References
- 국립산림과학원. 2009. 제5차 국가산림자원조사, 현지조사 매뉴얼. 54쪽.
- 김기영, 전명식, 강현철, 이성건 공역. 2009. 예제를 통한 회귀분석, 제4판. 자유아카데미. 393쪽.
- 단양군. 2009. 통계연보(제2장 토지 및 기후).
- 단양군. 2010. 단양군 산림정밀지도 제작 및 활용시스템 통합 완료보고서. 154쪽.
- 손영모, 이경학, 김래현. 2007. 우리나라 산림바이오매스 추정. 한국임학회지 96(4):477-482.
- 이승호, 김철민, 원현규, 김경민, 조현국. 2004. Landsat TM 위성영상을 이용한 산림자원량 산정. 한국임학회 2004 학술연구 발표논문집 제1권. 250-252쪽.
- 임종수, 공지수, 김성호, 신만용. 2007. kNN 기법을 이용한 강원도 평창군의 산림주제도 작성과 산림통계량 추정. 한국임학회지 96(3):259-268.
- 임종수, 한원성, 황주호, 정상영, 조현국, 신만용. 2009. 위성영상자료 및 국가 산림자원조사 자료를 이용한 산림 바이오매스 추정, 대한원격탐사학회지 25(4):311-320. https://doi.org/10.7780/kjrs.2009.25.4.311
- 장안진, 김형태. 2008. 항공사진과 Lidar 데이터를 이용한 산림지역의 바이오매스 추정에 관한 연구. 한국지리정보학회지 11(3):166-173.
- 정상영, 임종수, 조현국, 정진현, 김성호, 신만용. 2009. 산림 바이오매스 변환표와 위성영상을 이용한 무주군의 산림 바이오매스추정. 한국임학회지 98(4):409-417.
- 최종근. 2007. 지구통계학. 시그마프레스. 199쪽.
- Ahmed, S., G. de Marsily. 1987. Comparison of geostatistical methods for estimating transmissivity using data on transmissivity and specific capacity. Water Resources Research 23(9):1717-1737. https://doi.org/10.1029/WR023i009p01717
- Bailey, T.C. and A.C. Gatrell. 1996. Interactive Spatial Data Analysis. Prentice Hall, London, UK. 432pp.
- Cressie, N. 1993. Statistics for Spatial Data. John Wiley & Sons, NY, USA. 416pp.
- Goovaerts, P. 1997. Geostatistics for Natural Resources Evaluation(Applied Geostatistics). Oxford University Press, NY, USA. 496pp.
- Hengl, T. 2009. A Practical Guide to Geostatistical Mapping(2nd). University of Amsterdam, Netherlands. 291pp.
- Hengl, T., G. Heuvelink and A. Stein. 2004. A generic framework for spatial prediction of soil variables based on regression kriging. Geoderma, 122(1-2):75-93.
- Hengl, T., G. Heuvelink and D. Rossiter. 2007. About regression-kriging: From equations to case studies. Computers & Geosciences 33:1301-1315. https://doi.org/10.1016/j.cageo.2007.05.001
- Hosseini, S., S. Khajeddin and H. Azarnivand. 2004. Application of ETM+ data for estimating rangelands cover percentage. 20th ISPRS Congress Youth Forum. Istanbul, Turkey, July 12-23, 2004, pp.198-201.
- Isaaks, E. and R. Srivastava. 1989. An Introduction to Applied Geostatistics. Oxford University Press, NY, USA. 542pp.
- Lu, D. 2006. The potential and challenge of remote sensing based biomass estimation, International Journal of Remote Sensing 27:1297-1328. https://doi.org/10.1080/01431160500486732
- Meng, Q., C. Cieszewski and M. Madden. 2009. Large area forest inventory using Landsat ETM+: a geostatistical approach. ISPRS Journal of Photogrammetry and Remote Sensing 64(1):27-36. https://doi.org/10.1016/j.isprsjprs.2008.06.006
- Odeh, I., A. McBratney and D. Chittleborough. 1994. Spatial prediction of soil properties from landform attributes derived from a digital elevation model. Geoderma 63(3-4):197-214. https://doi.org/10.1016/0016-7061(94)90063-9
- Odeh, I., A. McBratney and D. Chittleborough. 1995. Further results on prediction of soil properties from terrain attributes: heterotopic cokriging and regression-kriging. Geoderma 67(3 -4):215-226. https://doi.org/10.1016/0016-7061(95)00007-B
- Rahman, M., E. Csaplivics. and B. Koch. 2008. Satellite estimation of forest carbon using regression model. International Journal of Remote Sensing 29(23):6917-6936. https://doi.org/10.1080/01431160802144187
- Sales, M., C. Souza Jr, P. Kyriakidis, D. Roberts and E. Vidal. 2007. Improving spatial distribution estimation of forest biomass with geostatistics: a case study for Rondonia, Brazil. Ecological Modelling 205(1-2):221-230. https://doi.org/10.1016/j.ecolmodel.2007.02.033
- Sappington, J.M., K.M. Longshore and D.B. Thomson. 2007. Quantifiying landscape ruggedness for animal habitat anaysis: a case study using bighorn sheep in the Mojave desert, Journal of Wildlife Management 71(5):1419-1426. https://doi.org/10.2193/2005-723
- Sorensen, R., U. Zinko and J. Seibert. 2006. On the calculation of the topographic wetness index: evaluation of different methods based on field observations. Hydrology and Earth System Sciences Discussions 10:101-112. https://doi.org/10.5194/hess-10-101-2006
- Webster, R. and M.A. Oliver. 2007. Geostatistics for Environmental Scientists, Statistics in Practice(2nd). John Wiley & Sons, Chichester, England. 330pp.
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