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Caveats in calculating crop specific pixel purity for agricultural monitoring using MODIS time series

机译:使用MODIS时间序列为农业监测计算作物特定像素纯度的警告

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Monitoring agriculture at regional to global scales with remote sensing requires the use of sensors that can provide information over large geographic extends with a high revisit frequency. Current sensors satisfying these criteria have, at best, a spatial resolution of the same order of magnitude as the field sizes in most agricultural landscapes. Research has demonstrated that crop specific monitoringis possible with medium spatial resolution instruments (such as with MODIS, 250 m at nadir) if a selection of purer time series is isolated. To do so, a mask of the target crop is necessary at fine spatial resolution in order to calculate the crop specific pixel purity at the coarser scale. Pixel purity represents the relative contribution of the surface of interest to the signal detected by the remote sensing instrument. A straightforward way to compute pixel purity is to calculate the area of the target crop that falls in the coarse spatial resolution grid. However, the observation footprint is generally larger than the squared projection of the pixel, especially when the observation is taken with high scan angles like MODIS does most of the time. Furthermore, the relative contribution within this footprint is not homogeneous: it depends on the spatial response of the sensor. This study analyses the error committed when crop specific pixel purity is calculated using the straightforward method instead of integrating the spatial response and taking into account gridding artefacts and other MODIS particularities such as the bow-tie effect. Differences caused by the orbit, i.e. whether MODIS is on a descending orbit for Terra or an ascending one for Aqua, are also explored. Finally, the consequence of overestimating the spatial response when calculating pixel purity is illustrated by analysing the effect on different agricultural landscapes.
机译:通过遥感监测区域到全球范围内的农业,需要使用能够以较高的重访频率在较大的地理范围内提供信息的传感器。满足这些标准的当前传感器最多具有与大多数农业景观中的田地大小相同数量级的空间分辨率。研究表明,如果分离出更纯净的时间序列,则可以使用中等空间分辨率的仪器(例如,在最低点为250 m的MODIS)进行作物特定的监测。为此,必须在精细的空间分辨率下屏蔽目标农作物,以便在较粗的尺度上计算农作物特定像素的纯度。像素纯度表示感兴趣的表面对遥感仪器检测到的信号的相对贡献。计算像素纯度的一种直接方法是计算落入粗糙空间分辨率网格中的目标作物的面积。但是,观察脚印通常大于像素的平方投影,尤其是当像MODIS在大多数情况下以高扫描角度进行观察时。此外,在该覆盖范围内的相对贡献不是均匀的:它取决于传感器的空间响应。这项研究分析了使用直接方法而不是整合空间响应并考虑网格伪影和其他MODIS特殊性(例如领结效应)来计算作物特定像素纯度时所犯的误差。还探讨了由轨道引起的差异,即,MODIS是Terra降落还是Aqua升降。最后,通过分析对不同农业景观的影响来说明计算像素纯度时高估空间响应的结果。

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