Using spectrotemporal indices to improve the fruit-tree crop classification accuracy

ISPRS Journal of Photogrammetry and Remote Sensing

Volumn 128, Issue , 2017, Pages 158-169

  Pena M A ^a,b   Liao, R ^c   Brenning, A ^b,c  

^a UNIVERSIDAD ALBERTO HURTADO   (Chile)

^b FRIEDRICH SCHILLER UNIVERSITY JENA   (Germany)

^c UNIVERSITY OF WATERLOO   (Canada)

Author keywords

Crop type classification; Landsat 8; Linear discriminant analysis; Satellite image time series; Spectrotemporal indices

Indexed keywords

AGRICULTURE; COMPOSTING; CROPS; DISCRIMINANT ANALYSIS; FORESTRY; FRUITS; IMAGE ANALYSIS; INFRARED DEVICES; ORCHARDS; TIME SERIES;

CROP TYPE CLASSIFICATION; LANDSAT; LINEAR DISCRIMINANT ANALYSIS; SATELLITE IMAGES; SPECTROTEMPORAL INDICES;

TIME SERIES ANALYSIS;

ACCURACY ASSESSMENT; ALGORITHM; DISCRIMINANT ANALYSIS; FRUIT; GROWING SEASON; IMAGE CLASSIFICATION; LANDSAT; SATELLITE DATA; SATELLITE IMAGERY; SPECTRAL RESOLUTION; TIME SERIES ANALYSIS; VEGETATION INDEX;

ACONCAGUA VALLEY; CHILE; VALPARAISO [CHILE];

EID: 85016964828     PISSN: 09242716     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.isprsjprs.2017.03.019     Document Type: Article

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