Potential of ensemble tree methods for early-season prediction of winter wheat yield from short time series of remotely sensed normalized difference vegetation index and in situ meteorological data

Journal of Applied Remote Sensing

Volumn 9, Issue 1, 2015, Pages

  Heremans, Stien ^a   Dong, Qinghan ^b   Zhang, Beier ^c   Bydekerke, Lieven ^b   Orshoven, Jos Van ^a  

^a UNIVERSITY OF LEUVEN   (Belgium)

^b FLEMISH INSTITUTE FOR TECHNOLOGICAL RESEARCH VITO   (Belgium)

^c Anhui Forestry Department   (China)

Author keywords

empirical models; ensemble trees; wheat yield estimation

Indexed keywords

CROPS; DECISION MAKING; DECISION TREES; FORESTRY; METEOROLOGY; REMOTE SENSING; TIME SERIES; VEGETATION; WEATHER FORECASTING;

BOOSTED REGRESSION TREES; EMPIRICAL MODEL; ENSEMBLE TREES; FORWARD FEATURE SELECTIONS; METEOROLOGICAL DATA; NORMALIZED DIFFERENCE VEGETATION INDEX; WHEAT YIELD; WINTER WHEAT YIELDS;

LEARNING SYSTEMS;

EID: 84925068245     PISSN: None     EISSN: 19313195     Source Type: Journal    
DOI: 10.1117/1.JRS.9.097095     Document Type: Article

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