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Monitoring vegetation phenology using MODIS

机译:使用MODIS监测植​​被物候

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Accurate measurements of regional to global scale vegetation dynamics (phenology) are required to improve models and understanding of inter-annual variability in terrestrial ecosystem carbon exchange and climate-biosphere interactions. Since the mid-1980s, satellite data have been used to study these processes. In this paper, a new methodology to monitor global vegetation phenology from time series of satellite data is presented. The method uses series of piecewise logistic functions, which are fit to remotely sensed vegetation index (VI) data, to represent intra-annual vegetation dynamics. Using this approach, transition dates for vegetation activity within annual time series of VI data can be determined from satellite data. The method allows vegetation dynamics to be monitored at large scales in a fashion that it is ecologically meaningful and does not require pre-smoothing of data or the use of user-defined thresholds. Preliminary results based on an annual time series of Moderate Resolution Imaging Spectroradiometer (MODIS) data for the northeastern United States demonstrate that the method is able to monitor vegetation phenology with good success. (C) 2002 Elsevier Science Inc. All rights reserved. [References: 19]
机译:需要精确测量区域到全球范围内的植被动态(物候学),以改进陆地生态系统碳交换和气候-生物圈相互作用的模型和对年际变化的理解。自1980年代中期以来,一直使用卫星数据来研究这些过程。本文提出了一种从卫星数据时间序列监测全球植被物候的新方法。该方法使用一系列分段逻辑函数,这些函数适合于遥感植被指数(VI)数据,以表示年内植被动态。使用这种方法,可以从卫星数据中确定VI数据的年度时间序列内植被活动的过渡日期。该方法允许以生态学意义且不需要数据预先平滑或使用用户定义的阈值的方式对植被动态进行大规模监控。根据美国东北部中等分辨率成像光谱仪(MODIS)数据的年度时间序列得出的初步结果表明,该方法能够成功监测植被物候。 (C)2002 Elsevier Science Inc.保留所有权利。 [参考:19]

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