A glacierized terrain comprises different land covers, and their mapping using satellite data is challenged by their spectral similarity. We propose a hierarchical knowledge-based classification (HKBC) approach for differentiation of glacier terrain classes and mapping of glacier boundaries, using Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) imagery and Global Digital ...

Today’s autonomous vehicles operate within an increasingly larger set of environments compared to earlier research in which environments were more controlled. In particular, unmanned ground vehicles (UGV’s) must be able to travel on whatever terrain the mission offers, including sand, mud, or even snow. These terrains can affect the performance and controllability of the vehicle. Like a human d...

A Multiple Natural Hazards Assessment (MNHA) procedural model was developed to provide stakeholders (e.g., community planners and decision makers) with a clear methodology that examines the landscape as a probabilistic-based composite measure of the natural hazards at a terrain mapping unit scale. The model consists of four phases: (1) data collection; (2) individual natural hazard assessment (...

The aim of this study is to evaluate three different strategies to improve classification accuracy in a highly fragmented semiarid area. i) Using different classification algorithms: Maximum Likelihood, Random Forest, Support Vector Machines and Sequential Maximum a Posteriori, with parameter optimisation in the second and third cases; ii) using different feature sets: spectral features, spectr...

Classification of terrain is one of the most important applications of Polarimetric Synthetic Aperture Radar (POLSAR) image analysis. This paper presents a simple method to classify terrain by the use of the correlation coefficients in the circular polarization basis together with the total power of the scattering matrix in the X-band. The reflection symmetry condition that the co-polarized and...

Mobile robots are increasingly used in unstructured domains without permanent supervision by a human operator. One example is Safety, Security and Rescue Robotics (SSRR) where human operators are a scarce resource. There are additional motivations in this domain to increase robot autonomy, e.g., the desire to decrease the cognitive load on the operator or to allow robot operations when communic...

We present an innovative way to autonomously classify LiDAR points into bare earth, building, vegetation, and other categories. One desirable product of LiDAR data is the automatic classification of the points in the scene. Our algorithm automatically classifies scene points using Compressed Sensing Methods via Orthogonal Matching Pursuit algorithms utilizing a generalized K-Means clustering al...

Terrain-induced variations of radar backscatter represent an important limiting factor many Synthetic Aperture Radar (SAR)-based applications. Radiometric terrain flattening (RTF) is a well-established method that minimizes these in SAR imagery. To fully understand the implications RTF, validation its impact on derived products needed. In this study, we quantified influence RTF forest mapping a...

The aim of this study was to evaluate three different strategies to improve classification accuracy in a highly fragmented semiarid area using, (i) different classification algorithms with parameter optimization in some cases; (ii) different feature sets including spectral, textural and terrain features; and (iii) different seasonal combinations of images. A three-way ANOVA was used to discern ...