基于空间角度理论的卫星光学遥感数据认知与挖掘

Understanding and Mining of Optical Satellite Data Based on the Space Angel Theory

随着科学技术的发展，新的探测器不断地升空，卫星光学遥感数据经历了长周期的积累和更新。如何有效地开发与利用巨量遥感数据，从中挖掘出隐藏的信息和信息的知识化是当前面临的严峻挑战。首先分析了地面物质和结构光谱与卫星遥感信息之间的关系，建立了空间角度模型；然后以多维遥感信息的象元矢量和波段趋势面分析为基础，分析了当前用来处理光学遥感数据的商业化“最优化”算法在处理遥感数据时经常出现的“欠优”结果的原因；最后，通过对美国陆地卫星ＴＭ

With the development of science and technology, new remote sensing devices are lunched on schedule. Optical satellite data have been undergone a long time renewal and accumulation. How to reveal hidden information from huge amount of remote sensing data and let it knowledgeable is new challenge for us. In this article, first we analysis the relation between material,structure spectral and remote sensing information, formulate space angel model. Then based on pixel vector and band vector tendency face of multi\|band remote sensing information, we analysis the results of “not proper” in the cases of mining some information from remote sensing data when using the software algorithms which are selected according to “the bast optimum” of the statistics. Finally, we illustrate the mathematical principles and effectiveness of algorithms that we used in mining multi\|band TM data.