참고문헌
- Ahn, J.B., J.N. Hur, and K.M. Shim, 2010. A Simulation of Agro-Climate Index over the Korean Peninsula Using Dynamical Downscaling with a Numerical Weather Prediction Model, Korean Journal of Agricultural and Forest Meteorology, 12(1): 1-10. https://doi.org/10.5532/KJAFM.2010.12.1.001
- Allen J.D., 1990. A Look at the Remote Sensing Applications Program of the National Agricultural Statistics Service. Journal of Official Statistics, 6(4): 393-409.
- Cressman, G.P., 1959. An operational objective analysis system. Mon. Wea. Rev., 87, 367-374. https://doi.org/10.1175/1520-0493(1959)087<0367:AOOAS>2.0.CO;2
- Doraiswamy, P.C, T.R. Sinclair, S. Hollinger, B. Akhmedov, A. Stern, and J. Prueger, 2005. Application of MODIS derived parameters for regional crop yield assessment, Remote Sensing of Environment, 97: 192-202. https://doi.org/10.1016/j.rse.2005.03.015
- Falcon, W.P., and R.L. Naylor, 2005. Rethinking Food Security for the Twenty-First Century, American Journal of Agricultural Economics, 85(5): 1113-1127.
- Ferencz Cs., P. Bognar, J. Lichtenberger, D. Hamar, G. Tarcsai, G. Timar, G. Molnar, SZ. Pasztor, P. Steinbach, B. Szekely, O.E. Ferencz, and I. FerenczArkos, 2004. Crop Yield Estimation by Satellite Remote Sensing, International Journal of Remote Sensing, 25(20): 4113-4149. https://doi.org/10.1080/01431160410001698870
- Field, C.B., J.T. Randerson, and C.M. Malmstrom, 1995. Global net primary production: Combining ecology and remote sensing, Remote Sensing of Environment, 51: 74-88. https://doi.org/10.1016/0034-4257(94)00066-V
- Hong, J.H., C.S. Shim, M.J. Lee, G.H. Baek, W.K. Song, S.W. Jeon, and Y.H. Park, 2011. Net Primary Production Changes over Korea and Climate Factors, Korean Journal of Remote Sensing, 27(4): 467-480 (in Korean with English abstract). https://doi.org/10.7780/kjrs.2011.27.4.467
- Hong, S.Y., E.Y. Choe, G.Y. Kim, S.K. Kang, Y.H. Kim, and Y.S. Zhang, 2009. A study on Estimating Rice Yield of North Korea using MODIS NDVI, Proc. of 2009 Korea Remote Sensing Symposium, Seoul, Korea, Mar. 25, 116-120.
- Hong, S.Y., J.N. Hur, J.B. Ahn, J.M. Lee, B.K. Min, C.K. Lee, Y.H. Kim, K.D. Lee, S.H. Kim, G.Y. Kim, and K.M. Shim, 2012. Estimating Rice Yield Using MODIS NDVI and Meteorological Data in Korea, Korean Journal of Remote Sensing, 28(5): 509-520 (in Korean with English abstract). https://doi.org/10.7780/kjrs.2012.28.5.4
- Hong, S.Y., J.T. Lee, S.K. Rim, and J.S. Shin, 1997. Radiometric estimates of grain yields related to crop aboveground net production (ANP) in paddy rice, Proc. of 1997 International Geoscience and Remote Sensing Symposium, Singapore, Aug. 3-8, 1793-1795.
- Kim, M.H., C.K. Lee, H.K. Park, J.E. Lee, B.C. Koo, and J.C. Shin, 2008. A Study on Rice Growth and Yield Monitoring Using Medium Resolution Landsat Imagery, Korean Journal Crop Science, 53(4): 388-393.
- Knorr, W., and M. Heimann, 1995. Impact of drought stress and other factors on seasonal land biosphere CO2 exchange studied through an atmospheric tracer transport model, Tellus, 47(4): 471-489. https://doi.org/10.1034/j.1600-0889.47.issue4.7.x
- Lobell, D.B., J.A. Hicke, G.P. Asner, C.B. Field, C.J. Tucker, and S.O. Los, 2002. Satellite estimates of productivity and light use efficiency in United States agriculture, 1982-1998. Global Change Biology, 8: 722-735. https://doi.org/10.1046/j.1365-2486.2002.00503.x
- Monteith, J.L., 1972. Solar radiation and productivity in tropical ecosystems, J. Appl. Ecol., 9: 747-766. https://doi.org/10.2307/2401901
- Na, S.I., J.K. Park, S.C. Baek, and J.H. Park, 2011. A Study on the Key Factors Extraction and Paddy Fields Mapping for the Development of Rice Yield Prediction Model using RS/GIS, Proc. of Annual Conference of Korea Society of Agricultural Engineers, Daegu, Korea, Sep. pp.22-23.
- Na, S.I., J.H. Park, and J.K. Park, 2012. Development of Korean Paddy Rice Yield Prediction Model (KRPM) using Meteorological Element and MODIS NDVI, Journal of the Korean Society of Agricultural Engineers, 54(3): 141-148. https://doi.org/10.5389/KSAE.2012.54.3.141
- Na, S.I., J.K. Park, C.S. Baek, S.Y. Oh, and J.H. Park. 2012. A Study on the Correlation between NDVI and Paddy Rice Yield by Spatial Scale, Proc. of Annual Conference of Korea Society of Agricultural Engineers, Cheonan, Korea, Sep. pp.18-19.
- Nayak, R.K., N.R. Patel, and V.K. Dadhwal, 2010. Estimation and analysis of terrestrial net primary productivity over India by remote-sensing-driven terrestrial biosphere model, Environ. Monit. Assess., 170: 195-213. https://doi.org/10.1007/s10661-009-1226-9
- Ozdogan, M., 2011. Exploring the potential contribution of irrigation to global agricultural primary productivity, Global Biogeochemical Cycles, 25(3): GB3016.
- Potter, C., S. Klooster, R. Myneni, and V. Genovese, 2004. Terrestrial Carbon Sinks Predicted from MODIS Satellite Data and Ecosystem Modeling, Earth Observer, 16(2): 15-20.
- Prince, S.D., and S.N. Goward, 1995. Global primary production: A remote sensing approach, Journal of Biogeography, 22: 815-835. https://doi.org/10.2307/2845983
- Raich, J.W., E.B. Rastetter, J.M. Melillo, D.W. Kicklighter, P.A. Steudler, B.J. Peterson, A. Grace , B. Moore, and C.J. Vorosmarty, 1991. Potential net primary productivity in South- America-application of a global-model, Ecological Applications, 1: 399-429. https://doi.org/10.2307/1941899
- Ren J.Q., Z.X. Chen, Q.B. Zhou, and H.J. Tang, 2008. Regional Yield Estimation for Winter Wheat with MODIS-NDVI Data in Shandong, China, International Journal of Applied Earth Observation and Geoinformation, 10: 403-413 https://doi.org/10.1016/j.jag.2007.11.003
- Ruimy, A., G. Dedieu, and B. Saugier, 1996. TURC: A diagnostic model of continental gross primary productivity and net primary productivity, Global Biogeochemical Cycles, 10(2): 269-285. https://doi.org/10.1029/96GB00349
- Running, S.W., R.R. Nemani, F.A. Heinsch, M.S. Zhao, M. Reeves, and H. Hashimoto, 2004. A continuous satellite-derived measure of global terrestrial primary production, Bioscience, 54(6): 547-560. https://doi.org/10.1641/0006-3568(2004)054[0547:ACSMOG]2.0.CO;2
- Tao, F., M. Yokozawa, Z. Zhang, Y. Xu, and Y. Hayashi, 2005. Remote sensing of crop production in China by production efficiency models: models comparisons, estimates and uncertainties, Ecological Modelling, 183: 385-396. https://doi.org/10.1016/j.ecolmodel.2004.08.023
- Veroustraete, F., 1994. On the use of a simple deciduous forest model for the interpretation of climate change effects at the level of carbon dynamics, Ecological Modelling, 75(76): 221-237.
- Wang, L., G. Hong, Z. Caiping, Z. Haitao, L. Chao, and Z. Qilin, 2008. Vegetation NPP distribution based on MODIS data and CASA model-A case study in Haihe River basin, China, Proc. of SPIE, Vol. 6625.
- Xiao, X.M., S. Boles, J.Y. Liu, D.F. Zhuang, and M.L. Liu, 2002. Characterization of forest types in Northeastern China, using multitemporal SPOT- 4 VEGETATION sensor data, Remote Sensing of Environment, 82: 335-348. https://doi.org/10.1016/S0034-4257(02)00051-2
- Xiao, X.M., D. Hollinger, J.D. Aber, M. Goltz, E.A. Davidson, and Q.Y. Zhang, 2004. Satellite-based modeling of gross primary production in an evergreen needleleaf forest, Remote Sensing of Environment, 89: 519-534. https://doi.org/10.1016/j.rse.2003.11.008
- Xiao, X., Q. Zh, S. Salesk, L. Hutyra, P.D. Camargo, S. Wofsy, S. Frolking, S. Boles, M. Keller, and B. Moore, 2005. Satellite-based modeling of gross primary production in a seasonally moist tropical evergreen forest, Remote Sensing of Environment, 94: 105-122. https://doi.org/10.1016/j.rse.2004.08.015
- Zhao, M., F.A. Heinsch, R.R. Nemani, and S.W. Running, 2005. Improvements of the MODIS terrestrial gross and net primary production global data set, Remote Sensing of Environment, 95: 164-176. https://doi.org/10.1016/j.rse.2004.12.011
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