Remote sensing images and techniques are powerful tools to investigate earth surface. Data quality is the key to enhance remote sensing applications and obtaining a clear and noise-free set of data is very difficult in most situations due to the varying acquisition (e.g., atmosphere and season), sensor, and platform (e.g., satellite angles and sensor characteristics) conditions. With the increasing development of satellites, nowadays Terabytes of remote sensing images can be acquired every day. Therefore, information and data fusion can be particularly important in the remote sensing community. The fusion integrates data from various sources acquired asynchronously for information extraction, analysis, and quality improvement. In this chapter, we aim to discuss the theory of spatiotemporal fusion by investigating previous works, in addition to describing the basic concepts and some of its applications by summarizing our prior and ongoing works.
翻译:遥感图像和技术是调查地球表面的有力工具,数据质量是加强遥感应用的关键,在多数情况下,由于获取条件(例如大气层和季节)、传感器和平台(例如卫星角度和传感器特性)条件不尽相同,获得一套明确和无噪音的数据非常困难。随着卫星的日益发展,现在每天都可以获得Terabyte的遥感图像,因此,信息和数据融合在遥感界尤其重要。聚合将各种来源获得的数据无同步地综合起来,用于信息提取、分析和质量改进。本章的目的是通过调查以往的工程,讨论波时融合理论,此外通过概述我们以前和正在进行的工程,说明基本概念及其一些应用。