1 |
Andersen, R., 2008. Modern methods for robust regression, series: Quantitative applications in the social sciences, Sage University Paper Series on Quantitative Applications in the Social Sciences 07-152. Beverly Hills, CA: Sage, USA.
|
2 |
Back, N., W. Choi, J. Ko, J. Nam, H. Park, J. Choung, S. Kim, and K. Park, 2005. Proper Transplanting Time for Improving the Rice Quality at Reclaimed Saline Land in the Southwestern Area, Korean Journal of Crop Science, 50(spc1): 41-45 (in Korean with English abstract).
|
3 |
Jang, K., S. Kang, and S. Y. Hong, 2014b. Comparisons of Collection 5 and 6 Aqua MODIS07_L2 air and dew temperature products with groundbased observation dataset, Korean Journal of Remote Sensing, 30(5): 571-586 (in Korean with English abstract).
DOI
|
4 |
Jeong, S., K. Jang, S. Hong, and S. Kang, 2011. Detection of irrigation timing and the mapping of paddy cover in Korea using MODIS images data, Korean Journal of Agricultural and Forest Meteorology, 13(2): 69-78 (in Korean with English abstract).
DOI
|
5 |
Joint-relevant authorities, 2011. Report on abnormal climate in 2011, Joint-relevant authorities, Korea.
|
6 |
Jones, C. A., J. R. Kiniry, and P. Dyke, 1986. CERESMaize: A simulation model of maize growth and development, Texas A&M University Press, College Station, USA.
|
7 |
Jones, J. W., G. Hoogenboom, C. H. Porter, K. J. Boote, W. D. Batchelor, L. A. Hunt, P. W. Wilkens, U. Singh, A. J. Gijsman, and J. T. Ritchie, 2003. The DSSAT cropping system model, European Journal of Agronomy, 18(3): 235-265.
DOI
|
8 |
Choi, W., J. Nam, S. Kim, J. Lee, J. Kim, H. Park, N. Back, M. Choi, C. Kim, and K. Jung, 2005. Optimum transplanting date for production quality rice in Honam plain area, Korean Journal of Crop Science, 50(6): 435-441 (in Korean with English abstract).
|
9 |
Becker-Reshef, I., E. Vermote, M. Lindeman, and C. Justice, 2010. A generalized regression-based model for forecasting winter wheat yields in Kansas and Ukraine using MODIS data, Remote Sensing of Environment, 114(6): 1312-1323.
DOI
|
10 |
Bird, R. E. and R. L. Hulstrom, 1981. Simplified clear sky model for direct and diffuse insolation on horizontal surfaces, Solar Energy Research Inst., Golden, USA.
|
11 |
Diepen, C. v., J. Wolf, H. v. Keulen, and C. Rappoldt, 1989. WOFOST: a simulation model of crop production, Soil Use and Management, 5(1): 16-24.
DOI
|
12 |
Do, N., S. Kang, S. Myeong, T. Chun, J. Lee, and C. Lee, 2012. The estimation of gross primary productivity over North Korea using MODIS FPAR and WRF meteorological data, Korean Journal of Remote Sensing, 28(2): 215-226 (in Korean with English abstract).
DOI
|
13 |
Lobell, D. B., M. J. Roberts, W. Schlenker, N. Braun, B. B. Little, R. M. Rejesus, and G. L. Hammer, 2014. Greater sensitivity to drought accompanies maize yield increase in the U.S. Midwest, Science, 344(6183): 516-519.
DOI
|
14 |
Kang, S., Y. Kim, and Y. Kim, 2005. Errors of MODIS product of Gross Primary Production by using Data Assimilation Office Meteorological Data, Korean Journal of Agricultural and Forest meteorology, 7(2): 171-183 (in Korean with English abstract).
|
15 |
Kastens, J. H., T. L. Kastens, D. L. Kastens, K. P. Price, E. A. Martinko, and R. Lee, 2005. Image masking for crop yield forecasting using AVHRR NDVI time series imagery, Remote Sensing of Environment, 99(3): 341-356.
DOI
|
16 |
Kiniry, J. R., B. Bean, Y. Xie, and P. Chen, 2004. Maize yield potential: critical processes and simulation modeling in a high-yielding environment, Agricultural Systems, 82(1): 45-56.
DOI
|
17 |
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(4): 385-396.
DOI
|
18 |
Yao, F., Y. Tang, P. Wang, and J. Zhang, 2015. Estimation of maize yield by using a processbased model and remote sensing data in the Northeast China Plain, Physics and Chemistry of the Earth, Parts A/B/C, 87: 142-152.
|
19 |
Lee, J., S. Kang, K. Jang, J. Ko, and S. Hong, 2011. The evaluation of meteorological inputs retrieved from MODIS for estimation of gross primary productivity in the US corn belt region, Korean Journal of Remote Sensing, 27(4): 481-494 (in Korean with English abstract).
DOI
|
20 |
Lee, J., S. Kang, K. Jang, and S. Y. Hong, 2016. A comparative study for reconstructing a highquality NDVI time series data derived from MODIS surface reflectance, Korean Journal of Remote Sensing, 31(2) (in Korean with English abstract).
DOI
|
21 |
McCree, K. and I. SETLIIK, 1970. An equation for the rate of respiration of white clover grown under controlled conditions, Prediction and measurement of photosynthetic productivity. Proceedings of the IBP/PP Technical Meeting, Trebon, [Czechoslovakia], Center for Agricultural Publishing and Documentation, Wageningen, Netherland.
|
22 |
Mu, Q., F. A. Heinsch, M. Zhao, and S. W. Running, 2007. Development of a global evapotranspiration algorithm based on MODIS and global meteorology data, Remote Sensing of Environment, 111(4): 519-536.
DOI
|
23 |
Fritsch, S., M. Machwitz, A. Ehammer, C. Conrad, and S. Dech, 2012. Validation of the collection 5 MODIS FPAR product in a heterogeneous agricultural landscape in arid Uzbekistan using multitemporal RapidEye imagery, International Journal of Remote Sensing, 33(21): 6818-6837.
DOI
|
24 |
Na, S. I., S. Y. Hong, Y. H. Kim, K. D. Lee, and S. Y. Jang, 2013. Prediction of rice yield in Korea using paddy rice NPP index-Application of MODIS data and CASA model, Korean Journal of Remote Sensing, 29(5): 461-476 (in Korean with English abstract).
DOI
|
25 |
Running, S. and M. Zhao, 2015. User's guide daily GPP and annual NPP (MOD17A2/A3) products NASA earth observing system MODIS land algorithm, Version 3 for Collection, University of Montana, Missoula, USA.
|
26 |
Stockle, C. O., M. Donatelli, and R. Nelson, 2003. CropSyst, a cropping systems simulation model, European Journal of Agronomy, 18(3): 289-307.
DOI
|
27 |
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(2): 192-202.
DOI
|
28 |
Ewert, F., R. P. Rotter, M. Bindi, H. Webber, M. Trnka, K. C. Kersebaum, J. E. Olesen, M. K. van Ittersum, S. Janssen, and M. Rivington, 2015. Crop modelling for integrated assessment of risk to food production from climate change, Environmental Modelling & Software, 72(1): 287-303.
DOI
|
29 |
Hong, S. Y., J. Hur, J. Ahn, J. Lee, B. Min, C. Lee, Y. Kim, K. D. Lee, S. Kim, and G. Y. Kim, 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).
DOI
|
30 |
Jang, K., S. Kang, H. Kim, and H. Kwon, 2009. Evaluation of shortwave irradiance and evapotranspiration derived from Moderate Resolution Imaging Spectroradiometer (MODIS), Asia-Pacific Journal of Atmospheric Sciences, 45(2): 233-246.
|
31 |
Jang, K., S. Kang, J. S. Kimball, and S. Y. Hong, 2014a. Retrievals of all-weather daily air temperature using MODIS and AMSR-E data, Remote Sensing, 6(9): 8387-8404.
DOI
|
32 |
Jang, K., S. Kang, Y. Lim, S. Jeong, J. Kim, J. S. Kimball, and S. Y. Hong, 2013. Monitoring daily evapotranspiration in Northeast Asia using MODIS and a regional Land Data Assimilation System, Journal of Geophysical Research: Atmospheres, 118(23): 12927-12940.
DOI
|