Comparison and assessment of different object-based classifications using machine learning algorithms and UAVs multispectral imagery: a case study in a citrus orchard and an onion crop

European Journal of Remote Sensing

Volumn 54, Issue 1, 2021, Pages 431-460

  Modica, Giuseppe ^a   De Luca, Giandomenico ^a   Messina, Gaetano ^a   Praticò, Salvatore ^a  

^a UNIVERSITY MEDITERRANEA OF REGGIO CALABRIA   (Italy)

Author keywords

eCognition; Geographic Object Based Image Analysis (GEOBIA); Orfeo Toolbox (OTB); Precision agriculture (PA); RGISLib and Scikit learn; Segmentation and classification accuracy assessment

Indexed keywords

ANTENNAS; CROPS; DECISION TREES; IMAGE CLASSIFICATION; LARGE SCALE SYSTEMS; LEARNING SYSTEMS; NEAREST NEIGHBOR SEARCH; ORCHARDS; REMOTE SENSING; SOFTWARE TESTING; SUPPORT VECTOR MACHINES;

CLASSIFICATION ACCURACY; CLASSIFICATION ALGORITHM; CLASSIFICATION RESULTS; GEOGRAPHIC OBJECT-BASED IMAGE ANALYSIS; K NEAREST NEIGHBOURS (K-NN); MULTI-SPECTRAL IMAGERY; OBJECT-BASED CLASSIFICATIONS; STATISTICAL SIGNIFICANCE;

LEARNING ALGORITHMS;

ALGORITHM; ASSESSMENT METHOD; COMPARATIVE STUDY; CROP PLANT; GIS; IMAGE CLASSIFICATION; MACHINE LEARNING; ORCHARD; SATELLITE IMAGERY; SEGMENTATION; SPECTRAL ANALYSIS; UNMANNED VEHICLE;

CALABRIA; ITALY;

CITRUS;

EID: 85111372463     PISSN: None     EISSN: 22797254     Source Type: Journal    
DOI: 10.1080/22797254.2021.1951623     Document Type: Article

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