{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,8]],"date-time":"2026-01-08T09:14:46Z","timestamp":1767863686794,"version":"3.49.0"},"reference-count":57,"publisher":"MDPI AG","issue":"18","license":[{"start":{"date-parts":[[2019,9,13]],"date-time":"2019-09-13T00:00:00Z","timestamp":1568332800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100003725","name":"National Research Foundation of Korea","doi-asserted-by":"publisher","award":["NRF-2015R1D1A1A01057586"],"award-info":[{"award-number":["NRF-2015R1D1A1A01057586"]}],"id":[{"id":"10.13039\/501100003725","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Remote sensing is a useful technique to determine spatial variations in crop growth while crop modelling can reproduce temporal changes in crop growth. In this study, we formulated a hybrid system of remote sensing and crop modelling based on a random-effect model and the empirical Bayesian approach for parameter estimation. Moreover, the relationship between the reflectance and the leaf area index was incorporated into the statistical model. Plant growth and ground-based canopy reflectance data of paddy rice were measured at three study sites in South Korea. Spatiotemporal vegetation indices were processed using remotely-sensed data from the RapidEye satellite and the Communication Ocean and Meteorological Satellite (COMS). Solar insulation data were obtained from the Meteorological Imager (MI) sensor of the COMS. Reanalysis of air temperature data was collected from the Korea Local Analysis and Prediction System (KLAPS). We report on a statistical hybrid approach of crop modelling and remote sensing and a method to project spatiotemporal crop growth information. Our study results show that the crop growth values predicted using the hybrid scheme were in statistically acceptable agreement with the corresponding measurements. Simulated yields were not significantly different from the measured yields at p = 0.883 in calibration and p = 0.839 in validation, according to two-sample t tests. In a geospatial simulation of yield, no significant difference was found between the simulated and observed mean value at p = 0.392 based on a two-sample t test as well. The fabricated approach allows us to monitor crop growth information and estimate crop-modelling processes using remote sensing data from various platforms and optical sensors with different ground resolutions.<\/jats:p>","DOI":"10.3390\/rs11182131","type":"journal-article","created":{"date-parts":[[2019,9,13]],"date-time":"2019-09-13T10:32:41Z","timestamp":1568370761000},"page":"2131","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":27,"title":["Mathematical Integration of Remotely-Sensed Information into a Crop Modelling Process for Mapping Crop Productivity"],"prefix":"10.3390","volume":"11","author":[{"given":"Van Cuong","family":"Nguyen","sequence":"first","affiliation":[{"name":"Department of Statistics, Chonnam National University, Gwangju 61186, Korea"}]},{"given":"Seungtaek","family":"Jeong","sequence":"additional","affiliation":[{"name":"Applied Plant Science, Chonnam National University, Gwangju 61186, Korea"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7974-3808","authenticated-orcid":false,"given":"Jonghan","family":"Ko","sequence":"additional","affiliation":[{"name":"Applied Plant Science, Chonnam National University, Gwangju 61186, Korea"}]},{"given":"Chi Tim","family":"Ng","sequence":"additional","affiliation":[{"name":"Department of Statistics, Chonnam National University, Gwangju 61186, Korea"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2321-731X","authenticated-orcid":false,"given":"Jongmin","family":"Yeom","sequence":"additional","affiliation":[{"name":"Satellite Information Center, Korea Aerospace Research Institute, 169-84 Gwahak-ro, Yuseong-gu, Daejeon 34133, Korea"}]}],"member":"1968","published-online":{"date-parts":[[2019,9,13]]},"reference":[{"key":"ref_1","unstructured":"Jones, H.G., and Vaughan, R.A. (2010). Remote Sensing of Vegetation: Principles, Techniques, and Applications, Oxford University Press."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"669","DOI":"10.2134\/agronj1993.00021962008500030028x","article-title":"Within-season calibration of modeled wheat growth using remote sensing and field sampling","volume":"85","author":"Maas","year":"1993","journal-title":"Agron. J."},{"key":"ref_3","unstructured":"Maas, S.J. (1992). GRAMI: A Crop Model Growth Model that Can Use Remotely Sensed Information, USDA-ARS."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"303","DOI":"10.13031\/2013.35293","article-title":"A model for calculating light interception by a grain sorghum canopy","volume":"21","author":"Arkin","year":"1978","journal-title":"Trans. ASAE"},{"key":"ref_5","unstructured":"Maas, S.J., and Arkin, G.F. (1978). User\u2019s Guide to SORGF: A Dynamic Grain SORGHUM Growth Model with Feedback Capacity, TAES Program and Model Documentation, Blackland Research Center. No. 78-1."},{"key":"ref_6","unstructured":"Rosenthal, W.D., Vanderlip, R.L., Jackson, B.S., and Arkin, G.F. (1989). SORKAM: A Grain Sorghum Crop Growth Model, The Texas agricultural experimental station."},{"key":"ref_7","unstructured":"Barnes, E.M., Paul, J., Pinter, J., Kimball, B.A., Wall, G.W., LaMorte, R.L., Husaker, D.J., Adamsen, F., Leavitt, S., and Thompson, T. (1997, January 14). Modification of CERES-wheat to accept leaf area index as an input variable. Proceedings of the ASAE Annual International Meeting, Minneapolis, MN, USA."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"235","DOI":"10.1016\/S1161-0301(02)00107-7","article-title":"The DSSAT cropping system model","volume":"18","author":"Jones","year":"2003","journal-title":"Eur. J. Agron."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"16","DOI":"10.1111\/j.1475-2743.1989.tb00755.x","article-title":"Wofost: A simulation model of crop production","volume":"5","author":"Wolf","year":"1989","journal-title":"Soil Use Manag."},{"key":"ref_10","unstructured":"Spitters, C., Van Keulen, H., and Van Kraalingen, D. (1989). A simple and universal crop growth simulator: SUCROS87. Simulation and Systems Management in Crop Protection, Pudoc."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"188","DOI":"10.1016\/j.agrformet.2015.10.013","article-title":"Assimilating a synthetic Kalman filter leaf area index series into the WOFOST model to improve regional winter wheat yield estimation","volume":"216","author":"Huang","year":"2016","journal-title":"Agric. For. Meteorol."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"30","DOI":"10.1016\/j.ecolmodel.2013.08.016","article-title":"Assimilating remote sensing information with crop model using Ensemble Kalman Filter for improving LAI monitoring and yield estimation","volume":"270","author":"Zhao","year":"2013","journal-title":"Ecol. Model."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"321","DOI":"10.1016\/j.agee.2005.06.005","article-title":"Assimilating remote sensing data into a crop model to improve predictive performance for spatial applications","volume":"111","author":"Launay","year":"2005","journal-title":"Agric. Ecosyst. Environ."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"354","DOI":"10.2134\/agronj1993.00021962008500020035x","article-title":"Parameterized model of gramineous crop growth: II. within-season simulation calibration","volume":"85","author":"Maas","year":"1993","journal-title":"Agron. J."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"348","DOI":"10.2134\/agronj1993.00021962008500020034x","article-title":"Parameterized model of gramineous crop growth: I. leaf area and dry mass simulation","volume":"85","author":"Maas","year":"1993","journal-title":"Agron. J."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"6","DOI":"10.2134\/agronj2004.0267","article-title":"Modification of the GRAMI model for cotton","volume":"97","author":"Ko","year":"2005","journal-title":"Agron. J."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"1600","DOI":"10.2134\/agronj2005.0284","article-title":"Modeling water-stressed cotton growth using within-season remote sensing data","volume":"98","author":"Ko","year":"2006","journal-title":"Agron. J."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"096067","DOI":"10.1117\/1.JRS.9.096067","article-title":"Simulation and mapping of rice growth and yield based on remote sensing","volume":"9","author":"Ko","year":"2015","journal-title":"J. Appl. Remote Sens."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"548","DOI":"10.1016\/j.rse.2004.05.017","article-title":"Crop condition and yield simulations using Landsat and MODIS","volume":"92","author":"Doraiswamy","year":"2004","journal-title":"Remote Sens. Environ."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"192","DOI":"10.1016\/j.rse.2005.03.015","article-title":"Application of MODIS derived parameters for regional crop yield assessment","volume":"97","author":"Doraiswamy","year":"2005","journal-title":"Remote Sens. Environ."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"534","DOI":"10.1080\/15481603.2017.1291783","article-title":"Monitoring canopy growth and grain yield of paddy rice in South Korea by using the GRAMI model and high spatial resolution imagery","volume":"54","author":"Kim","year":"2017","journal-title":"Giscience Remote Sens."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"145","DOI":"10.1016\/j.fcr.2012.02.025","article-title":"Monitoring regional wheat yield in Southern Spain using the GRAMI model and satellite imagery","volume":"130","author":"Padilla","year":"2012","journal-title":"Field Crop. Res."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.compag.2015.08.017","article-title":"Application of GOCI-derived vegetation index profiles to estimation of paddy rice yield using the GRAMI rice model","volume":"118","author":"Yeom","year":"2015","journal-title":"Comput. Electron. Agric."},{"key":"ref_24","unstructured":"Maas, S.J., and Doraiswamy, P.C. (1996, January 21\u201325). Integration of satellite data and model simulations in a GIS for monitoring regional evaporation and biomass production. Proceedings of the 3rd International Conference on Integrating GIS and Environmental Modeling, Santa Fe, NM, USA."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"335","DOI":"10.1080\/02757259509532290","article-title":"Combining remote sensing and modeling for estimating surface evaporation and biomass production","volume":"12","author":"Moran","year":"1995","journal-title":"Remote Sens. Rev."},{"key":"ref_26","unstructured":"James, W., and Stein, C. (July, January 20). Estimation with quadratic loss. Proceedings of the 4th Berkeley Symposium Mathematical Statistics and Probability, Statistical Laboratory of the University of California, Berkeley, CA, USA."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"311","DOI":"10.1080\/01621459.1975.10479864","article-title":"Data analysis using Stein\u2019s estimator and its generalizations","volume":"70","author":"Efron","year":"1975","journal-title":"J. Am. Stat. Assoc."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"119","DOI":"10.1038\/scientificamerican0577-119","article-title":"Stein\u2019s paradox in statistics","volume":"236","author":"Efron","year":"1977","journal-title":"Sci. Am."},{"key":"ref_29","unstructured":"(2019, September 03). Korea Meteorological Administration (KMA). Available online: www.kma.go.kr."},{"key":"ref_30","unstructured":"Rouse, J.W., Haas, R.H., Schell, J.A., and Deering, D.W. (1974, January 1). Monitoring vegetation systems in the Great Plains with ERTS. Proceedings of the NASA. Goddard Space Flight Center 3d ERTS-1 Symposium, Texas A&M Univ., College Station, TX, USA."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"375","DOI":"10.1016\/0034-4257(94)00114-3","article-title":"Estimating PAR absorbed by vegetation from bidirectional reflectance measurements","volume":"51","author":"Roujean","year":"1995","journal-title":"Remote Sens. Environ."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"95","DOI":"10.1016\/0034-4257(95)00186-7","article-title":"Optimization of soil-adjusted vegetation indices","volume":"55","author":"Rondeaux","year":"1996","journal-title":"Remote Sens. Environ."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"337","DOI":"10.1016\/j.rse.2003.12.013","article-title":"Hyperspectral vegetation indices and novel algorithms for predicting green LAI of crop canopies: Modeling and validation in the context of precision agriculture","volume":"90","author":"Haboudane","year":"2004","journal-title":"Remote Sens. Environ."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"348","DOI":"10.1016\/S0034-4257(98)00095-9","article-title":"A Sensitivity Study of the SeaWiFS Atmospheric Correction Algorithm: Effects of Spectral Band Variations","volume":"67","author":"Wang","year":"1999","journal-title":"Remote Sens. Environ."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"213","DOI":"10.1016\/j.actaastro.2004.09.029","article-title":"The RapidEye mission design","volume":"56","author":"Tyc","year":"2005","journal-title":"Acta Astronaut."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"607","DOI":"10.1002\/joc.3370130603","article-title":"The development of a satellite-based insolation model for the tropical western Pacific Ocean","volume":"13","author":"Nunez","year":"1993","journal-title":"Int. J. Climatol."},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"460","DOI":"10.1175\/JHM440.1","article-title":"Validation of GOES-Based Insolation Estimates Using Data from the U.S. Climate Reference Network","volume":"6","author":"Otkin","year":"2005","journal-title":"J. Hydrometeorol."},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"194","DOI":"10.1175\/1520-0450(1992)031<0194:MSSIFS>2.0.CO;2","article-title":"Modeling surface solar irradiance for satellite applications on a global scale","volume":"31","author":"Pinker","year":"1992","journal-title":"J. Appl. Meteorol."},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"457","DOI":"10.1007\/BF02742448","article-title":"Estimation of insolation over the Pacific Ocean off the Sanriku coast","volume":"54","author":"Kawamura","year":"1998","journal-title":"J. Oceanogr."},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"115","DOI":"10.1007\/s13143-012-0011-9","article-title":"Evaluation on penetration rate of cloud for incoming solar radiation using geostationary satellite data","volume":"48","author":"Yeom","year":"2012","journal-title":"Asia Pac. J. Atmos. Sci."},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"79","DOI":"10.1007\/s10872-005-0021-7","article-title":"Validation and Improvement of Satellite-Derived Surface Solar Radiation over the Northwestern Pacific Ocean","volume":"61","author":"Kawai","year":"2005","journal-title":"J. Oceanogr."},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"412","DOI":"10.1016\/S0034-4257(00)00183-8","article-title":"A system to distribute satellite incident solar radiation in real-time","volume":"75","author":"Tanahashi","year":"2001","journal-title":"Remote Sens. Environ."},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1155\/2016\/4834579","article-title":"Solar Radiation Received by Slopes Using COMS Imagery, a Physically Based Radiation Model, and GLOBE","volume":"2016","author":"Yeom","year":"2016","journal-title":"J. Sens."},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"118","DOI":"10.1175\/1520-0469(1974)031<0118:APFTAO>2.0.CO;2","article-title":"A Parameterization for the Absorption of Solar Radiation in the Earth\u2019s Atmosphere","volume":"31","author":"Lacis","year":"1974","journal-title":"J. Atmos. Sci."},{"key":"ref_45","unstructured":"Kizu, S. (1995). A Study on Thermal Response of Ocean Surface Layer to Solar Radiation Using Satellite Sensing, Tohoku University."},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"9731","DOI":"10.1029\/JC094iC07p09731","article-title":"A simple analytical formula to compute clear sky total and photosynthetically available solar irradiance at the ocean surface","volume":"94","author":"Frouin","year":"1989","journal-title":"J. Geophys. Res. Ocean."},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"19","DOI":"10.1007\/BF02317950","article-title":"Absorption of solar radiation by atmospheric aerosol, as revealed by measurements at the ground","volume":"12","author":"Robinson","year":"1962","journal-title":"Arch. F\u00fcr Meteorol. Geophys. Und Bioklimatol. Ser. B"},{"key":"ref_48","doi-asserted-by":"crossref","first-page":"209","DOI":"10.1007\/BF00151291","article-title":"Solar radiation and its variation in time","volume":"74","author":"Brusa","year":"1981","journal-title":"Sol. Phys."},{"key":"ref_49","first-page":"1","article-title":"Realtime operation of the Korea Local Analysis and prediction system at METRI","volume":"38","author":"Kim","year":"2002","journal-title":"Asia Pac. J. Atmos. Sci."},{"key":"ref_50","doi-asserted-by":"crossref","first-page":"273","DOI":"10.1175\/1520-0434(1996)011<0273:TLAAPS>2.0.CO;2","article-title":"The Local Analysis and Prediction System (LAPS): Analyses of Clouds, Precipitation, and Temperature","volume":"11","author":"Albers","year":"1996","journal-title":"Weather Forecast."},{"key":"ref_51","unstructured":"Press, W.H., Teukolsky, S.A., Vetterling, W.T., and Flannery, B.P. (1992). Numerical Recipes: The Art of Scientific Computing, Cambridge University Press."},{"key":"ref_52","unstructured":"Nash, J.C. (1990). Compact Numerical Methods for Computers: Linear Algebra and Function Minimisation, Adam Hilger."},{"key":"ref_53","doi-asserted-by":"crossref","first-page":"282","DOI":"10.1016\/0022-1694(70)90255-6","article-title":"River flow forecasting through conceptual models part I\u2014A discussion of principles","volume":"10","author":"Nash","year":"1970","journal-title":"J. Hydrol."},{"key":"ref_54","unstructured":"(2019, July 25). R: The R project for statistical computing. Available online: https:\/\/www.r-project.org\/."},{"key":"ref_55","doi-asserted-by":"crossref","first-page":"2441","DOI":"10.1080\/01431161.2018.1425567","article-title":"Application of an unmanned aerial system for monitoring paddy productivity using the GRAMI-rice model","volume":"39","author":"Jeong","year":"2018","journal-title":"Int. J. Remote Sens."},{"key":"ref_56","doi-asserted-by":"crossref","unstructured":"Jeong, S., Ko, J., and Yeom, J.-M. (2018). Nationwide Projection of Rice Yield Using a Crop Model Integrated with Geostationary Satellite Imagery: A Case Study in South Korea. Remote Sens., 10.","DOI":"10.20944\/preprints201809.0016.v1"},{"key":"ref_57","doi-asserted-by":"crossref","first-page":"16121","DOI":"10.1038\/s41598-018-34550-0","article-title":"Monitoring paddy productivity in North Korea employing geostationary satellite images integrated with GRAMI-rice model","volume":"8","author":"Yeom","year":"2018","journal-title":"Sci. Rep."}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/11\/18\/2131\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T13:19:45Z","timestamp":1760188785000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/11\/18\/2131"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,9,13]]},"references-count":57,"journal-issue":{"issue":"18","published-online":{"date-parts":[[2019,9]]}},"alternative-id":["rs11182131"],"URL":"https:\/\/doi.org\/10.3390\/rs11182131","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2019,9,13]]}}}