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MODIS-Based Monthly LST Products over Amazonia under Different Cloud Mask Schemes

机译:不同云掩码方案下基于MODIS的Amazonia每月LST产品

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One of the major problems in the monitoring of tropical rainforests using satellite imagery is their persistent cloud coverage. The use of daily observations derived from high temporal resolution sensors, such as Moderate Resolution Imaging Spectroradiometer (MODIS), could potentially help to mitigate this issue, increasing the number of clear-sky observations. However, the cloud contamination effect should be removed from these results in order to provide a reliable description of these forests. In this study the available MODIS Land Surface Temperature (LST) products have been reprocessed over the Amazon Basin (10 N–20 S, 80 W–45 W) by introducing different cloud masking schemes. The monthly LST datasets can be used for the monitoring of thermal anomalies over the Amazon forests and the analysis of spatial patterns of warming events at higher spatial resolutions than other climatic datasets.
机译:使用卫星图像监测热带雨林的主要问题之一是其持续的云覆盖。使用源自高时间分辨率传感器(例如中分辨率成像光谱仪(MODIS))的每日观测值可能有助于缓解此问题,从而增加晴空观测值的数量。但是,应从这些结果中消除云污染的影响,以便对这些森林提供可靠的描述。在这项研究中,通过引入不同的云遮蔽方案,对亚马逊盆地(10 N–20 S,80 W–45 W)上可用的MODIS地表温度(LST)产品进行了重新处理。每月的LST数据集可用于监视亚马逊森林的热异常,并以比其他气候数据集更高的空间分辨率分析变暖事件的空间模式。

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