Hyperspectral vegetation indices and novel algorithms for predicting green LAI of crop canopies: Modeling and validation in the context of precision agriculture

Remote Sensing of Environment

Volumn 90, Issue 3, 2004, Pages 337-352

  Haboudane, Driss ^a   Miller, John R ^a,b   Pattey, Elizabeth ^c   Zarco Tejada, Pablo J ^d   Strachan, Ian B ^e  

^a YORK UNIVERSITY   (Canada)

^b YORK UNIVERSITY   (Canada)

^c AGRICULTURE AND AGRI FOOD CANADA   (Canada)

^d UNIVERSITY OF CALIFORNIA   (United States)

^e MCGILL UNIVERSITY   (Canada)

Author keywords

Chlorophyll content; Green LAI; Hyperspectral; Precision agriculture; Prediction algorithms; Spectral indices

Indexed keywords

ALGORITHMS; HEAT RADIATION; SENSITIVITY ANALYSIS; VEGETATION;

BIOPHYSICS; HYPERSPECTRAL VEGETATION;

REMOTE SENSING;

ALGORITHM; CANOPY; LEAF AREA INDEX; NDVI; PRECISION AGRICULTURE; SPECTRAL ANALYSIS;

GLYCINE MAX; TRITICUM AESTIVUM; ZEA MAYS;

EID: 1842431418     PISSN: 00344257     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.rse.2003.12.013     Document Type: Article

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