Rapid computation of set boundaries of multi-scale grids and its application in coverage analysis of remote sensing images

摘要

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.