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dc.contributor.authorHouborg, Rasmus
dc.contributor.authorFisher, Joshua B.
dc.contributor.authorSkidmore, Andrew K.
dc.date.accessioned2016-10-12T10:19:48Z
dc.date.available2016-10-12T10:19:48Z
dc.date.issued2015-07-09
dc.identifier.citationRasmus Houborg, Joshua B. Fisher, Andrew K. Skidmore, Advances in remote sensing of vegetation function and traits, International Journal of Applied Earth Observation and Geoinformation, Volume 43, December 2015, Pages 1-6, ISSN 0303-2434, http://dx.doi.org/10.1016/j.jag.2015.06.001.
dc.identifier.issn0303-2434
dc.identifier.doi10.1016/j.jag.2015.06.001
dc.identifier.urihttp://hdl.handle.net/10754/620951
dc.description.abstractRemote sensing of vegetation function and traits has advanced significantly over the past half-century in the capacity to retrieve useful plant biochemical, physiological and structural quantities across a range of spatial and temporal scales. However, the translation of remote sensing signals into meaningful descriptors of vegetation function and traits is still associated with large uncertainties due to complex interactions between leaf, canopy, and atmospheric mediums, and significant challenges in the treatment of confounding factors in spectrum-trait relations. This editorial provides (1) a background on major advances in the remote sensing of vegetation, (2) a detailed timeline and description of relevant historical and planned satellite missions, and (3) an outline of remaining challenges, upcoming opportunities and key research objectives to be tackled. The introduction sets the stage for thirteen Special Issue papers here that focus on novel approaches for exploiting current and future advancements in remote sensor technologies. The described enhancements in spectral, spatial and temporal resolution and radiometric performance provide exciting opportunities to significantly advance the ability to accurately monitor and model the state and function of vegetation canopies at multiple scales on a timely basis.
dc.description.sponsorshipRH acknowledges funding support from the King Abdullah University of Science and Technology (KAUST). JBF contributed from the Jet Propulsion Laboratory (JPL), California Institute of Technology, under a contract with the National Aeronautics and Space Administration (NASA); government sponsorship acknowledged. Support was provided by NASA Carbon Cycle Science, Terrestrial Hydrology Program, and Earth Ventures Instruments, and by JPL Research & Technology Development. AS activities are funded by the University of Twente, Faculty of ITC.
dc.language.isoen
dc.publisherElsevier BV
dc.relation.urlhttp://www.sciencedirect.com/science/article/pii/S0303243415001300
dc.rights© <2015>. This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subjectRemote sensing
dc.subjectTraits
dc.subjectVegetation function
dc.subjectSatellites
dc.subjectUAV
dc.subjectMultispectral
dc.subjectHyperspectral
dc.subjectThermal
dc.titleAdvances in remote sensing of vegetation function and traits
dc.typeArticle
dc.contributor.departmentBiological and Environmental Sciences and Engineering (BESE) Division
dc.contributor.departmentWater Desalination and Reuse Research Center (WDRC)
dc.identifier.journalInternational Journal of Applied Earth Observation and Geoinformation
dc.eprint.versionPost-print
dc.contributor.institutionJet Propulsion Laboratory, California Institute of Technology, 4800 Oak Grove Dr., Pasadena, CA, 91109, USA
dc.contributor.institutionFaculty of Geo-information Science and Earth Observation (ITC), University of Twente, Hengelosestraat 99, 7500 AA Enschede, The Netherlands
dc.contributor.affiliationKing Abdullah University of Science and Technology (KAUST)
kaust.personHouborg, Rasmus
kaust.personFisher, Joshua B.
kaust.personSkidmore, Andrew K.
refterms.dateFOA2017-07-08T00:00:00Z


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