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Volumn 10, Issue 12, 2018, Pages

Utilizing collocated crop growth model simulations to train agronomic satellite retrieval algorithms

Author keywords

BLSTMs; Crop growth models; MODIS

Indexed keywords

AGRONOMY; CROPS; FORESTRY; PLANTS (BOTANY); RADIOMETERS; REMOTE SENSING;

EID: 85058880636     PISSN: None     EISSN: 20724292     Source Type: Journal    
DOI: 10.3390/rs10121968     Document Type: Article
Times cited : (7)

References (103)
  • 1
    • 85058877769 scopus 로고    scopus 로고
    • Assessment of the Information Content in Solar Reflective Satellite Measurements with Respect to Crop Growth Model State Variables
    • Montreal, QC, Canada, 24-27 June 2018 International Society of Precision Agriculture: Monticello, IL, USA
    • Levitan, N.; Gross, B. Assessment of the Information Content in Solar Reflective Satellite Measurements with Respect to Crop Growth Model State Variables. In Proceedings of the 14th International Conference on Precision Agriculture, Montreal, QC, Canada, 24-27 June 2018; International Society of Precision Agriculture: Monticello, IL, USA, 2018; pp. 1-12
    • (2018) Proceedings of the 14th International Conference on Precision Agriculture , pp. 1-12
    • Levitan, N.1    Gross, B.2
  • 3
    • 85044967207 scopus 로고    scopus 로고
    • Assessing the information in crop model and meteorological indicators to forecast crop yield over Europe
    • Lecerf, R.; Ceglar, A.; López-Lozano, R.; Van Der Velde, M.; Baruth, B. Assessing the information in crop model and meteorological indicators to forecast crop yield over Europe. Agric. Syst. 2018, 168, 191-202
    • (2018) Agric. Syst , vol.168 , pp. 191-202
    • Lecerf, R.1    Ceglar, A.2    López-Lozano, R.3    Van Der Velde, M.4    Baruth, B.5
  • 4
    • 84984653424 scopus 로고    scopus 로고
    • Integrating high resolution soil data into federal crop insurance policy: Implications for policy and conservation
    • Woodard, J.D. Integrating high resolution soil data into federal crop insurance policy: Implications for policy and conservation. Environ. Sci. Policy 2016, 66, 93-100
    • (2016) Environ. Sci. Policy , vol.66 , pp. 93-100
    • Woodard, J.D.1
  • 5
    • 71949127326 scopus 로고    scopus 로고
    • Integrating farmer knowledge, precision agriculture tools, and crop simulation modelling to evaluate management options for poor-performing patches in cropping fields
    • Oliver, Y.M.; Robertson, M.J.; Wong, M.T.F. Integrating farmer knowledge, precision agriculture tools, and crop simulation modelling to evaluate management options for poor-performing patches in cropping fields. Eur. J. Agron. 2010, 32, 40-50
    • (2010) Eur. J. Agron , vol.32 , pp. 40-50
    • Oliver, Y.M.1    Robertson, M.J.2    Wong, M.T.F.3
  • 6
    • 84875500101 scopus 로고    scopus 로고
    • Yield gap analysis with local to global relevance-A review
    • Grassini, P.;Wolf, J.; Tittonell, P.; Hochman, Z. Yield gap analysis with local to global relevance-A review. Field Crop. Res. 2013, 143, 4-17
    • (2013) Field Crop. Res , vol.143 , pp. 4-17
    • Grassini, P.1    Wolf, J.2    Tittonell, P.3    Hochman, Z.4
  • 7
    • 84925348739 scopus 로고    scopus 로고
    • Upscaling modelled crop yields to regional scale: A case study using DSSAT for spring wheat on the Canadian prairies
    • Huffman, T.; Qian, B.; De Jong, R.; Liu, J.;Wang, H.; McConkey, B.; Brierley, T.; Yang, J.; Jong, D. Upscaling modelled crop yields to regional scale: A case study using DSSAT for spring wheat on the Canadian prairies. Can. J. Soil Sci. 2015, 95, 49-61
    • (2015) Can. J. Soil Sci , vol.95 , pp. 49-61
    • Huffman, T.1    Qian, B.2    De Jong, R.3    Liu, J.4    Wang, H.5    McConkey, B.6    Brierley, T.7    Yang, J.8    Jong, D.9
  • 9
    • 84856896529 scopus 로고    scopus 로고
    • Simulating the effects of climate and agricultural management practices on global crop yield
    • Deryng, D.; Sacks, W.J.; Barford, C.C.; Ramankutty, N. Simulating the effects of climate and agricultural management practices on global crop yield. Glob. Biogeochem. Cycles 2011, 25
    • (2011) Glob. Biogeochem. Cycles , pp. 25
    • Deryng, D.1    Sacks, W.J.2    Barford, C.C.3    Ramankutty, N.4
  • 12
    • 84983486825 scopus 로고    scopus 로고
    • Calibration-induced uncertainty of the EPIC model to estimate climate change impact on global maize yield
    • Xiong, W.; Skalský, R.; Porter, C.H.; Balkovič, J.; Jones, J.W.; Yang, D. Calibration-induced uncertainty of the EPIC model to estimate climate change impact on global maize yield. J. Adv. Model. Earth Syst. 2016, 8, 1358-1375
    • (2016) J. Adv. Model. Earth Syst , vol.8 , pp. 1358-1375
    • Xiong, W.1    Skalský, R.2    Porter, C.H.3    Balkovič, J.4    Jones, J.W.5    Yang, D.6
  • 15
    • 84872934055 scopus 로고    scopus 로고
    • Implication of crop model calibration strategies for assessing regional impacts of climate change in Europe
    • Angulo, C.; Rötter, R.; Lock, R.; Enders, A.; Fronzek, S.; Ewert, F. Implication of crop model calibration strategies for assessing regional impacts of climate change in Europe. Agric. For. Meteorol. 2013, 170, 32-46
    • (2013) Agric. For. Meteorol , vol.170 , pp. 32-46
    • Angulo, C.1    Rötter, R.2    Lock, R.3    Enders, A.4    Fronzek, S.5    Ewert, F.6
  • 16
    • 84952673764 scopus 로고    scopus 로고
    • Effects of automatic multi-objective optimization of crop models on corn yield reproducibility in the U.S.A
    • Tatsumi, K. Effects of automatic multi-objective optimization of crop models on corn yield reproducibility in the U.S.A. Ecol. Model. 2016, 322, 124-137
    • (2016) Ecol. Model , vol.322 , pp. 124-137
    • Tatsumi, K.1
  • 19
    • 84923830705 scopus 로고    scopus 로고
    • Joint leaf chlorophyll content and leaf area index retrieval from Landsat data using a regularized model inversion system (REGFLEC)
    • Houborg, R.; McCabe, M.; Cescatti, A.; Gao, F.; Schull, M.; Gitelson, A. Joint leaf chlorophyll content and leaf area index retrieval from Landsat data using a regularized model inversion system (REGFLEC). Remote Sens. Environ. 2015, 159, 203-221
    • (2015) Remote Sens. Environ , vol.159 , pp. 203-221
    • Houborg, R.1    McCabe, M.2    Cescatti, A.3    Gao, F.4    Schull, M.5    Gitelson, A.6
  • 20
    • 84907177618 scopus 로고    scopus 로고
    • Estimating leaf chlorophyll of barley at different growth stages using spectral indices to reduce soil background and canopy structure effects
    • Yu, K.; Lenz-Wiedemann, V.; Chen, X.; Bareth, G. Estimating leaf chlorophyll of barley at different growth stages using spectral indices to reduce soil background and canopy structure effects. ISPRS J. Photogramm. Remote Sens. 2014, 97, 58-77
    • (2014) ISPRS J. Photogramm. Remote Sens , vol.97 , pp. 58-77
    • Yu, K.1    Lenz-Wiedemann, V.2    Chen, X.3    Bareth, G.4
  • 21
    • 84899653728 scopus 로고    scopus 로고
    • Evaluating APSIM maize, soil water, soil nitrogen, manure, and soil temperature modules in the Midwestern United States
    • Archontoulis, S.V.; Miguez, F.E.; Moore, K.J. Evaluating APSIM maize, soil water, soil nitrogen, manure, and soil temperature modules in the Midwestern United States. Agron. J. 2014, 106, 1025-1040
    • (2014) Agron. J , vol.106 , pp. 1025-1040
    • Archontoulis, S.V.1    Miguez, F.E.2    Moore, K.J.3
  • 24
    • 0037211652 scopus 로고    scopus 로고
    • Retrieval of canopy biophysical variables from bidirectional reflectance: Using prior information to solve the ill-posed inverse problem
    • Combal, B.; Baret, F.; Weiss, M.; Trubuil, A.; Macé, D.; Pragnère, A.; Myneni, R.; Knyazikhin, Y.; Wang, L. Retrieval of canopy biophysical variables from bidirectional reflectance: Using prior information to solve the ill-posed inverse problem. Remote Sens. Environ. 2003, 84, 1-15
    • (2003) Remote Sens. Environ , vol.84 , pp. 1-15
    • Combal, B.1    Baret, F.2    Weiss, M.3    Trubuil, A.4    Macé, D.5    Pragnère, A.6    Myneni, R.7    Knyazikhin, Y.8    Wang, L.9
  • 25
    • 33847629701 scopus 로고    scopus 로고
    • Quantification of plant stress using remote sensing observations and crop models: The case of nitrogen management
    • Baret, F.; Houles, V.; Guerif, M. Quantification of plant stress using remote sensing observations and crop models: The case of nitrogen management. J. Exp. Bot. 2006, 58, 869-880
    • (2006) J. Exp. Bot , vol.58 , pp. 869-880
    • Baret, F.1    Houles, V.2    Guerif, M.3
  • 26
    • 84897827083 scopus 로고    scopus 로고
    • Inversion of the PROSAIL model to estimate leaf area index of maize, potato, and sunflower fields from unmanned aerial vehicle hyperspectral data
    • Duan, S.-B.; Li, Z.-L.;Wu, H.; Tang, B.-H.; Ma, L.; Zhao, E.; Li, C. Inversion of the PROSAIL model to estimate leaf area index of maize, potato, and sunflower fields from unmanned aerial vehicle hyperspectral data. Int. J. Appl. Earth Obs. Geoinf. 2014, 26, 12-20
    • (2014) Int. J. Appl. Earth Obs. Geoinf , vol.26 , pp. 12-20
    • Duan, S.-B.1    Li, Z.-L.2    Wu, H.3    Tang, B.-H.4    Ma, L.5    Zhao, E.6    Li, C.7
  • 29
    • 84861977025 scopus 로고    scopus 로고
    • Estimating crop biophysical properties from remote sensing data by inverting linked radiative transfer and ecophysiological models
    • Thorp, K.R.; Wang, G.; West, A.L.; Moran, M.S.; Bronson, K.F.; White, J.W.; Mon, J. Estimating crop biophysical properties from remote sensing data by inverting linked radiative transfer and ecophysiological models. Remote Sens. Environ. 2012, 124, 224-233
    • (2012) Remote Sens. Environ , vol.124 , pp. 224-233
    • Thorp, K.R.1    Wang, G.2    West, A.L.3    Moran, M.S.4    Bronson, K.F.5    White, J.W.6    Mon, J.7
  • 31
    • 85048777158 scopus 로고    scopus 로고
    • Does remote and proximal optical sensing successfully estimate maize variables?. A review
    • Corti, M.; Cavalli, D.; Cabassi, G.; Marino Gallina, P.; Bechini, L. Does remote and proximal optical sensing successfully estimate maize variables? A review. Eur. J. Agron. 2018, 99, 37-50
    • (2018) Eur. J. Agron , vol.99 , pp. 37-50
    • Corti, M.1    Cavalli, D.2    Cabassi, G.3    Marino Gallina, P.4    Bechini, L.5
  • 32
    • 84891866626 scopus 로고    scopus 로고
    • Testing Remote Sensing Approaches for Assessing Yield Variability among Maize Fields
    • Sibley, A.M.; Grassini, P.; Thomas, N.E.; Cassman, K.G.; Lobell, D.B. Testing Remote Sensing Approaches for Assessing Yield Variability among Maize Fields. Agron. J. 2014, 106, 24
    • (2014) Agron. J , vol.106 , pp. 24
    • Sibley, A.M.1    Grassini, P.2    Thomas, N.E.3    Cassman, K.G.4    Lobell, D.B.5
  • 34
    • 85029355039 scopus 로고    scopus 로고
    • Improving the accuracy of satellite-based high-resolution yield estimation: A test of multiple scalable approaches
    • Jin, Z.; Azzari, G.; Lobell, D.B. Improving the accuracy of satellite-based high-resolution yield estimation: A test of multiple scalable approaches. Agric. For. Meteorol. 2017, 247, 207-220
    • (2017) Agric. For. Meteorol , vol.247 , pp. 207-220
    • Jin, Z.1    Azzari, G.2    Lobell, D.B.3
  • 35
    • 0031205919 scopus 로고    scopus 로고
    • A simplified approach for yield prediction of sugar beet based on optical remote sensing data
    • Clevers, J.G.P. A simplified approach for yield prediction of sugar beet based on optical remote sensing data. Remote Sens. Environ. 1997, 61, 221-228
    • (1997) Remote Sens. Environ , vol.61 , pp. 221-228
    • Clevers, J.G.P.1
  • 36
    • 84872872459 scopus 로고    scopus 로고
    • MODIS-based corn grain yield estimation model incorporating crop phenology information
    • Sakamoto, T.; Gitelson, A.A.; Arkebauer, T.J. MODIS-based corn grain yield estimation model incorporating crop phenology information. Remote Sens. Environ. 2013, 131, 215-231
    • (2013) Remote Sens. Environ , vol.131 , pp. 215-231
    • Sakamoto, T.1    Gitelson, A.A.2    Arkebauer, T.J.3
  • 37
    • 84997771292 scopus 로고    scopus 로고
    • A comprehensive assessment of the correlations between field crop yields and commonly used MODIS products
    • Johnson, D.M. A comprehensive assessment of the correlations between field crop yields and commonly used MODIS products. Int. J. Appl. Earth Obs. Geoinf. 2016, 52, 65-81
    • (2016) Int. J. Appl. Earth Obs. Geoinf , vol.52 , pp. 65-81
    • Johnson, D.M.1
  • 39
    • 67249166180 scopus 로고    scopus 로고
    • Validating the FAO AquaCrop Model for Irrigated and Water Deficient Field Maize
    • Heng, L.K.; Hsiao, T.; Evett, S.; Howell, T.; Steduto, P. Validating the FAO AquaCrop Model for Irrigated and Water Deficient Field Maize. Agron. J. 2009, 101, 488
    • (2009) Agron. J , vol.101 , pp. 488
    • Heng, L.K.1    Hsiao, T.2    Evett, S.3    Howell, T.4    Steduto, P.5
  • 41
    • 0033710227 scopus 로고    scopus 로고
    • Using the CERES-Maize model in a semi-arid Mediterranean environment Evaluation of model performance
    • Ben Nouna, B.; Katerji, N.; Mastrorilli, M. Using the CERES-Maize model in a semi-arid Mediterranean environment. Evaluation of model performance. Eur. J. Agron. 2000, 13, 309-322
    • (2000) Eur. J. Agron , vol.13 , pp. 309-322
    • Ben Nouna, B.1    Katerji, N.2    Mastrorilli, M.3
  • 46
    • 84964865015 scopus 로고    scopus 로고
    • Narrowing the Agronomic Yield Gaps of Maize by Improved Soil, Cultivar, and Agricultural Management Practices in Different Climate Zones of Northeast China
    • Liu, Z.; Yang, X.; Lin, X.; Hubbard, K.G.; Lv, S.;Wang, J. Narrowing the Agronomic Yield Gaps of Maize by Improved Soil, Cultivar, and Agricultural Management Practices in Different Climate Zones of Northeast China. Earth Interact. 2016, 20
    • (2016) Earth Interact , pp. 20
    • Liu, Z.1    Yang, X.2    Lin, X.3    Hubbard, K.G.4    Lv, S.5    Wang, J.6
  • 48
    • 0002292236 scopus 로고    scopus 로고
    • The PRISM approach to mapping precipitation and temperature
    • Reno, NV, USA, 20-23 October 1997 American Meteorological Society: Boston, MA, USA
    • Daly, C.; Taylor, G.; Gibson, W. The PRISM approach to mapping precipitation and temperature. In Proceedings of the 10th Conference on Applied Climatology, Reno, NV, USA, 20-23 October 1997; American Meteorological Society: Boston, MA, USA, 1997; pp. 10-12
    • (1997) Proceedings of the 10th Conference on Applied Climatology , pp. 10-12
    • Daly, C.1    Taylor, G.2    Gibson, W.3
  • 51
    • 85027939545 scopus 로고    scopus 로고
    • Assessment of irrigation performance and water productivity in irrigated areas of the middle Heihe River basin using a distributed agro-hydrological model
    • Jiang, Y.; Xu, X.; Huang, Q.; Huo, Z.; Huang, G. Assessment of irrigation performance and water productivity in irrigated areas of the middle Heihe River basin using a distributed agro-hydrological model. Agric. Water Manag. 2015, 147, 67-81
    • (2015) Agric. Water Manag , vol.147 , pp. 67-81
    • Jiang, Y.1    Xu, X.2    Huang, Q.3    Huo, Z.4    Huang, G.5
  • 52
    • 84979684353 scopus 로고    scopus 로고
    • Image (Re-)projections and Merging
    • Springer International Publishing: Cham, Switzerland
    • McInerney, D.; Kempeneers, P. Image (Re-)projections and Merging. In Open Source Geospatial Tools; Springer International Publishing: Cham, Switzerland, 2015; pp. 99-127
    • (2015) Open Source Geospatial Tools , pp. 99-127
    • McInerney, D.1    Kempeneers, P.2
  • 53
    • 79960831514 scopus 로고    scopus 로고
    • Monitoring US agriculture: The US Department of Agriculture, National Agricultural Statistics Service, Cropland Data Layer Program
    • Boryan, C.; Yang, Z.; Mueller, R.; Craig, M. Monitoring US agriculture: The US Department of Agriculture, National Agricultural Statistics Service, Cropland Data Layer Program. Geocarto Int. 2011, 26, 341-358
    • (2011) Geocarto Int , vol.26 , pp. 341-358
    • Boryan, C.1    Yang, Z.2    Mueller, R.3    Craig, M.4
  • 54
    • 84949212522 scopus 로고    scopus 로고
    • The U. drought of 2012
    • Rippey, B.R. The U.S. drought of 2012. Weather Clim. Extrem. 2015, 10, 57-64
    • (2015) Weather Clim. Extrem , vol.10 , pp. 57-64
    • Rippey, B.R.1
  • 55
    • 85006337717 scopus 로고    scopus 로고
    • The Purdue Agro-climatic (PAC) dataset for the U.S Corn Belt: Development and initial results
    • Liu, X.; Jacobs, E.; Kumar, A.; Biehl, L.; Andresen, J.; Niyogi, D. The Purdue Agro-climatic (PAC) dataset for the U.S. Corn Belt: Development and initial results. Clim. Risk Manag. 2017, 15, 61-72
    • (2017) Clim. Risk Manag , vol.15 , pp. 61-72
    • Liu, X.1    Jacobs, E.2    Kumar, A.3    Biehl, L.4    Andresen, J.5    Niyogi, D.6
  • 56
    • 84996910395 scopus 로고    scopus 로고
    • From grid to field: Assessing quality of gridded weather data for agricultural applications
    • Mourtzinis, S.; Rattalino Edreira, J.I.; Conley, S.P.; Grassini, P. From grid to field: Assessing quality of gridded weather data for agricultural applications. Eur. J. Agron. 2017, 82, 163-172
    • (2017) Eur. J. Agron , vol.82 , pp. 163-172
    • Mourtzinis, S.1    Rattalino Edreira, J.I.2    Conley, S.P.3    Grassini, P.4
  • 57
    • 79960687094 scopus 로고    scopus 로고
    • Evaluation of Satellite-Based, Modeled-Derived Daily Solar Radiation Data for the Continental United States
    • White, J.W.; Hoogenboom, G.; Wilkens, P.W.; Stackhouse, P.W.; Hoel, J.M. Evaluation of Satellite-Based, Modeled-Derived Daily Solar Radiation Data for the Continental United States. Agron. J. 2011, 103, 1242
    • (2011) Agron. J , vol.103 , pp. 1242
    • White, J.W.1    Hoogenboom, G.2    Wilkens, P.W.3    Stackhouse, P.W.4    Hoel, J.M.5
  • 58
    • 41149096384 scopus 로고    scopus 로고
    • A crop model cross calibration for use in regional climate impacts studies
    • Xiong,W.; Holman, I.; Conway, D.; Lin, E.; Li, Y. A crop model cross calibration for use in regional climate impacts studies. Ecol. Model. 2008, 213, 365-380
    • (2008) Ecol. Model , vol.213 , pp. 365-380
    • Xiong, W.1    Holman, I.2    Conway, D.3    Lin, E.4    Li, Y.5
  • 59
    • 85058892908 scopus 로고    scopus 로고
    • (accessed on 27 July 2018)
    • Butzen, S. Corn Seeding Rate Considerations. Available online: https://www.pioneer.com/home/site/us/agronomy/library/corn-seeding-rate-considerations/(accessed on 27 July 2018)
    • Corn Seeding Rate Considerations
    • Butzen, S.1
  • 60
    • 85058904251 scopus 로고    scopus 로고
    • Calibration and Validation of the Hybrid-Maize Crop Model for Regional Analysis and Application over the U.S
    • Liu, X.; Andresen, J.; Yang, H.; Niyogi, D. Calibration and Validation of the Hybrid-Maize Crop Model for Regional Analysis and Application over the U.S. Corn Belt. Earth Interact. 2015, 19
    • (2015) Corn Belt. Earth Interact , pp. 19
    • Liu, X.1    Andresen, J.2    Yang, H.3    Niyogi, D.4
  • 62
    • 18544382055 scopus 로고    scopus 로고
    • Probabilistic simulations of crop yield over western India using the DEMETER seasonal hindcast ensembles
    • Challinor, A.J.; Slingo, J.M.; Wheeler, T.R.; Doblas-Reyes, F.J. Probabilistic simulations of crop yield over western India using the DEMETER seasonal hindcast ensembles. Tellus A 2005, 57, 498-512
    • (2005) Tellus A , vol.57 , pp. 498-512
    • Challinor, A.J.1    Slingo, J.M.2    Wheeler, T.R.3    Doblas-Reyes, F.J.4
  • 63
    • 84875506025 scopus 로고    scopus 로고
    • Estimating crop yield potential at regional to national scales
    • vanWart, J.; Kersebaum, K.C.; Peng, S.; Milner, M. Estimating crop yield potential at regional to national scales. Field Crop. Res. 2013, 143, 34-43
    • (2013) Field Crop. Res , vol.143 , pp. 34-43
    • vanWart, J.1    Kersebaum, K.C.2    Peng, S.3    Milner, M.4
  • 65
    • 34548030241 scopus 로고    scopus 로고
    • Mechanisms Governing Interannual Variability of Upper-Ocean Temperature in a Global Ocean Hindcast Simulation
    • Doney, S.C.; Yeager, S.; Danabasoglu, G.; Large, W.G.; Mcwilliams, J.C. Mechanisms Governing Interannual Variability of Upper-Ocean Temperature in a Global Ocean Hindcast Simulation. J. Phys. Oceanogr. 2007, 37
    • (2007) J. Phys. Oceanogr , pp. 37
    • Doney, S.C.1    Yeager, S.2    Danabasoglu, G.3    Large, W.G.4    Mcwilliams, J.C.5
  • 68
    • 84930639546 scopus 로고    scopus 로고
    • Introducing CURRENNT: The Munich Open-Source CUDA RecurREnt Neural Network Toolkit
    • Weninger, F.; Bergmann, J.; Schuller, B. Introducing CURRENNT: The Munich Open-Source CUDA RecurREnt Neural Network Toolkit. J. Mach. Learn. Res. 2015, 16, 547-551
    • (2015) J. Mach. Learn. Res , vol.16 , pp. 547-551
    • Weninger, F.1    Bergmann, J.2    Schuller, B.3
  • 70
    • 84920647571 scopus 로고    scopus 로고
    • Assessment of RapidEye vegetation indices for estimation of leaf area index and biomass in corn and soybean crops
    • Kross, A.; McNairn, H.; Lapen, D.; Sunohara, M.; Champagne, C. Assessment of RapidEye vegetation indices for estimation of leaf area index and biomass in corn and soybean crops. Int. J. Appl. Earth Obs. Geoinf. 2015, 34, 235-248
    • (2015) Int. J. Appl. Earth Obs. Geoinf , vol.34 , pp. 235-248
    • Kross, A.1    McNairn, H.2    Lapen, D.3    Sunohara, M.4    Champagne, C.5
  • 71
    • 84989829890 scopus 로고    scopus 로고
    • Estimating maize biomass and yield over large areas using high spatial and temporal resolution Sentinel-2 like remote sensing data
    • Battude, M.; Al Bitar, A.; Morin, D.; Cros, J.; Huc, M.; Marais Sicre, C.; Le Dantec, V.; Demarez, V. Estimating maize biomass and yield over large areas using high spatial and temporal resolution Sentinel-2 like remote sensing data. Remote Sens. Environ. 2016, 184, 668-681
    • (2016) Remote Sens. Environ , vol.184 , pp. 668-681
    • Battude, M.1    Al Bitar, A.2    Morin, D.3    Cros, J.4    Huc, M.5    Marais Sicre, C.6    Le Dantec, V.7    Demarez, V.8
  • 72
    • 84875854453 scopus 로고    scopus 로고
    • Relationships between vegetation indices and root zone soil moisture under maize and soybean canopies in the US Corn Belt: A comparative study using a close-range sensing approach
    • Swain, S.;Wardlow, B.D.; Narumalani, S.; Rundquist, D.C.; Hayes, M.J. Relationships between vegetation indices and root zone soil moisture under maize and soybean canopies in the US Corn Belt: A comparative study using a close-range sensing approach. Int. J. Remote Sens. 2013, 34, 2814-2828
    • (2013) Int. J. Remote Sens , vol.34 , pp. 2814-2828
    • Swain, S.1    Wardlow, B.D.2    Narumalani, S.3    Rundquist, D.C.4    Hayes, M.J.5
  • 73
    • 84921021786 scopus 로고    scopus 로고
    • Relationships between Remote-Sensing-Based Agricultural Drought Indicators and Root Zone Soil Moisture: A Comparative Study of Iowa
    • Peng, C.; Deng, M.; Di, L. Relationships between Remote-Sensing-Based Agricultural Drought Indicators and Root Zone Soil Moisture: A Comparative Study of Iowa. IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens. 2014, 7, 4572-4580
    • (2014) IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens , vol.7 , pp. 4572-4580
    • Peng, C.1    Deng, M.2    Di, L.3
  • 74
    • 84893498266 scopus 로고    scopus 로고
    • Relationships between gross primary production, green LAI, and canopy chlorophyll content in maize: Implications for remote sensing of primary production
    • Gitelson, A.A.; Peng, Y.; Arkebauer, T.J.; Schepers, J. Relationships between gross primary production, green LAI, and canopy chlorophyll content in maize: Implications for remote sensing of primary production. Remote Sens. Environ. 2014, 144, 65-72
    • (2014) Remote Sens. Environ , vol.144 , pp. 65-72
    • Gitelson, A.A.1    Peng, Y.2    Arkebauer, T.J.3    Schepers, J.4
  • 75
    • 84880397637 scopus 로고    scopus 로고
    • Hidden Markov Models for Real-Time Estimation of Corn Progress Stages Using MODIS and Meteorological Data
    • Shen, Y.; Wu, L.; Di, L.; Yu, G.; Tang, H.; Yu, G.; Shao, Y. Hidden Markov Models for Real-Time Estimation of Corn Progress Stages Using MODIS and Meteorological Data. Remote Sens. 2013, 5, 1734-1753
    • (2013) Remote Sens , vol.5 , pp. 1734-1753
    • Shen, Y.1    Wu, L.2    Di, L.3    Yu, G.4    Tang, H.5    Yu, G.6    Shao, Y.7
  • 76
    • 79957630538 scopus 로고    scopus 로고
    • Detecting Spatiotemporal Changes of Corn Developmental Stages in the U.S Corn Belt Using MODIS WDRVI Data
    • Sakamoto, T.; Wardlow, B.D.; Gitelson, A.A. Detecting Spatiotemporal Changes of Corn Developmental Stages in the U.S. Corn Belt Using MODIS WDRVI Data. IEEE Trans. Geosci. Remote Sens. 2011, 49, 1926-1936
    • (2011) IEEE Trans. Geosci. Remote Sens , vol.49 , pp. 1926-1936
    • Sakamoto, T.1    Wardlow, B.D.2    Gitelson, A.A.3
  • 77
    • 85042402897 scopus 로고    scopus 로고
    • Refined shape model fitting methods for detecting various types of phenological information on major U.S. crops
    • Sakamoto, T. Refined shape model fitting methods for detecting various types of phenological information on major U.S. crops. ISPRS J. Photogramm. Remote Sens. 2018, 138, 176-192
    • (2018) ISPRS J. Photogramm. Remote Sens , vol.138 , pp. 176-192
    • Sakamoto, T.1
  • 79
    • 13844266849 scopus 로고    scopus 로고
    • Use of coupled canopy structure dynamic and radiative transfer models to estimate biophysical canopy characteristics
    • Koetz, B.; Baret, F.; Poilvé, H.; Hill, J. Use of coupled canopy structure dynamic and radiative transfer models to estimate biophysical canopy characteristics. Remote Sens. Environ. 2005, 95, 115-124
    • (2005) Remote Sens. Environ , vol.95 , pp. 115-124
    • Koetz, B.1    Baret, F.2    Poilvé, H.3    Hill, J.4
  • 80
    • 84875117682 scopus 로고    scopus 로고
    • Forecasting crop yield using remotely sensed vegetation indices and crop phenology metrics
    • Bolton, D.K.; Friedl, M.A. Forecasting crop yield using remotely sensed vegetation indices and crop phenology metrics. Agric. For. Meteorol. 2013, 173, 74-84
    • (2013) Agric. For. Meteorol , vol.173 , pp. 74-84
    • Bolton, D.K.1    Friedl, M.A.2
  • 81
    • 85048923897 scopus 로고    scopus 로고
    • Estimating Corn Yield in The United States with Modis EVI and Machine Learning Methods
    • Kuwata, K.; Shibasaki, R. Estimating Corn Yield in The United States with Modis EVI and Machine Learning Methods. ISPRS Ann. Photogramm. Remote Sens. Spat. Inf. Sci. 2016, III-8, 131-136
    • (2016) ISPRS Ann. Photogramm. Remote Sens. Spat. Inf. Sci , vol.3 , Issue.8 , pp. 131-136
    • Kuwata, K.1    Shibasaki, R.2
  • 82
    • 0348202932 scopus 로고    scopus 로고
    • Calibration of CERES3 (Maize) to improve silking date prediction values for South Africa
    • Du Toit, A.S.; Booysen, J.; Human, J.J. Calibration of CERES3 (Maize) to improve silking date prediction values for South Africa. S. Afr. J. Plant Soil 1998, 15, 61-66
    • (1998) S. Afr. J. Plant Soil , vol.15 , pp. 61-66
    • Du Toit, A.S.1    Booysen, J.2    Human, J.J.3
  • 83
    • 85018475292 scopus 로고    scopus 로고
    • Retrieval of Specific Leaf Area from Landsat-8 Surface Reflectance Data Using Statistical and Physical Models
    • Ali, A.M.; Darvishzadeh, R.; Skidmore, A.K. Retrieval of Specific Leaf Area from Landsat-8 Surface Reflectance Data Using Statistical and Physical Models. IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens. 2017, 10, 3529-3536
    • (2017) IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens , vol.10 , pp. 3529-3536
    • Ali, A.M.1    Darvishzadeh, R.2    Skidmore, A.K.3
  • 84
    • 0033982721 scopus 로고    scopus 로고
    • Estimation of Canopy-Average Surface-Specific Leaf Area Using Landsat TM Data
    • Lymburner, L.; Beggs, P.J.; Jacobson, C.R. Estimation of Canopy-Average Surface-Specific Leaf Area Using Landsat TM Data. Photogramm. Eng. Remote Sens. 2000, 66, 183-191
    • (2000) Photogramm. Eng. Remote Sens , vol.66 , pp. 183-191
    • Lymburner, L.1    Beggs, P.J.2    Jacobson, C.R.3
  • 87
    • 85053623996 scopus 로고    scopus 로고
    • Assessing the Variability of Corn and Soybean Yields in Central Iowa Using High Spatiotemporal Resolution Multi-Satellite Imagery
    • Gao, F.; Anderson, M.; Daughtry, C.; Johnson, D. Assessing the Variability of Corn and Soybean Yields in Central Iowa Using High Spatiotemporal Resolution Multi-Satellite Imagery. Remote Sens. 2018, 10, 1489
    • (2018) Remote Sens , vol.10 , pp. 1489
    • Gao, F.1    Anderson, M.2    Daughtry, C.3    Johnson, D.4
  • 89
    • 77952008588 scopus 로고    scopus 로고
    • Zone mapping application for precision-farming: A decision support tool for variable rate application
    • Zhang, X.; Shi, L.; Jia, X.; Seielstad, G.; Helgason, C. Zone mapping application for precision-farming: A decision support tool for variable rate application. Precis. Agric. 2010, 11, 103-114
    • (2010) Precis. Agric , vol.11 , pp. 103-114
    • Zhang, X.1    Shi, L.2    Jia, X.3    Seielstad, G.4    Helgason, C.5
  • 90
    • 84946888122 scopus 로고    scopus 로고
    • Conterminous United States crop field size quantification from multi-temporal Landsat data
    • Yan, L.; Roy, D.P. Conterminous United States crop field size quantification from multi-temporal Landsat data. Remote Sens. Environ. 2016, 172, 67-86
    • (2016) Remote Sens. Environ , vol.172 , pp. 67-86
    • Yan, L.1    Roy, D.P.2
  • 91
    • 33746932125 scopus 로고    scopus 로고
    • On the blending of the Landsat and MODIS surface reflectance: Predicting daily Landsat surface reflectance
    • Gao, F.; Masek, J.; Schwaller, M.; Hall, F. On the blending of the Landsat and MODIS surface reflectance: Predicting daily Landsat surface reflectance. IEEE Trans. Geosci. Remote Sens. 2006, 44, 2207-2218
    • (2006) IEEE Trans. Geosci. Remote Sens , vol.44 , pp. 2207-2218
    • Gao, F.1    Masek, J.2    Schwaller, M.3    Hall, F.4
  • 93
    • 85043598532 scopus 로고    scopus 로고
    • A high-performance and in-season classification system of field-level crop types using time-series Landsat data and a machine learning approach
    • Cai, Y.; Guan, K.; Peng, J.; Wang, S.; Seifert, C.; Wardlow, B.; Li, Z. A high-performance and in-season classification system of field-level crop types using time-series Landsat data and a machine learning approach. Remote Sens. Environ. 2018, 210, 35-47
    • (2018) Remote Sens. Environ , vol.210 , pp. 35-47
    • Cai, Y.1    Guan, K.2    Peng, J.3    Wang, S.4    Seifert, C.5    Wardlow, B.6    Li, Z.7
  • 94
    • 84937897682 scopus 로고    scopus 로고
    • A Hidden Markov Models Approach for Crop Classification: Linking Crop Phenology to Time Series of Multi-Sensor Remote Sensing Data
    • Siachalou, S.; Mallinis, G.; Tsakiri-Strati, M. A Hidden Markov Models Approach for Crop Classification: Linking Crop Phenology to Time Series of Multi-Sensor Remote Sensing Data. Remote Sens. 2015, 7, 3633-3650
    • (2015) Remote Sens , vol.7 , pp. 3633-3650
    • Siachalou, S.1    Mallinis, G.2    Tsakiri-Strati, M.3
  • 95
    • 85017192157 scopus 로고    scopus 로고
    • Deep Learning Classification of Land Cover and Crop Types Using Remote Sensing Data
    • Kussul, N.; Lavreniuk, M.; Skakun, S.; Shelestov, A. Deep Learning Classification of Land Cover and Crop Types Using Remote Sensing Data. IEEE Geosci. Remote Sens. Lett. 2017, 14, 778-782
    • (2017) IEEE Geosci. Remote Sens. Lett , vol.14 , pp. 778-782
    • Kussul, N.1    Lavreniuk, M.2    Skakun, S.3    Shelestov, A.4
  • 98
    • 85048136406 scopus 로고    scopus 로고
    • Rapid Crop Cover Mapping for the Conterminous United States
    • Dahal, D.;Wylie, B.; Howard, D. Rapid Crop Cover Mapping for the Conterminous United States. Sci. Rep. 2018, 8, 8631
    • (2018) Sci. Rep , vol.8 , pp. 8631
    • Dahal, D.1    Wylie, B.2    Howard, D.3
  • 99
    • 84897374226 scopus 로고    scopus 로고
    • Near real-time prediction of U.S. corn yields based on time-series MODIS data
    • Sakamoto, T.; Gitelson, A.A.; Arkebauer, T.J. Near real-time prediction of U.S. corn yields based on time-series MODIS data. Remote Sens. Environ. 2014, 147, 219-231
    • (2014) Remote Sens. Environ , vol.147 , pp. 219-231
    • Sakamoto, T.1    Gitelson, A.A.2    Arkebauer, T.J.3
  • 100
    • 85026740667 scopus 로고    scopus 로고
    • Understanding the temporal behavior of crops using Sentinel-1 and Sentinel-2-like data for agricultural applications
    • Veloso, A.; Mermoz, S.; Bouvet, A.; Le Toan, T.; Planells, M.; Dejoux, J.-F.; Ceschia, E. Understanding the temporal behavior of crops using Sentinel-1 and Sentinel-2-like data for agricultural applications. Remote Sens. Environ. 2017, 199, 415-426
    • (2017) Remote Sens. Environ , vol.199 , pp. 415-426
    • Veloso, A.1    Mermoz, S.2    Bouvet, A.3    Le Toan, T.4    Planells, M.5    Dejoux, J.-F.6    Ceschia, E.7
  • 101
    • 84981328348 scopus 로고    scopus 로고
    • Crop Monitoring Based on SPOT-5 Take-5 and Sentinel-1A Data for the Estimation of CropWater Requirements
    • Navarro, A.; Rolim, J.; Miguel, I.; Catalão, J.; Silva, J.; Painho, M.; Vekerdy, Z. Crop Monitoring Based on SPOT-5 Take-5 and Sentinel-1A Data for the Estimation of CropWater Requirements. Remote Sens. 2016, 8, 525
    • (2016) Remote Sens , vol.8 , pp. 525
    • Navarro, A.1    Rolim, J.2    Miguel, I.3    Catalão, J.4    Silva, J.5    Painho, M.6    Vekerdy, Z.7
  • 103
    • 84991593765 scopus 로고    scopus 로고
    • Retrieval of agricultural crop height from space: A comparison of SAR techniques
    • Erten, E.; Lopez-Sanchez, J.M.; Yuzugullu, O.; Hajnsek, I. Retrieval of agricultural crop height from space: A comparison of SAR techniques. Remote Sens. Environ. 2016, 187, 130-144
    • (2016) Remote Sens. Environ , vol.187 , pp. 130-144
    • Erten, E.1    Lopez-Sanchez, J.M.2    Yuzugullu, O.3    Hajnsek, I.4


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