참고문헌
- Arkin, G. F., C. L. Wiegand, and H. Huddleston. 1977. The future role of a crop model in large area yield estimation. In Proceedings of the Crop Modeling Workshop, PP. 87-116. USDA-NOAA-EDIS-CEAS, Columbia, MO
- Baez-Gonzalez, A. D., P. Chen, M. Tiscareno-Lopez, and R. Srinivasan. 2002. Using satellite and field data with crop growth modeling to monitor and estimate corn yield in Mexico. Crop Sci. 42 : 1943-1949 https://doi.org/10.2135/cropsci2002.1943
- Barns, M. B. P. J. Pinter Jr., B. A. Kimball, G. W. Wall, R. L. LaMorte, D. J. Husaker, F. Adamsen, S. Leavitt, T. Thompson, and J. Mathius. 1997. Modification of CERES-Wheat to accept leaf area index as an input variable. The 1997 ASAE Annual International Meeting Sponsored by ASAE, Minneapolis, Minnesota, August 10-14. ASABE, St. Joseph, MI
- Bronson, K. F., J. W. Keeling, J. D. Booker, T. T. Chua, T. A. Wheeler, R. K. Boman, and R. J. Lascano. 2003. Influence of landscape position, soil series, and phosphorus fertilizer on cotton lint yield. Agron. J. 95 : 947-957
- Charles-Edwards, D. A., D. Doley, and G. M. Rimmington. 1986. Modeling plant and development. Academic Press, Orlando, FL
- Chiarello, N. R. and S. L. Gulmon. 1991. Stress effects on plant reproduction. In: Mooney H. A., Winner W. E., Pell E. J., Chu E, Eds. Response of plants to multiple stresses. New York: Academic Press, 161-168
- Constable, G. C. and A. B. Hearn. 1981. Irrigation of crops in a subhumid environment. VI. Effect of irrigation and nitrogen fertilizer on growth, yield, and quality of cotton. Irrigation Science 3 : 17-28
- Conte, S. D. and D. de Boor. 1965. Elementary numerical analysis: An algorithmic approach. McGraw-Hill, New York
- Guo, W. 2005. Spatial and temporal variability in cotton yield in relation to soil apparent electrical conductivity, topography, and remote sensing imagery. Ph. D. diss. Texas Tech Univ., Lubbock
- Howell, T. A., K. R. Davis, R. L. McCormick, H. Yamada, V. T. Walhood, and D. W. Meek. 1984. Water use efficiency in narrow row cotton. Irr. Sci. 5 : 195-214
- Jackson, B. S., G. F. Arkin, and A. B. Hearn. 1988. The cotton simulation model 'COTTAM': fruiting model calibration and testing. Trans. of the ASAE. 31(3) : 846-854 https://doi.org/10.13031/2013.30790
- Jackson, B. S., G. F. Arkin, and A. B. Hearn. 1990. COTTAM: a cotton plant simulation model for an IBM PC microcomputer. College Station, Texas, The Texas Agricultural Experiment Station, The Texas A&M University System: 241p
- Jones, C. A. and J. R. Kiniry. 1986. CERES-MAIZE: A simulation model of maize growth and development. Texas A&M University Press. College Station, TX
-
Kimball, B. A. and J. R. Mauney. 1993. Response of cotton to varying
$CO_{2}$ , irrigation, and nitrogen: yield and growth. Agron. J. 85 : 700-706 - Ko, J., S. J. Maas, R. J. Lascano, and D. Wanjura. 2005. Modification of the GRAMI model for cotton. Agron. J. 97: 1374-1379 https://doi.org/10.2134/agronj2004.0267
- Ko, J., S. J. Maas, S. Mauget, G. Piccinni, and D. Wanjura. 2006. Modeling water-stressed cotton growth using within-season remote sensing data. Agron. J. 98 : 1600-1609 https://doi.org/10.2134/agronj2005.0284
- Li, H., R. J. Lascano, E. M. Barnes, J. Booker, L. T. Wilson, K. F. Bronson, and E. Segarra. 2001. Multispectral reflectance of cotton related to plant growth, soil water and texture, and site elevation. Agron. J. 93 : 1327-1337 https://doi.org/10.2134/agronj2001.1327
- Maas, S. J. 1998. Estimating cotton ground cover from remotely sensed scene reflectance. Agron. J. 90 : 384-388 https://doi.org/10.2134/agronj1998.00021962009000030011x
- Maas, S. J. 1992. GRAMI: a crop growth model that can use remotely sensed information. USDA, ARS-91, 77p
- Maas, S. J. 1993a. Parameterized model of gramineous crop growth: I. Leaf area and dry mass simulation. Agron. J. 85 : 348-353 https://doi.org/10.2134/agronj1993.00021962008500020034x
- Maas, S. J. 1993b. Parameterized model of gramineous crop growth: II. Within-season simulation calibration. Agron. J. 85 : 354-358 https://doi.org/10.2134/agronj1993.00021962008500020035x
- Maas, S. J. 1993c. Within-season calibration of modeled wheat growth using remote sensing and field sampling. Agron. J. 85 : 669-672 https://doi.org/10.2134/agronj1993.00021962008500030028x
- Maas, S. J. 2000. Linear mixture modeling approach for estimating cotton canopy ground cover using satellite multi-spectral imagery. Remote sensing. Environ. 73 : 304-308
- Maas, S. J. and P. C. Doraiswamy. 1996. Integration of satellite data and model simulation in a GIS for monitoring regional evaporation and biomass production. Proceedings of 3rd International Conference on Integrating GIS and Environmental Modeling, Santa Fe, NM, Jan. 21-26, 2006, CD-ROM. The National Center for Geographic Information and Analysis, Santa Barbara, CA
- Maas, S. J. and G. F. Arkin. 1978. User's guide to SORGF: A dynamic grain sorghum growth model with feedback capacity. Research Center Program and Model Documentation No. 78-1, Texas Agricultural Experiment Station. College Station, TX
- Monteith, J. L. and M. H. Unsworth. 1990. Principles of environmental physics, second edition. Edward Arnold. New York. 291p
- Moran, M. S, S. J. Maas, and P. J. Pinter, Jr. 1995. Combining remote sensing and modeling for estimating surface evaporation and biomass production. Remote Sensing Reviews 12 : 335-353 https://doi.org/10.1080/02757259509532290
- Orgaz, F., L. Mateos, and E. Fereres. 1992. Season length and cultivar determine the optimum evapotranspiration deficit in cotton. Agron. J. 84 : 700-706 https://doi.org/10.2134/agronj1992.00021962008400040031x
- Press, W. H., B. P. Flannery, S. A. Teukolsky, and W. T. Vetterling. 1992. Numerical recipes in Fortran: The art of scientific computing, second edition. Cambridge Univ. Press, New York
- Rajapakse, S. S. 2005. Automated radiometric normalization techniques for multi-temporal Landsat-TM and ETM+ imagery. Dissertation, Texas Tech University
- Reddy, V. R., B. Acock, D. N. Baker, and M. Acock. 1989. Seasonal leaf area - leaf weight relationships in the cotton canopy. Agron. J. 81 : 1-4 https://doi.org/10.2134/agronj1989.00021962008100010001x
- Rhoads, F. M. and M. E. Bloodworth. 1964. Area measurement of cotton leaves by dry-weight method. Agon. J. 56 : 520-522
- Richardson, A. J. and C. L. Wiegand. 1977. Distinguishing vegetation from soil background information. Photogrammetric Engineering and Remote Sensing 43 : 1541-1552
- Ritchie, J. T. and S. Otter. 1985. Description and performance of CERES-Wheat: A User-oriented wheat yield model. P. 159-175. In ARS Wheat Yield Project. ARS-38. National Technology Information Service, Springfield, VA
- Rosenthal, W. D., R. L. Vanderlip, B. S. Jackson, and G. F. Arkin. 1989. SORKAM: A grain sorghum crop model. Texas Agric. Exp. Stn. Miscellaneous Publication MP-1669
- Sanders, V. O., M. P. Bange, and S. P. Milroy. 1997. Reproductive allocation of cotton in response to plant environmental factors. Annuals of Botany. 80 : 75-81 https://doi.org/10.1006/anbo.1997.0402
- Wanjura, D. F. and J. R. Supak. 1985. Temperature methods for monitoring cotton development. Beltwide Cotton Conferences. pp. 369-372
- Wanjura, D. F., D. R. Upchurch, and S. J. Maas. 2004. Spectral reflectance estimates of cotton biomass and yield. Beltwide Cotton Conference, pp. 838-851
- Wilkerson, G. G., J. W. Jones, K. J. Boot, and J. W. Mishoe. 1985. SOYGRO V5.0: Soybean crop growth and yield model. Technical Documentation, Univ. Florida, Gainesville, FL