References
- Anderson, M. C., C. M. U. Neale, F. Li, J. M. Norman, W. P. Kustas, H. Jayanthi, and J. Chavez. 2004. Upscaling ground observations of vegetation water content, canopy height, and leaf area index during SMEX02 using aircraft and Landsat imagery. Remote Sensing of Environment, 92: 447-464. https://doi.org/10.1016/j.rse.2004.03.019
- Gebhardt, S., J. Huth, L. D. Nguyen, A. Roth, and C. Kuenzer. 2012. A comparison of Terra SAR‐X Quadpol backscattering with RapidEye multispectral vegetation indices over rice fields in the Mekong Delta, Vietnam. International Journal of Remote Sensing, 33(24): 7644-7661. https://doi.org/10.1080/01431161.2012.702233
- Goudriaan, J. and J.L. Monteith. 1990. A mathematical function for crop growth based on light interception and leaf area expansion. Annals of Botany, 66: 695-701 https://doi.org/10.1093/oxfordjournals.aob.a088084
- Gower, S., C. Kucharik, and J. Norman. 1999. Direct and indirect estimation of leaf area index, fAPAR, and net primary production of terrestrial ecosystems. Remote Sensing of Environment, 70: 29-51. https://doi.org/10.1016/S0034-4257(99)00056-5
- Hatfield, J. L., C. D. Stanley, and R. E. Carlson. 1976. Evaluation of an electronic foliometer to measure leaf area in corn and soybean. Agronomy Journal, 68: 434-436. https://doi.org/10.2134/agronj1976.00021962006800020063x
- Huete, A., and H. Liu. 1994. An error and sensitivity analysis of the atmospheric‐ and soil‐ correcting variants of the NDVI for the MODIS‐EOS. IEEE Transactions on Geoscience and Remote Sensing, 32: 897-905. https://doi.org/10.1109/36.298018
- Justice, C. O. et al. 1985. Analysis of the phenology of global vegetation using meteorological satellite data. International Journal of Remote Sensing, 6: 1271-1318. https://doi.org/10.1080/01431168508948281
- Kim, S. H., S. Y. Hong, A. S. Kenneth, Y. H. Kim, and K. D. Lee. 2012. Comparing LAI estimates of corn and soybean from vegetation indices of multi‐resolution satellite images. Korean Journal of Remote Sensing, 28(6): 597-609. https://doi.org/10.7780/kjrs.2012.28.6.1
- Korea Meteorological Administration Homepage, http://www. kma.go.kr/. Accessed 17 June 2012.
- Lee, J. H., J. Goudriaan, and H. Challa. 2003. Using the expolinear growth equation for modelling crop growth in yearround cut chrysanthemum. Annals of Botany, 92: 697-708. https://doi.org/10.1093/aob/mcg195
- Lee, K. S., S. H. Kim, J. H. Park, T. G. Kim, Y. I. Park, and C. S. Woo. 2006. Estimation of forest LAI in close canopy situation using optical remote sensing data. Korean Journal of Remote Sensing, 22(5): 305-311. https://doi.org/10.7780/kjrs.2006.22.5.305
- Leprieur, C., Y. H. Kerr, S. Mastorchio, and J. C. Meunier. 2000. Monitoring vegetation cover across semi‐arid regions : comparison of remote observations from various scales. International Journal of Remote Sensing, 21: 281-300. https://doi.org/10.1080/014311600210830
- Na, S. I., and J. H. Park. 2008. Regional scale evapotranspiration mapping using Landsat 7 ETM+ land surface temperature and NDVI Space. Journal of the Korean Society of Agricultural Engineers, 50(3): 115-123. https://doi.org/10.5389/KSAE.2008.50.3.115
- Na, S. I., J. H. Park, K. H. Lee, S. J. Kim, and J. W. Lee. 2010. Estimating leaf area index for vegetation indices and its application in paddy. International Symposium on Remote Sensing 2010. Jeju, Korea, October 26-29, 2010
- Park, J. H., and S. I. Na. 2007. MODIS and Landsat TM data image fusion based on improved resolution method: Assessing the quality of resulting NDVI images. Proceeding of SPIE The International Society for Optical Engineering 6742, art. No. 67420S.
- Price, J. C. 1992. Estimating vegetation amount from visible and near infrared reflectances. Remote Sensing of Environment, 41: 29-34. https://doi.org/10.1016/0034-4257(92)90058-R
- Price, J. C., and W. C. Bausch. 1995. Leaf area index estimation from visible and near‐infrared reflectance data, Remote Sensing Environ, 52: 55-65. https://doi.org/10.1016/0034-4257(94)00111-Y
- Qi, J., Y. H. Kerr, M. S. Moran, A. R. Huete, S. Sorooshian, and R. Bryant. 2007. Leaf area index estimates using remotely sensed data and BRDF models in a semiarid region. Remote Sensing Environ, 73: 18-30.
- Qin, J., S. Liang, X. Li. 2008. Development of the adjoint model of a canopy radiative transfer model for sensitivity study and inversion of leaf area index. IEEE Trans Geosci Remote Sens, 46: 2028‐2037. https://doi.org/10.1109/TGRS.2008.916637
- Richter, R. 1996. Atmospheric correction of DAIS hyperspectral image data. Computers & Geosciences, 22: 785-793. https://doi.org/10.1016/0098-3004(96)00016-7
- Shin, S. C., M. H. Hwang, I. H. Ko, and S. J. Lee. 2006. Suggestion of simple method to estimate evapotranspiration using vegetation and temperature information. Journal of Korea Water Resources Association, 39(4): 363-372. https://doi.org/10.3741/JKWRA.2006.39.4.363
- Stenberg, P., M. Rautiainen, T. Manninen, P. Voipio, and H. Smolander. 2004. Reduced simple ratio better than NDVI for estimating LAI in Finnish pine and spruce stands. Silva Fennica, 38(1): 3-14.
- Tyc, G., J. Tulip, D. Schulten, M. Krischke, and M. Oxfort. 2005. The RapidEye mission design. Acta Astronautica, 56: 213219.
- Wang, Q., S. Adiku, J. Tenhunen, and A. Granier. 2005. On the relationship of NDVI with leaf area index in a deciduous forest site. Remote Sensing of Environment, 94: 244-255. https://doi.org/10.1016/j.rse.2004.10.006
- Watson, D. J. 1947. Comparative physiological studies on the growth of field crops: I. Variation in net assimilation rate and leaf area between species and varieties, and with and between years. Annual. Botany, (N.S.), 11: 41-76. https://doi.org/10.1093/oxfordjournals.aob.a083148
Cited by
- Evaluation of the Applicability of Rice Growth Monitoring on Seosan and Pyongyang Region using RADARSAT-2 SAR -By Comparing RapidEye- vol.56, pp.5, 2014, https://doi.org/10.5389/KSAE.2014.56.5.055