气候变化领域集成服务门户(CCPortal): Global LAI uncertainty and relative uncertainty datasets derived from a Triple Collocation Error Model (TCEM)

CCPortal

DOI	https://doi.org/10.1594/PANGAEA.792867
	Global LAI uncertainty and relative uncertainty datasets derived from a Triple Collocation Error Model (TCEM)
	Fang; Hongliang; Wei; Shanshan; Jiang; Chongya; Scipal; Klaus
发布日期	2012-10-22
数据集类型	dataset
英文简介	Uncertainty information for global leaf area index (LAI) products is important for global modeling studies but usually difficult to systematically obtain at a global scale. Here, we present a new method that cross-validates existing global LAI products and produces consistent uncertainty information. The method is based on a triple collocation error model (TCEM) that assumes errors among LAI products are not correlated. Global monthly absolute and relative uncertainties, in 0.05° spatial resolutions, were generated for MODIS, CYCLOPES, and GLOBCARBON LAI products, with reasonable agreement in terms of spatial patterns and biome types. CYCLOPES shows the lowest absolute and relative uncertainties, followed by GLOBCARBON and MODIS. Grasses, crops, shrubs, and savannas usually have lower uncertainties than forests in association with the relatively larger forest LAI. With their densely vegetated canopies, tropical regions exhibit the highest absolute uncertainties but the lowest relative uncertainties, the latter of which tend to increase with higher latitudes. The estimated uncertainties of CYCLOPES generally meet the quality requirements (± 0.5) proposed by the Global Climate Observing System (GCOS), whereas for MODIS and GLOBCARBON only non-forest biome types have met the requirement. Nevertheless, none of the products seems to be within a relative uncertainty requirements of 20%. Further independent validation and comparative studies are expected to provide a fair assessment of uncertainties derived from TCEM. Overall, the proposed TCEM is straightforward and could be automated for the systematic processing of real time remote sensing observations to provide theoretical uncertainty information for a wider range of land products.
语种	英语
国家	国际
学科大类	气候变化
学科子类	气候变化
文献类型	数据集
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/217612
推荐引用方式 GB/T 7714	Fang,Hongliang,Wei,et al. Global LAI uncertainty and relative uncertainty datasets derived from a Triple Collocation Error Model (TCEM).2012-10-22.https://doi.org/10.1594/PANGAEA.792867.