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dc.contributor.authorSampson, P. H.-
dc.contributor.authorZarco-Tejada, Pablo J.-
dc.contributor.authorMohammed, G. H.-
dc.contributor.authorMiller, John R.-
dc.contributor.authorNoland, Thomas L.-
dc.contributor.authorFleming, R. L.-
dc.date.accessioned2009-02-04T10:46:48Z-
dc.date.available2009-02-04T10:46:48Z-
dc.date.issued2003-
dc.identifier.citationForest Science, 49(3), 381-391en_US
dc.identifier.issn0015-749X-
dc.identifier.urihttp://hdl.handle.net/10261/10268-
dc.description.abstractTo develop practical and objective measures of forest condition, the Bioindicators of Forest Sustainability Project has used a physiological, remote sensing approach that emphasizes identifying early warning measures of stress effects in forests. While stress indicators exist at the leaf level (e.g., chlorophyll fluorescence, pigment levels), developing reliable indicators at the canopy level is a challenge. Hyperspectral sensors, such as the Compact Airborne Spectrographic Imager (CASI), may be useful in remotely detecting vegetation stress effects. In this study, an inverse modeling approach demonstrated that the CASI could be used to map chlorophyll content (root mean square errors ranging from 12.6 to 13.0 mg/cm2) following different silvicultural treatments in a tolerant hardwood (sugar maple [Acer saccharum M.]) forest. This capability could be readily applied to operationally assessing forest physiological strain and in classifying forest condition based on chlorophyll content. A change analysis study was also conducted to evaluate chlorophyll estimation across seasons for a range of sites. The implications of these findings and recommendations for a prototype system to monitor forest condition are presented.en_US
dc.description.sponsorshipThe authors gratefully acknowledge the financial support provided for this research through the Ontario Ministry of Natural Resources, the Centre for Research in Earth and Space Technology (CRESTech), and Geomatics for Informed Decisions (GEOIDE)—a Canadian Centre of Excellence.en_US
dc.format.extent4085 bytes-
dc.format.mimetypeimage/gif-
dc.language.isoengen_US
dc.publisherSociety of American Forestersen_US
dc.rightsclosedAccessen_US
dc.subjectBioindicatorsen_US
dc.subjectCASIen_US
dc.subjectChange analysisen_US
dc.subjectMERISen_US
dc.subjectMODISen_US
dc.subjectRadiative transferen_US
dc.subjectPhysiologyen_US
dc.subjectSilvicultureen_US
dc.subjectSugar mapleen_US
dc.subjectAcer saccharumen_US
dc.titleHyperspectral Remote Sensing of Forest Condition: Estimation of Chlorophyll content in tolerant Hardwoodsen_US
dc.typeartículoen_US
dc.description.peerreviewedPeer revieweden_US
dc.relation.publisherversionhttp://saf.publisher.ingentaconnect.com/content/saf/fs/2003/00000049/00000003/art00005#availen_US
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