Using satellite based soil moisture to quantify the water driven variability in NDVI: A case study over mainland Australia
Using satellite based soil moisture to quantify the water driven variability in NDVI: A case study over mainland Australia
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DOI：
10.1016/j.rse.2013.08.022
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发表时间：
2014-01-01
影响因子：
13.5
通讯作者：
Dolman, A. J.
中科院分区：
文献类型：
--
作者：
Chen, T.;de Jeu, R. A. M.;Dolman, A. J.
土壤水分对调节植被生产力和控制陆地碳吸收至关重要。本研究旨在利用独立的卫星观测，在大空间和长时间尺度上量化土壤湿度对植被的影响。利用新开发的卫星土壤湿度产品和归一化植被指数（NDVI），研究了1991 - 2009年澳大利亚大陆土壤湿度对植被的影响。我们的方法依赖于多种统计方法，包括：(i)窗口交叉相关；（二）分位数回归（三）分段线性回归。我们发现土壤湿度与NDVI之间存在很强的正相关关系，NDVI通常滞后于土壤湿度一个月。这一关系的时间特征显示出很大的区域差异。在NDVI分布的高端，低植被密度的干旱区对土壤湿度的敏感性高于湿润区，说明土壤湿度对干旱区和湿润区植被生长的促进作用处于早期阶段。采用分段线性回归方法，对19年土壤湿度变化趋势进行了分析。NDVI变化趋势在2000年初和2002年底与土壤湿度的拐点呈显著性变化（p < 0.01）。我们的研究结果通过展示土壤水分在不同时间尺度上对植被的影响，说明了新的土壤水分产品的实用性。该分析结果可作为耦合植被气候模型的基准。(C) 2013 Elsevier Inc .版权所有
Soil moisture is crucial in regulating vegetation productivity and controlling terrestrial carbon uptake. This study aims to quantify the impact of soil moisture on vegetation at large spatial and long-term temporal scales using independent satellite observations. We used a newly developed satellite-derived soil moisture product and the Normalized Difference Vegetation Index (NDVI) to investigate the impact of soil moisture on vegetation across mainland Australia between 1991 and 2009. Our approach relied on multiple statistical methods including: (i) windowed cross correlation; (ii) quantile regression: (iii) piecewise linear regression. We found a strong positive relationship between soil moisture and NDVI, with NDVI typically lagging behind soil moisture by one month. The temporal characteristics of this relation show substantial regional variability. Dry regions with low vegetation density are more sensitive to soil moisture for the high end of the distribution of NDVI than moist regions, suggesting that soil moisture enhances vegetation growth in dry regions and in the early stage in wet regions. Using piecewise linear regression, we detected three periods with different soil moisture trends over the 19 years. The changes in NDVI trends are significant (p < 0.01) with turning points of soil moisture in the beginning of 2000 and the end of 2002. Our findings illustrate the usefulness of the new soil moisture product by demonstrating the impacts of soil moisture on vegetation at various temporal scales. This analysis could be used as a benchmark for coupled vegetation climate models. (C) 2013 Elsevier Inc All rights reserved.