Dr. Huemmrich has developed and used models of light interactions with vegetation, and has studied the use of remotely sensed data to collect information on biophysical variables and land cover type using both computer models and field measurements. He is familiar with bi-directional and hyperspectral data and their uses in determining biophysical characteristics. He has been involved in the analysis of remotely sensed data from a variety of platforms, including data collected from surface, aircraft, and satellite instruments.
He has experience in collecting data on biophysical variables in the field, with direct experience with both broad band and hyperspectral radiometers to determine vegetation canopy spectral reflectance, measured leaf level reflectance and transmittance using an integration sphere, measured light transmittance of vegetation canopies and their leaf area index. He has performed fieldwork on the use of remote sensing in a variety of habitats, including the tundra, desert, shrubland, tall grass prairie, agricultural fields, boreal forest, temperate rain forest, and temperate deciduous forest. Dr. Huemmrich was involved in the operations and data analysis for the Boreal Ecosystem and Atmosphere Study (BOREAS) and the First International Satellite Land Surface Climatology Project Field Experiment (FIFE) in Kansas. He was the assistant Information Scientist on these experiments, in particular working directly with the archival of the flux tower data, and has experience in the development and operation of interdisciplinary information systems in support of large field experiments.
Karl F Huemmrich
(RESEARCH ASSISTANT)
Org Code: 618
NASA/GSFCMail Code: 618
Greenbelt, MD 20771
Employer: UNIVERSITY OF MARYLAND BALTIMORE CO
Brief Bio
Teaching Experience
‘Arctic Geography.’ Geography and Environmental Sciences Department, University of Maryland Baltimore County, Spring 2007, 2009, 2011, and Fall 2012.
‘Seminar on Ecophysiology and Plant Distribution,’ Geography and Environmental Sciences Department, University of Maryland Baltimore County, Spring 2002.
‘Advanced Remote Sensing,’ Geography Department, University of Maryland College Park, Spring 2000 and 2001.
‘Seminar on Ecophysiology and Plant Distribution,’ Geography and Environmental Sciences Department, University of Maryland Baltimore County, Spring 2002.
‘Advanced Remote Sensing,’ Geography Department, University of Maryland College Park, Spring 2000 and 2001.
Education
Ph.D., Geography, May 1995
University of Maryland, College Park, MD 20741.
B.S., Physics, May 1978
Carnegie-Mellon University, Pittsburgh, PA 15213-3980.
University of Maryland, College Park, MD 20741.
B.S., Physics, May 1978
Carnegie-Mellon University, Pittsburgh, PA 15213-3980.
Publications
Refereed
Huemmrich, K. F., J. Gamon, C. Tweedie, et al. P. K. Campbell, D. R. Landis, and E. M. Middleton. 2013. Arctic Tundra Vegetation Functional Types Based on Photosynthetic Physiology and Optical Properties IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 6 (2): 265-275 [10.1109/JSTARS.2013.2253446]
Cheng, Y., E. Middleton, Q. Zhang, et al. K. Huemmrich, P. Campbell, L. Corp, B. Cook, W. Kustas, and C. Daughtry. 2013. Integrating Solar Induced Fluorescence and the Photochemical Reflectance Index for Estimating Gross Primary Production in a Cornfield Remote Sensing 5 (12): 6857-6879 [10.3390/rs5126857]
Gamon, J., K. Huemmrich, R. Stone, and C. Tweedie. 2013. Spatial and temporal variation in primary productivity (NDVI) of coastal Alaskan tundra: Decreased vegetation growth following earlier snowmelt Remote Sensing of Environment 129 144–153 [10.1016/j.rse.2012.10.030]
Thenkabail, P., I. Mariotto, M. Gumma, et al. E. Middleton, D. Landis, and K. Huemmrich. 2013. Selection of Hyperspectral Narrowbands (HNBs) and Composition of Hyperspectral Twoband Vegetation Indices (HVIs) for Biophysical Characterization and Discrimination of Crop Types Using Field Reflectance and Hyperion/EO-1 Data IEEE J. Sel. Top. Appl. Earth Observations Remote Sensing 6 (2): 427-439 [10.1109/JSTARS.2013.2252601]
Huemmrich, K. 2013. Simulations of Seasonal and Latitudinal Variations in Leaf Inclination Angle Distribution: Implications for Remote Sensing Advances in Remote Sensing 2 (2): 93-101 [10.4236/ars.2013.22013]
Campbell, P. K., E. M. Middleton, K. J. Thome, et al. F. Kokaly, K. F. Huemmrich, D. Lagomasino, K. Novick, and N. Brunsell. 2013. EO-1 Hyperion Reflectance Time Series at Calibration and Validation Sites: Stability and Sensitivity to Seasonal Dynamics IEEE J. Sel. Top. Appl. Earth Observations Remote Sensing 6 (2): 276-290 [10.1109/JSTARS.2013.2246139]
Joiner, J., L. Guanter, R. Lindstrot, et al. M. Voigt, A. P. Vasilkov, E. M. Middleton, K. F. Huemmrich, Y. Yoshida, and C. Frankenberg. 2013. Global monitoring of terrestrial chlorophyll fluorescence from moderate-spectral-resolution near-infrared satellite measurements: methodology, simulations, and application to GOME-2 Atmos. Meas. Tech. 6 (10): 2803-2823 [10.5194/amt-6-2803-2013]
Peddle, D., K. F. Huemmrich, F. G. Hall, et al. J. G. Masek, S. A. Soenen, and C. D. Jackson. 2011. Applications of the BIOPHYS algorithm for physically - based retrieval of biophysical , structural and forest disturbance information IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 4 971-982 [10.1109/JSTARS.2011.2164899]
Huemmrich, K. F., J. Gamon, C. Tweedie, et al. S. Oberbauer, G. Kinoshita, S. Houston, A. Kuchy, R. Hollister, H. Kwon, M. Mano, Y. Harazono, P. Webber, and W. Oechel. 2010. Remote sensing of tundra gross ecosystem productivity and light use efficiency under varying temperature and moisture conditions Remote Sensing of Environment 114 (3): 481-489
Huemmrich, K. F., G. Kinoshita, J. Gamon, et al. S. Houston, H. Kwan, and W. Oechel. 2010. Tundra carbon balance under varying temperature and moisture regimes Journal of Geophysical Research-Biogeosciences 115
Middleton, E. M., Y. Cheng, T. Hilker, et al. T. Black, P. Krishnan, N. Coops, and K. F. Huemmrich. 2009. Linking foliage spectral responses to canopy-level ecosystem photosynthetic light-use efficiency at a Douglas-fir forest in Canada Canadian J Remote Sens 35 (2): 166-188 [ISSN 1712-7971]
Drolet, G., E. M. Middleton, K. Huemmrich, et al. F. G. Hall, B. Amiro, A. Barr, T. Black, J. McGaughey, and H. Margolis. 2008. Regional mapping of gross light-use efficiency using MODIS spectral indices Remote Sens Environ 112 (6): 3064-3078
Hilker, T., N. Coops, F. G. Hall, et al. T. Black, B. Chen, P. Krishnan, M. Wulder, P. J. Sellers, E. M. Middleton, and K. F. Huemmrich. 2008. A modeling approach for upscaling gross ecosystem production to the landscape scale using remote sensing data J. Geophys. Res. 113 (G3): 10.1029/2007JG000666 [10.1029/2007JG000666]
Hall, F. G., T. Hilker, N. Coops, et al. A. Lyapustin, K. Huemmrich, E. M. Middleton, H. Margolis, G. Drolet, and T. Black. 2008. Multi-angle remote sensing of forest light use efficiency by observing PRI variation with canopy shadow fraction Remote Sensing of Environment 112 (7): 3201-3211 [10.1016/j.rse.2008.03.015]
Masek, J. G., E. F. Vermote, N. Z. Saleous, et al. R. E. Wolfe, F. G. Hall, K. F. Huemmrich, F. Gao, J. L. Kutler, and T. Lim. 2006. A Landsat Surface Reflectance Dataset for North America, 1990–2000 IEEE Geosci. Remote Sensing Lett. 3 (1): 68-72 [10.1109/LGRS.2005.857030]
Drolet, G. G., K. F. Huemmrich, F. G. Hall, et al. E. M. Middleton, T. A. Black, A. G. Barr, and H. A. Margolis. 2005. A MODIS-derived photochemical reflectance index to detect inter-annual variations in the photosynthetic light-use efficiency of a boreal deciduous forest Remote Sens Environ 98 (2-3): 212-224 [10.1016/j.rse.2005.07.006]
Huemmrich, K. F., J. L. Privette, M. Mukelabai, R. B. Myneni, and Y. Knyazikhin. 2005. Time-series validation of MODIS land biophysical products in a Kalahari woodland, Africa Int J Remote Sens 26 (10): 4381-4398
Gamon, J., K. Huemmrich, D. Peddle, et al. J. Chen, D. Fuentes, F. Hall, J. Kimball, S. Goetz, J. Gu, K. McDonald, J. Miller, M. Moghaddam, A. Rahman, J. Roujean, and E. Smith. 2004. Remote sensing in BOREAS: Lessons learned Remote Sens Environ 89 139-162
Huemmrich, K. F. 2001. The GeoSail model: a simple addition to the SAIL model to describe discontinuous canopy reflectance emote Sensing of Environment 75 423-431
Non-Refereed
Corp, L. A., Y.-B. Cheng, E. M. Middleton, et al. G. G. Parker, K. F. Huemmrich, and P. K. Campbell. 2009. Hyperspectral-LIDAR system and data product integration for terrestrial applications SPIE Optics Photonics, Optical Engineering plus Applications, Imaging Spectrometry
Corp, L. A., E. M. Middleton, P. K. Campbell, et al. K. F. Huemmrich, Y.-B. Cheng, and C. S. Daughtry. 2009. Remote Sensing techniques to monitor Nitrogen driven Carbon dynamics in vegetation SPIE Optics Photonics, Optical Engineering plus Applications, Remote Sensing and Modeling of Ecosystems for Sustainability
Cheng, Y.-B., L. A. Corp, E. M. Middleton, et al. K. F. Huemmrich, Q. Zhang, P. E. Campbell, and G. Parker. 2008. Comparisons between in Situ Anisotropic Reflectance Measurements and Simulations for Vegetation Canopies: Validation and Sensitivity Analysis IGARSS 2008 - 2008 IEEE International Geoscience and Remote Sensing Symposium 3 III-790 - III-792 [10.1109/IGARSS.2008.4779467]
Corp, L. A., E. M. Middleton, C. S. Daughtry, et al. P. K. Campbell, K. F. Huemmrich, and Y.-B. Cheng. 2008. Impact of Spectral Resolution on Solar Induced Fluorescence and Reflectance Indices for Monitoring Vegetation IGARSS 2008 - 2008 IEEE International Geoscience and Remote Sensing Symposium 4 1387 - 1390 [10.1109/IGARSS.2008.4779991]