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首页> 外文期刊>International journal of remote sensing >Predicting intra-seasonal fluctuations of NDVI phenology from daily rainfall in the East Sahel: a simple linear reservoir model
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Predicting intra-seasonal fluctuations of NDVI phenology from daily rainfall in the East Sahel: a simple linear reservoir model

机译：根据东萨赫勒地区的每日降雨量，预测NDVI物候的季节内波动：简单的线性储层模型

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摘要

Short-term predictive models are essential for understanding the temporal relationships between the variability of impulsive daily rainfall and the attendant dynamics of vegetation development in rangelands, particularly for the water-limited, semi-arid East Sahel. After identifying selected rain-dependent sites in southeast Sudan, this report applies a procedure to predict seasonal biomass development in response to impulse-like daily storm events using a simple linear reservoir model as an analogue for the coupled soil-plant-atmosphere ecosystem. Key parameters are the characteristic time of the reservoir and the number (n) of elementary reservoirs in series. Surface vegetative biomass is represented by the normalized difference vegetation index (NDVI) provided by the MODIS satellite MOD13A2 16day 1x1km product. Our specific metric is the commonly used differential NDVI, or NDVI, the difference between the actual NDVI value and its long-term fallow season baseline. We review the concept of the modelling method, with selected application to 15years (2000-2014) of NDVI data from a 51x51km study area in the East Sahel, centred on the standard WMO Gauge 62752 at Gedaref City in southeast Sudan. Results indicate that as few as four - even as few as two - model parameters might be used to describe intra-seasonal to multiple-year vegetation dynamics. Allowing for inter-annually variable parameters, the predicted results exhibit a coefficient of determination of 0.96. An alternative formulation using a single set of four, seasonally dependent model parameters, globally determined from 15years of observed reference data, results in a coefficient of determination of 0.90; a version using only two, globally determined model parameters works almost as well for the type of phenology characteristic of this area. In addition to enabling a number of applications that would benefit from the availability of a synthetic phenological time series that is solely dependent on daily rainfall, one of the most important applications may be for infilling data gaps in the observed time series, which for this area of the Sahel are typically encountered during early-season green-up; a critical time for most NDVI studies. We found that the 1year lagged autocorrelation coefficient, and some version of the conventional rain use efficiency (RUE) factor with its associated annual correlation coefficient, are essential adjunct screening parameters when identifying sites with the highest inter-annual variability in biomass production (typical of the most natural rain-fed sites in this area).
机译：短期预测模型对于了解脉冲日降雨量的变化与牧场中植被发展的伴随动力之间的时间关系至关重要，特别是对于水有限，半干旱的东萨赫勒地区。在确定了苏丹东南部选定的依赖雨水的地点之后，本报告采用了一种程序，以简单的线性水库模型作为耦合的土壤-植物-大气生态系统的模拟物，以应对脉冲状的日常暴雨事件，预测季节性生物量的发展。关键参数是储层的特征时间和基本储层的数量（n）串联。表面营养生物量由MODIS卫星MOD13A2 16天1x1公里产品提供的归一化差异植被指数（NDVI）表示。我们的特定指标是常用的差分NDVI或NDVI，即实际NDVI值与其长期休耕季节基线之间的差。我们回顾了建模方法的概念，并选择了将其应用到东南萨赫勒地区51x51公里研究区的15年（2000-2014年）NDVI数据中，该数据集中在苏丹东南部格达雷夫市的标准WMO仪表62752上。结果表明，最少可使用四个（甚至最少两个）模型参数来描述季节内至多年的植被动态。考虑到年际可变参数，预测结果的确定系数为0.96。从15年观察的参考数据中整体确定的，使用一组四个季节性相关的模型参数的替代公式得出的确定系数为0.90；仅使用两个全局确定的模型参数的版本对于该区域的物候特征类型几乎适用。除了可以从仅依赖于每日降雨的合成物候时间序列的可用性中受益的众多应用程序之外，最重要的应用程序之一可能是填补观察到的时间序列中的数据空白。萨赫勒地区通常在季初绿化期间遇到；大多数NDVI研究的关键时刻。我们发现1年滞后自相关系数以及一些常规的雨水利用效率（RUE）因子及其相关的年度相关系数，是确定生物量生产中年际变化最大的站点时必不可少的辅助筛选参数。该地区最自然的雨养地点）。

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  • 来源
    《International journal of remote sensing》 |2016年第14期|3293-3321|共29页
  • 作者

    Hermance John F.; Sulieman Hussein M.; Mustafa Abdel G.;

  • 作者单位

    Brown Univ, Dept Earth Environm & Planetary Sci, Providence, RI 02912 USA;

    Univ Gadarif, Fac Agr & Environm Sci, Ctr Remote Sensing & Geog Informat Syst, Gadarif, Sudan;

    Fitchburg State Univ, Dept Ind Technol, Fitchburg, MA USA;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);
  • 原文格式 PDF
  • 正文语种 eng
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