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全球LAI地面验证方法及验证数据综述 被引量:23

Global LAI Ground Validation Dataset and Product Validation Framework: A Review
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摘要 叶面积指数(LAI)的地面验证是LAI反演算法研究及LAI产品验证的重要部分。近年来,为了验证遥感参数产品以及对大气、地表的系统性研究,国际上在全球主要大洲开展了多个针对主要植被类型的大型观测项目,逐渐形成了较完善的地面采样框架与全球尺度不同植被类型的地面验证数据集。国内外已开展的大型观测项目采用的采样框架对以后观测试验中LAI的地面验证框架的制定与研究具有重要的借鉴意义,同时,已观测到的全球LAI地面验证数据集是开展全球LAI算法及产品验证的基础数据集,因此,有必要对目前全球LAI地面验证方法及验证数据情况做个综述。首先综述全球主要LAI地面观测项目及其所采用的地面验证框架。在此基础上,分析比较各大观测项目中所采用的地面测量方法、采样方法及像元真值估算方法。最后,指出全球LAI产品地面验证中存在的不足,并对尚需进一步研究的方向进行展望。 The LAI ground measurement is an important support to the LAI retrieval method research and LAI products validation.In recent years,in order to validate the satellite products and improve the understanding of the atmosphere and land surface process system,many global-scale or continental-scale ground observing programs were organized,such as the FIFE,BOREAS,PROVE programs in Europe and North America,and Heihe,Shunyi,Xilinhaote in China.Through these programs,a product validation framework,which solves the problem of scale difference between ground point measurement and the pixel,was developed.Under this framework,a global-scale LAI validation dataset for different vegetation types have come into being gradually.In this paper,firstly,we investigated some large-scale ground observing programs,which have the standard measuring principle and share the dataset well.Secondly,we summarized the product validation framework,including the ground observing techniques,the sampling strategies and the pixel true value estimation methods.And then we made a short introduction to the global LAI validation dataset we collected from those well-shared observing programs,including the affiliated parameter dataset.Finally we made a prospect on the LAI sampling method and the global validation.
出处 《地球科学进展》 CAS CSCD 北大核心 2012年第2期165-174,共10页 Advances in Earth Science
基金 国家自然科学基金青年基金项目“基于叶片和棉花棉套组分的模型改进及棉花棉絮量反演方法研究”(编号:40801143) 国家自然科学基金重点项目“光学与微波遥感的模型协同及联合反演研究”(编号:40730525) 国家高技术研究发展计划项目“全球陆表特征参量产品生成与应用研究”(编号:2009AA122102)资助
关键词 叶面积指数(LAI) 地面验证 采样方法 Leaf Area Index(LAI); Ground-based validation; Sampling strategy;
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