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Applying Fuzzy Sets to Composite Algorithm for Remote Sensing Data

机译:模糊集在遥感数据合成算法中的应用

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摘要

Remote sensing of the earth surface using satellite mounted sensor data is a major method for global environmental monitoring today. However, when using satellite sensor data, clouds in the atmosphere can interfere with the readings, and specific land points may not be correctly monitored on a given day. In order to overcome this problem, multiple day composite data is frequently used. Multiple day composite data uses several consecutive days' remote sensing data, and picks the most accurate data within the temporal dataset for the same land point. This allows creating a more complete dataset by patching together data not interfered by clouds during a specified time period, to create a clearer, more usable dataset. In this paper, we propose applying fuzzy set logic in order to select the clearest data in the temporal interval for the composite data. Moderate resolution remote sensing data of areas in Japan were used for evaluation.
机译:使用卫星安装的传感器数据对地球表面进行遥感是当今全球环境监测的一种主要方法。但是,当使用卫星传感器数据时,大气中的云会干扰读数,并且在特定的一天可能无法正确监视特定的着陆点。为了克服该问题,经常使用多日合成数据。多日合成数据使用连续几天的遥感数据,并在时间数据集中为同一陆地点选择最准确的数据。这允许通过将在指定时间段内不受云干扰的数据拼凑在一起来创建更完整的数据集,以创建更清晰,更可用的数据集。在本文中,我们提出应用模糊集逻辑,以便在时间间隔内为复合数据选择最清晰的数据。使用日本地区中等分辨率的遥感数据进行评估。

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