卫星遥感技术为我们研究全球变化提供了时间、空间、光谱多维度的海量遥感大数据，目前还没有一种针对遥感数据的多维度的特性设计的一体化存储结构。本文提出了一种多维遥感数据的组织方式，设计了SPAtial-Temporal-Spectral（SPATS）时空谱多维遥感数据一体化存储结构，定义了5种多维数据存储格式：Temporal Sequential in Band（TSB）、Temporal Sequential in Pixel（TSP）、Temporal Interleaved by Band（TIB）、Temporal Interleaved by Pixel（TIP）和Temporal Interleaved by Spectrum（TIS），设计了Multi-dimensional Data Analysis（MDA）多维数据分析模块，实现了长时间序列遥感影像的时空谱多维一体化存储，并能够进行不同维度的数据分析与显示，构建了基于不同光谱指数的时间谱影像立方体，为时空谱多维遥感数据的综合与表征提供数据组织解决方案。

The techniques of satellite remote sensing has been providing massive remote sensing data, however there's no integrated storage structure specially designed for the characters of remote sensing's multi-dimensions. In this context, a method of organizing multi-dimensional remote sensing data is proposed, and an integrated storage structure of SPAtial-Temporal-Spectral (SPATS) multi-dimensional remote sensing images is designed with five multi-dimensional storage format defined:Temporal Sequential in Band (TSB)、Temporal Sequential in Pixel (TSP)、Temporal Interleaved by Band (TIB)、Temporal Interleaved by Pixel (TIP) and Temporal Interleaved by Spectrum (TIS). In addition, Based on this structure, a multi-dimensional data analysis module, namely MDA, is designed, which could implement the SPATS integrated storage of long time-series remote sensing imagery, perform data analysis and display, and build temporal image cubes of a variety of spectral indices, providing a solution of organizing data for the synthesis and characterization of SPATS multi-dimensional remote sending images.