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Sensor Network for Landslide Monitoring With Laser Ranging System Avoiding Rainfall Influence on Laser Ranging by Means of Time Diversity and Satellite Imagery Data Based Landslide Disaster Relief
Kohei Arai
Pages - 1 - 12     |    Revised - 15-01-2012     |    Published - 21-02-2012
Volume - 3   Issue - 1    |    Publication Date - June 2012  Table of Contents
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KEYWORDS
landslide, Satellite Remote Sensing, Automatic Control Point Detection, laser Ranging With Time Diversity, Change Detection, Sensor Network
ABSTRACT
Sensor network for landslide monitoring with laser ranging system is developed together with landslide disaster relief with remote sensing satellite imagery data. Time diversity is utilized for rainfall influence avoidance in the distance measurements between laser ranging equipment and targets. Also automatic tie point extraction method is proposed. Experimental results show that (1) the proposed time diversity of the laser ranging measurement does work for avoidance from rainfall influence; (2) the proposed automatic control point extraction method does work for tie point matching together with change detection for landslide disaster relief.
CITED BY (1)  
1 Dawood, M. S., Suganya, J., Devi, R. K., & Athisha, G. (2013). A Review on Wireless Sensor Network Protocol for Disaster Management. International Journal of Computer Applications Technology and Research, 2(2), 141-146.
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1 Dunnicliff, J. 1993. Geotechnical Instrumentation for Monitoring Field Performance. New York: John Wiley & Sons
2 Mikkelsen, P.E. 1996. Field instrumentation. In A.K. Turner & R.L. Schuster (eds), Landslides: Investigation and Mitigation, Special Report 247: 278–316. Washington, DC: National Academy Press.
3 Eyers, R., Moore, J. McM., Hervas, J. and Lui, J. G., 1995. Landslide mapping using digital imagery: a case history from south east Spain”. Proc. 31st Annual Conf. on Geohazards and Engineering Geology, 379 – 388. 1995, Coventry, UK
4 Wang, L. and He, D. C. “A new statistical approach for texture analysis”. Photogrammetric Engineering and Remote Sensing, 56 (1), 61 – 66. 1990.
5 Zhang, Z.; Gong, H.; Zhao, W.; Zhang, Y. 2005. AppLeication of remote sensing to study of landslides. IEEE, 1546-1549.
6 Rosin, P.L. and Hervás, J. (2005). Remote sensing image thresholding methods to determining landslide activity. International Journal of Remote Sensing, 26, 6, 1075-1092.
7 Forstner W. and E. Gulch, 1987, A fast operator for detection and precise location of distinct points, corners and centers of circular features, ISPRS Intercom. Workshop, Interlaken, 281- 304.
8 Schmidt, R., Brand, R., 2003. Automatic determination of tie points for HRSC on Mars Express, ISPRS Workshop High Resolution Mapping from Space 2003, October 6-8, 2003, Hannover.
9 Förstner, W., 1986. A feature based correspondence algorithm for image matching, IntArchPhRS, (26) 3/3, pp. 150-166.
Professor Kohei Arai
Saga University - Japan
arai@is.saga-u.ac.jp