Abstract With the rapid development of remote sensing technology, the amount of remote sensing data is increasing, service objects are increasingly extensive, and requests from users to query the coverage of remote sensing images under specific conditions have also increased. These conditions have increased efficiency and precision requirements for concurrent access and response. Remote sensing images provide multiple coverages of the same area, and the nested and overlapping relationships among data are complex. Therefore, calculating the range of multiple overlaps of images becomes increasingly difficult as the number of images increases. To query the range of a coverage area of multiple images is to calculate its boundary, which is an important part of spatial overlay analysis. Traditional vector methods are inefficient in processing many spatial objects or complex shapes. The overlay of traditional spatial grids is mostly addressed via single-scale methods, which have low computational efficiency and low boundary fitting precision. Combined with the current gridding management method for multi-source remote sensing images, we proposed a new algorithm for rapid computation of the set boundaries of multi-scale grids and applied it to coverage analysis of remote sensing images. The algorithm can effectively trace the boundaries of multi-scale grids formed in the regions covered by remote sensing images, and it can solve all types of complex boundaries, such as convex and concave boundaries, holes and islands. The experiments in this study show that the new algorithm greatly improves computational efficiency and boundary fitting precision compared with the single-scale grid methods. Compared with the vector algorithms of ArcGIS and other commercial software, this study's algorithm can greatly improve calculation efficiency while ensuring a precision above 99%. The new algorithm is suitable for rapid calculations of large areas and widespread coverage of remote sensing images.

中文翻译：

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多尺度网格集边界的快速计算及其在遥感影像覆盖分析中的应用

摘要 随着遥感技术的飞速发展，遥感数据量越来越大，服务对象越来越广泛，用户查询特定条件下遥感影像覆盖范围的要求也越来越多。这些条件提高了并发访问和响应的效率和精度要求。遥感影像提供同一区域的多个覆盖范围，数据之间的嵌套和重叠关系复杂。因此，随着图像数量的增加，计算图像多次重叠的范围变得越来越困难。查询多幅图像覆盖区域的范围就是计算其边界，这是空间叠加分析的重要组成部分。传统的矢量方法在处理许多空间对象或复杂形状时效率低下。传统空间网格的叠加多采用单尺度方法解决，计算效率低，边界拟合精度低。结合现有的多源遥感影像网格化管理方法，提出了一种快速计算多尺度网格集边界的新算法，并将其应用于遥感影像的覆盖分析。该算法能够有效地追踪遥感影像覆盖区域形成的多尺度网格的边界，可以求解各种类型的复杂边界，如凸凹边界、孔洞和岛屿。本研究的实验表明，与单尺度网格方法相比，新算法大大提高了计算效率和边界拟合精度。与ArcGIS等商业软件的矢量算法相比，本研究的算法在保证精度99%以上的同时，大大提高了计算效率。新算法适用于大面积、大范围覆盖遥感影像的快速计算。