Visualization of Predicted Ground Vibration Induced by Blasting in Urban Quarry Site Utilizing Web-GIS

Abstract

Blasting is routinely carried out at various quarries. When blasting is done in an urban area, the ground vibration induced by the operation may affect nearby residents physically and mentally. In this study, a visualization system of ground vibration induced by blasting is constructed for the purpose of reducing these adverse effects. The system consists of two phases. The first is the ground vibration prediction by using artificial intelligence, specifically an ANN (Artificial Neural Network). The second is the visualization of the predicted vibration through Web-GIS. Four prediction factors, namely MIC (Maximum Instantaneous Charge), distance, elevation difference, and direction were used and PPV (Peak Particle Velocity) was used as an index of ground vibration strength. Colored contours representing vibration intensity were generated using GIS tools based on predicted PPV. Furthermore, the contour is converted into a KMZ file and overlaid on a web-based map (Google Maps) that also displays other pertinent information about the quarry vicinity. This means that the system can be used by anyone who has an internet connection and access to a browser. The data would be available to residents, local government officers, and anyone else who wishes to use it. In addition, the ground vibration prediction data and contour maps could also be used to optimize blasting designs in advance. Through the use of this system, optimal blasting can be done, maximizing the productivity of the quarry as well as minimizing the impact on the local residences.