Improvement of spatio-temporal growth estimates in heterogeneous forests using gaussian bayesian networks

IEEE Transactions on Geoscience and Remote Sensing

Volumn 52, Issue 8, 2014, Pages 4980-4991

  Mustafa, Yaseen T ^a   Tolpekin, Valentyn A ^b   Stein, Alfred ^b  

^a UNIVERSITY OF ZAKHO   (Iraq)

^b UNIVERSITY OF TWENTE   (Netherlands)

Author keywords

Gaussian Bayesian networks (GBNs); leaf area index (LAI); linear mixture model (LMM); mixed pixels; Moderate Resolution Imaging Spectroradiometer (MODIS); physiological principles predicting growth (3PG) model

Indexed keywords

BAYESIAN NETWORKS; FORESTRY; GAUSSIAN DISTRIBUTION; MIXTURES; PHYSIOLOGICAL MODELS; PHYSIOLOGY; PIXELS; RADIOMETERS;

GAUSSIAN BAYESIAN NETWORK (GBNS); LEAF AREA INDEX; LINEAR MIXTURE MODELS; MIXED PIXEL; MODERATE RESOLUTION IMAGING SPECTRORADIOMETER; PHYSIOLOGICAL PRINCIPLES;

SATELLITE IMAGERY;

ACCURACY ASSESSMENT; AERIAL SURVEY; BAYESIAN ANALYSIS; CANOPY ARCHITECTURE; ERROR ANALYSIS; FOREST ECOSYSTEM; GAUSSIAN METHOD; GROWTH MODELING; GROWTH RATE; IMAGE ANALYSIS; LEAF AREA INDEX; MODIS; NUMERICAL MODEL; PHYSIOLOGY; SATELLITE IMAGERY; SPATIOTEMPORAL ANALYSIS;

FORESTRY; MATHEMATICAL MODELS; PHYSIOLOGY; RADIOMETRY; SPECTROMETERS;

NETHERLANDS;

EID: 84896315647     PISSN: 01962892     EISSN: None     Source Type: Journal    
DOI: 10.1109/TGRS.2013.2286219     Document Type: Article

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