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1 IGS (2016b), IGS Products, International GNSS Services, https://igscb.jpl.nasa.gov/components/prods.html (last data accessed: 10 January 2016)./ View Article
2 UNAVCO (2016), The toolkit for GPS/GLONASS/Galileo/SBAS/QZSS data, University Navstar Consortium, https://www.unavco.org/software/data-processing/teqc/teqc.html (last date accessed: 10 January 2016)./ View Article
3 IGS (2016a), IGS tracking network, International GNSS Services, https://igscb.jpl.nasa.gov/network/netindex.html (last date accessed: 10 January 2016)./ View Article
4 NGII (2016), Current geoid models of Korea, National Geographic Information Institute, Suwon, Korea, http://ngii.go.kr/geoid/intro/geoid_condition.do (last date accessed: 15 January 2016). (in Korean)/ View Article
5 Wikipedia contributors (2016), Line-line intersection, Wikipedia, The Free Encyclopedia, https://en.wikipedia. org/wiki/Line-line_intersection (last date accessed: 3 February 2016)./ View Article
6 USGS (2016), Map Locator & Downloader, USGS, Reston, VA, USA, http://store.usgs.gov/b2c_usgs/usgs/maplocator/, Map Locator & Downloader (last date accessed: 2 march 2016)./ View Article
7 Moon, K.I., Pyeon, M.W., Kim, J.H., Kim, K.S., and Lim, Y.S. (2016), A Study of Construction of Utilization of Realtime Digital Map (RDM) Using CCTV and Multi-source Data Tools, Proceedings of 2016 International Conference on Urban Planning, Transport and Construction Engineering (ICUPTCE’16), 2-3 Jan., Pattaya, Thailand, pp. 1-6./ View Article
8 Bui, D.T., Tuan, T.A., Klempe, H., Pradhan, B., and Revhaug, I. (2016), Spatial prediction models for shallow landslide hazards: a comparative assessment of the efficacy of support vector machines, artificial neural networks, kernel logistic regression, and logistic model tree, Landslides, Vol. 13, No. 2, pp. 361-378./   DOI View Article
9 Acharya, T.D., Yang, I.T., and Lee, D.H. (2016). Geospatial technologies for landslide inventory: application and analysis to earthquake-triggered landslide of Sindhupalchowk, Nepal, Journal of the Korean Society for Geo-spatial Information Science, Vol. 24, No. 2, pp. 95-106./   DOI View Article
10 Hong, H., Pourghasemi, H.R., and Pourtaghi, Z.S. (2016), Landslide susceptibility assessment in Lianhua county (China): A comparison between a random forest data mining technique and bivariate and multivariate statistical models, Geomorphology, Vol. 259, pp. 105-118./   DOI View Article