Mapping wheat rust based on high spatial resolution satellite imagery

Computers and Electronics in Agriculture

Volumn 152, Issue , 2018, Pages 109-116

  Chen, Dongmei ^a   Shi, Yeyin ^b   Huang, Wenjiang ^c   Zhang, Jingcheng ^a   Wu, Kaihua ^a  

^a HANGZHOU DIANZI UNIVERSITY   (China)

^b UNIVERSITY OF NEBRASKA LINCOLN   (United States)

^c INSTITUTE OF GEOLOGY AND GEOPHYSICS   (China)

Author keywords

Feature selection; Mapping; Multispectral remote sensing; Support vector machine; Wheat rust

Indexed keywords

DECISION TREES; DISEASE CONTROL; FEATURE EXTRACTION; MAPPING; PHOTOMAPPING; REMOTE SENSING; SUPPORT VECTOR MACHINES; VEGETATION;

CLASSIFICATION METHODS; FEATURE SELECTION METHODS; HIGH SPATIAL RESOLUTION SATELLITE IMAGERY; MULTISPECTRAL REMOTE SENSING; MULTISPECTRAL SATELLITE IMAGE; OPERATIONAL MONITORING; SUPPORT VECTOR MACHINE METHOD; WHEAT RUST;

SATELLITE IMAGERY;

ACCURACY ASSESSMENT; DISEASE INCIDENCE; ESTIMATION METHOD; MAPPING METHOD; MONITORING SYSTEM; NUMERICAL METHOD; REMOTE SENSING; RUST DISEASE; SATELLITE DATA; SATELLITE IMAGERY; SPATIAL RESOLUTION; SPECTRAL ANALYSIS; SUPPORT VECTOR MACHINE; VEGETATION CLASSIFICATION; VEGETATION INDEX; VEGETATION MAPPING; ZIYUAN;

CHINA; HENAN;

PUCCINIA GRAMINIS F. SP. TRITICI; TRITICUM AESTIVUM;

EID: 85049726138     PISSN: 01681699     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.compag.2018.07.002     Document Type: Article

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