Enhancement of radar based DEMs using 3D techniques

Digital elevation models may contain several errors, what causes uncertainty about the reliability of the data. Reliable use of elevation data requires that uncertainty associated with the data be accounted for and that the errors responsible for this uncertainty are identified, quantified and removed. Several studies have proposed assorted methods to detect and quantify, and also to remove different kinds of errors. However, these automatic procedures apply algorithms that are specialized in detecting errors with particular characteristics, producing good results only when the model contains predominantly these specific types of errors. In this context, this paper presents a methodology and a tool for enhancing digital elevation models, named DEMEditor. Visual interpretation plays an important role in this work, which exploits user’s knowledge about the data in the decision-making process about areas to be enhanced in the digital elevation model. The background of the user allows the identification of any type of error, relieving the need for automatic detection algorithms that specialize in detecting errors with particular characteristics.