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Exploiting the multi-angularity of the MODIS temporal signal to identify spatially homogeneous vegetation cover: A demonstration for agricultural monitoring applications

机译:利用MODIS时间信号的多角度识别空间均匀的植被覆盖:农业监测应用演示

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MODIS has been providing daily imagery for retrieving land surface properties with a spatial resolution 250 m since the year 2000. In many places, this pixel size is closer to that of individual landscape elements, such as managed forest stands or crop fields, than those of time series more typically used in vegetation analyses (with pixel sizes ranging from about 1 km to 8 km). With such spatial resolution, combined with its increasingly long archive, MODIS data offers great potential for vegetation monitoring applications in general, and crop growth monitoring in particular. However, due to its whiskbroom design, the observation geometry of the MODIS instrument, combined with the spatial uncertainty in the registration of the images, can result in different (albeit neighbouring) physical areas being mapped onto the same pixel depending on the view zenith angle (which varies from day to the next). Rather than considering this as an inconvenience, a method is here proposed to exploit this peculiarity to identify pixels corresponding to a homogeneous plant cover, in order to retrieve surface specific time series of satellite products. This method is based on quantifying the temporal signal-to-noise ratio (SNR, hereafter) of the daily MODIS NDVI time series, defined as the variance of smoothed temporal signal over the variance of the residues. If consecutive observations of the same pixel (which have thus sampled the spatial vicinity of that pixel) provide similar NDVI values, the resulting temporal signal is relatively stable and the SNR is high. Such stability can indicate that the signal comes from a spatially homogeneous surface, such as a single large field covered by the same crop with similar agro-management practices. On the contrary, a noisy time series indicates instead a transition zone between different land uses or between fields with different management practices. SNR maps therefore serve as a proxy for sub-pixel homogeneity from which time series originating from a specific land cover or land use can be retrieved. This approach is demonstrated over 12 contrasting agricultural landscapes across the globe from which clearly distinctive crop specific signals are extracted. Exploiting the full MODIS archive to derive surface specific information in this way should open new avenues for regional to global agricultural monitoring applications. Expanding this method to derive satellite products for specific land cover classes could also be useful for many other applications linked to dynamics of land cover and land use change. (C) 2015 The Authors. Published by Elsevier Inc.
机译:自2000年以来,MODIS一直在提供每日图像以获取空间分辨率为250 m的土地表面属性。在许多地方,此像素大小比诸如林地或农田等单个景观元素的像素大小要近。时间序列更通常用于植被分析(像素大小范围从1 km到8 km)。有了这样的空间分辨率,再加上存档时间越来越长,MODIS数据为一般的植被监测应用特别是作物生长监测提供了巨大的潜力。但是,由于其旋转扫帚设计,MODIS仪器的观察几何形状与图像配准中的空间不确定性相结合,可能导致不同的(尽管是相邻的)物理区域根据视图天顶角度映射到同一像素上(每天之间都有所不同)。而不是将其视为不便之处,这里提出一种方法来利用这种特殊性来识别对应于均匀植物覆盖的像素,以便检索卫星产品的地面特定时间序列。该方法基于量化每日MODIS NDVI时间序列的时间信噪比(以下称为SNR),该时间序列定义为平滑时间信号相对于残差方差的方差。如果对同一像素的连续观察(因此已经对该像素的空间附近进行了采样)提供了相似的NDVI值,则生成的时间信号相对稳定并且SNR高。这种稳定性可以表明信号来自空间上均匀的表面,例如具有相似农业管理实践的同一农作物覆盖的单个大田地。相反,嘈杂的时间序列表示不同土地用途之间或具有不同管理实践的田地之间的过渡区。因此,SNR映射可作为亚像素同质性的代理,从中可以检索源自特定土地覆盖或土地利用的时间序列。这种方法在全球12个对比鲜明的农业景观中得到了证明,从中可以提取明显不同的作物特定信号。利用完整的MODIS档案库以这种方式获取地面特定信息,应该为区域到全球的农业监测应用开辟新的途径。扩展此方法以得出特定土地覆盖类别的卫星产品,对于与土地覆盖动态和土地利用变化相关的许多其他应用也可能有用。 (C)2015作者。由Elsevier Inc.发布

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