遥感影像动态瓦片关键技术研究与实现

Research on Key Technologies and Implementation of Dynamic Tiling for Remote Sensing Images

摘要: 近年来，随着遥感技术与自然资源信息化建设的持续推进，高分辨率、多时序、多源遥感影像在城市规划、土地管理、灾害监测及应急响应等领域得到广泛应用，影像数据规模已达到TB级，并呈现向PB级持续扩展的发展趋势。传统静态瓦片服务模式存在存储冗余大、更新滞后和访问延迟高等问题，已难以满足实时在线访问和多系统共享需求。本文构建了一套基于Cloud Optimized GeoTIFF (COG)的遥感影像动态瓦片生成系统，并使用Qt C++实现WMTS与XYZ服务。系统通过影像预处理生成COG文件，实现按需裁切和多分辨率瓦片生成；服务端结合多线程、缓存机制和索引优化，实现高并发下的高性能访问。实践表明，单瓦片生成平均时间为50 ms，缓存命中率达95%，并发访问延迟低于150 ms，系统在高分辨率遥感影像动态服务中具有良好的应用前景。

Abstract: In recent years, with the continuous advancement of remote sensing technology and the informatization of natural resources management, high-resolution, multi-temporal, and multi-source remote sensing images have been widely applied in urban planning, land management, disaster monitoring, and emergency response. The volume of image data has reached the Terabyte (TB) scale and continues to expand toward the Petabyte (PB) level. Traditional static tile service models suffer from large storage redundancy, delayed updates, and high access latency, which are inadequate for real-time online access and multi-system data sharing. This paper proposes a dynamic tile generation system for remote sensing images based on Cloud Optimized GeoTIFF (COG), and implements WMTS and XYZ services using Qt C++. The system generates COG files through image preprocessing, enabling on-demand cropping and multi-resolution tile generation. By integrating multi-threading, caching mechanisms, and index optimization strategies on the server side, high-performance access under concurrent requests is achieved. Experimental results show that the average generation time of a single tile is approximately 50 ms, the cache hit rate reaches 95%, and the latency under concurrent access remains below 150 ms. The system demonstrates strong applicability and engineering feasibility for dynamic services of high-resolution remote sensing images.