This evaluate the performance of geospatial image processing using two distinct data storage formats: Zarr and TIFF. Geospatial images, converted to numerous applications like environmental monitoring, urban planning, and disaster management. Traditional Tagged Image File Format is mostly used because it is simple and compatible but may lack by performance limitations while working on large datasets. Zarr is a new format designed for the cloud systems,that offers scalability and efficient storage with data chunking and compression techniques. This study compares the two formats in terms of storage efficiency, access speed, and computational performance during typical geospatial processing tasks. Through analysis on a range of geospatial datasets, this provides details about the practical advantages and limitations of each format,helping users to select the appropriate format based on their specific needs and constraints.

翻译：本研究评估了使用两种不同数据存储格式（Zarr与TIFF）处理地理空间图像的性能。地理空间图像广泛应用于环境监测、城市规划与灾害管理等多个领域。传统的标记图像文件格式（TIFF）因其简单性与兼容性而被广泛采用，但在处理大规模数据集时可能面临性能限制。Zarr是一种专为云系统设计的新格式，通过数据分块与压缩技术提供可扩展性与高效存储。本研究在典型地理空间处理任务中，从存储效率、访问速度与计算性能三方面对两种格式进行比较。通过对一系列地理空间数据集的分析，本文详细阐述了每种格式的实际优势与局限性，以帮助用户根据其具体需求与约束条件选择合适的格式。