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随着对地观测技术的日新月异,遥感数据已形成大数据、海量化的发展趋势.面对海量遥感数据的应用需求,如何快速、准确地查找到所需数据是目前遥感数据组织管理研究的问题之一,而在众多遥感数据查找方式中,针对某一地区单时相全覆盖影像数据集筛选又是遥感数据应用过程的重要一环.然而,目前国内外主要遥感数据服务平台都缺乏相关工具,单时相全覆盖影像数据集的筛选主要还是通过人工方式完成,不仅效率极低,还容易造成遗漏等问题.因此,本文结合实际需求,提出了一种基于空间二次过滤的遥感数据单时相全覆盖检索方法,通过对比实验,该方法在低云量数据充分的情况下,能够自动、快速、准确地筛选出目标区域最新单一时相全覆盖遥感影像数据集,具有很好的实用意义.
With the rapid development of earth observation technology, remote sensing data has become a trend of big data and massification.With the application demand of massive remote sensing data, how to find the required data quickly and accurately is the research topic of remote sensing data organization and management However, in many remote sensing data search methods, the screening of single-time full-coverage image dataset in an area is an important part of the remote sensing data application process.However, the main remote sensing data service platforms at home and abroad lack the related tools , The screening of single-time full-coverage image dataset is mainly done manually, which is not only inefficient, but also easy to cause omissions and other issues.Therefore, this paper presents a remote sensing data sheet based on spatial quadratic filtering This method can automatically, quickly and accurately select the latest single-phase full-coverage remote sensing image dataset in the target area under the condition of low amount of cloud cover data through comparative experiments, which is of good practicality significance.