Dataset of three-dimensional traces of roads.

We present a dataset consisting of three-dimensional traces, captured by Global Navigation Satellite System techniques with three-dimensional coordinates. It offers 138 traces (69 going and 69 returning), in addition to the actual mean axis of the road determined by precise surveying techniques to be used as ground truth for research activities. These data may serve as a test bed for research on data mining applications related to Global Navigation Satellite System multitraces, particularly the development and testing of algorithms intended for mining mean axis data from road multitraces.

Variables Influencing the Accuracy of 3D Modeling of Existing Roads Using Consumer Cameras in Aerial Photogrammetry.

Point cloud (PC) generation from photogrammetry⁻remotely piloted aircraft systems (RPAS) at high spatial and temporal resolution and accuracy is of increasing importance for many applications. For several years, photogrammetry⁻RPAS has been used to recover civil engineering works such as digital elevation models (DEMs), triangle irregular networks (TINs), contour levels, orthophotographs, etc. This study analyzes the influence of variables involved in the accuracy of PC generation over asphalt shapes and determines the most influential variable based on the development of an artificial neural network (ANN) with patterns identified in the test flights.

MatchingLand, geospatial data testbed for the assessment of matching methods.

This article presents datasets prepared with the aim of helping the evaluation of geospatial matching methods for vector data. These datasets were built up from mapping data produced by official Spanish mapping agencies. The testbed supplied encompasses the three geometry types: point, line and area.