Infiltration Route Analysis Using Thermal Observation Devices (TOD) and Optimization Techniques in a GIS Environment

Sensors

Soonam Bang¹  Joon Heo²  Soohee Han² 

[1] Agency for Defense Development, P.O. Box 35 Yuseong, Daejeon, Korea; E-Mail:;School of Civil and Environmental Engineering, Yonsei University, 262 Seongsanno, Seodaemun-gu, Seoul 120-749, Korea; E-Mails:

关键词: thermal observation device;    infiltration-route analysis;    dynamic simulation;    GIS;    A* algorithm;   

DOI  :  10.3390/s100100342

来源: mdpi

【 摘 要 】

Infiltration-route analysis is a military application of geospatial information system (GIS) technology. In order to find susceptible routes, optimal-path-searching algorithms are applied to minimize the cost function, which is the summed result of detection probability. The cost function was determined according to the thermal observation device (TOD) detection probability, the viewshed analysis results, and two feature layers extracted from the vector product interim terrain data. The detection probability is computed and recorded for an individual cell (50 m × 50 m), and the optimal infiltration routes are determined with A* algorithm by minimizing the summed costs on the routes from a start point to an end point. In the present study, in order to simulate the dynamic nature of a real-world problem, one thousand cost surfaces in the GIS environment were generated with randomly located TODs and randomly selected infiltration start points. Accordingly, one thousand sets of vulnerable routes for infiltration purposes could be found, which could be accumulated and presented as an infiltration vulnerability map. This application can be further utilized for both optimal infiltration routing and surveillance network design. Indeed, dynamic simulation in the GIS environment is considered to be a powerful and practical solution for optimization problems. A similar approach can be applied to the dynamic optimal routing for civil infrastructure, which requires consideration of terrain-related constraints and cost functions.

【 授权许可】

CC BY   
©2010 by the authors; licensee Molecular Diversity Preservation International, Basel, Switzerland.