OCCRI Researchers

Title: Assistant Professor
Name: Thomas Hilker
Institution: Oregon State University
Department: College of Forestry – Forest Engineering, Resources and Management

PhD Forestry, University of British Columbia, 2008
MS Photogrammetry and Geoinformatics, HfT Stuttgart, 2002
BS Forestry, University of Applied Sciences, Göttingen, 2000

Research Theme: Remote sensing of the carbon, water and energy balance of terrestrial ecosystems.

Research Fields:

Modeling Ecosystems

Professional Activities:

Member of the Editorial Board of Remote Sensing of Environment.

Development of multi-angle remote sensing algorithm to obtain photosynthetic activity of vegetation

Development of data fusion technique to generate high spatial resolution and high temporal resolution time series

Reviewer: Nature Geoscience , Remote Sensing of Environment, Global Change Biology, Journal of Geophysical Research, Agricultural and Forest Meteorology, and others

Member American Geophysical Union

Selected Publications:

Hilker, T., Lyapustin, A.I., Tucker, C.J., Sellers, P.J., Hall, F.G., Wang, Y (2012) Remote Sensing of Tropical Ecosystems: Atmospheric Correction and Cloud Masking Matter. Remote Sensing of Environment 127, 370-384

Lyapustin, A.I., Wang, Y., Lazlo, I., Hilker, T., Hall, F.G., Sellers, P.J., Tucker, C.J., Korkin, S.V. (2012) Multi-Angle Implementation of Atmospheric Correction for MODIS (MAIAC). Part 3: Atmospheric Correction. Remote Sensing of Environment 127, 385-393

Hall, F.G., Hilker, T., Coops, N.C. (2012) Data assimilation of photosynthetic light-use efficiency using multi-angular satellite data: I. Model formulation Remote Sensing of Environment, 121, 301–308

Hilker, T., Hall, F.G., Tucker, C.J., Coops, N.C., Black, T.A., Nichol, C.J., Sellers, P.J., Barr, A., Hollinger, D.Y., Munger, W. (2012) Data assimilation of photosynthetic light-use efficiency using multi-angular satellite data: II Model implementation and validation Remote Sensing of Environment, 121 287–300

Coops, N.C., Waring, R.H., Hilker, T. (2012) Prediction of Soil Properties using a Process-based Forest Growth Model to Match Satellite-Derived Estimates of Leaf Area Index. Remote Sensing of Environment, in press