BAYESIAN MAXIMUM ENTROPY DATA FUSION OF FIELD OBSERVED LAI AND LANDSAT ETM plus DERIVED LAI

被引：0

作者：

Li, Aihua ^{[1
]}

Bo, Yanchen ^{[1
]}

Chen, Ling ^{[1
]}

机构：

[1] Beijing Normal Univ, State Key Lab Remote Sensing Sci, Dept Geog & Remote Sensing, Beijing Key Lab Remote Sensing Environm & Digital, Beijing 100875, Peoples R China

来源：

2011 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS) | 2011年

关键词：

Bayesian Maximum Entropy; fusion; LAI; uncertainty; LEAF-AREA-INDEX; REGRESSION;

D O I：

10.1109/IGARSS.2011.6049739

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

Accurate high resolution LAI reference maps are necessary for the validation of coarser resolution satellite derived LAI products. In this paper, an efficient method for combining field observations and Landsat ETM+ derived LAI is proposed based on the Bayesian Maximum Entropy paradigm to get more accurate reference maps. This method can take account of the uncertainties associated with field observations and linear relationship between the ETM+ LAI and in situ measurements to perform a nonlinear prediction of the interest variable. A comparison with ETM+ derived LAI surfaces in three validation sites from the BIGFOOT project showed that the RMSE can be reduced by this approach, indicating a promising method in fusing different sources and different types of data.

引用

页码：2617 / 2620

页数：4

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