Estimating leaf chlorophyll content in sugar beet canopies using millimeter- to centimeter-scale reflectance imagery

Remote Sensing of Environment

Volumn 198, Issue , 2017, Pages 173-186

  Jay, Sylvain ^a,b   Gorretta, Nathalie ^a   Morel, Julien ^a   Maupas, Fabienne ^c   Bendoula, Ryad ^a   Rabatel, Gilles ^a   Dutartre, Dan ^c   Comar, Alexis ^d   Baret, Frédéric ^e  

^a UMR ITAP   (France)

^b AIX MARSEILLE UNIVERSITÉ   (France)

^c Institut Technique de la Betterave   (France)

^d HIPHEN   (France)

^e CEMAGREF   (France)

Author keywords

Leaf chlorophyll content; Millimeter to centimeter spatial resolutions; mNDblue; Reflectance imagery; Vegetation index

Indexed keywords

CHLOROPHYLL; FORESTRY; IMAGE RESOLUTION; INFRARED DEVICES; MEAN SQUARE ERROR; REFLECTION; REMOTE SENSING; SPECTROSCOPY; SUGAR BEETS; VEGETATION;

CENTIMETER SPATIAL RESOLUTION; LEAF CHLOROPHYLL CONTENT; MNDBLUE; MULTISPECTRAL SENSORS; NEAR-INFRARED DOMAINS; NORMALIZED DIFFERENCES; ROOT-MEAN-SQUARE ERROR OF PREDICTIONS; VEGETATION INDEX;

PIXELS;

BIOCHEMICAL COMPOSITION; CANOPY ARCHITECTURE; CHLOROPHYLL; CONCENTRATION (COMPOSITION); DYE; ESTIMATION METHOD; PERFORMANCE ASSESSMENT; PHYSIOLOGICAL RESPONSE; PIXEL; PRIMARY PRODUCTION; REMOTE SENSING; SENSOR; SPATIAL RESOLUTION; SPECTRAL REFLECTANCE; SUGAR BEET;

BETA VULGARIS SUBSP. VULGARIS;

EID: 85020048051     PISSN: 00344257     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.rse.2017.06.008     Document Type: Article

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