Using NDVI to differentiate wheat genotypes productivity under dryland and irrigated conditions

Remote Sensing

Volumn 12, Issue 5, 2020, Pages

  Naser, Mohammed A ^a,b   Khosla, Raj ^c   Longchamps, Louis ^d   Dahal, Subash ^c  

^a AL MUTHANNA UNIVERSITY   (Iraq)

^b UNIVERSITY OF NEBRASKA LINCOLN   (United States)

^c Department of Environmental and Radiological Health Sciences   (United States)

^d AGRICULTURE AND AGRI FOOD CANADA   (Canada)

Author keywords

Dryland; Genotypes; Irrigated; K means clustering; NDVI; Proximal sensor

Indexed keywords

CROPS; K-MEANS CLUSTERING; PRODUCTIVITY; REMOTE SENSING; VEGETATION;

DRYLAND; GENOTYPES; IRRIGATED; K-MEANS CLUSTERING METHOD; NDVI; NORMALIZED DIFFERENCES; PEARSON'S PRODUCT-MOMENT CORRELATION COEFFICIENT; WINTER WHEAT (TRITICUM AESTIVUM L.);

GRAIN (AGRICULTURAL PRODUCT);

EID: 85081914650     PISSN: None     EISSN: 20724292     Source Type: Journal    
DOI: 10.3390/rs12050824     Document Type: Article

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