Abstract
The identification of underground geohazards is always a difficult issue in the field of underground public safety. This study proposes an interactive visualization framework for underground geohazard recognition on urban roads, which constructs a whole recognition workflow by incorporating data collection, preprocessing, modeling, rendering and analyzing. In this framework, two proposed sampling point selection methods have been adopted to enhance the interpolated accuracy for the Kriging algorithm based on ground penetrating radar (GPR) technology. An improved Kriging algorithm was put forward, which applies a particle swarm optimization (PSO) algorithm to optimize the Kriging parameters and adopts in parallel the Compute Unified Device Architecture (CUDA) to run the PSO algorithm on the GPU side in order to raise the interpolated efficiency. Furthermore, a layer-constrained triangulated irregular network algorithm was proposed to construct the 3D geohazard bodies and the space geometry method was used to compute their volume information. The study also presents an implementation system to demonstrate the application of the framework and its related algorithms. This system makes a significant contribution to the demonstration and understanding of underground geohazard recognition in a three-dimensional environment.
Highlights
In the last decade, the visualization platforms of above-ground geographical information have been constructed in various fields [1,2,3,4,5]
Ground penetrating radar (GPR) technology enables geologists to explore the evolution mechanism and adopt measures to avoid underground geohazards on urban roads, enhancing the quality of preprocessed ground penetrating radar (GPR) data, where the generated data can affect the accuracy of geohazard recognition directly, is still a considerable problem
Based on our research team’s self-developed GPR equipment, this study presents an interactive 3D visualization framework for underground geohazard recognition on urban roads called 3DVF4UDR, which complements the existing GPR instrument and visualization platforms profoundly
Summary
The visualization platforms of above-ground geographical information have been constructed in various fields [1,2,3,4,5]. (1) We presented a framework that integrates the detection processes into one workflow, including data acquisition, preprocessing, modeling, visualization and interactive geohazard recognition and analysis. (2) In this framework, a series of proposed novel algorithms provided the theoretical support for the recognition processes, including the data selection methods of the Kriging algorithm, the improved GPU-PSO-Kriging algorithm and the layer-constrained triangulated irregular network (TIN) algorithm These can make the GPR data preprocessing faster and more accurate, but can construct geohazard bodies of arbitrary shapes either in part or as a whole.
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
