43-6대지.14장동호cok

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1 Mapping of Temperature and Rainfall Using DEM and Multivariate Kriging No-Wook Park* Dong-Ho Jang** DEM DEM Abstract We investigate the potential of digital elevation model and multivariate geostatistical kriging in mapping of temperature and rainfall based on sparse weather station observations. By using elevation data which have reasonable correlation with temperature and rainfall, and are exhaustively sampled in the study area, we try to generate spatial distributions of temperature and rainfall which well reflect topographic effects and have less smoothing effects. To illustrate the applicability of this approach, we carried out a case study of Jeju island using observation data acquired in January, April, August, and October, From the case study results, accounting for elevation via colocated cokriging could reflect detailed topographic characteristics in the study area with less smoothing effects. Colocated cokriging also showed much improved prediction capability, compared to that of traditional univariate ordinary kriging. According to the increase of the magnitude of correlation between temperature or rainfall and elevation, much improved prediction capability could be obtained. The decrease of relative nugget effects also resulted in the improvement of prediction capability. : kriging, digital elevation model, temperature, rainfall (Assistant Professor, Dept. of Geoinformatic Engineering, Inha University), nwpark@inha.ac.kr (Assistant Professor, Dept. of Geography, Kongju National University), gisrs@kongju.ac.kr 1002

2 2007 AWS(Automatic Weather System) 300m 2007 GIS Goovaerts 1997 Creutin et al Hevesi et al Radarsat Glenn and Carr 2003 Daly et al PRISM(Parameter-elevation Regressions on Independent Slopes Model) GIS Ninyerola et al Perry and Konrad 2006 Simbahan et al Goovaerts et al Patriarche et al Park et al IKONOS GIS PRISM

Digital Elevation Model: DEM 1 250 000 DEM ordinary kriging DEM cokriging 1,438

10 1999 15 6 1 4 8 10 3 901-110 6 120 7 10 7 3 11 113 8 125 8 17 4 5 80 115 4

3 Digital Elevation Model: DEM DEM ordinary kriging DEM cokriging 1,438 4mm mm 1 800mm m 2004 DEM m 100m 2005 AWS mm

4 DEM vs. vs Goovaerts n {z(u å ), å=1,, n} 1 h 1 N(h) çˆz(h)= Ç [z(u å ) z(u å h)] 2 1 2N(h) å=1 N(h) h h anisotropy isotropy 1005

5 h z* OK (u) 2 Goovaerts 1997 n(u) z* OK (u)= Ç O å K (u)z(u å ), Ç O å K (u)=1 2 å=1 n(u) O å K (u) universal kriging Deutsch and Journel å=1 Goovaerts 1997 colocated Colocated Goovaerts 1997 Deutsch and Journel 1998 Ma and Journel 1999 n(u) z* CK (u)= Ç C å K (u)z(u å ) CK (u)[y(u) m Y m Z ] 3 å=1 y(u) u m Y m Z 4 1 çˆzy(h)= 2N(h) N(h) Ç å=1 [z(u å ) z(u å h)][y(u å ) y(u å h)]

6 linear model of coregionalization 2 Markov Goovaerts 1997 Markov sill Sill ZY nugget effect Nugget ZY Sill Z Sill Y Nugget Z Nugget Y Goovaerts n MAE= Ç z(u å ) z * (u å ) n å=1 1 RMSE= n n Ç å=1 [z(u å ) zu * (Uu å U)] 2 U (MAE RI MAE = OK MAE CK ) *100 MAE OK (RMSE RI RMSE = OK RMSE CK ) *100 (6) RMSE OK z * (u å ) MAE OK MAE CK RMSE OK RMSE CK Sill ZY ÁSill Z \ Sil l Y Nugget ZY ÁNug get Z \ Nu ggët Ÿ 5 Isaaks and Srivastava Mean Absolute Error: MAE Root Mean Square Error: RMSE Relative Index: RI 19 DEM VARIOWIN Pannatier 1996 GSLIB Deutsch and Journel 1998 Fortran

7 1008

8 2002 (3h) ç(h)=c[1 exp( 2 )] 7 a 2 c a m m 4 71m m mm 8 256mm 1009

9 1010

10 1011

11 130mm 4 33mm 135mm mm OK CK OK CK OK CK OK CK MAE RI MAE RMSE RI RMSE MAE RI MAE RMSE RI RMSE

12 1013

13 5 5 Kyriakidis and Journel C03 CATER GIS PRISM

14 GIS PRISM Creutin, J. D., Delrieu, G., and Lebel, T., 1988, Rain measurement by raingage-radar combination: a geostatistical approach, Journal of Atmospheric and Oceanic Technologies, 5, Daly, C., Helmer, E. H., and Maya, Q., 2003, Mapping the Climate of Puerto Rico, Vieques and Culebra, International Journal of Climatology, 23, Deutsch, C. V. and Journel, A. G., 1998, GSLIB: Geostatistical Software Library and User s Guide, Oxford University Press, Oxford. Glenn, N. F. and Carr, J. R., 2003, The use of geostatistics in relating soil moisture to RADARSAT-1 SAR data obtained over the Gread Basin, Nevada, USA, Computers & Geosciences, 29, Goovaerts, P., 1997, Geostatistics for Natural Resources Evaluation, Oxford University Press, Oxford. Goovaerts, P., AvRuskin, G., Meliker, J., Slotnick, M., Jacquez, G., and Nriagu, J., 2005, Geostatistical modeling of the spatial variability of arsenic in groundwater of southeast Michigan, Water Resources Research, 41, W07013, doi: / 2004WR Hevesi, J. A., Flint, A. L., and Istok, J. D., 1992, Precipitation estimation in mountainous terrain using multivariate geostatistics. Part I: structural analysis, Journal of Applied Meteorology, 31, Isaaks, E. H. and Srivastava, R. M., 1989, An Introduction to Applied Geostatistics, Oxford University Press, Oxford. Kyriakidis, P. C. and Journel, A. G., 1999, Geostatistical space-time models, Mathematical Geology, 31(6), Ma, X. and Journel, A. G., 1999, An expanded GSLIB cokriging program allowing for two Markov models, Computers & Geosciences, 25, Ninyerola, M., Pons, X., and Roure, J. M., 2000, A methodological approach of climatological modelling of air temperature and precipitation through GIS techniques, International Journal of Climatology, 20, Pannatier, Y., 1996, VARIOWIN: Software for Spatial Data Analysis in 2D, Springer-Verlag, New York. Park, N.-W., Jang, D.-H., and Chi, K. H., 2008, Integration of IKONOS imagery for geostatistical mapping of sediment grain size at Baramarae beach, Korea, International Journal of Remote Sensing, in press. Patriarche, D., Castro, M. C., and Goovaerts, P., 2005, Estimating regional hydraulic conductivity fields - a comparative study of geostatistical methods, Mathematical Geology, 37(6), Perry, L. B. and Konrad, C. E., 2006, Relationships between NW flow snowfall and topography in the southern appalachians, USA, Climatology Research, 32, Simbahan, G. C., Dobermann, A., Goovaerts, P., Ping, J., and Haddix, M. L., 2006, Fine-resolution mapping of soil organic carbon based on multivariate secondary data, Geoderma, 132, gisrs@kongju. ac.kr Correspondence: Dong-Ho, Jang, Department of Geography, College of Humanities and Social Sciences, Kongju National University, 182, Shinkwandong, Gongju, Chungnam, , Korea( gisrs@kongju.ac.kr, phone: ) 1015

09구자용(489~500)

09구자용(489~500) The Study on the Grid Size Regarding Spatial Interpolation for Local Climate Maps* Cha Yong Ku** Young Ho Shin*** Jae-Won Lee**** Hee-Soo Kim*****.,...,,,, Abstract : Recent global warming and abnormal