Multi-agent Systems in Remote Sensing Image Analysis

Abstract

With remote sensing data and methods we gain deeper insight in many processes at the Earth’s surface. Thus, they are a valuable data source to gather geo-information of almost any kind. While the progress of remote sensing technology continues, the amount of available remote sensing data increases. Hence, besides effective strategies for data mining and image data retrieval, reliable and efficient methods of image analysis with a high degree of automation are needed in order to extract the information hidden in remote sensing data. Due to the complex nature of remote sensing data, recent methods of computer vision and image analysis do not allow a fully automatic and highly reliable analysis of remote sensing data, yet. Most of these methods are rather semi-automatic with a varying degree of automation depending on the data quality, the complexity of the image content and the information to be extracted. Thus, visual image interpretation in many cases is still seen as the most appropriate method to gather (geo-) information from remote sensing data. To increase the degree of automation, the application of multi-agent systems in remote sensing image analysis is recently under research. The paper present summarizes recent approaches and outlines their potentials.