Global Land Surface Fractional Vegetation Cover Estimation Using General Regression Neural Networks from MODIS Surface Reflectance

IEEE Transactions on Geoscience and Remote Sensing

Volumn 53, Issue 9, 2015, Pages 4787-4796

  Jia, Kun ^a   Liang, Shunlin ^a,b   Liu, Suhong ^a   Li, Yuwei ^a   Xiao, Zhiqiang ^a   Yao, Yunjun ^a   Jiang, Bo ^a   Zhao, Xiang ^a   Wang, Xiaoxia ^a   Xu, Shuai ^a   Cui, Jiao ^a  

^a BEIJING NORMAL UNIVERSITY   (China)

^b UNIVERSITY OF MARYLAND   (United States)

Author keywords

Estimation; fractional vegetation cover (FVC); general regression neural networks (GRNNs); global; ModerateResolution Imaging Spectroradiometer (MODIS)

Indexed keywords

CLIMATE CHANGE; EARTH (PLANET); ESTIMATION; IMAGE RECONSTRUCTION; IMAGE RESOLUTION; REFLECTION; REGRESSION ANALYSIS; REMOTE SENSING; SATELLITE IMAGERY; SPECTROMETERS; VEGETATION;

EARTH SURFACE PROCESS; EUROPEAN REMOTE SENSING; FRACTIONAL VEGETATION COVER; GENERAL REGRESSION NEURAL NETWORK; GENERAL REGRESSION NEURAL NETWORKS (GRNNS); GLOBAL; HIGH SPATIAL RESOLUTION; MODERATE RESOLUTION IMAGING SPECTRORADIOMETER;

RADIOMETERS;

ALGORITHM; DISCONTINUITY; ESTIMATION METHOD; GLOBAL PERSPECTIVE; LAND SURFACE; LANDSAT; MODIS; PERFORMANCE ASSESSMENT; REGRESSION ANALYSIS; REMOTE SENSING; SATELLITE DATA; SPATIAL RESOLUTION; SPOT; SURFACE REFLECTANCE; VEGETATION COVER;

EUROPE;

EID: 85027922015     PISSN: 01962892     EISSN: None     Source Type: Journal    
DOI: 10.1109/TGRS.2015.2409563     Document Type: Article

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