References
- Bannari, A., H. Rhinane and H. Bahi. 2018. Synergy between SMOS-MIRAS and Landsat-OLI/TIRS Data for Soil Moisture Mapping before, during, and after Flash-Flood Storm in Southwestern Morocco, Chapter 2:5-28.
- Choung, Y.J., K.K. Yu and Y.I. Lee. 2020. A Study on Monitoring the Land Surface Temperature Changes Caused by Constructions of Rainwater Villages Using the Multi-temporal Landsat-8 Satellite Images. Journal of the Korean Association of Geographic Information Studies 23(1): 30-40.
- Choung, Y.J., Y.I. Choung and S.Y. Choi. 2018. Assessment of the Relationship between Air Temperature and TOA Brightness Temperature in Different Seasons Using Landsat-8 TIRS. Journal of the Korean Association of Geographic Information Studies 21(2):68-79.. https://doi.org/10.11108/KAGIS.2018.21.2.068
- Giglio, L., J. Descloitres, C.O. Justice and Y.J. Kaufman. 2013. An enhanced contextual fire detection algorithm for MODIS, Rem. Sens, Environm. 87(2-3): 273-282.
- Gillespie, T.W., J. Chu, E. Frankenberg and D. Thomas. 2007. Assesment and Prediction of Natural Hazards from Satellite Imagery. Prog Phys Geogr. Oc.t; 31(5):459-470. https://doi.org/10.1177/0309133307083296
- Guha. S., H. Govi, A. Dey and N. Gill. 2018. Analytical study of land surface temperature with NDVI and NDBI using Landsat 8 OLI and TIRS data in Florence and Naples city, Italy, EUROPEAN JOURNAL OF REMOTE SENSING. 51 (1):667-678. https://doi.org/10.1080/22797254.2018.1474494
- Ha, I.S. and M.S. Jung. 2018. A Case Study on Liquefaction occurred during the Pohang Earthquak. Earthquake Engineering Society of Korea 15:2.
- Hazen, A. 1920. Hydraulic Fill Dams. Transactions of the American Society of Civil Engineers. 83:1717-1745.
- Hunt, E.D., K.G. Hubbard, D.A. Wilhite, T.J. Arkebauer and A.L. Dutcher. 2009. The development and evaluation of a soil moisture index, Int. J. Climatol. 29:747-759. https://doi.org/10.1002/joc.1749
- Iwasaki, T., F. Tatsuoka, K. Tokida and S. Yasuda. 1978. A Practical Method for Assessing Soil Liquefaction Potential Based on Case Studies at Various site in Japan. 5th Japan Earthquake Engineering Symposium. Vol(2):641-648.
- Iwasaki, T., K. Tokida, F. Tatsuoka, S. Watanabe, S. Yasuda and H. Sato. 1982. Microzonation for soil liquefaction potential using simplified methods. Proceedings 3rd International Conference on Microzonation, Seattle, USA. 1319-1330.
- Jung, M.S., H.S. Kang, S.Y. Park and G.H. Na. 2018. Pohang liquefaction risk assessment, Disaster & Safety. 20(1):14-19.
- Kaufman, Y., C.O. Justice, L.P. Flynn, J.D Kendall, E.M. Prins, L. Giglio, D.E. Ward, W.P. Menzel and A.W. Setzer. 1998. Potential grobal fire monitoring from EOS-MODIS, J. Geophys. Res. 103(D24): 32,215-32, 238. https://doi.org/10.1029/98JD01644
- Kim, J.K., T.Y. Kwak, J.T. Han, B.Y. Hwang and K.S. Kim. 2020. Evaluation of Dynamic Ground Properties of Pohang Area Based on In-situ and Laboratory Test. JOURNAL OF THE KOREAN GEOTECHNICAL SOCIETY. 36(9):5-20. https://doi.org/10.7843/KGS.2020.36.9.5
- Kim, K.S., G.S. MOON and Y.J. CHOUNG. 2020. Analysis on the Changes of Remote Sensing Indices on Each Land Cover Before and After Heavy Rainfall Using Multi-temporal Sentinel-2 Satellite Imagery and Daily Precipitation Data. Journal of the Korean Association of Geographic Information Studies 23(2): 70-82. https://doi.org/10.11108/KAGIS.2020.23.2.070
- Korea Meteorological Administration(KMA). 2017 Earthquake Annual Report. p.214.
- Korea Meteorological Administration(KMA), Open MET Data Portal, Weather Data Service. https://data.kma.go.kr/data/grnd/selectAsosRltmList.do?pgmNo=36. (Accessed January 20, 2021).
- Lee, H., J.K. Kim, K. Ko,Y.S. Ghim, J. Kim and S.R. Lee. 2018. Characteristics of sand volcanoes caused by 2017 Pohang Earthquake-induced liquefaction and their paleoseismological approach. Journal of the Geological Society of Korea 54(3):221-235. https://doi.org/10.14770/jgsk.2018.54.3.221
- National Institute of Meteorological Sciences (NIMS). 2016. Generation of Land Surface Temperature and Analysis of theEffects in Urban Green Areas Using Landsat-8 Satellite Data. Technical Notes, NIMS, Seogui-po, Korea. p.53.
- Saha. A., M. Patil, V.C. Goyal and D.S. Rathore. 2019. Assessment and Impact of Soil Moisture Index in Agricultural Drought Estimation Using Remote Sensing and GIS Techniques, MDPI. 7(1):2.
- Salvia, S., S. Stramondoa, G.J. Funningb, A. Ferrettic, F. Sartid and A. Mouratidisd., 2012. The Sentinel-1 mission 0for the improvement of the scientific understanding and the operational monitoring of the seismic cycle, Remote Sensing of Environment. 120(15):164-174. https://doi.org/10.1016/j.rse.2011.09.029
- SEO M.W., C.G. SUN and M.H. OH. 2009. LPI-based Assessment of Liquefaction Potential on the West Coastal Region of Korea, Journal of the Earthquake Engineering Society of Korea. 13(4):1-13. https://doi.org/10.5000/EESK.2009.13.4.001
- Seed, H.B. and L.M. Idriss. 1971. Simplified Procedure for Evaluating Soil Liquefaction Potential. Journal of the Soil Mechanics and Foundations Division, ASCE. 97(SM9):1249-1273. https://doi.org/10.1061/JSFEAQ.0001662
- United States Geological Survey(USGS). 2015. Landsat 8(L8) Data Users Handbook. https://www.usgs.gov/land-resources/nli/landsat/landsat-8-data-users-handbook. (Accessed January 15, 2021).
- Zeri, Mi., R.C.S. Alvala, R. Carneiro, G. Cunha-Zeri, J.M. Costa, L.R. Spatafora, D. Urbano, M. Vall-Llossera and J. Marengo. 2018. Tools for Communicating Agricultural Drought over the Brazilian Semiarid Using the Soil Moisture Index, Water. 10(10):1421. https://doi.org/10.3390/w10101421