There is a variety of different terrain types in outdoor environments, each posing different dangers to the robot and demanding a different driving style. In a previous paper, we presented a terrain classification method based on Support Vector Machines (SVM), which uses vibrations induced in the body of the robot to learn different terrain classes. However, in the previous paper, our experimen...

One of the most promising approaches to solve the challenging task of thematic mapping in urban environments is the integration of multiple data sources to benefit from the complementary types of available information. Within the paper the combination of Digital Surface Models (DSM) resulting from airborne laser scanning and colour aerial imagery for landuse classification in urban environments...

Extensive parts of Arctic permafrost-dominated lowlands were affected by large-scale permafrost degradation, mainly through Holocene thermokarst activity. The effect of thermokarst is nowadays observed in most periglacial lowlands of the Arctic. Since permafrost degradation is a consequence as well as a significant factor of global climate change, it is necessary to develop efficient methods fo...

This paper exploits an effective water extraction method using SAR imagery in preparation for flood mapping in unpredictable flood situations. The proposed method is based on the thresholding method using SAR amplitude, terrain information, and object-based classification techniques for noise removal. Since the water areas in SAR images have the lowest amplitude value, the thresholding method u...

Autonomous rover operation plays a key role in planetary exploration missions. Rover systems require more and more autonomous capabilities to improve efficiency and robustness. Rover mobility is one of the critical components that can directly affect mission success. Knowledge of the physical properties of the terrain surrounding a planetary exploration rover can be used to allow a rover system...

The motivation of our work is to detect different terrain types traversed by a robot based on acoustic data from the robot-terrain interaction. Different acoustic features and classifiers were investigated, such as Mel-frequency cepstral coefficient and Gamma-tone frequency cepstral coefficient for the feature extraction, and Gaussian mixture model and Feed forward neural network for the classi...

The knowledge of the surface topography has a major importance in the field of Earth sciences. It is essential in any discipline concerned with process modeling like hydrology, climatology, geomorphology and ecology. The present study utilized Environmental Systems Research Institute’s (ESRI) ArcGIS 9.3 (with the spatial analyst extension) software, remote sensing data ( DEM and Digital Aerial ...

In this paper we consider the problem of interpreting the data of a 3D laser range finder. The surrounding terrain is segmented into a 2D grid where each cell can be an obstacle or negotiable region. A Markov random field models the relationships between neighboring terrain cells and classifies the whole surrounding terrain. This allows us to add context sensitive information to the grid cells ...

Classification of terrain is one of the most important applications of Polarimetric Synthetic Aperture Radar (POLSAR) sensing. This paper presents a simple method to classify terrain by the correlation coefficients in the circular polarization basis and the total power of scattering matrix in the X-band. It is known that the circular polarization correlation coefficient contains essential polar...