remote sensing  ObituaryIn Memorium: Thomas HilkerAlexei I. Lyapustin 1,*, Nicholas. C. Coops 2, Forrest G. Hall 1, Compton J. Tucker 1,Piers J. Sellers 1, Lenio Soares Galvão 3, Luiz E. O. C. Aragão 3, Liana O. Anderson 3,Caroline J. Nichol 4 and Richard H. Waring 51 NASA Goddard Space Flight Center, Greenbelt, MD 20771, USA; forrest.g.hall@nasa.gov (F.G.H.);compton.j.tucker@nasa.gov (C.J.T.); piers.j.sellers@nasa.gov (P.J.S.)2 University of British Columbia, Vancouver, BC V6T 1Z4, Canada; nicholas.coops@ubc.ca3 National Institute for Space Research (INPE), São José dos Campos 12227-010, Brazil;lenio.galvao@inpe.br (L.S.G.); laragao@dsr.inpe.br (L.E.O.C.A.); liana.anderson@cemaden.gov.br (L.O.A.)4 School of GeoSciences, University of Edinburgh, Edinburgh EH9 3FF, UK; caroline.nichol@ed.ac.uk5 Oregon State University, Corvallis, OR 97331, USA; richard.waring@oregonstate.edu* Correspondence: alexei.i.lyapustin@nasa.gov; Tel.: +1-301-614-5998Academic Editor: Prasad S. ThenkabailReceived: 8 October 2016; Accepted: 12 October 2016; Published: 17 October 2016Dr. Thomas Hilker left us on 4 September 2016 following a sudden cardiac arrest. Thomas was adevoted husband to Yhasmin, and a brother and son to his family in Germany to whom we expressour deepest sympathies. Friends and colleagues of Thomas in the remote sensing and ecologicalcommunities lament this tragic loss. During his short but stellar science career, Thomas becamea world leader in the field of carbon, water and energy exchange from the land. He pioneeredstudies in the Amazonian forests, using anisotropy information acquired from satellites to describethree-dimensional structures that linked these ecosystems functionally to climatic variation.Thomas had an extreme range of interests—from the engineering of advanced spectrometers toproviding new theories and innovative methods to process remotely sensed data. Dr. Piers Sellers,Acting Director of the Earth Sciences Division at NASA/GSFC, and Deputy Director of the Sciences andExploration Directorate wrote: “Thomas Hilker was something of a renaissance man in Earth Science.He could climb towers, measure tall trees, and calculate spectral indices in his head. Working with himwas like collaborating with two or three normal people. He had some of the best and most originalideas in remote sensing that I’ve come across, but unlike most of us, he could go get the data to provehis point. And he was always the best fun. I remember him coming to a couple of parties of ours—hewas always relaxed, humorous, charming. He could make people laugh and everyone felt so goodaround him.”Thomas obtained a Bachelor of Science degree in Forestry from the University of Applied Sciences,in Goettingen, Germany in 2000, a Master in Photogrammetry and Geoinformatics from the Universityof Applied Sciences in Stuttgart in 2002 and a PhD from the University of British Columbia (UBC) inForestry in 2008. After a three year postdoctoral position at UBC (2008–2011), he worked as a ResearchAssociate at NASA’s Goddard Space Flight Center (2011–2012). From 2012 to 2016, Thomas held aposition as Assistant Professor at Oregon State University’s College of Forestry, leading the RemoteSensing Laboratory and teaching classes in Remote Sensing and Spatial Data Analysis. In 2015 and2016 he was a visiting researcher at the National Institute for Space Studies in Brazil (Instituto Nacionalde Pesquisas Espaciais, INPE). He looked forward to starting a position as an Associate Professor ofEarth System Science and Remote Sensing at the University of Southampton, UK.Thomas became fascinated by the global carbon cycle following receipt of his Master’s degree andwas keen to utilize his geospatial skills to unlock the details of the cycle. Inspired by the linksbetween canopy reflectance and photosynthesis, Thomas designed an Automated MultiangularSpectroradiometer for Estimation of Canopy reflectance [1] and improved it in subsequentiterations [2,3] to be able to continuously monitor subtle changes in the reflected spectra fromRemote Sens. 2016, 8, 853; doi:10.3390/rs8100853 www.mdpi.com/journal/remotesensingRemote Sens. 2016, 8, 853 2 of 4forest canopies. Appreciating the potential of a photochemical reflectance index (PRI) developedby Gamon et al. [4] to indicate when the photosynthetic process was down-regulated, Thomas,supported by the Canadian Carbon Program (CCP), developed new techniques for processing spectraldata acquired from multi-angular observations. Changes in spectral bi-directional reflectance (BRDF)help derive remotely sensed estimates of gross primary productivity (GPP) in close agreement withthat measured at a number of eddy-flux tower sites in Canada [5,6].In his PhD dissertation, he found a way to measure and describe forest structure in strikingdetail using airborne Light Detection and Ranging (LiDAR) data. His innovative approach helpedto explain differences measured in net ecosystem production at a range of forest sites [7]. For thiseffort, Thomas was jointly awarded the best PhD thesis in 2008 by the Canadian Remote SensingSociety (CRSS).Thomas enjoyed the elegant simplicity of laser return data and completed a number of studiesexamining how airborne and ground-based laser scanning could be used to provide insights intoecological processes as well as estimates of productivity in lodgepole-pine and Douglas-forests [8,9].His work with LiDAR continued after his PhD [10] and at Oregon State University he continued toexamine uncertainties in above ground biomass estimates from LiDAR [11] and that fused with othersensors such as Landsat [12]. He also developed an approach to effectively fuse Landsat and MODISimagery, in what has become his highest cited paper to date [13].Joining NASA in 2009, Thomas, collaborating with a group of established scientists, built thetheoretical foundations for a satellite that could carry instruments to sense constraints onphotosynthesis (light-use-efficiency), which could be compared with measurements acquired at towersites and expanded to encompass all terrestrial vegetation [14–19].Thomas was intrigued by the ongoing controversy around the dry-season greening of the Amazonforests. As a result, he led a MODIS-based analysis that demonstrated a strong correlation of theremotely sensed greening and browning anomalies of the Amazonian rainforest with the short-termclimate variability as expressed in the ENSO index [20]. The power of multi-angle satellite observationsof vegetation properties to estimate photosynthesis and other key processes encouraged Thomas to jointhe National Institute for Space Research in Brazil as a visiting scientist in 2014 and establish importantcollaborations with Brazilian scientists. With their help, and that of colleagues at Goddard Space FlightCenter, he developed the project “MAPS: Multi-angle Amazon Physiology and Structure” funded bythe Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq), as part of the Brazilian program“Science without Borders”. Previous studies had demonstrated the high sensitivity of the EnhancedVegetation Index (EVI) to differences in view-illumination geometry. While conventionally, this BRDFeffect was considered as a “noise” in the MODIS time series, Hilker and colleagues proposed a uniqueapproach using EVI anisotropy as a source of information on canopy structure in the Amazon [21].Seasonality and drought effects were quantified using directional information obtained from the EVIin MODIS forward scattering and backscattering view directions. This step was preceded by a carefuldefinition of the length of the dry season over the different regions of the Amazon.Within the scope of the MAPS project, Thomas was striving to develop a first-principle wayto characterize vegetation using spectral reflectance in place of more conventional vegetationindices. Atmospherically corrected data from Multi-Angle Implementation of Atmospheric Correction(MAIAC) algorithm [17] in MODIS bands 1–12 were used to invert the fully-coupled canopyreflectance model ProSAIL to estimate monthly canopy chemistry (carotenoids, canopy water,and nitrogen content) focusing the analysis on chlorophyll [22]. The results showed strong seasonalvariations in ProSAIL-derived pigment estimates in central Amazon with marked increases inchlorophyll concentrations early during the dry season. Hilker concluded that vegetation phenology,rather than changes in sunlight, directly controls seasonality of plant productivity across the region.This pioneering work allowed Thomas to experience in loco the intensity of Amazon forest functioning.Thomas’s sharp ideas on using multi-angular information for studying Amazon forest processes willRemote Sens. 2016, 8, 853 3 of 4be eternized by his legacy of scientific writings and passionate engagement with students and scientistsduring his time in Brazil.Thomas was on the editorial board of Remote Sensing of Environment and a dedicated reviewerfor a large number of Forestry and Remote Sensing journals. He served on the Scientific Committee ofthe XVII Symposium on Brazilian Remote Sensing (SBRS) and was the organizer of Special Sessions onXVII SBRS held in 2015 and on the next XVIII SBRS to be held in 2017.In his own way, Thomas had an irresistible personality—kind and humble, always smiling andin good humor. In combination with his engaging and sharp mind, and boundless enthusiasm forhis work, he drew many researches into his orbit starting multiple collaborations. In every place heworked, he rapidly became a reference for students and researchers who sought his scientific advice.Each of us, blessed with a chance to meet and work with Dr. Hilker, have benefitted immeasurablyfrom the opportunity, and his scientific legacy will benefit future generations. We will miss you,Thomas, brilliant scientist, amazing friend and wonderful human being.Remote Sens. 2016, 8, 853 3 of 4  proc sses will be eternized by his legacy of scientific writi s and passionate gagement with st dents and scientists during his time in Brazil.     t  it i l  f t  i  f i t   i t  i    l       i  j l .    t  i tifi  itt   t   osiu  on Brazilian Remote Sensing (SBRS) and was the organizer of Special Sessions on XVII SBRS held in 2015 and on the next XVIII SBRS to be held in 2017.  i   ,    i i ti l  li i   l , l  ili   i   or. In combination with his engaging and sharp mind, and boundless enthusiasm for his work, he drew many res arches into his orbit starting multiple collaborations. In every l   ,  i l           i  i ifi  i .   of us, bl ssed with a chanc  o meet and wo k with Dr. Hilker, have benefitted im easurably from the opportun ty, and his scientific legacy will ben fit fu ure generations. We will miss you, Thomas, brill ant scientist, amazing frie  and wonderful human being.  Conflicts of Interest: The authors declare no conflict of interest. References 1. Hilker, T.; Coops, N.C.; Nesic, Z.; Wulder, M.A.; Black, T.A. Instrumentation and approach for unattended year round tower based measurements of spectral reflectance. Comput. Electron. Agric. 2007, 56, 72–84. 2. Hilker, T.; Nesic, Z.; Coops, N.C.; Lessard, D. A new automated multi-angular radiometer instrument for tower based observations of canopy reflectance (AMSPEC II). Instrum. Sci. Technol. 2010, 38, 319–340. 3. Tortini, R.; Hilker, T.; Coops, N.C.; Nesic, Z. Technological advancement in tower-based canopy reflectance monitoring: The AMSPEC-III system. Sensors 2015, 15, 32020–32030. 4. Gamon, J.A.; Penuelas, J.; Field, C.B.A. Narrow-Waveband spectral index that tracks diurnal changes in photosynthetic efficiency. Remote Sens. Environ. 1992, 41, 35–44.  5. Hilker, T.; Coops, N.C.; Schwalm, C.R.; Jassal, R.S.; Black, T.A.; Krishnan, P. Effects of mutual shading of tree crowns on prediction of photosynthetic light-use efficiency in a coastal Douglas-fir forest. Tree Physiol. 2008, 28, 825–834. 6. Hilker, T.; Coops, N.C.; Hall, F.G.; Black, T.A.; Wulder, M.A.; Nesic, Z.; Krishnan, P. Separating physiologically and directionally induced changes in PRI using BRDF models. Remote Sens. Environ. 2008, 112, 2777–2788.  7. Hilker, T.; Coops, N.C.; Hall, F.G.; Black, T.A.; Chen, B.; Krishnan, P.; Wulder, M.A.; Sellers, P.J.; Middleton, E.M.; Huemmrich, K.F. A modeling approach for upscaling gross ecosystem production to the landscape scale using remote sensing data. J. Geophys. Res. Biogeosci. 2008, 113, doi:10.1029/2007JG000666. 8. Hilker, T.; Coops, N.C.; Newnham, G.J.; van Leeuwen, M.; Wulder, M.A.; Stewart, J.; Culvenor, D.S. Comparison of terrestrial and airborne LiDAR in describing stand structure of a thinned lodgepole pine forest. J. For. 2012, 110, 97–104. 9. Hilker, T.; van Leeuwen, M.; Coops, N.C.; Wulder, M.A.; Newnham, G.J.; Jupp, D.L.B.; Culvenor, D.S. Comparing canopy metrics derived from terrestrial and airborne laser scanning in a Douglas-fir dominated forest stand. Trees Struct. Funct. 2010, 24, 819–832. Conflicts of Interest: The authors declare no conflict of interest.References1. Hilker, T.; Coops, N.C.; Nesic, Z.; Wulder, M.A.; Black, T.A. Instru entation a d approach for unattendedyear round tower based measurem nts of spectral reflectanc . Comput. Electron. Agric. 2007, 56, 72–84.[CrossRef]2. Hilker, T.; Nesic, Z.; Co ps, N.C.; Lessard, D. A ew automated multi-angular radiometer instrument fortower based observations of canopy r flectance (AMSPEC II). Instrum. Sci. Technol. 2010, 38, 319–340.[CrossRef]3. Tortini, R.; Hilker, T.; Coops, N.C.; Nesic, Z. Technological advancement in tower-based canopy reflectancemonitoring: The AMSPEC-III system. Sensors 2015, 15, 32020–32030. [CrossRef] [PubMed]4. Gamon, J.A.; Penuelas, J.; Field, C.B.A. Narrow-Waveband spectral index that tracks diurnal changes inphotosynthetic efficiency. Remote Sens. Environ. 1992, 41, 35–44. [CrossRef]5. ilker, T.; Coops, N.C.; Schwalm, C.R.; Jassal, R.S.; Black, T.A.; Krishnan, P. Effects of mutual shading of treecrowns on prediction of photosynthetic light-use efficiency in a coastal Douglas-fir forest. Tree Physiol. 2008,28, 825–834. [CrossRef] [PubMed]6. ilker, T.; Coops, N.C.; Hall, F.G.; Black, T.A.; Wulder, M.A.; Nesic, Z.; Krishnan, P. Separating physiologicallyand directionally induced changes in PRI using BRDF models. Remote Sens. Environ. 2008, 112, 2777–2788.[CrossRef]7. ilker, T.; Coops, .C.; Hall, F.G.; Black, T.A.; Chen, B.; Krishnan, P.; Wulder, M.A.; Sellers, P.J.;Middleton, E.M.; Huemmrich, K.F. A modeling approach for upscaling gross ecosystem production tothe landscape scale using remote sensing data. J. Geophys. Res. Biogeosci. 2008, 113. [CrossRef]Remote Sens. 2016, 8, 853 4 of 48. Hilker, T.; Coops, N.C.; Newnham, G.J.; van Leeuwen, M.; Wulder, M.A.; Stewart, J.; Culvenor, D.S.Comparison of terrestrial and airborne LiDAR in describing stand structure of a thinned lodgepole pineforest. J. For. 2012, 110, 97–104. [CrossRef]9. Hilker, T.; van Leeuwen, M.; Coops, N.C.; Wulder, M.A.; Newnham, G.J.; Jupp, D.L.B.; Culvenor, D.S.Comparing canopy metrics derived from terrestrial and airborne laser scanning in a Douglas-fir dominatedforest stand. Trees Struct. Funct. 2010, 24, 819–832. [CrossRef]10. Wulder, M.A.; White, J.C.; Nelson, R.F.; Næsset, E.; Ørka, H.O.; Coops, N.C.; Hilker, T.; Bater, C.W.;Gobakken, T. Lidar sampling for large-area forest characterization: A review. Remote Sens. Environ. 2012,121, 196–209. [CrossRef]11. Shettles, M.; Hilker, T.; Gray, A.; Temesgen, H. Examination of uncertainty in per unit area estimates of aboveground biomass using terrestrial LiDAR. Can. J. For. Res. 2016, 46, 706–715. [CrossRef]12. Zald, H.; Wulder, M.A.; White, J.C.; Hilker, T.; Hermosilla, T.; Hobart, G.W.; Coops, N.C. Integrating Landsatpixel composites and change metrics with lidar plots to predictively map forest structure and abovegroundbiomass in Saskatchewan, Canada. Remote Sens. Environ. 2016, 176, 188–201. [CrossRef]13. Hilker, T.; Wulder, M.A.; Coops, N.C.; Seitz, N.; White, J.C.; Gao, F.; Masek, J.G.; Stenhouse, G. Generation ofdense time series synthetic Landsat data through data blending with MODIS using a spatial and temporaladaptive reflectance fusion model. Remote Sens. Environ. 2009, 113, 1988–1999. [CrossRef]14. Hall, F.G.; Hilker, T.; Coops, N.C. Photosynthat, photosynthesis from space: Theoretical foundations of asatellite concept and validation from tower and spaceborne data. Remote Sens. Environ. 2011, 115, 1918–1925.[CrossRef]15. Hall, F.G.; Hilker, T.; Coops, N.C. Data assimilation of photosynthetic light-use efficiency using multi-angularsatellite data: I. Model formulation. Remote Sens. Environ. 2012, 121, 301–308. [CrossRef]16. Hilker, T.; Coops, N.C.; Hall, F.G.; Nichol, C.J.; Lyapustin, A.; Black, T.A.; Wulder, M.A.; Leuning, R.; Barr, A.;Hollinger, D.Y.; et al. Inferring terrestrial photosynthetic light use efficiency of temperate ecosystems fromspace. J. Geophys. Res. 2011, 116, 11. [CrossRef]17. Lyapustin, A.I.; Wang, Y.; Lazlo, I.; Hilker, T.; Hall, F.G.; Sellers, P.J.; Tucker, C.J.; Korkin, S.V.Multi-Angle Implementation of Atmospheric Correction for MODIS (MAIAC). Part 3: Atmosphericcorrection. Remote Sens. Environ. 2012, 127, 385–393. [CrossRef]18. Hilker, T.; Hall, F.G.; Coops, N.C.; Collatz, J.G.; Black, T.A.; Tucker, C.J.; Sellers, P.J.; Grant, N. Remote sensingof transpiration and heat fluxes using multi-angle observations. Remote Sens. Environ. 2013, 137, 31–42.[CrossRef]19. Nag, S.; Gatebe, C.; Hilker, T.; Hall, F.; Dyrud, L.; de Weck, O. Gross primary productivity estimation usingmulti-angular measurements from small satellite clusters. In Proceedings of the 2014 IEEE InternationalSymposium on Geoscience and Remote Sensing (IGARSS), Beijing, China, 13–18 July 2014.20. Hilker, T.; Lyapustin, A.I.; Tucker, C.J.; Hall, F.G.; Myneni, R.B.; Wang, Y.; Bi, J.; de Moura, Y.M.; Sellers, P.J.Vegetation dynamics and rainfall sensitivity of the Amazon. Proc. Natl. Acad. Sci. USA 2014, 111, 16041–16046.[CrossRef] [PubMed]21. Moura, Y.M.; Hilker, T.; Lyapustin, A.I.; Galvão, L.S.; Santos, J.R.; Anderson, L.O.; Sousa, C.H.R.;Arai, E. Seasonality and drought effects of Amazonian forests observed from multi-angle satellite data.Remote Sens. Environ. 2015, 171, 278–290. [CrossRef]22. Hilker, T.; Galvão, L.S.; Aragão, L.E.O.C.; Moura, Y.M.; Amaral, C.H.; Lyapustin, A.I.; Wu, J.; Albert, L.P.;Ferreira, M.J.; Santos, V.A.H.F.; et al. Vegetation chlorophyll estimated from multi-angle MODIS and towerhyperspectral observations: A tool for scaling ecosystem seasonality and leaf demography across Amazonianevergreen forests. Remote Sens. Environ. 2016, under review.© 2016 by the authors; licensee MDPI, Basel, Switzerland. This article is an open accessarticle distributed under the terms and conditions of the Creative Commons Attribution(CC-BY) license (http://creativecommons.org/licenses/by/4.0/).