Meroni, M.,
Marinho, E.,
Sghaier, N.,
Verstrate, M.,
Leo, O.,
Remote Sensing Based Yield Estimation in a Stochastic Framework:
Case Study of Durum Wheat in Tunisia,
RS(5), No. 2, February 2013, pp. 539-557.
DOI Link
1303
BibRef
Dempewolf, J.[Jan],
Adusei, B.[Bernard],
Becker-Reshef, I.[Inbal],
Hansen, M.[Matthew],
Potapov, P.[Peter],
Khan, A.[Ahmad],
Barker, B.[Brian],
Wheat Yield Forecasting for Punjab Province from Vegetation Index
Time Series and Historic Crop Statistics,
RS(6), No. 10, 2014, pp. 9653-9675.
DOI Link
1411
BibRef
Hernandez, J.[Javier],
Lobos, G.A.[Gustavo A.],
Matus, I.[Iván],
del Pozo, A.[Alejandro],
Silva, P.[Paola],
Galleguillos, M.[Mauricio],
Using Ridge Regression Models to Estimate Grain Yield from Field
Spectral Data in Bread Wheat (Triticum Aestivum L.) Grown under Three
Water Regimes,
RS(7), No. 2, 2015, pp. 2109-2126.
DOI Link
1503
BibRef
Hank, T.B.[Tobias B.],
Bach, H.[Heike],
Mauser, W.[Wolfram],
Using a Remote Sensing-Supported Hydro-Agroecological Model for
Field-Scale Simulation of Heterogeneous Crop Growth and Yield:
Application for Wheat in Central Europe,
RS(7), No. 4, 2015, pp. 3934-3965.
DOI Link
1505
BibRef
Zheng, Y.[Yang],
Zhang, M.[Miao],
Zhang, X.[Xin],
Zeng, H.W.[Hong-Wei],
Wu, B.F.[Bing-Fang],
Mapping Winter Wheat Biomass and Yield Using Time Series Data Blended
from PROBA-V 100- and 300-m S1 Products,
RS(8), No. 10, 2016, pp. 824.
DOI Link
1609
BibRef
Li, Z.H.[Zhen-Hai],
Wang, J.[Jihua],
Xu, X.G.[Xin-Gang],
Zhao, C.J.[Chun-Jiang],
Jin, X.L.[Xiu-Liang],
Yang, G.J.[Gui-Jun],
Feng, H.K.[Hai-Kuan],
Assimilation of Two Variables Derived from Hyperspectral Data into
the DSSAT-CERES Model for Grain Yield and Quality Estimation,
RS(7), No. 9, 2015, pp. 12400.
DOI Link
1511
BibRef
Jin, X.L.[Xiu-Liang],
Kumar, L.[Lalit],
Li, Z.H.[Zhen-Hai],
Xu, X.G.[Xin-Gang],
Yang, G.J.[Gui-Jun],
Wang, J.H.[Ji-Hua],
Estimation of Winter Wheat Biomass and Yield by Combining the
AquaCrop Model and Field Hyperspectral Data,
RS(8), No. 12, 2016, pp. 972.
DOI Link
1612
BibRef
Jin, X.L.[Xiu-Liang],
Li, Z.H.[Zhen-Hai],
Yang, G.J.[Gui-Jun],
Yang, H.[Hao],
Feng, H.K.[Hai-Kuan],
Xu, X.G.[Xin-Gang],
Wang, J.[Jihua],
Li, X.C.[Xin-Chuan],
Luo, J.[Juhua],
Winter wheat yield estimation based on multi-source medium resolution
optical and radar imaging data and the AquaCrop model using the
particle swarm optimization algorithm,
PandRS(126), No. 1, 2017, pp. 24-37.
Elsevier DOI
1704
Optical spectral vegetation indices (OSVIs)
BibRef
Du, M.M.[Meng-Meng],
Noguchi, N.[Noboru],
Monitoring of Wheat Growth Status and Mapping of Wheat Yield's
within-Field Spatial Variations Using Color Images Acquired from
UAV-camera System,
RS(9), No. 3, 2017, pp. xx-yy.
DOI Link
1704
BibRef
Silvestro, P.C.[Paolo Cosmo],
Pignatti, S.[Stefano],
Pascucci, S.[Simone],
Yang, H.[Hao],
Li, Z.H.[Zhen-Hai],
Yang, G.J.[Gui-Jun],
Huang, W.J.[Wen-Jiang],
Casa, R.[Raffaele],
Estimating Wheat Yield in China at the Field and District Scale from
the Assimilation of Satellite Data into the Aquacrop and Simple
Algorithm for Yield (SAFY) Models,
RS(9), No. 5, 2017, pp. xx-yy.
DOI Link
1706
BibRef
Li, H.[He],
Chen, Z.X.[Zhong-Xin],
Liu, G.H.[Gao-Huan],
Jiang, Z.W.[Zhi-Wei],
Huang, C.[Chong],
Improving Winter Wheat Yield Estimation from the CERES-Wheat Model to
Assimilate Leaf Area Index with Different Assimilation Methods and
Spatio-Temporal Scales,
RS(9), No. 3, 2017, pp. xx-yy.
DOI Link
1704
BibRef
Becker-Reshef, I.[Inbal],
Franch, B.[Belen],
Barker, B.[Brian],
Murphy, E.[Emilie],
Santamaria-Artigas, A.[Andres],
Humber, M.[Michael],
Skakun, S.[Sergii],
Vermote, E.[Eric],
Prior Season Crop Type Masks for Winter Wheat Yield Forecasting: A US
Case Study,
RS(10), No. 10, 2018, pp. xx-yy.
DOI Link
1811
BibRef
Kanning, M.[Martin],
Kühling, I.[Insa],
Trautz, D.[Dieter],
Jarmer, T.[Thomas],
High-Resolution UAV-Based Hyperspectral Imagery for LAI and
Chlorophyll Estimations from Wheat for Yield Prediction,
RS(10), No. 12, 2018, pp. xx-yy.
DOI Link
1901
BibRef
Zhang, Y.[Yao],
Qin, Q.M.[Qi-Ming],
Ren, H.Z.[Hua-Zhong],
Sun, Y.H.[Yuan-Heng],
Li, M.Z.[Min-Zan],
Zhang, T.Y.[Tian-Yuan],
Ren, S.L.[Shi-Long],
Optimal Hyperspectral Characteristics Determination for Winter Wheat
Yield Prediction,
RS(10), No. 12, 2018, pp. xx-yy.
DOI Link
1901
BibRef
Wang, Y.L.[Yu-Long],
Xu, X.G.[Xin-Gang],
Huang, L.S.[Lin-Sheng],
Yang, G.J.[Gui-Jun],
Fan, L.L.[Ling-Ling],
Wei, P.F.[Peng-Fei],
Chen, G.[Guo],
An Improved CASA Model for Estimating Winter Wheat Yield from Remote
Sensing Images,
RS(11), No. 9, 2019, pp. xx-yy.
DOI Link
1905
BibRef
Skakun, S.[Sergii],
Vermote, E.[Eric],
Franch, B.[Belen],
Roger, J.C.[Jean-Claude],
Kussul, N.[Nataliia],
Ju, J.C.[Jun-Chang],
Masek, J.[Jeffrey],
Winter Wheat Yield Assessment from Landsat 8 and Sentinel-2 Data:
Incorporating Surface Reflectance, Through Phenological Fitting, into
Regression Yield Models,
RS(11), No. 15, 2019, pp. xx-yy.
DOI Link
1908
BibRef
Tuvdendorj, B.[Battsetseg],
Wu, B.F.[Bing-Fang],
Zeng, H.W.[Hong-Wei],
Batdelger, G.[Gantsetseg],
Nanzad, L.[Lkhagvadorj],
Determination of Appropriate Remote Sensing Indices for Spring Wheat
Yield Estimation in Mongolia,
RS(11), No. 21, 2019, pp. xx-yy.
DOI Link
1911
BibRef
Han, J.C.[Ji-Chong],
Zhang, Z.[Zhao],
Cao, J.[Juan],
Luo, Y.C.[Yu-Chuan],
Zhang, L.L.[Liang-Liang],
Li, Z.Y.[Zi-Yue],
Zhang, J.[Jing],
Prediction of Winter Wheat Yield Based on Multi-Source Data and
Machine Learning in China,
RS(12), No. 2, 2020, pp. xx-yy.
DOI Link
2001
BibRef
Wang, Y.M.[Yu-Miao],
Zhang, Z.[Zhou],
Feng, L.[Luwei],
Du, Q.Y.[Qing-Yun],
Runge, T.[Troy],
Combining Multi-Source Data and Machine Learning Approaches to
Predict Winter Wheat Yield in the Conterminous United States,
RS(12), No. 8, 2020, pp. xx-yy.
DOI Link
2004
BibRef
Cao, J.[Juan],
Zhang, Z.[Zhao],
Tao, F.[Fulu],
Zhang, L.L.[Liang-Liang],
Luo, Y.C.[Yu-Chuan],
Han, J.C.[Ji-Chong],
Li, Z.Y.[Zi-Yue],
Identifying the Contributions of Multi-Source Data for Winter Wheat
Yield Prediction in China,
RS(12), No. 5, 2020, pp. xx-yy.
DOI Link
2003
BibRef
Kamir, E.[Elisa],
Waldner, F.[François],
Hochman, Z.[Zvi],
Estimating wheat yields in Australia using climate records, satellite
image time series and machine learning methods,
PandRS(160), 2020, pp. 124-135.
Elsevier DOI
2001
Agriculture, Machine learning, Actual yield, Yield Gap,
Remote sensing, National scale, Regression
BibRef
Dong, J.[Jie],
Lu, H.B.[Hai-Bo],
Wang, Y.W.[Ya-Wen],
Ye, T.[Tao],
Yuan, W.P.[Wen-Ping],
Estimating winter wheat yield based on a light use efficiency model
and wheat variety data,
PandRS(160), 2020, pp. 18-32.
Elsevier DOI
2001
Landsat, Crop yield, Gross primary productivity, Crop variety,
Light use efficiency
BibRef
Fu, Z.P.[Zhao-Peng],
Jiang, J.[Jie],
Gao, Y.[Yang],
Krienke, B.[Brian],
Wang, M.[Meng],
Zhong, K.T.[Kai-Tai],
Cao, Q.A.[Qi-Ang],
Tian, Y.C.[Yong-Chao],
Zhu, Y.[Yan],
Cao, W.X.[Wei-Xing],
Liu, X.J.[Xiao-Jun],
Wheat Growth Monitoring and Yield Estimation based on Multi-Rotor
Unmanned Aerial Vehicle,
RS(12), No. 3, 2020, pp. xx-yy.
DOI Link
2002
BibRef
Zhao, Y.[Yan],
Potgieter, A.B.[Andries B.],
Zhang, M.[Miao],
Wu, B.F.[Bing-Fang],
Hammer, G.L.[Graeme L.],
Predicting Wheat Yield at the Field Scale by Combining
High-Resolution Sentinel-2 Satellite Imagery and Crop Modelling,
RS(12), No. 6, 2020, pp. xx-yy.
DOI Link
2003
BibRef
Wang, X.L.[Xin-Lei],
Huang, J.X.[Jian-Xi],
Feng, Q.L.[Quan-Long],
Yin, D.Q.[Dong-Qin],
Winter Wheat Yield Prediction at County Level and Uncertainty
Analysis in Main Wheat-Producing Regions of China with Deep Learning
Approaches,
RS(12), No. 11, 2020, pp. xx-yy.
DOI Link
2006
BibRef
Vannoppen, A.[Astrid],
Gobin, A.[Anne],
Kotova, L.[Lola],
Top, S.[Sara],
de Cruz, L.[Lesley],
Viksna, A.[Andris],
Aniskevich, S.[Svetlana],
Bobylev, L.[Leonid],
Buntemeyer, L.[Lars],
Caluwaerts, S.[Steven],
de Troch, R.[Rozemien],
Gnatiuk, N.[Natalia],
Hamdi, R.[Rafiq],
Remedio, A.R.[Armelle Reca],
Sakalli, A.[Abdulla],
van de Vyver, H.[Hans],
van Schaeybroeck, B.[Bert],
Termonia, P.[Piet],
Wheat Yield Estimation from NDVI and Regional Climate Models in
Latvia,
RS(12), No. 14, 2020, pp. xx-yy.
DOI Link
2007
BibRef
Segarra, J.[Joel],
González-Torralba, J.[Jon],
Aranjuelo, Í.[Íker],
Araus, J.L.[Jose Luis],
Kefauver, S.C.[Shawn C.],
Estimating Wheat Grain Yield Using Sentinel-2 Imagery and Exploring
Topographic Features and Rainfall Effects on Wheat Performance in
Navarre, Spain,
RS(12), No. 14, 2020, pp. xx-yy.
DOI Link
2007
BibRef
Song, Y.[Yang],
Wang, J.F.[Jin-Fei],
Shang, J.L.[Jia-Li],
Liao, C.H.[Chun-Hua],
Using UAV-Based SOPC Derived LAI and SAFY Model for Biomass and Yield
Estimation of Winter Wheat,
RS(12), No. 15, 2020, pp. xx-yy.
DOI Link
2008
BibRef
Aranguren, M.[Marta],
Castellón, A.[Ander],
Aizpurua, A.[Ana],
Wheat Yield Estimation with NDVI Values Using a Proximal Sensing Tool,
RS(12), No. 17, 2020, pp. xx-yy.
DOI Link
2009
BibRef
Zhuo, W.[Wen],
Huang, J.X.[Jian-Xi],
Gao, X.R.[Xin-Ran],
Ma, H.Y.[Hong-Yuan],
Huang, H.[Hai],
Su, W.[Wei],
Meng, J.[Jihua],
Li, Y.[Ying],
Chen, H.L.[Huai-Liang],
Yin, D.Q.[Dong-Qin],
Prediction of Winter Wheat Maturity Dates through Assimilating
Remotely Sensed Leaf Area Index into Crop Growth Model,
RS(12), No. 18, 2020, pp. xx-yy.
DOI Link
2009
BibRef
Zhuo, W.[Wen],
Huang, H.[Hai],
Gao, X.R.[Xin-Ran],
Li, X.C.[Xue-Cao],
Huang, J.X.[Jian-Xi],
An Improved Approach of Winter Wheat Yield Estimation by Jointly
Assimilating Remotely Sensed Leaf Area Index and Soil Moisture into
the WOFOST Model,
RS(15), No. 7, 2023, pp. 1825.
DOI Link
2304
BibRef
Song, Y.[Yang],
Wang, J.[Jing],
Wang, L.X.[Li-Xin],
Satellite Solar-Induced Chlorophyll Fluorescence Reveals Heat Stress
Impacts on Wheat Yield in India,
RS(12), No. 20, 2020, pp. xx-yy.
DOI Link
2010
BibRef
Marino, S.[Stefano],
Alvino, A.[Arturo],
Vegetation Indices Data Clustering for Dynamic Monitoring and
Classification of Wheat Yield Crop Traits,
RS(13), No. 4, 2021, pp. xx-yy.
DOI Link
2103
BibRef
Raya-Sereno, M.D.[María D.],
Ortiz-Monasterio, J.I.[J. Ivan],
Alonso-Ayuso, M.[María],
Rodrigues, F.A.[Francelino A.],
Rodríguez, A.A.[Arlet A.],
González-Perez, L.[Lorena],
Quemada, M.[Miguel],
High-Resolution Airborne Hyperspectral Imagery for Assessing Yield,
Biomass, Grain N Concentration, and N Output in Spring Wheat,
RS(13), No. 7, 2021, pp. xx-yy.
DOI Link
2104
BibRef
Shiff, S.[Shilo],
Lensky, I.M.[Itamar M.],
Bonfil, D.J.[David J.],
Using Satellite Data to Optimize Wheat Yield and Quality under
Climate Change,
RS(13), No. 11, 2021, pp. xx-yy.
DOI Link
2106
BibRef
Shen, J.X.[Jian-Xiu],
Evans, F.H.[Fiona H.],
The Potential of Landsat NDVI Sequences to Explain Wheat Yield
Variation in Fields in Western Australia,
RS(13), No. 11, 2021, pp. xx-yy.
DOI Link
2106
BibRef
Romano, E.[Elio],
Bergonzoli, S.[Simone],
Pecorella, I.[Ivano],
Bisaglia, C.[Carlo],
de Vita, P.[Pasquale],
Methodology for the Definition of Durum Wheat Yield Homogeneous Zones
by Using Satellite Spectral Indices,
RS(13), No. 11, 2021, pp. xx-yy.
DOI Link
2106
BibRef
Fei, S.P.[Shuai-Peng],
Hassan, M.A.[Muhammad Adeel],
He, Z.H.[Zhong-Hu],
Chen, Z.[Zhen],
Shu, M.Y.[Mei-Yan],
Wang, J.K.[Jian-Kang],
Li, C.C.[Chang-Chun],
Xiao, Y.G.[Yong-Gui],
Assessment of Ensemble Learning to Predict Wheat Grain Yield Based on
UAV-Multispectral Reflectance,
RS(13), No. 12, 2021, pp. xx-yy.
DOI Link
2106
BibRef
Manivasagam, V.S.,
Sadeh, Y.[Yuval],
Kaplan, G.[Gregoriy],
Bonfil, D.J.[David J.],
Rozenstein, O.[Offer],
Studying the Feasibility of Assimilating Sentinel-2 and PlanetScope
Imagery into the SAFY Crop Model to Predict Within-Field Wheat Yield,
RS(13), No. 12, 2021, pp. xx-yy.
DOI Link
2106
BibRef
Evans, F.H.[Fiona H.],
Shen, J.X.[Jian-Xiu],
Long-Term Hindcasts of Wheat Yield in Fields Using Remotely Sensed
Phenology, Climate Data and Machine Learning,
RS(13), No. 13, 2021, pp. xx-yy.
DOI Link
2107
BibRef
Zeng, L.L.[Ling-Lin],
Peng, G.Z.[Guo-Zhang],
Meng, R.[Ran],
Man, J.G.[Jian-Guo],
Li, W.[Weibo],
Xu, B.[Binyuan],
Lv, Z.G.[Zhen-Gang],
Sun, R.[Rui],
Wheat Yield Prediction Based on Unmanned Aerial Vehicles-Collected
Red-Green-Blue Imagery,
RS(13), No. 15, 2021, pp. xx-yy.
DOI Link
2108
BibRef
Colaço, A.F.[André Freitas],
Schaefer, M.[Michael],
Bramley, R.G.V.[Robert G. V.],
Broadacre Mapping of Wheat Biomass Using Ground-Based LiDAR
Technology,
RS(13), No. 16, 2021, pp. xx-yy.
DOI Link
2109
BibRef
Choudhury, M.R.[Malini Roy],
Das, S.[Sumanta],
Christopher, J.[Jack],
Apan, A.[Armando],
Chapman, S.[Scott],
Menzies, N.W.[Neal W.],
Dang, Y.P.[Yash P.],
Improving Biomass and Grain Yield Prediction of Wheat Genotypes on
Sodic Soil Using Integrated High-Resolution Multispectral,
Hyperspectral, 3D Point Cloud, and Machine Learning Techniques,
RS(13), No. 17, 2021, pp. xx-yy.
DOI Link
2109
BibRef
Eyre, R.[Riley],
Lindsay, J.[John],
Laamrani, A.[Ahmed],
Berg, A.[Aaron],
Within-Field Yield Prediction in Cereal Crops Using LiDAR-Derived
Topographic Attributes with Geographically Weighted Regression Models,
RS(13), No. 20, 2021, pp. xx-yy.
DOI Link
2110
BibRef
Wu, S.R.[Shang-Rong],
Ren, J.Q.[Jian-Qiang],
Chen, Z.X.[Zhong-Xin],
Yang, P.[Peng],
Li, H.[He],
Liu, J.[Jia],
Evaluation of Winter Wheat Yield Simulation Based on Assimilating LAI
Retrieved From Networked Optical and SAR Remotely Sensed Images Into
the WOFOST Model,
GeoRS(59), No. 11, November 2021, pp. 9071-9085.
IEEE DOI
2111
Agriculture, Remote sensing, Synthetic aperture radar,
Optical sensors, Optical imaging, Data models, Yield estimation,
yield simulation
BibRef
Fu, Y.Y.[Yang-Yang],
Huang, J.X.[Jian-Xi],
Shen, Y.J.[Yan-Jun],
Liu, S.M.[Shao-Min],
Huang, Y.[Yong],
Dong, J.[Jie],
Han, W.[Wei],
Ye, T.[Tao],
Zhao, W.Z.[Wen-Zhi],
Yuan, W.P.[Wen-Ping],
A Satellite-Based Method for National Winter Wheat Yield Estimating
in China,
RS(13), No. 22, 2021, pp. xx-yy.
DOI Link
2112
BibRef
Xie, Y.[Yi],
Huang, J.X.[Jian-Xi],
Integration of a Crop Growth Model and Deep Learning Methods to
Improve Satellite-Based Yield Estimation of Winter Wheat in Henan
Province, China,
RS(13), No. 21, 2021, pp. xx-yy.
DOI Link
2112
BibRef
Ganeva, D.[Dessislava],
Roumenina, E.[Eugenia],
Dimitrov, P.[Petar],
Gikov, A.[Alexander],
Jelev, G.[Georgi],
Dragov, R.[Rangel],
Bozhanova, V.[Violeta],
Taneva, K.[Krasimira],
Phenotypic Traits Estimation and Preliminary Yield Assessment in
Different Phenophases of Wheat Breeding Experiment Based on UAV
Multispectral Images,
RS(14), No. 4, 2022, pp. xx-yy.
DOI Link
2202
BibRef
Ahmed, A.A.M.[A. A. Masrur],
Sharma, E.[Ekta],
Jui, S.J.J.[S. Janifer Jabin],
Deo, R.C.[Ravinesh C.],
Nguyen-Huy, T.[Thong],
Ali, M.[Mumtaz],
Kernel Ridge Regression Hybrid Method for Wheat Yield Prediction with
Satellite-Derived Predictors,
RS(14), No. 5, 2022, pp. xx-yy.
DOI Link
2203
BibRef
Bian, C.F.[Chao-Fa],
Shi, H.T.[Hong-Tao],
Wu, S.[Suqin],
Zhang, K.F.[Ke-Fei],
Wei, M.[Meng],
Zhao, Y.[Yindi],
Sun, Y.Q.[Ya-Qin],
Zhuang, H.F.[Hui-Fu],
Zhang, X.W.[Xue-Wei],
Chen, S.[Shuo],
Prediction of Field-Scale Wheat Yield Using Machine Learning Method
and Multi-Spectral UAV Data,
RS(14), No. 6, 2022, pp. xx-yy.
DOI Link
2204
BibRef
Zare, H.[Hossein],
Weber, T.K.D.[Tobias K. D.],
Ingwersen, J.[Joachim],
Nowak, W.[Wolfgang],
Gayler, S.[Sebastian],
Streck, T.[Thilo],
Combining Crop Modeling with Remote Sensing Data Using a Particle
Filtering Technique to Produce Real-Time Forecasts of Winter Wheat
Yields under Uncertain Boundary Conditions,
RS(14), No. 6, 2022, pp. xx-yy.
DOI Link
2204
BibRef
Cao, J.J.[Jun-Jun],
Wang, H.J.[Hui-Jing],
Li, J.X.[Jin-Xiao],
Tian, Q.[Qun],
Niyogi, D.[Dev],
Improving the Forecasting of Winter Wheat Yields in Northern China
with Machine Learning-Dynamical Hybrid Subseasonal-to-Seasonal
Ensemble Prediction,
RS(14), No. 7, 2022, pp. xx-yy.
DOI Link
2205
BibRef
Deng, Q.Z.[Qiu-Zhuo],
Wu, M.X.[Meng-Xuan],
Zhang, H.Y.[Hai-Yang],
Cui, Y.T.[Yun-Tian],
Li, M.Z.[Min-Zan],
Zhang, Y.[Yao],
Winter Wheat Yield Estimation Based on Optimal Weighted Vegetation
Index and BHT-ARIMA Model,
RS(14), No. 9, 2022, pp. xx-yy.
DOI Link
2205
BibRef
Lu, J.J.[Jun-Jun],
Wang, H.Y.[Hong-Ye],
Miao, Y.X.[Yu-Xin],
Zhao, L.Q.[Li-Qin],
Zhao, G.M.[Guang-Ming],
Cao, Q.[Qiang],
Kusnierek, K.[Krzysztof],
Developing an Active Canopy Sensor-Based Integrated Precision Rice
Management System for Improving Grain Yield and Quality, Nitrogen Use
Efficiency, and Lodging Resistance,
RS(14), No. 10, 2022, pp. xx-yy.
DOI Link
2206
BibRef
Bognár, P.[Péter],
Kern, A.[Anikó],
Pásztor, S.[Szilárd],
Steinbach, P.[Péter],
Lichtenberger, J.[János],
Testing the Robust Yield Estimation Method for Winter Wheat, Corn,
Rapeseed, and Sunflower with Different Vegetation Indices and
Meteorological Data,
RS(14), No. 12, 2022, pp. xx-yy.
DOI Link
2206
BibRef
Meraj, G.[Gowhar],
Kanga, S.[Shruti],
Ambadkar, A.[Abhijeet],
Kumar, P.[Pankaj],
Singh, S.K.[Suraj Kumar],
Farooq, M.[Majid],
Johnson, B.A.[Brian Alan],
Rai, A.[Akshay],
Sahu, N.[Netrananda],
Assessing the Yield of Wheat Using Satellite Remote Sensing-Based
Machine Learning Algorithms and Simulation Modeling,
RS(14), No. 13, 2022, pp. xx-yy.
DOI Link
2208
BibRef
Wu, Y.T.[Yan-Tong],
Xu, W.B.[Wen-Bo],
Huang, H.[Hai],
Huang, J.X.[Jian-Xi],
Bayesian Posterior-Based Winter Wheat Yield Estimation at the Field
Scale through Assimilation of Sentinel-2 Data into WOFOST Model,
RS(14), No. 15, 2022, pp. xx-yy.
DOI Link
2208
BibRef
Bebie, M.[Maria],
Cavalaris, C.[Chris],
Kyparissis, A.[Aris],
Assessing Durum Wheat Yield through Sentinel-2 Imagery:
A Machine Learning Approach,
RS(14), No. 16, 2022, pp. xx-yy.
DOI Link
2208
BibRef
Feng, H.K.[Hai-Kuan],
Tao, H.L.[Hui-Lin],
Fan, Y.G.[Yi-Guang],
Liu, Y.[Yang],
Li, Z.H.[Zhen-Hai],
Yang, G.J.[Gui-Jun],
Zhao, C.J.[Chun-Jiang],
Comparison of Winter Wheat Yield Estimation Based on Near-Surface
Hyperspectral and UAV Hyperspectral Remote Sensing Data,
RS(14), No. 17, 2022, pp. xx-yy.
DOI Link
2209
BibRef
Hassan, M.A.[Muhammad Adeel],
Fei, S.[Shuaipeng],
Li, L.[Lei],
Jin, Y.R.[Yi-Rong],
Liu, P.[Peng],
Rasheed, A.[Awais],
Shawai, R.S.[Rabiu Sani],
Zhang, L.[Liang],
Ma, A.[Aimin],
Xiao, Y.G.[Yong-Gui],
He, Z.[Zhonghu],
Stacking of Canopy Spectral Reflectance from Multiple Growth Stages
Improves Grain Yield Prediction under Full and Limited Irrigation in
Wheat,
RS(14), No. 17, 2022, pp. xx-yy.
DOI Link
2209
BibRef
Tian, Z.Z.[Ze-Zhong],
Zhang, Y.[Yao],
Liu, K.D.[Kai-Di],
Li, Z.H.[Zhen-Hai],
Li, M.Z.[Min-Zan],
Zhang, H.Y.[Hai-Yang],
Wu, J.[Jiangmei],
UAV Remote Sensing Prediction Method of Winter Wheat Yield Based on
the Fused Features of Crop and Soil,
RS(14), No. 19, 2022, pp. xx-yy.
DOI Link
2210
BibRef
Huang, H.[Hai],
Huang, J.X.[Jian-Xi],
Feng, Q.L.[Quan-Long],
Liu, J.M.[Jun-Ming],
Li, X.C.[Xue-Cao],
Wang, X.L.[Xin-Lei],
Niu, Q.[Quandi],
Developing a Dual-Stream Deep-Learning Neural Network Model for
Improving County-Level Winter Wheat Yield Estimates in China,
RS(14), No. 20, 2022, pp. xx-yy.
DOI Link
2211
BibRef
Zhao, Y.[Yu],
Han, S.Y.[Shao-Yu],
Meng, Y.[Yang],
Feng, H.K.[Hai-Kuan],
Li, Z.H.[Zhen-Hai],
Chen, J.L.[Jing-Li],
Song, X.Y.[Xiao-Yu],
Zhu, Y.[Yan],
Yang, G.J.[Gui-Jun],
Transfer-Learning-Based Approach for Yield Prediction of Winter Wheat
from Planet Data and SAFY Model,
RS(14), No. 21, 2022, pp. xx-yy.
DOI Link
2212
BibRef
Karimli, N.[Nilufar],
Selbesoglu, M.O.[Mahmut Oguz],
Remote Sensing-Based Yield Estimation of Winter Wheat Using
Vegetation and Soil Indices in Jalilabad, Azerbaijan,
IJGI(12), No. 3, 2023, pp. xx-yy.
DOI Link
2303
BibRef
Uribeetxebarria, A.[Asier],
Castellón, A.[Ander],
Aizpurua, A.[Ana],
Optimizing Wheat Yield Prediction Integrating Data from Sentinel-1
and Sentinel-2 with CatBoost Algorithm,
RS(15), No. 6, 2023, pp. 1640.
DOI Link
2304
BibRef
Belmahi, M.[Mohamed],
Hanchane, M.[Mohamed],
Krakauer, N.Y.[Nir Y.],
Kessabi, R.[Ridouane],
Bouayad, H.[Hind],
Mahjoub, A.[Aziz],
Zouhri, D.[Driss],
Analysis of Relationship between Grain Yield and NDVI from MODIS in
the Fez-Meknes Region, Morocco,
RS(15), No. 11, 2023, pp. 2707.
DOI Link
2306
BibRef
Garcia-Perez, M.A.,
Rodriguez-Galiano, V.,
Sanchez-Rodriguez, E.,
Egea-Cobrero, V.,
Yield Estimation of Wheat Using Cropland Masks from European Common
Agrarian Policy: Comparing the Performance of Enhanced Vegetation
Index 2, Normalized Difference Vegetation Index, and MERIS
Terrestrial Chlorophyll Index in Spanish Nomenclature of Territorial
Units for Statistics Level 2 Regions,
RS(15), No. 22, 2023, pp. 5423.
DOI Link
2311
BibRef
Ma, J.C.[Jun-Cheng],
Wu, Y.F.[Yong-Feng],
Liu, B.[Binhui],
Zhang, W.Y.[Wen-Ying],
Wang, B.[Bianyin],
Chen, Z.Y.[Zhao-Yang],
Wang, G.C.[Guang-Cai],
Guo, A.[Anqiang],
Wheat Yield Prediction Using Unmanned Aerial Vehicle
RGB-Imagery-Based Convolutional Neural Network and Limited Training
Samples,
RS(15), No. 23, 2023, pp. 5444.
DOI Link
2312
BibRef
Ganeva, D.[Dessislava],
Roumenina, E.[Eugenia],
Dimitrov, P.[Petar],
Gikov, A.[Alexander],
Bozhanova, V.[Violeta],
Dragov, R.[Rangel],
Jelev, G.[Georgi],
Taneva, K.[Krasimira],
Preharvest Durum Wheat Yield, Protein Content, and Protein Yield
Estimation Using Unmanned Aerial Vehicle Imagery and Pleiades
Satellite Data in Field Breeding Experiments,
RS(16), No. 3, 2024, pp. 559.
DOI Link
2402
BibRef
Zhang, M.[Meng],
Sun, P.J.[Pei-Jun],
Sun, Z.L.[Zhang-Li],
Spatiotemporally Mapping Non-Grain Production of Winter Wheat Using a
Developed Auto-Generating Sample Algorithm on Google Earth Engine,
RS(16), No. 4, 2024, pp. 659.
DOI Link
2402
BibRef
Kamenova, I.[Ilina],
Chanev, M.[Milen],
Dimitrov, P.[Petar],
Filchev, L.[Lachezar],
Bonchev, B.[Bogdan],
Zhu, L.[Liang],
Dong, Q.[Qinghan],
Crop Type Mapping and Winter Wheat Yield Prediction Utilizing
Sentinel-2: A Case Study from Upper Thracian Lowland, Bulgaria,
RS(16), No. 7, 2024, pp. 1144.
DOI Link
2404
BibRef
Zhao, Y.X.[Yan-Xi],
He, J.[Jiaoyang],
Yao, X.[Xia],
Cheng, T.[Tao],
Zhu, Y.[Yan],
Cao, W.X.[Wei-Xing],
Tian, Y.C.[Yong-Chao],
Wheat Yield Robust Prediction in the Huang-Huai-Hai Plain by Coupling
Multi-Source Data with Ensemble Model under Different Irrigation and
Extreme Weather Events,
RS(16), No. 7, 2024, pp. 1259.
DOI Link
2404
BibRef
Wang, Z.[Ziwen],
Zhang, C.M.[Chuan-Mao],
Gao, L.X.[Li-Xin],
Fan, C.Z.[Cheng-Zhi],
Xu, X.X.[Xue-Xin],
Zhang, F.Z.[Fang-Zhao],
Zhou, Y.M.[Yi-Ming],
Niu, F.P.[Fang-Peng],
Li, Z.H.[Zhen-Hai],
Time Phase Selection and Accuracy Analysis for Predicting Winter
Wheat Yield Based on Time Series Vegetation Index,
RS(16), No. 11, 2024, pp. 1995.
DOI Link
2406
BibRef
Li, Z.P.[Zong-Peng],
Cheng, Q.[Qian],
Chen, L.[Li],
Zhang, B.[Bo],
Guo, S.[Shuzhe],
Zhou, X.G.[Xin-Guo],
Chen, Z.[Zhen],
Predicting Winter Wheat Yield with Dual-Year Spectral Fusion,
Bayesian Wisdom, and Cross-Environmental Validation,
RS(16), No. 12, 2024, pp. 2098.
DOI Link
2406
BibRef
Zhang, Z.[Zhao],
Luo, Y.C.[Yu-Chuan],
Han, J.C.[Ji-Chong],
Xu, J.[Jialu],
Tao, F.[Fulu],
Estimating Global Wheat Yields at 4 km Resolution during 1982-2020 by
a Spatiotemporal Transferable Method,
RS(16), No. 13, 2024, pp. 2342.
DOI Link
2407
BibRef
Li, S.[Shiji],
Huang, J.X.[Jian-Xi],
Xiao, G.[Guilong],
Huang, H.[Hai],
Sun, Z.G.[Zhi-Gang],
Li, X.C.[Xue-Cao],
Improved Winter Wheat Yield Estimation by Combining Remote Sensing
Data, Machine Learning, and Phenological Metrics,
RS(16), No. 17, 2024, pp. 3217.
DOI Link
2409
BibRef
Chiu, M.S.[Marco Spencer],
Wang, J.F.[Jin-Fei],
Local Field-Scale Winter Wheat Yield Prediction Using VENµS Satellite
Imagery and Machine Learning Techniques,
RS(16), No. 17, 2024, pp. 3132.
DOI Link
2409
BibRef
Peng, D.[Dailiang],
Cheng, E.[Enhui],
Feng, X.[Xuxiang],
Hu, J.[Jinkang],
Lou, Z.H.[Zi-Hang],
Zhang, H.C.[Hong-Chi],
Zhao, B.[Bin],
Lv, Y.L.[Yu-Long],
Peng, H.[Hao],
Zhang, B.[Bing],
A Deep-Learning Network for Wheat Yield Prediction Combining Weather
Forecasts and Remote Sensing Data,
RS(16), No. 19, 2024, pp. 3613.
DOI Link
2410
BibRef
Zhou, X.J.[Xi-Jia],
Wang, T.[Tao],
Zheng, W.[Wei],
Zhang, M.W.[Ming-Wei],
Wang, Y.Y.[Yuan-Yuan],
Reconstruction of Fine-Spatial-Resolution FY-3D-Based Vegetation
Indices to Achieve Farmland-Scale Winter Wheat Yield Estimation via
Fusion with Sentinel-2 Data,
RS(16), No. 22, 2024, pp. 4143.
DOI Link
2412
BibRef
Shen, Y.L.[Yu-Lin],
Mercatoris, B.[Benoît],
Liu, Q.Z.[Qing-Zhi],
Yao, H.X.[Hong-Xun],
Li, Z.P.[Zong-Peng],
Chen, Z.[Zhen],
Wang, W.[Wensheng],
Use Self-Training Random Forest for Predicting Winter Wheat Yield,
RS(16), No. 24, 2024, pp. 4723.
DOI Link
2501
BibRef
Zhang, H.,
Chen, H.,
Zhou, G.,
The Model Of Wheat Yield Forecast Based On Modis-ndvi: A Case Study Of
Xinxiang,
AnnalsPRS(I-7), No. 2012, pp. 25-28.
DOI Link
1209
BibRef
Chapter on Remote Sensing General Issue, Land Use, Land Cover continues in
Wheat Rust, Blight, Disease, Damage .