang, Z., Schaaf, C., Philip, L., Knyazikhin, Y., Schull, M., Strahler, A., Yao, T., Myneni, R.B., Chopping, M. (2011). Retrieval of canopy height using moderate-resolution imaging spectroradiometer (MODIS) data, Remote sensing of Environment, 115(6), 1595-1601.
    2010 Ni-Meister, W., S. Lee, A. H. Strahler, C. E. Woodcock, C. Schaaf, T. Yao, K. J. Ranson, G. Sun, and J. B. Blair, (2010), Assessing general relationships between aboveground biomass and vegetation structure parameters for improved carbon estimate from lidar remote sensing, J. Geophys. Res., 115(G00E11).
    2008 Ni-Meister, W., Strahler, A., Woodcock, C.E., Schaaf, C.B., Jupp, L.B.D., Yao, T., Zhao, F., and Yang, X., (2008), Modeling the hemispherical scanning, below-canopy lidar and vegetation structure characteristics with a geometric-optical and radiative-transfer model, Canadian Journal of Remote Sensing, 34(2), 385-S397.
    2008 Strahler, A.H., Jupp, D.L.B., Woodcock, C.E., Schaaf, C. B., Yao, T., Zhao, F., Yang, X., Lovell, J.L., Culvenor, D.S., Newnham, G.J, Ni-Meister, W., and Boykin-Morris, W. (2008), Retrieval of forest structure parameters using a ground based laser Instrument (Echidna®), Special issue for Canadian Journal of Remote Sensing. 34(2), 426-440.

                                                                                                                                                                                            
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