首页> 外文期刊>Photogrammetric Engineering & Remote Sensing: Journal of the American Society of Photogrammetry >Estimation of inter-annual crop area variation by the application of spectral angle mapping to low resolution multitemporal NDVI images.
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Estimation of inter-annual crop area variation by the application of spectral angle mapping to low resolution multitemporal NDVI images.

机译:通过将光谱角度映射应用于低分辨率多时相NDVI图像来估算年际作物面积变化。

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摘要

This current work is aimed at developing and testing a methodology which can be applied to low spatial resolution satellite data to assess inter-annual crop area variations on a regional scale. The methodology is based on the assumption that within mixed pixels, such variations are reflected by changes of the related multitemporal Normalised Difference Vegetation Index (NDVI) profiles. This implies that low resolution NDVI images with high temporal frequency can be used to update land cover estimates derived from higher resolution cartography. Specifically, changes in shape of NDVI profiles are quantified by Spectral Angle Mapping (SAM), which has the advantage of being nearly insensitive to inter-year NDVI differences caused by meteorological variability. A calibration phase is then necessary to convert the information derived from SAM into relevant area variations which is carried out by a regression estimator calibrated to the data of a training year for which both low-resolution NDVI data and higher-resolution land-cover references are available. The methodology can also cope with inter-annual differences in the crop phenological cycles through temporal shifting of the reference NDVI profiles. The proposed methodology was applied in a study region in central Italy to estimate area changes of winter crops from low-resolution NDVI profiles. The accuracy of such estimates was assessed by comparison to official agricultural statistics. The method showed promise for estimating crop area variation on a regional scale with the accuracy of the final results dependent on the quality of the satellite data time series and of the reference high-resolution land-cover maps..
机译:这项当前的工作旨在开发和测试一种方法,该方法可用于低空间分辨率的卫星数据,以评估区域范围内的年度作物面积变化。该方法基于以下假设:在混合像素内,此类变化通过相关的多时间归一化差异植被指数(NDVI)轮廓的变化反映出来。这意味着具有较高时频的低分辨率NDVI图像可用于更新从高分辨率制图获得的土地覆盖估算。具体而言,NDVI轮廓的形状变化通过频谱角度映射(SAM)进行量化,其优点是对由气象变异性引起的年际NDVI差异几乎不敏感。然后需要一个校准阶段,以将来自SAM的信息转换为相关的区域变化,这由回归估计器执行,该回归估计器根据训练年的数据进行校准,对于该训练年的数据,低分辨率的NDVI数据和高分辨率的土地覆盖物参考都是可用。该方法还可以通过参考NDVI配置文件的时间偏移来应对作物物候周期的年际差异。拟议的方法已在意大利中部的一个研究区域中应用,可以根据低分辨率NDVI剖面估算冬季作物的面积变化。通过与官方农业统计数据进行比较,评估了这种估计的准确性。该方法显示了在区域范围内估计作物面积变化的希望,最终结果的准确性取决于卫星数据时间序列和参考高分辨率土地覆盖图的质量。

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