Study on the Uncertainty of Remote Sensing Information

摘要

To date, Remote Sensing technologies have been applied to environmental management, monitoring and control. Remote Sensing technologies are also being applied to monitor land desertification, land use cover, environment pollution, et al. Due to limitations in apparatus and processing technology in RS, system errors and measurement errors may corrupt the data. Errors may be associated both with attribute values and the location of attribute values. After collecting spatial data, we then need to process, analyze and convert the data in order to make RS information understandable to users. When products of RS are produced, new errors will be introduced due to operating spatially on maps or images. If we ignore these errors in the RS products, it can result in wrong decision-making and economic losses. Though, the uncertainty of remote sensing information has been a hotspot in the spatial information handling and many issues have provide us lots of valuable results, very little research lies on the mechanism-based uncertainty analysis of remote sensing information. The existing methods dealing with the uncertainty analysis RS have some disadvantages and limitations, such as leading some important process of remote information to "blind spots" of uncertainty analysis, that is, their uncertainties not analyzed. Consequently, the uncertainty in final image product would not be analyzed quantitatively and expressed accurately. In this paper, we propose one new method to deal with these problems.