23.2.8.5 Wheat Crop Analysis, Detection, Change

Chapter Contents (Back)
Classification. Wheat Classification. Includes some similar grains, rye, etc.
See also Wheat Yield Estimates, Prediction.
See also Wheat Rust, Blight, Disease, Damage. Related grains:
See also Barley.
See also Gross Primary Production, Net Primary Production, GPP, NPP. A number of wheat related papers with canola:
See also Rapeseed Crop Analysis, Canola Analysis, Production, Detection.

Haralick, R.M.[Robert M.], Hlavka, C.A., Carlyle, S.M., and Yokoyama, R.,
The Discrimination of Winter Wheat Using a Growth-State Signature,
RSE(9), 1980, pp. 277-294. BibRef 8000

Hosoi, F.[Fumiki], Omasa, K.[Kenji],
Estimating vertical plant area density profile and growth parameters of a wheat canopy at different growth stages using three-dimensional portable lidar imaging,
PandRS(64), No. 2, March 2009, pp. 151-158.
Elsevier DOI 0903
Carbon stock; Plant area density; Portable scanning lidar; Three-dimensional imaging; Voxel-based canopy profiling BibRef

Koppe, W.[Wolfgang], Gnyp, M.L.[Martin L.], Hennig, S.D.[Simon D.], Li, F.[Fei], Miao, Y.X.[Yu-Xin], Chen, X.P.[Xin-Ping], Jia, L.L.[Liang-Liang], Bareth, G.[Georg],
Multi-Temporal Hyperspectral and Radar Remote Sensing for Estimating Winter Wheat Biomass in the North China Plain,
PFG(2012), No. 3, 2012, pp. 281-298.
WWW Link. 1211
BibRef

Koppe, W.[Wolfgang], Li, F.[Fei], Gnyp, M.L.[Martin L.], Miao, Y.X.[Yu-Xin], Jia, L.L.[Liang-Liang], Chen, X.P.[Xin-Ping], Zhang, F.[Fusuo], Bareth, G.[Georg],
Evaluating Multispectral and Hyperspectral Satellite Remote Sensing Data for Estimating Winter Wheat Growth Parameters at Regional Scale in the North China Plain,
PFG(2010), No. 3, 2010, pp. 167-178.
WWW Link. 1211
BibRef

Cammarano, D.[Davide], Fitzgerald, G.J.[Glenn J.], Casa, R.[Raffaele], Basso, B.[Bruno],
Assessing the Robustness of Vegetation Indices to Estimate Wheat N in Mediterranean Environments,
RS(6), No. 4, 2014, pp. 2827-2844.
DOI Link 1405
Nitrogen. BibRef

Li, F.[Fei], Mistele, B.[Bodo], Hu, Y.C.[Yun-Cai], Chen, X.P.[Xin-Ping], Schmidhalter, U.[Urs],
Optimising three-band spectral indices to assess aerial N concentration, N uptake and aboveground biomass of winter wheat remotely in China and Germany,
PandRS(92), No. 1, 2014, pp. 112-123.
Elsevier DOI 1407
Band selection BibRef

Vincini, M., Amaducci, S., Frazzi, E.,
Empirical Estimation of Leaf Chlorophyll Density in Winter Wheat Canopies Using Sentinel-2 Spectral Resolution,
GeoRS(52), No. 6, June 2014, pp. 3220-3235.
IEEE DOI 1403
BibRef
And: Corrections: GeoRS(52), No. 6, June 2014, pp. 3753-3753.
IEEE DOI 1403
Equations Agriculture BibRef

Burkart, A.[Andreas], Aasen, H.[Helge], Alonso, L.[Luis], Menz, G.[Gunter], Bareth, G.[Georg], Rascher, U.[Uwe],
Angular Dependency of Hyperspectral Measurements over Wheat Characterized by a Novel UAV Based Goniometer,
RS(7), No. 1, 2015, pp. 725-746.
DOI Link 1502
BibRef

Ali, M.[Muhammad], Montzka, C.[Carsten], Stadler, A.[Anja], Menz, G.[Gunter], Thonfeld, F.[Frank], Vereecken, H.[Harry],
Estimation and Validation of RapidEye-Based Time-Series of Leaf Area Index for Winter Wheat in the Rur Catchment (Germany),
RS(7), No. 3, 2015, pp. 2808-2831.
DOI Link 1504
BibRef

Tanaka, S.[Shinya], Kawamura, K.[Kensuke], Maki, M.[Masayasu], Muramoto, Y.[Yasunori], Yoshida, K.[Kazuaki], Akiyama, T.[Tsuyoshi],
Spectral Index for Quantifying Leaf Area Index of Winter Wheat by Field Hyperspectral Measurements: A Case Study in Gifu Prefecture, Central Japan,
RS(7), No. 5, 2015, pp. 5329-5346.
DOI Link 1506
BibRef

Gonzalez-Dugo, V.[Victoria], Hernandez, P.[Pilar], Solis, I.[Ignacio], Zarco-Tejada, P.J.[Pablo J.],
Using High-Resolution Hyperspectral and Thermal Airborne Imagery to Assess Physiological Condition in the Context of Wheat Phenotyping,
RS(7), No. 10, 2015, pp. 13586.
DOI Link 1511
BibRef

Jin, X.L.[Xiu-Liang], Yang, G.J.[Gui-Jun], Xu, X.G.[Xin-Gang], Yang, H.[Hao], Feng, H.K.[Hai-Kuan], Li, Z.H.[Zhen-Hai], Shen, J.X.[Jia-Xiao], Lan, Y.B.[Yu-Bin], Zhao, C.J.[Chun-Jiang],
Combined Multi-Temporal Optical and Radar Parameters for Estimating LAI and Biomass in Winter Wheat Using HJ and RADARSAR-2 Data,
RS(7), No. 10, 2015, pp. 13251.
DOI Link 1511
BibRef

Siegmann, B.[Bastian], Jarmer, T.[Thomas], Beyer, F.[Florian], Ehlers, M.[Manfred],
The Potential of Pan-Sharpened EnMAP Data for the Assessment of Wheat LAI,
RS(7), No. 10, 2015, pp. 12737.
DOI Link 1511
BibRef

Jin, N.[Ning], Tao, B.[Bo], Ren, W.[Wei], Feng, M.C.[Mei-Chen], Sun, R.[Rui], He, L.[Liang], Zhuang, W.[Wei], Yu, Q.A.[Qi-Ang],
Mapping Irrigated and Rainfed Wheat Areas Using Multi-Temporal Satellite Data,
RS(8), No. 3, 2016, pp. 207.
DOI Link 1604
BibRef

Liu, L., Liu, X., Wang, Z., Zhang, B.,
Measurement and Analysis of Bidirectional SIF Emissions in Wheat Canopies,
GeoRS(54), No. 5, May 2016, pp. 2640-2651.
IEEE DOI 1604
geophysical techniques BibRef

Boyle, R.D., Corke, F.M.K., Doonan, J.H.,
Automated estimation of tiller number in wheat by ribbon detection,
MVA(27), No. 5, July 2016, pp. 637-646.
Springer DOI 1608
BibRef

Schirrmann, M.[Michael], Giebel, A.[Antje], Gleiniger, F.[Franziska], Pflanz, M.[Michael], Lentschke, J.[Jan], Dammer, K.H.[Karl-Heinz],
Monitoring Agronomic Parameters of Winter Wheat Crops with Low-Cost UAV Imagery,
RS(8), No. 9, 2016, pp. 706.
DOI Link 1610
BibRef

Schirrmann, M.[Michael], Hamdorf, A.[André], Giebel, A.[Antje], Gleiniger, F.[Franziska], Pflanz, M.[Michael], Dammer, K.H.[Karl-Heinz],
Regression Kriging for Improving Crop Height Models Fusing Ultra-Sonic Sensing with UAV Imagery,
RS(9), No. 7, 2017, pp. xx-yy.
DOI Link 1708
BibRef

Zhang, X.[Xin], Zhang, M.[Miao], Zheng, Y.[Yang], Wu, B.F.[Bing-Fang],
Crop Mapping Using PROBA-V Time Series Data at the Yucheng and Hongxing Farm in China,
RS(8), No. 11, 2016, pp. 915.
DOI Link 1612
BibRef

Song, X.[Xiao], Feng, W.[Wei], He, L.[Li], Xu, D.Y.[Duan-Yang], Zhang, H.Y.[Hai-Yan], Li, X.[Xiao], Wang, Z.J.[Zhi-Jie], Coburn, C.A.[Craig A.], Wang, C.Y.[Chen-Yang], Guo, T.C.[Tian-Cai],
Examining view angle effects on leaf N estimation in wheat using field reflectance spectroscopy,
PandRS(122), No. 1, 2016, pp. 57-67.
Elsevier DOI 1612
Wheat BibRef

Holman, F.H.[Fenner H.], Riche, A.B.[Andrew B.], Michalski, A.[Adam], Castle, M.[March], Wooster, M.J.[Martin J.], Hawkesford, M.J.[Malcolm J.],
High Throughput Field Phenotyping of Wheat Plant Height and Growth Rate in Field Plot Trials Using UAV Based Remote Sensing,
RS(8), No. 12, 2016, pp. 1031.
DOI Link 1612
BibRef

Qiu, B.W.[Bing-Wen], Luo, Y.H.[Yu-Han], Tang, Z.H.[Zheng-Hong], Chen, C.C.[Chong-Cheng], Lu, D.F.[Di-Fei], Huang, H.Y.[Hong-Yu], Chen, Y.Z.[Yun-Zhi], Chen, N.[Nan], Xu, W.M.[Wei-Ming],
Winter wheat mapping combining variations before and after estimated heading dates,
PandRS(123), No. 1, 2017, pp. 35-46.
Elsevier DOI 1612
Time series analysis BibRef

Zhao, C., Li, H., Li, P., Yang, G., Gu, X., Lan, Y.,
Effect of Vertical Distribution of Crop Structure and Biochemical Parameters of Winter Wheat on Canopy Reflectance Characteristics and Spectral Indices,
GeoRS(55), No. 1, January 2017, pp. 236-247.
IEEE DOI 1701
vegetation BibRef

Goulas, Y.[Yves], Fournier, A.[Antoine], Daumard, F.[Fabrice], Champagne, S.[Sébastien], Ounis, A.[Abderrahmane], Marloie, O.[Olivier], Moya, I.[Ismael],
Gross Primary Production of a Wheat Canopy Relates Stronger to Far Red Than to Red Solar-Induced Chlorophyll Fluorescence,
RS(9), No. 1, 2017, pp. xx-yy.
DOI Link 1702
BibRef

Dahms, T.[Thorsten], Seissiger, S.[Sylvia], Borg, E.[Erik], Vajen, H.[Hermann], Fichtelmann, B.[Bernd], Conrad, C.[Christopher],
Important Variables of a RapidEye Time Series for Modelling Biophysical Parameters of Winter Wheat,
PFG(2016), No. 5-6, 2016, pp. 285-299.
DOI Link 1703

See also Modelling Biophysical Parameters of Maize Using Landsat 8 Time Series. BibRef

Liu, Z.J.[Zheng-Jia], Wu, C.Y.[Chao-Yang], Liu, Y.S.[Yan-Sui], Wang, X.Y.[Xiao-Yue], Fang, B.[Bin], Yuan, W.P.[Wen-Ping], Ge, Q.S.[Quan-Sheng],
Spring green-up date derived from GIMMS3g and SPOT-VGT NDVI of winter wheat cropland in the North China Plain,
PandRS(130), No. 1, 2017, pp. 81-91.
Elsevier DOI 1708
Spring, phenology BibRef

Yue, J.[Jibo], Yang, G.J.[Gui-Jun], Li, C.C.[Chang-Chun], Li, Z.H.[Zhen-Hai], Wang, Y.J.[Yan-Jie], Feng, H.K.[Hai-Kuan], Xu, B.[Bo],
Estimation of Winter Wheat Above-Ground Biomass Using Unmanned Aerial Vehicle-Based Snapshot Hyperspectral Sensor and Crop Height Improved Models,
RS(9), No. 7, 2017, pp. xx-yy.
DOI Link 1708
BibRef

Yue, J.[Jibo], Feng, H.K.[Hai-Kuan], Yang, G.J.[Gui-Jun], Li, Z.H.[Zhen-Hai],
A Comparison of Regression Techniques for Estimation of Above-Ground Winter Wheat Biomass Using Near-Surface Spectroscopy,
RS(10), No. 1, 2018, pp. xx-yy.
DOI Link 1802
BibRef

Liu, T.[Tao], Li, R.[Rui], Jin, X.[Xiuliang], Ding, J.F.[Jin-Feng], Zhu, X.[Xinkai], Sun, C.M.[Cheng-Ming], Guo, W.[Wenshan],
Evaluation of Seed Emergence Uniformity of Mechanically Sown Wheat with UAV RGB Imagery,
RS(9), No. 12, 2017, pp. xx-yy.
DOI Link 1802
BibRef

Yao, X.[Xia], Wang, N.[Ni], Liu, Y.[Yong], Cheng, T.[Tao], Tian, Y.C.[Yong-Chao], Chen, Q.[Qi], Zhu, Y.[Yan],
Estimation of Wheat LAI at Middle to High Levels Using Unmanned Aerial Vehicle Narrowband Multispectral Imagery,
RS(9), No. 12, 2017, pp. xx-yy.
DOI Link 1802
BibRef

Zhou, C.Q.[Cheng-Quan], Liang, D.[Dong], Yang, X.D.[Xiao-Dong], Xu, B.[Bo], Yang, G.J.[Gui-Jun],
Recognition of Wheat Spike from Field Based Phenotype Platform Using Multi-Sensor Fusion and Improved Maximum Entropy Segmentation Algorithms,
RS(10), No. 2, 2018, pp. xx-yy.
DOI Link 1804
BibRef

Khan, A.[Ahmad], Hansen, M.C.[Matthew C.], Potapov, P.V.[Peter V.], Adusei, B.[Bernard], Pickens, A.[Amy], Krylov, A.[Alexander], Stehman, S.V.[Stephen V.],
Evaluating Landsat and RapidEye Data for Winter Wheat Mapping and Area Estimation in Punjab, Pakistan,
RS(10), No. 4, 2018, pp. xx-yy.
DOI Link 1805
BibRef

Hassan, M.A.[Muhammad Adeel], Yang, M.J.[Meng-Jiao], Rasheed, A.[Awais], Jin, X.L.[Xiu-Liang], Xia, X.C.[Xian-Chun], Xiao, Y.G.[Yong-Gui], He, Z.H.[Zhong-Hu],
Time-Series Multispectral Indices from Unmanned Aerial Vehicle Imagery Reveal Senescence Rate in Bread Wheat,
RS(10), No. 6, 2018, pp. xx-yy.
DOI Link 1806
BibRef

Sui, J.[Juan], Qin, Q.M.[Qi-Ming], Ren, H.Z.[Hua-Zhong], Sun, Y.H.[Yuan-Heng], Zhang, T.Y.[Tian-Yuan], Wang, J.D.[Jian-Dong], Gong, S.H.[Shi-Hong],
Winter Wheat Production Estimation Based on Environmental Stress Factors from Satellite Observations,
RS(10), No. 6, 2018, pp. xx-yy.
DOI Link 1806
BibRef

Khan, Z.[Zohaib], Chopin, J.[Joshua], Cai, J.H.[Jin-Hai], Eichi, V.R.[Vahid-Rahimi], Haefele, S.[Stephan], Miklavcic, S.J.[Stanley J.],
Quantitative Estimation of Wheat Phenotyping Traits Using Ground and Aerial Imagery,
RS(10), No. 6, 2018, pp. xx-yy.
DOI Link 1806
BibRef
And: Erratum: RS(10), No. 7, 2018, pp. xx-yy.
DOI Link 1808
BibRef

Liu, J.H.[Jian-Hong], Zhu, W.Q.[Wen-Quan], Atzberger, C.[Clement], Zhao, A.Z.[An-Zhou], Pan, Y.Z.[Yao-Zhong], Huang, X.[Xin],
A Phenology-Based Method to Map Cropping Patterns under a Wheat-Maize Rotation Using Remotely Sensed Time-Series Data,
RS(10), No. 8, 2018, pp. xx-yy.
DOI Link 1809
BibRef

Meyer, T.[Thomas], Weihermüller, L.[Lutz], Vereecken, H.[Harry], Jonard, F.[François],
Vegetation Optical Depth and Soil Moisture Retrieved from L-Band Radiometry over the Growth Cycle of a Winter Wheat,
RS(10), No. 10, 2018, pp. xx-yy.
DOI Link 1811
BibRef

Chen, H.Y.[Han-Yue], Huang, W.J.[Wen-Jiang], Li, W.[Wang], Niu, Z.[Zheng], Zhang, L.M.[Li-Ming], Xing, S.[Shihe],
Estimation of LAI in Winter Wheat from Multi-Angular Hyperspectral VNIR Data: Effects of View Angles and Plant Architecture,
RS(10), No. 10, 2018, pp. xx-yy.
DOI Link 1811
BibRef

Kuester, T.[Theres], Spengler, D.[Daniel],
Structural and Spectral Analysis of Cereal Canopy Reflectance and Reflectance Anisotropy,
RS(10), No. 11, 2018, pp. xx-yy.
DOI Link 1812
BibRef

El Hajj, M.[Mohammad], Baghdadi, N.[Nicolas], Bazzi, H.[Hassan], Zribi, M.[Mehrez],
Penetration Analysis of SAR Signals in the C and L Bands for Wheat, Maize, and Grasslands,
RS(11), No. 1, 2018, pp. xx-yy.
DOI Link 1901
BibRef

Liu, L.Y.[Lin-Yi], Dong, Y.Y.[Ying-Ying], Huang, W.J.[Wen-Jiang], Du, X.P.[Xiao-Ping], Luo, J.[Juhua], Shi, Y.[Yue], Ma, H.Q.[Hui-Qin],
Enhanced Regional Monitoring of Wheat Powdery Mildew Based on an Instance-Based Transfer Learning Method,
RS(11), No. 3, 2019, pp. xx-yy.
DOI Link 1902
BibRef

He, L., Coburn, C.A., Wang, Z., Feng, W., Guo, T.,
Reduced Prediction Saturation and View Effects for Estimating the Leaf Area Index of Winter Wheat,
GeoRS(57), No. 3, March 2019, pp. 1637-1652.
IEEE DOI 1903
crops, soil, vegetation mapping, reduced prediction saturation, view effects, leaf area index, winter wheat, vegetation indices, LAI, winter wheat BibRef

Yue, J.[Jibo], Yang, G.J.[Gui-Jun], Tian, Q.J.[Qing-Jiu], Feng, H.K.[Hai-Kuan], Xu, K.J.[Kai-Jian], Zhou, C.Q.[Cheng-Quan],
Estimate of winter-wheat above-ground biomass based on UAV ultrahigh-ground-resolution image textures and vegetation indices,
PandRS(150), 2019, pp. 226-244.
Elsevier DOI 1903
Unmanned aerial vehicle, Vegetation indices, Ultrahigh ground-resolution image, Image textures, Reproductive growth stages BibRef

Song, Y.[Yang], Wang, J.[Jing],
Mapping Winter Wheat Planting Area and Monitoring Its Phenology Using Sentinel-1 Backscatter Time Series,
RS(11), No. 4, 2019, pp. xx-yy.
DOI Link 1903
BibRef

Upreti, D.[Deepak], Huang, W.J.[Wen-Jiang], Kong, W.P.[Wei-Ping], Pascucci, S.[Simone], Pignatti, S.[Stefano], Zhou, X.F.[Xian-Feng], Ye, H.[Huichun], Casa, R.[Raffaele],
A Comparison of Hybrid Machine Learning Algorithms for the Retrieval of Wheat Biophysical Variables from Sentinel-2,
RS(11), No. 5, 2019, pp. xx-yy.
DOI Link 1903
BibRef

He, Y.H.[Yuan-Huizi], Wang, C.L.[Chang-Lin], Chen, F.[Fang], Jia, H.C.[Hui-Cong], Liang, D.[Dong], Yang, A.[Aqiang],
Feature Comparison and Optimization for 30-M Winter Wheat Mapping Based on Landsat-8 and Sentinel-2 Data Using Random Forest Algorithm,
RS(11), No. 5, 2019, pp. xx-yy.
DOI Link 1903
BibRef

Zhang, C.M.[Cheng-Ming], Han, Y.J.[Ying-Juan], Li, F.[Feng], Gao, S.[Shuai], Song, D.[Dejuan], Zhao, H.[Hui], Fan, K.Q.[Ke-Qi], Zhang, Y.[Ya'nan],
A New CNN-Bayesian Model for Extracting Improved Winter Wheat Spatial Distribution from GF-2 imagery,
RS(11), No. 6, 2019, pp. xx-yy.
DOI Link 1903
BibRef

Ma, H.Q.[Hui-Qin], Huang, W.J.[Wen-Jiang], Jing, Y.S.[Yuan-Shu], Yang, C.H.[Cheng-Hai], Han, L.X.[Liang-Xiu], Dong, Y.Y.[Ying-Ying], Ye, H.C.[Hui-Chun], Shi, Y.[Yue], Zheng, Q.[Qiong], Liu, L.Y.[Lin-Yi], Ruan, C.[Chao],
Integrating Growth and Environmental Parameters to Discriminate Powdery Mildew and Aphid of Winter Wheat Using Bi-Temporal Landsat-8 Imagery,
RS(11), No. 7, 2019, pp. xx-yy.
DOI Link 1904
BibRef

Fernandez-Gallego, J.A.[Jose A.], Buchaillot, M.L.[Ma. Luisa], Gutiérrez, N.A.[Nieves Aparicio], Nieto-Taladriz, M.T.[María Teresa], Araus, J.L.[José Luis], Kefauver, S.C.[Shawn C.],
Automatic Wheat Ear Counting Using Thermal Imagery,
RS(11), No. 7, 2019, pp. xx-yy.
DOI Link 1904
BibRef

Shah, S.H.[Syed Haleem], Angel, Y.[Yoseline], Houborg, R.[Rasmus], Ali, S.[Shawkat], McCabe, M.F.[Matthew F.],
A Random Forest Machine Learning Approach for the Retrieval of Leaf Chlorophyll Content in Wheat,
RS(11), No. 8, 2019, pp. xx-yy.
DOI Link 1905
BibRef

Ren, S.[Shilong], Qin, Q.M.[Qi-Ming], Ren, H.Z.[Hua-Zhong], Sui, J.[Juan], Zhang, Y.[Yao],
Heat and Drought Stress Advanced Global Wheat Harvest Timing from 1981-2014,
RS(11), No. 8, 2019, pp. xx-yy.
DOI Link 1905
BibRef

Cui, B.[Bei], Zhao, Q.J.[Qian-Jun], Huang, W.J.[Wen-Jiang], Song, X.Y.[Xiao-Yu], Ye, H.C.[Hui-Chun], Zhou, X.F.[Xian-Feng],
A New Integrated Vegetation Index for the Estimation of Winter Wheat Leaf Chlorophyll Content,
RS(11), No. 8, 2019, pp. xx-yy.
DOI Link 1905
BibRef

Aranguren, M.[Marta], Castellón, A.[Ander], Aizpurua, A.[Ana],
Crop Sensor-Based In-Season Nitrogen Management of Wheat with Manure Application,
RS(11), No. 9, 2019, pp. xx-yy.
DOI Link 1905
BibRef

Xiong, B.[Biao], Wang, B.[Bo], Xiong, S.W.[Sheng-Wu], Lin, C.D.[Cheng-De], Yuan, X.H.[Xiao-Hui],
3D Morphological Processing for Wheat Spike Phenotypes Using Computed Tomography Images,
RS(11), No. 9, 2019, pp. xx-yy.
DOI Link 1905
BibRef

Danner, M.[Martin], Berger, K.[Katja], Wocher, M.[Matthias], Mauser, W.[Wolfram], Hank, T.[Tobias],
Fitted PROSAIL Parameterization of Leaf Inclinations, Water Content and Brown Pigment Content for Winter Wheat and Maize Canopies,
RS(11), No. 10, 2019, pp. xx-yy.
DOI Link 1906
BibRef

Yang, Y.J.[Yan-Jun], Tao, B.[Bo], Ren, W.[Wei], Zourarakis, D.P.[Demetrio P.], El Masri, B.[Bassil], Sun, Z.G.[Zhi-Gang], Tian, Q.J.[Qing-Jiu],
An Improved Approach Considering Intraclass Variability for Mapping Winter Wheat Using Multitemporal MODIS EVI Images,
RS(11), No. 10, 2019, pp. xx-yy.
DOI Link 1906
BibRef

Song, Y.[Yang], Wang, J.F.[Jin-Fei],
Winter Wheat Canopy Height Extraction from UAV-Based Point Cloud Data with a Moving Cuboid Filter,
RS(11), No. 10, 2019, pp. xx-yy.
DOI Link 1906
BibRef

Gracia-Romero, A.[Adrian], Kefauver, S.C.[Shawn C.], Fernandez-Gallego, J.A.[Jose A.], Vergara-Díaz, O.[Omar], Nieto-Taladriz, M.T.[María Teresa], Araus, J.L.[José L.],
UAV and Ground Image-Based Phenotyping: A Proof of Concept with Durum Wheat,
RS(11), No. 10, 2019, pp. xx-yy.
DOI Link 1906
BibRef

Li, F.L.[Fen-Ling], Wang, L.[Li], Liu, J.[Jing], Wang, Y.[Yuna], Chang, Q.R.[Qing-Rui],
Evaluation of Leaf N Concentration in Winter Wheat Based on Discrete Wavelet Transform Analysis,
RS(11), No. 11, 2019, pp. xx-yy.
DOI Link 1906
BibRef

Guo, L.H.[Ling-Hui], Gao, J.B.[Jiang-Bo], Hao, C.Y.[Cheng-Yuan], Zhang, L.L.[Lin-Lin], Wu, S.H.[Shao-Hong], Xiao, X.M.[Xiang-Ming],
Winter Wheat Green-up Date Variation and its Diverse Response on the Hydrothermal Conditions over the North China Plain, Using MODIS Time-Series Data,
RS(11), No. 13, 2019, pp. xx-yy.
DOI Link 1907
BibRef

Zhang, C.[Chao], Liu, J.[Jiangui], Dong, T.[Taifeng], Pattey, E.[Elizabeth], Shang, J.L.[Jia-Li], Tang, M.[Min], Cai, H.[Huanjie], Saddique, Q.[Qaisar],
Coupling Hyperspectral Remote Sensing Data with a Crop Model to Study Winter Wheat Water Demand,
RS(11), No. 14, 2019, pp. xx-yy.
DOI Link 1908
BibRef

He, T.[Tianle], Xie, C.J.[Chuan-Jie], Liu, Q.S.[Qing-Sheng], Guan, S.Y.[Shi-Ying], Liu, G.H.[Gao-Huan],
Evaluation and Comparison of Random Forest and A-LSTM Networks for Large-scale Winter Wheat Identification,
RS(11), No. 14, 2019, pp. xx-yy.
DOI Link 1908
BibRef

Prudnikova, E.[Elena], Savin, I.[Igor], Vindeker, G.[Gretelerika], Grubina, P.[Praskovia], Shishkonakova, E.[Ekaterina], Sharychev, D.[David],
Influence of Soil Background on Spectral Reflectance of Winter Wheat Crop Canopy,
RS(11), No. 16, 2019, pp. xx-yy.
DOI Link 1909
BibRef

Revill, A.[Andrew], Florence, A.[Anna], MacArthur, A.[Alasdair], Hoad, S.P.[Stephen P.], Rees, R.M.[Robert M.], Williams, M.[Mathew],
The Value of Sentinel-2 Spectral Bands for the Assessment of Winter Wheat Growth and Development,
RS(11), No. 17, 2019, pp. xx-yy.
DOI Link 1909
BibRef

Nasrallah, A.[Ali], Baghdadi, N.[Nicolas], El Hajj, M.[Mohammad], Darwish, T.[Talal], Belhouchette, H.[Hatem], Faour, G.[Ghaleb], Darwich, S.[Salem], Mhawej, M.[Mario],
Sentinel-1 Data for Winter Wheat Phenology Monitoring and Mapping,
RS(11), No. 19, 2019, pp. xx-yy.
DOI Link 1910
BibRef

Meyer, T.[Thomas], Jagdhuber, T.[Thomas], Piles, M.[María], Fink, A.[Anita], Grant, J.[Jennifer], Vereecken, H.[Harry], Jonard, F.[François],
Estimating Gravimetric Water Content of a Winter Wheat Field from L-Band Vegetation Optical Depth,
RS(11), No. 20, 2019, pp. xx-yy.
DOI Link 1910
BibRef

Zhu, W.X.[Wan-Xue], Sun, Z.G.[Zhi-Gang], Huang, Y.H.[Yao-Huan], Lai, J.B.[Jian-Bin], Li, J.[Jing], Zhang, J.Q.A.[Jun-Qi-Ang], Yang, B.[Bin], Li, B.B.[Bin-Bin], Li, S.[Shiji], Zhu, K.Y.[Kang-Ying], Li, Y.[Yang], Liao, X.H.[Xiao-Han],
Improving Field-Scale Wheat LAI Retrieval Based on UAV Remote-Sensing Observations and Optimized VI-LUTs,
RS(11), No. 20, 2019, pp. xx-yy.
DOI Link 1910
BibRef

Zhang, D.Y.[Dong-Yan], Fang, S.M.[Sheng-Mei], She, B.[Bao], Zhang, H.H.[Hui-Hui], Jin, N.[Ning], Xia, H.M.[Hao-Ming], Yang, Y.Y.[Yu-Ying], Ding, Y.[Yang],
Winter Wheat Mapping Based on Sentinel-2 Data in Heterogeneous Planting Conditions,
RS(11), No. 22, 2019, pp. xx-yy.
DOI Link 1911
BibRef

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Quantifying Chlorophyll Fluorescence Parameters from Hyperspectral Reflectance at the Leaf Scale under Various Nitrogen Treatment Regimes in Winter Wheat,
RS(11), No. 23, 2019, pp. xx-yy.
DOI Link 1912
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Wu, X.F.[Xi-Fang], Yang, W.[Wei], Wang, C.Y.[Chun-Yang], Shen, Y.J.[Yan-Jun], Kondoh, A.[Akihiko],
Interactions among the Phenological Events of Winter Wheat in the North China Plain-Based on Field Data and Improved MODIS Estimation,
RS(11), No. 24, 2019, pp. xx-yy.
DOI Link 1912
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Marino, S.[Stefano], Alvino, A.[Arturo],
Agronomic Traits Analysis of Ten Winter Wheat Cultivars Clustered by UAV-Derived Vegetation Indices,
RS(12), No. 2, 2020, pp. xx-yy.
DOI Link 2001
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Xing, N.C.[Nai-Chen], Huang, W.J.[Wen-Jiang], Xie, Q.Y.[Qiao-Yun], Shi, Y.[Yue], Ye, H.C.[Hui-Chun], Dong, Y.Y.[Ying-Ying], Wu, M.Q.[Ming-Quan], Sun, G.[Gang], Jiao, Q.J.[Quan-Jun],
A Transformed Triangular Vegetation Index for Estimating Winter Wheat Leaf Area Index,
RS(12), No. 1, 2019, pp. xx-yy.
DOI Link 2001
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Xing, N.C.[Nai-Chen], Huang, W.J.[Wen-Jiang], Ye, H.C.[Hui-Chun], Ren, Y.[Yu], Xie, Q.Y.[Qiao-Yun],
Joint Retrieval of Winter Wheat Leaf Area Index and Canopy Chlorophyll Density Using Hyperspectral Vegetation Indices,
RS(13), No. 16, 2021, pp. xx-yy.
DOI Link 2109
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Li, F.[Feng], Zhang, C.M.[Cheng-Ming], Zhang, W.W.[Wen-Wen], Xu, Z.G.[Zhi-Gang], Wang, S.Y.[Shou-Yi], Sun, G.[Genyun], Wang, Z.J.[Zhen-Jie],
Improved Winter Wheat Spatial Distribution Extraction from High-Resolution Remote Sensing Imagery Using Semantic Features and Statistical Analysis,
RS(12), No. 3, 2020, pp. xx-yy.
DOI Link 2002
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Hu, Y.C.[Yun-Cai], Knapp, S.[Samuel], Schmidhalter, U.[Urs],
Advancing High-Throughput Phenotyping of Wheat in Early Selection Cycles,
RS(12), No. 3, 2020, pp. xx-yy.
DOI Link 2002
BibRef

Murphy, M.E.[Mary E.], Boruff, B.[Bryan], Callow, J.N.[J. Nikolaus], Flower, K.C.[Ken C.],
Detecting Frost Stress in Wheat: A Controlled Environment Hyperspectral Study on Wheat Plant Components and Implications for Multispectral Field Sensing,
RS(12), No. 3, 2020, pp. xx-yy.
DOI Link 2002
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Song, Y.[Yang], Wang, J.[Jing], Yu, Q.A.[Qi-Ang], Huang, J.X.[Jian-Xi],
Using MODIS LAI Data to Monitor Spatio-Temporal Changes of Winter Wheat Phenology in Response to Climate Warming,
RS(12), No. 5, 2020, pp. xx-yy.
DOI Link 2003
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Wang, S.Y.[Shou-Yi], Xu, Z.G.[Zhi-Gang], Zhang, C.M.[Cheng-Ming], Zhang, J.H.[Jing-Han], Mu, Z.S.[Zhong-Shan], Zhao, T.Y.[Tian-Yu], Wang, Y.Y.[Yuan-Yuan], Gao, S.[Shuai], Yin, H.[Hao], Zhang, Z.Y.[Zi-Yun],
Improved Winter Wheat Spatial Distribution Extraction Using A Convolutional Neural Network and Partly Connected Conditional Random Field,
RS(12), No. 5, 2020, pp. xx-yy.
DOI Link 2003
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And: Erratum: RS(12), No. 10, 2020, pp. xx-yy.
DOI Link 2006
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Tewes, A.[Andreas], Hoffmann, H.[Holger], Nolte, M.[Manuel], Krauss, G.[Gunther], Schäfer, F.[Fabian], Kerkhoff, C.[Christian], Gaiser, T.[Thomas],
How Do Methods Assimilating Sentinel-2-Derived LAI Combined with Two Different Sources of Soil Input Data Affect the Crop Model-Based Estimation of Wheat Biomass at Sub-Field Level?,
RS(12), No. 6, 2020, pp. xx-yy.
DOI Link 2003
BibRef

Dong, Q.[Qi], Chen, X.H.[Xue-Hong], Chen, J.[Jin], Zhang, C.S.[Chi-Shan], Liu, L.[Licong], Cao, X.[Xin], Zang, Y.Z.[Yun-Ze], Zhu, X.F.[Xiu-Fang], Cui, X.H.[Xi-Hong],
Mapping Winter Wheat in North China Using Sentinel 2A/B Data: A Method Based on Phenology-Time Weighted Dynamic Time Warping,
RS(12), No. 8, 2020, pp. xx-yy.
DOI Link 2004
BibRef

Xu, X.O.[Xia-Obin], Teng, C.[Cong], Zhao, Y.[Yu], Du, Y.[Ying], Zhao, C.Q.[Chun-Qi], Yang, G.J.[Gui-Jun], Jin, X.L.[Xiu-Liang], Song, X.Y.[Xiao-Yu], Gu, X.H.[Xiao-He], Casa, R.[Raffaele], Chen, L.P.[Li-Ping], Li, Z.[Zhenhai],
Prediction of Wheat Grain Protein by Coupling Multisource Remote Sensing Imagery and ECMWF Data,
RS(12), No. 8, 2020, pp. xx-yy.
DOI Link 2004
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Xu, W., Zhang, Z., Qin, Q., Hui, J., Long, Z.,
Soil Moisture Estimation With SVR and Data Augmentation Based on Alpha Approximation Method,
GeoRS(58), No. 5, May 2020, pp. 3190-3201.
IEEE DOI 2005
Soil moisture, Soil measurements, Synthetic aperture radar, Approximation methods, Agriculture, Estimation, winter wheat BibRef

El-Hendawy, S.[Salah], Al-Suhaibani, N.[Nasser], Al-Ashkar, I.[Ibrahim], Alotaibi, M.[Majed], Tahir, M.U.[Muhammad Usman], Solieman, T.[Talaat], Hassan, W.M.[Wael M.],
Combining Genetic Analysis and Multivariate Modeling to Evaluate Spectral Reflectance Indices as Indirect Selection Tools in Wheat Breeding under Water Deficit Stress Conditions,
RS(12), No. 9, 2020, pp. xx-yy.
DOI Link 2005
BibRef

Chen, S.[Shi], Fan, L.L.[Ling-Ling], Liang, S.[Shefang], Chen, H.[Hao], Sun, X.[Xiao], Hu, Y.[Yanan], Liu, Z.[Zhenhuan], Sun, J.[Jing], Yang, P.[Peng],
Spatiotemporal Dynamics of the Northern Limit of Winter Wheat in China Using MODIS Time Series Images,
RS(12), No. 15, 2020, pp. xx-yy.
DOI Link 2008
BibRef

Vavlas, N.C.[Nikolaos-Christos], Waine, T.W.[Toby W.], Meersmans, J.[Jeroen], Burgess, P.J.[Paul J.], Fontanelli, G.[Giacomo], Richter, G.M.[Goetz M.],
Deriving Wheat Crop Productivity Indicators Using Sentinel-1 Time Series,
RS(12), No. 15, 2020, pp. xx-yy.
DOI Link 2008
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Zhou, X.F.[Xian-Feng], Zhang, J.C.[Jing-Cheng], Chen, D.M.[Dong-Mei], Huang, Y.B.[Yan-Bo], Kong, W.P.[Wei-Ping], Yuan, L.[Lin], Ye, H.C.[Hui-Chun], Huang, W.J.[Wen-Jiang],
Assessment of Leaf Chlorophyll Content Models for Winter Wheat Using Landsat-8 Multispectral Remote Sensing Data,
RS(12), No. 16, 2020, pp. xx-yy.
DOI Link 2008
BibRef

Upreti, D.[Deepak], Pignatti, S.[Stefano], Pascucci, S.[Simone], Tolomio, M.[Massimo], Huang, W.J.[Wen-Jiang], Casa, R.[Raffaele],
Bayesian Calibration of the Aquacrop-OS Model for Durum Wheat by Assimilation of Canopy Cover Retrieved from VENµS Satellite Data,
RS(12), No. 16, 2020, pp. xx-yy.
DOI Link 2008
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Lang, T.T.[Ting-Ting], Yang, Y.Z.[Yan-Zhao], Jia, K.[Kun], Zhang, C.[Chao], You, Z.[Zhen], Liang, Y.B.[Yu-Bin],
Estimation of Winter Wheat Production Potential Based on Remotely-Sensed Imagery and Process-Based Model Simulations,
RS(12), No. 17, 2020, pp. xx-yy.
DOI Link 2009
BibRef

Zhu, K.Y.[Kang-Ying], Sun, Z.G.[Zhi-Gang], Zhao, F.H.[Feng-Hua], Yang, T.[Ting], Tian, Z.R.[Zhen-Rong], Lai, J.B.[Jian-Bin], Long, B.[Buju], Li, S.[Shiji],
Remotely sensed canopy resistance model for analyzing the stomatal behavior of environmentally-stressed winter wheat,
PandRS(168), 2020, pp. 197-207.
Elsevier DOI 2009
Remote sensing model, Canopy resistance, Stomatal behavior, Dry-hot wind stress, Salt stress, Winter wheat BibRef

Flynn, K.C.[K. Colton], Frazier, A.E.[Amy E.], Admas, S.[Sintayehu],
Nutrient Prediction for Tef (Eragrostis tef) Plant and Grain with Hyperspectral Data and Partial Least Squares Regression: Replicating Methods and Results across Environments,
RS(12), No. 18, 2020, pp. xx-yy.
DOI Link 2009
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Flynn, K.C.[K. Colton], Lee, T.[Trey], Endale, D.[Dinku], Franzluebbers, A.[Alan], Ma, S.F.[Sheng-Fang], Zhou, Y.T.[Yu-Ting],
Assessing Remote Sensing Vegetation Index Sensitivities for Tall Fescue (Schedonorus arundinaceus) Plant Health with Varying Endophyte and Fertilizer Types: A Case for Improving Poultry Manuresheds,
RS(13), No. 3, 2021, pp. xx-yy.
DOI Link 2102
BibRef

Sapkota, B.[Bishwa], Singh, V.[Vijay], Neely, C.[Clark], Rajan, N.[Nithya], Bagavathiannan, M.[Muthukumar],
Detection of Italian Ryegrass in Wheat and Prediction of Competitive Interactions Using Remote-Sensing and Machine-Learning Techniques,
RS(12), No. 18, 2020, pp. xx-yy.
DOI Link 2009
BibRef

Weiß, T.[Thomas], Ramsauer, T.[Thomas], Löw, A.[Alexander], Marzahn, P.[Philip],
Evaluation of Different Radiative Transfer Models for Microwave Backscatter Estimation of Wheat Fields,
RS(12), No. 18, 2020, pp. xx-yy.
DOI Link 2009
BibRef

Chen, P.F.[Peng-Fei],
Estimation of Winter Wheat Grain Protein Content Based on Multisource Data Assimilation,
RS(12), No. 19, 2020, pp. xx-yy.
DOI Link 2010
BibRef

Huang, X.[Xin], Zhu, W.Q.[Wen-Quan], Wang, X.Y.[Xiao-Ying], Zhan, P.[Pei], Liu, Q.F.[Qiu-Feng], Li, X.Y.[Xue-Ying], Sun, L.X.[Li-Xin],
A Method for Monitoring and Forecasting the Heading and Flowering Dates of Winter Wheat Combining Satellite-Derived Green-up Dates and Accumulated Temperature,
RS(12), No. 21, 2020, pp. xx-yy.
DOI Link 2011
BibRef

Tian, H.F.[Hai-Feng], Pei, J.[Jie], Huang, J.X.[Jian-Xi], Li, X.C.[Xue-Cao], Wang, J.[Jian], Zhou, B.Y.[Bo-Yan], Qin, Y.C.[Yao-Chen], Wang, L.[Li],
Garlic and Winter Wheat Identification Based on Active and Passive Satellite Imagery and the Google Earth Engine in Northern China,
RS(12), No. 21, 2020, pp. xx-yy.
DOI Link 2011
BibRef

Aharon, S.[Shlomi], Peleg, Z.[Zvi], Argaman, E.[Eli], Ben-David, R.[Roi], Lati, R.N.[Ran N.],
Image-Based High-Throughput Phenotyping of Cereals Early Vigor and Weed-Competitiveness Traits,
RS(12), No. 23, 2020, pp. xx-yy.
DOI Link 2012
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Das, S.[Sumanta], Christopher, J.[Jack], Apan, A.[Armando], Roy Choudhury, M.[Malini], Chapman, S.[Scott], Menzies, N.W.[Neal W.], Dang, Y.P.[Yash P.],
UAV-Thermal imaging and agglomerative hierarchical clustering techniques to evaluate and rank physiological performance of wheat genotypes on sodic soil,
PandRS(173), 2021, pp. 221-237.
Elsevier DOI 2102
Canopy temperature, Plant water stress, Vegetation indices, Agglomerative hierarchical clustering, Wheat genotypes, Sodic soil BibRef

Bates, J.S.[Jordan Steven], Montzka, C.[Carsten], Schmidt, M.[Marius], Jonard, F.[François],
Estimating Canopy Density Parameters Time-Series for Winter Wheat Using UAS Mounted LiDAR,
RS(13), No. 4, 2021, pp. xx-yy.
DOI Link 2103
BibRef

Fu, Y.Y.[Yuan-Yuan], Yang, G.J.[Gui-Jun], Song, X.Y.[Xiao-Yu], Li, Z.H.[Zhen-Hong], Xu, X.G.[Xin-Gang], Feng, H.K.[Hai-Kuan], Zhao, C.J.[Chun-Jiang],
Improved Estimation of Winter Wheat Aboveground Biomass Using Multiscale Textures Extracted from UAV-Based Digital Images and Hyperspectral Feature Analysis,
RS(13), No. 4, 2021, pp. xx-yy.
DOI Link 2103
BibRef

Gorrab, A.[Azza], Ameline, M.[Maël], Albergel, C.[Clément], Baup, F.[Frédéric],
Use of Sentinel-1 Multi-Configuration and Multi-Temporal Series for Monitoring Parameters of Winter Wheat,
RS(13), No. 4, 2021, pp. xx-yy.
DOI Link 2103
BibRef

Sadeghi-Tehran, P.[Pouria], Virlet, N.[Nicolas], Hawkesford, M.J.[Malcolm J.],
A Neural Network Method for Classification of Sunlit and Shaded Components of Wheat Canopies in the Field Using High-Resolution Hyperspectral Imagery,
RS(13), No. 5, 2021, pp. xx-yy.
DOI Link 2103
BibRef

Bhandari, M.[Mahendra], Baker, S.[Shannon], Rudd, J.C.[Jackie C.], Ibrahim, A.M.H.[Amir M. H.], Chang, A.[Anjin], Xue, Q.W.[Qing-Wu], Jung, J.H.[Jin-Ha], Landivar, J.[Juan], Auvermann, B.[Brent],
Assessing the Effect of Drought on Winter Wheat Growth Using Unmanned Aerial System (UAS)-Based Phenotyping,
RS(13), No. 6, 2021, pp. xx-yy.
DOI Link 2104
BibRef

Li, F.J.[Fang-Jie], Ren, J.Q.[Jian-Qiang], Wu, S.R.[Shang-Rong], Zhao, H.W.[Hong-Wei], Zhang, N.D.[Ning-Dan],
Comparison of Regional Winter Wheat Mapping Results from Different Similarity Measurement Indicators of NDVI Time Series and Their Optimized Thresholds,
RS(13), No. 6, 2021, pp. xx-yy.
DOI Link 2104
BibRef

Rufo, R.[Rubén], Soriano, J.M.[Jose Miguel], Villegas, D.[Dolors], Royo, C.[Conxita], Bellvert, J.[Joaquim],
Using Unmanned Aerial Vehicle and Ground-Based RGB Indices to Assess Agronomic Performance of Wheat Landraces and Cultivars in a Mediterranean-Type Environment,
RS(13), No. 6, 2021, pp. xx-yy.
DOI Link 2104
BibRef

Zhang, W.M.[Wen-Min], Brandt, M.[Martin], Prishchepov, A.V.[Alexander V.], Li, Z.F.[Zhao-Fu], Lyu, C.G.[Chun-Guang], Fensholt, R.[Rasmus],
Mapping the Dynamics of Winter Wheat in the North China Plain from Dense Landsat Time Series (1999 to 2019),
RS(13), No. 6, 2021, pp. xx-yy.
DOI Link 2104
BibRef

Dandrifosse, S.[Sébastien], Carlier, A.[Alexis], Dumont, B.[Benjamin], Mercatoris, B.[Benoît],
Registration and Fusion of Close-Range Multimodal Wheat Images in Field Conditions,
RS(13), No. 7, 2021, pp. xx-yy.
DOI Link 2104
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Ayari, E.[Emna], Kassouk, Z.[Zeineb], Lili-Chabaane, Z.[Zohra], Baghdadi, N.[Nicolas], Bousbih, S.[Safa], Zribi, M.[Mehrez],
Cereal Crops Soil Parameters Retrieval Using L-Band ALOS-2 and C-Band Sentinel-1 Sensors,
RS(13), No. 7, 2021, pp. xx-yy.
DOI Link 2104
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Wu, B.[Bin], Huang, W.J.[Wen-Jiang], Ye, H.[Huichun], Luo, P.[Peilei], Ren, Y.[Yu], Kong, W.P.[Wei-Ping],
Using Multi-Angular Hyperspectral Data to Estimate the Vertical Distribution of Leaf Chlorophyll Content in Wheat,
RS(13), No. 8, 2021, pp. xx-yy.
DOI Link 2104
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Pour, M.K.[Majid Khak], Fotouhi, R.[Reza], Hucl, P.[Pierre], Zhang, Q.W.[Qian-Wei],
Development of a Mobile Platform for Field-Based High-Throughput Wheat Phenotyping,
RS(13), No. 8, 2021, pp. xx-yy.
DOI Link 2104
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Qu, C.[Chang], Li, P.J.[Pei-Jun], Zhang, C.M.[Cheng-Ming],
A spectral index for winter wheat mapping using multi-temporal Landsat NDVI data of key growth stages,
PandRS(175), 2021, pp. 431-447.
Elsevier DOI 2105
Winter wheat mapping, Multi-temporal Landsat NDVI, Winter wheat index (WWI), Growth stages BibRef

Li, S.L.[Shi-Lei], Li, F.J.[Fang-Jie], Gao, M.F.[Mao-Fang], Li, Z.L.[Zhao-Liang], Leng, P.[Pei], Duan, S.[Sibo], Ren, J.Q.[Jian-Qiang],
A New Method for Winter Wheat Mapping Based on Spectral Reconstruction Technology,
RS(13), No. 9, 2021, pp. xx-yy.
DOI Link 2105
BibRef

Zhao, F.[Fa], Yang, G.J.[Gui-Jun], Yang, X.D.[Xiao-Dong], Cen, H.Y.[Hai-Yan], Zhu, Y.O.[Ya-Ohui], Han, S.Y.[Shao-Yu], Yang, H.[Hao], He, Y.[Yong], Zhao, C.J.[Chun-Jiang],
Determination of Key Phenological Phases of Winter Wheat Based on the Time-Weighted Dynamic Time Warping Algorithm and MODIS Time-Series Data,
RS(13), No. 9, 2021, pp. xx-yy.
DOI Link 2105
BibRef

Wu, X.C.[Xiao-Cui], Xiao, X.M.[Xiang-Ming], Steiner, J.[Jean], Yang, Z.W.[Zheng-Wei], Qin, Y.W.[Yuan-Wei], Wang, J.[Jie],
Spatiotemporal Changes of Winter Wheat Planted and Harvested Areas, Photosynthesis and Grain Production in the Contiguous United States from 2008-2018,
RS(13), No. 9, 2021, pp. xx-yy.
DOI Link 2105
BibRef

de Camargo, T.[Tibor], Schirrmann, M.[Michael], Landwehr, N.[Niels], Dammer, K.H.[Karl-Heinz], Pflanz, M.[Michael],
Optimized Deep Learning Model as a Basis for Fast UAV Mapping of Weed Species in Winter Wheat Crops,
RS(13), No. 9, 2021, pp. xx-yy.
DOI Link 2105
BibRef

Jenal, A.[Alexander], Hüging, H.[Hubert], Ahrends, H.E.[Hella Ellen], Bolten, A.[Andreas], Bongartz, J.[Jens], Bareth, G.[Georg],
Investigating the Potential of a Newly Developed UAV-Mounted VNIR/SWIR Imaging System for Monitoring Crop Traits: A Case Study for Winter Wheat,
RS(13), No. 9, 2021, pp. xx-yy.
DOI Link 2105
BibRef

Weiß, T.[Thomas], Ramsauer, T.[Thomas], Jagdhuber, T.[Thomas], Löw, A.[Alexander], Marzahn, P.[Philip],
Sentinel-1 Backscatter Analysis and Radiative Transfer Modeling of Dense Winter Wheat Time Series,
RS(13), No. 12, 2021, pp. xx-yy.
DOI Link 2106
BibRef

Ji, J.C.[Jing-Chun], Liu, J.[Jianli], Chen, J.J.[Jing-Jing], Niu, Y.J.[Yu-Jie], Xuan, K.F.[Ke-Fan], Jiang, Y.F.[Yi-Fei], Jia, R.[Renhao], Wang, C.[Can], Li, X.P.[Xiao-Peng],
Optimization of Topdressing for Winter Wheat by Accurate Growth Monitoring and Improved Production Estimation,
RS(13), No. 12, 2021, pp. xx-yy.
DOI Link 2106
BibRef

Zhao, J.Q.[Jian-Qing], Zhang, X.O.[Xia-Ohu], Yan, J.W.[Jia-Wei], Qiu, X.L.[Xiao-Lei], Yao, X.[Xia], Tian, Y.C.[Yong-Chao], Zhu, Y.[Yan], Cao, W.X.[Wei-Xing],
A Wheat Spike Detection Method in UAV Images Based on Improved YOLOv5,
RS(13), No. 16, 2021, pp. xx-yy.
DOI Link 2109
BibRef

Zhao, L.C.[Li-Cheng], Guo, W.[Wei], Wang, J.[Jian], Wang, H.Z.[Hao-Zhou], Duan, Y.L.[Yu-Lin], Wang, C.[Cong], Wu, W.B.[Wen-Bin], Shi, Y.[Yun],
An Efficient Method for Estimating Wheat Heading Dates Using UAV Images,
RS(13), No. 16, 2021, pp. xx-yy.
DOI Link 2109
BibRef

Peron-Danaher, R.[Raquel], Russell, B.[Blake], Cotrozzi, L.[Lorenzo], Mohammadi, M.[Mohsen], Couture, J.J.[John J.],
Incorporating Multi-Scale, Spectrally Detected Nitrogen Concentrations into Assessing Nitrogen Use Efficiency for Winter Wheat Breeding Populations,
RS(13), No. 19, 2021, pp. xx-yy.
DOI Link 2110
BibRef

Kong, W.P.[Wei-Ping], Huang, W.J.[Wen-Jiang], Ma, L.L.[Ling-Ling], Tang, L.[Lingli], Li, C.R.[Chuan-Rong], Zhou, X.F.[Xian-Feng], Casa, R.[Raffaele],
Estimating Vertical Distribution of Leaf Water Content within Wheat Canopies after Head Emergence,
RS(13), No. 20, 2021, pp. xx-yy.
DOI Link 2110
BibRef

Traore, A.[Adama], Ata-Ul-Karim, S.T.[Syed Tahir], Duan, A.[Aiwang], Soothar, M.K.[Mukesh Kumar], Traore, S.[Seydou], Zhao, B.[Ben],
Predicting Equivalent Water Thickness in Wheat Using UAV Mounted Multispectral Sensor through Deep Learning Techniques,
RS(13), No. 21, 2021, pp. xx-yy.
DOI Link 2112
BibRef

Zhao, F.[Fa], Yang, G.J.[Gui-Jun], Yang, H.[Hao], Zhu, Y.H.[Yao-Hui], Meng, Y.[Yang], Han, S.Y.[Shao-Yu], Bu, X.L.[Xin-Lei],
Short and Medium-Term Prediction of Winter Wheat NDVI Based on the DTW-LSTM Combination Method and MODIS Time Series Data,
RS(13), No. 22, 2021, pp. xx-yy.
DOI Link 2112
BibRef

Zhang, X.Y.[Xiao-Yuan], Liu, K.[Kai], Wang, S.D.[Shu-Dong], Long, X.[Xin], Li, X.[Xueke],
A Rapid Model (COV_PSDI) for Winter Wheat Mapping in Fallow Rotation Area Using MODIS NDVI Time-Series Satellite Observations: The Case of the Heilonggang Region,
RS(13), No. 23, 2021, pp. xx-yy.
DOI Link 2112
BibRef

Li, Y.S.[Yin-Shuai], Chang, C.Y.[Chun-Yan], Wang, Z.R.[Zhuo-Ran], Qi, G.H.[Guang-Hui], Dong, C.[Chao], Zhao, G.X.[Geng-Xing],
Upscaling Remote Sensing Inversion Model of Wheat Field Cultivated Land Quality in the Huang-Huai-Hai Agricultural Region, China,
RS(13), No. 24, 2021, pp. xx-yy.
DOI Link 2112
BibRef

Cao, X.F.[Xiao-Feng], Liu, Y.L.[Yu-Lin], Yu, R.[Rui], Han, D.J.[De-Jun], Su, B.F.[Bao-Feng],
A Comparison of UAV RGB and Multispectral Imaging in Phenotyping for Stay Green of Wheat Population,
RS(13), No. 24, 2021, pp. xx-yy.
DOI Link 2112
BibRef

Wang, J.J.[Jian-Jun], Zhou, Q.[Qi], Shang, J.L.[Jia-Li], Liu, C.[Chang], Zhuang, T.X.[Ting-Xuan], Ding, J.J.[Jun-Jie], Xian, Y.Y.[Yun-Yu], Zhao, L.T.[Ling-Tian], Wang, W.L.[Wei-Ling], Zhou, G.S.[Gui-Sheng], Tan, C.W.[Chang-Wei], Huo, Z.Y.[Zhong-Yang],
UAV- and Machine Learning-Based Retrieval of Wheat SPAD Values at the Overwintering Stage for Variety Screening,
RS(13), No. 24, 2021, pp. xx-yy.
DOI Link 2112
BibRef

Bastos, L.M.[Leonardo M.], Froes de Borja Reis, A.[Andre], Sharda, A.[Ajay], Wright, Y.[Yancy], Ciampitti, I.A.[Ignacio A.],
Current Status and Future Opportunities for Grain Protein Prediction Using On- and Off-Combine Sensors: A Synthesis-Analysis of the Literature,
RS(13), No. 24, 2021, pp. xx-yy.
DOI Link 2112
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Zhang, Y.X.[Yu-Xi], Walker, J.P.[Jeffrey P.], Pauwels, V.R.N.[Valentijn R. N.], Sadeh, Y.[Yuval],
Assimilation of Wheat and Soil States into the APSIM-Wheat Crop Model: A Case Study,
RS(14), No. 1, 2022, pp. xx-yy.
DOI Link 2201
BibRef

Yang, F.F.[Fei-Fei], Liu, S.P.[Sheng-Ping], Wang, Q.Y.[Qi-Yuan], Liu, T.[Tao], Li, S.[Shijuan],
Assessing Waterlogging Stress Level of Winter Wheat from Hyperspectral Imagery Based on Harmonic Analysis,
RS(14), No. 1, 2022, pp. xx-yy.
DOI Link 2201
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Li, C.C.[Chang-Chun], Chen, W.N.[Wei-Nan], Wang, Y.L.[Yi-Lin], Wang, Y.[Yu], Ma, C.Y.[Chun-Yan], Li, Y.C.[Ya-Cong], Li, J.B.[Jing-Bo], Zhai, W.G.[Wei-Guang],
Mapping Winter Wheat with Optical and SAR Images Based on Google Earth Engine in Henan Province, China,
RS(14), No. 2, 2022, pp. xx-yy.
DOI Link 2201
BibRef

Huang, F.[Fujue], Xia, X.S.[Xing-Sheng], Huang, Y.S.[Yong-Sheng], Lv, S.H.[Sheng-Hui], Chen, Q.[Qiong], Pan, Y.Z.[Yao-Zhong], Zhu, X.F.[Xiu-Fang],
Comparison of Winter Wheat Extraction Methods Based on Different Time Series of Vegetation Indices in the Northeastern Margin of the Qinghai-Tibet Plateau: A Case Study of Minhe, China,
RS(14), No. 2, 2022, pp. xx-yy.
DOI Link 2201
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Zhang, X.C.[Xiao-Chun], Yuan, X.[Xu], Liu, H.[Hairuo], Gao, H.[Hongsi], Wang, X.[Xiugui],
Soil Moisture Estimation for Winter-Wheat Waterlogging Monitoring by Assimilating Remote Sensing Inversion Data into the Distributed Hydrology Soil Vegetation Model,
RS(14), No. 3, 2022, pp. xx-yy.
DOI Link 2202
BibRef

Liu, S.W.[Sheng-Wei], Peng, D.L.[Dai-Liang], Zhang, B.[Bing], Chen, Z.C.[Zheng-Chao], Yu, L.[Le], Chen, J.J.[Jun-Jie], Pan, Y.H.[Yu-Hao], Zheng, S.J.[Shi-Jun], Hu, J.K.[Jin-Kang], Lou, Z.[Zihang], Chen, Y.[Yue], Yang, S.L.[Song-Lin],
The Accuracy of Winter Wheat Identification at Different Growth Stages Using Remote Sensing,
RS(14), No. 4, 2022, pp. xx-yy.
DOI Link 2202
BibRef

Wang, F.[Falv], Yang, M.[Mao], Ma, L.F.[Long-Fei], Zhang, T.[Tong], Qin, W.L.[Wei-Long], Li, W.[Wei], Zhang, Y.H.[Ying-Hua], Sun, Z.C.[Zhen-Cai], Wang, Z.M.[Zhi-Min], Li, F.[Fei], Yu, K.[Kang],
Estimation of Above-Ground Biomass of Winter Wheat Based on Consumer-Grade Multi-Spectral UAV,
RS(14), No. 5, 2022, pp. xx-yy.
DOI Link 2203
BibRef

Mikhailenko, I.M.[Ilya Mikhayilovich],
Estimation of Parameters of Biomass State of Sowing Spring Wheat,
RS(14), No. 6, 2022, pp. xx-yy.
DOI Link 2204
BibRef

Zhang, X.[Xin], Han, L.X.[Liang-Xiu], Sobeih, T.[Tam], Lappin, L.[Lewis], Lee, M.A.[Mark A.], Howard, A.[Andew], Kisdi, A.[Aron],
The Self-Supervised Spectral-Spatial Vision Transformer Network for Accurate Prediction of Wheat Nitrogen Status from UAV Imagery,
RS(14), No. 6, 2022, pp. xx-yy.
DOI Link 2204
BibRef

Lin, J.Y.[Jing-Yu], Shen, Q.[Qiu], Wu, J.J.[Jian-Jun], Zhao, W.H.[Wen-Hui], Liu, L.Z.[Lei-Zhen],
Assessing the Potential of Downscaled Far Red Solar-Induced Chlorophyll Fluorescence from the Canopy to Leaf Level for Drought Monitoring in Winter Wheat,
RS(14), No. 6, 2022, pp. xx-yy.
DOI Link 2204
BibRef

Wu, F.[Fei], Wang, J.[Junchan], Zhou, Y.Z.[Yu-Zhuang], Song, X.X.[Xiao-Xin], Ju, C.X.[Cheng-Xin], Sun, C.M.[Cheng-Ming], Liu, T.[Tao],
Estimation of Winter Wheat Tiller Number Based on Optimization of Gradient Vegetation Characteristics,
RS(14), No. 6, 2022, pp. xx-yy.
DOI Link 2204
BibRef

Fan, L.L.[Ling-Ling], Yang, J.[Jing], Sun, X.[Xiao], Zhao, F.[Fen], Liang, S.F.[She-Fang], Duan, D.D.[Ding-Ding], Chen, H.[Hao], Xia, L.[Lang], Sun, J.[Jing], Yang, P.[Peng],
The effects of Landsat image acquisition date on winter wheat classification in the North China Plain,
PandRS(187), 2022, pp. 1-13.
Elsevier DOI 2205
Multi-temporal, Acquisition dates, Effects evaluation, Winter wheat, Landsat BibRef

Ren, J.Q.[Jian-Qiang], Zhang, N.D.[Ning-Dan], Liu, X.R.[Xing-Ren], Wu, S.R.[Shang-Rong], Li, D.D.[Dan-Dan],
Dynamic Harvest Index Estimation of Winter Wheat Based on UAV Hyperspectral Remote Sensing Considering Crop Aboveground Biomass Change and the Grain Filling Process,
RS(14), No. 9, 2022, pp. xx-yy.
DOI Link 2205
BibRef

Chen, L.[Lin], Xing, M.[Minfeng], He, B.B.[Bin-Bin], Wang, J.F.[Jin-Fei], Xu, M.[Min], Song, Y.[Yang], Huang, X.D.[Xiao-Dong],
Estimating Soil Moisture over Winter Wheat Fields during Growing Season Using RADARSAT-2 Data,
RS(14), No. 9, 2022, pp. xx-yy.
DOI Link 2205
BibRef

Jennewein, J.S.[Jyoti S.], Lamb, B.T.[Brian T.], Hively, W.D.[W. Dean], Thieme, A.[Alison], Thapa, R.[Resham], Goldsmith, A.[Avi], Mirsky, S.B.[Steven B.],
Integration of Satellite-Based Optical and Synthetic Aperture Radar Imagery to Estimate Winter Cover Crop Performance in Cereal Grasses,
RS(14), No. 9, 2022, pp. xx-yy.
DOI Link 2205
BibRef

Huang, X.J.[Xiao-Juan], Fu, Y.Y.[Yang-Yang], Wang, J.J.[Jing-Jing], Dong, J.[Jie], Zheng, Y.[Yi], Pan, B.[Baihong], Skakun, S.[Sergii], Yuan, W.P.[Wen-Ping],
High-Resolution Mapping of Winter Cereals in Europe by Time Series Landsat and Sentinel Images for 2016-2020,
RS(14), No. 9, 2022, pp. xx-yy.
DOI Link 2205
BibRef

Mulero, G.[Gabriel], Bacher, H.[Harel], Kleiner, U.[Uri], Peleg, Z.[Zvi], Herrmann, I.[Ittai],
Spectral Estimation of In Vivo Wheat Chlorophyll a/b Ratio under Contrasting Water Availabilities,
RS(14), No. 11, 2022, pp. xx-yy.
DOI Link 2206
BibRef

Goffart, D.[Dimitri], Dvorakova, K.[Klara], Crucil, G.[Giacomo], Curnel, Y.[Yannick], Limbourg, Q.[Quentin], van Oost, K.[Kristof], Castaldi, F.[Fabio], Planchon, V.[Viviane], Goffart, J.P.[Jean-Pierre], van Wesemael, B.[Bas],
UAV Remote Sensing for Detecting within-Field Spatial Variation of Winter Wheat Growth and Links to Soil Properties and Historical Management Practices. A Case Study on Belgian Loamy Soil,
RS(14), No. 12, 2022, pp. xx-yy.
DOI Link 2206
BibRef

Uribeetxebarria, A.[Asier], Castellón, A.[Ander], Aizpurua, A.[Ana],
A First Approach to Determine If It Is Possible to Delineate In-Season N Fertilization Maps for Wheat Using NDVI Derived from Sentinel-2,
RS(14), No. 12, 2022, pp. xx-yy.
DOI Link 2206
BibRef

Isik, S.[Sahin], Özkan, K.[Kemal], Demirez, D.Z.[Duygu Zeynep], Seke, E.[Erol],
Consensus rule for wheat cultivar classification on VL, VNIR and SWIR imaging,
IET-IPR(16), No. 11, 2022, pp. 2834-2844.
DOI Link 2208
BibRef

Chen, J.[Jidai], Liu, X.J.[Xin-Jie], Yang, G.J.[Gui-Jun], Han, S.Y.[Shao-Yu], Ma, Y.[Yan], Liu, L.Y.[Liang-Yun],
Different Responses of Solar-Induced Chlorophyll Fluorescence at the Red and Far-Red Bands and Gross Primary Productivity to Air Temperature for Winter Wheat,
RS(14), No. 13, 2022, pp. xx-yy.
DOI Link 2208
BibRef

Fan, K.[Kai], Li, F.L.[Fen-Ling], Chen, X.K.[Xiao-Kai], Li, Z.F.[Zhen-Fa], Mulla, D.J.[David J.],
Nitrogen Balance Index Prediction of Winter Wheat by Canopy Hyperspectral Transformation and Machine Learning,
RS(14), No. 14, 2022, pp. xx-yy.
DOI Link 2208
BibRef

Han, Y.X.[Yi-Xiu], Tang, R.[Rui], Liao, Z.Q.[Zhen-Qi], Zhai, B.[Bingnian], Fan, J.L.[Jun-Liang],
A Novel Hybrid GOA-XGB Model for Estimating Wheat Aboveground Biomass Using UAV-Based Multispectral Vegetation Indices,
RS(14), No. 14, 2022, pp. xx-yy.
DOI Link 2208
BibRef

Han, S.Y.[Shao-Yu], Zhao, Y.[Yu], Cheng, J.P.[Jin-Peng], Zhao, F.[Fa], Yang, H.[Hao], Feng, H.K.[Hai-Kuan], Li, Z.H.[Zhen-Hai], Ma, X.M.[Xin-Ming], Zhao, C.J.[Chun-Jiang], Yang, G.J.[Gui-Jun],
Monitoring Key Wheat Growth Variables by Integrating Phenology and UAV Multispectral Imagery Data into Random Forest Model,
RS(14), No. 15, 2022, pp. xx-yy.
DOI Link 2208
BibRef

Feng, H.K.[Hai-Kuan], Tao, H.L.[Hui-Lin], Li, Z.H.[Zhen-Hai], Yang, G.J.[Gui-Jun], Zhao, C.J.[Chun-Jiang],
Comparison of UAV RGB Imagery and Hyperspectral Remote-Sensing Data for Monitoring Winter Wheat Growth,
RS(14), No. 15, 2022, pp. xx-yy.
DOI Link 2208
BibRef

Lu, Z.[Zhuo], Deng, L.[Lei], Lu, H.[Han],
An Improved LAI Estimation Method Incorporating with Growth Characteristics of Field-Grown Wheat,
RS(14), No. 16, 2022, pp. xx-yy.
DOI Link 2208
BibRef

Wang, L.[Limei], Jin, G.W.[Guo-Wang], Xiong, X.[Xin], Zhang, H.M.[Hong-Min], Wu, K.[Ke],
Object-Based Automatic Mapping of Winter Wheat Based on Temporal Phenology Patterns Derived from Multitemporal Sentinel-1 and Sentinel-2 Imagery,
IJGI(11), No. 8, 2022, pp. xx-yy.
DOI Link 2209
BibRef

Khotimah, W.N.[Wijayanti Nurul], Boussaid, F.[Farid], Sohel, F.[Ferdous], Xu, L.[Lian], Edwards, D.[David], Jin, X.[Xiu], Bennamoun, M.[Mohammed],
SC-CAN: Spectral Convolution and Channel Attention Network for Wheat Stress Classification,
RS(14), No. 17, 2022, pp. xx-yy.
DOI Link 2209
BibRef

Zhao, Y.J.[Yi-Jing], Wang, X.L.[Xiao-Li], Guo, Y.[Yu], Hou, X.[Xiyong], Dong, L.J.[Li-Jie],
Winter Wheat Phenology Variation and Its Response to Climate Change in Shandong Province, China,
RS(14), No. 18, 2022, pp. xx-yy.
DOI Link 2209
BibRef

Cai, W.X.[Wen-Xin], Tian, J.[Jinyan], Li, X.J.[Xiao-Juan], Zhu, L.[Lin], Chen, B.B.[Bei-Bei],
A New Multiple Phenological Spectral Feature for Mapping Winter Wheat,
RS(14), No. 18, 2022, pp. xx-yy.
DOI Link 2209
BibRef

Caballero, G.[Gabriel], Pezzola, A.[Alejandro], Winschel, C.[Cristina], Casella, A.[Alejandra], Angonova, P.S.[Paolo Sanchez], Rivera-Caicedo, J.P.[Juan Pablo], Berger, K.[Katja], Verrelst, J.[Jochem], Delegido, J.[Jesus],
Seasonal Mapping of Irrigated Winter Wheat Traits in Argentina with a Hybrid Retrieval Workflow Using Sentinel-2 Imagery,
RS(14), No. 18, 2022, pp. xx-yy.
DOI Link 2209
BibRef

Shen, L.Z.[Lan-Zhi], Gao, M.F.[Mao-Fang], Yan, J.W.[Jing-Wen], Wang, Q.Z.[Qi-Zhi], Shen, H.[Hua],
Winter Wheat SPAD Value Inversion Based on Multiple Pretreatment Methods,
RS(14), No. 18, 2022, pp. xx-yy.
DOI Link 2209
BibRef

Longmire, A.R., Poblete, T., Hunt, J.R., Chen, D., Zarco-Tejada, P.J.,
Assessment of crop traits retrieved from airborne hyperspectral and thermal remote sensing imagery to predict wheat grain protein content,
PandRS(193), 2022, pp. 284-298.
Elsevier DOI 2210
Hyperspectral, Radiative transfer, Stress detection, Grain protein content, Machine learning, Thermal BibRef

Wang, S.[Shuai], Chen, J.[Jin], Shen, M.G.[Miao-Gen], Shi, T.T.[Ting-Ting], Liu, L.C.[Li-Cong], Zhang, L.Y.[Lu-Yun], Dong, Q.[Qi], Wang, C.[Cong],
Characterizing Spatiotemporal Patterns of Winter Wheat Phenology from 1981 to 2016 in North China by Improving Phenology Estimation,
RS(14), No. 19, 2022, pp. xx-yy.
DOI Link 2210
BibRef

Sui, M.M.[Ming-Ming], Chen, K.[Kun], Shen, F.[Fei],
Monitoring of Wheat Height Based on Multi-GNSS Reflected Signals,
RS(14), No. 19, 2022, pp. xx-yy.
DOI Link 2210
BibRef

Zhang, X.W.[Xue-Wei], Zhang, K.[Kefei], Wu, S.Q.[Su-Qin], Shi, H.T.[Hong-Tao], Sun, Y.Q.[Ya-Qin], Zhao, Y.D.[Yin-Di], Fu, E.[Erjiang], Chen, S.[Shuo], Bian, C.F.[Chao-Fa], Ban, W.[Wei],
An Investigation of Winter Wheat Leaf Area Index Fitting Model Using Spectral and Canopy Height Model Data from Unmanned Aerial Vehicle Imagery,
RS(14), No. 20, 2022, pp. xx-yy.
DOI Link 2211
BibRef

Zhu, J.P.[Jiang-Peng], Yang, G.F.[Guo-Feng], Feng, X.P.[Xu-Ping], Li, X.[Xiyao], Fang, H.[Hui], Zhang, J.N.[Jin-Nuo], Bai, X.L.[Xiu-Lin], Tao, M.Z.[Ming-Zhu], He, Y.[Yong],
Detecting Wheat Heads from UAV Low-Altitude Remote Sensing Images Using Deep Learning Based on Transformer,
RS(14), No. 20, 2022, pp. xx-yy.
DOI Link 2211
BibRef

Wang, D.[Dong], Yue, D.X.[Dong-Xia], Zhou, Y.Y.[Yan-Yan], Huo, F.[Feibiao], Bao, Q.[Qiong], Li, K.[Kai],
Drought Resistance of Vegetation and Its Change Characteristics before and after the Implementation of the Grain for Green Program on the Loess Plateau, China,
RS(14), No. 20, 2022, pp. xx-yy.
DOI Link 2211
BibRef

Caballero, G.[Gabriel], Pezzola, A.[Alejandro], Winschel, C.[Cristina], Casella, A.[Alejandra], Angonova, P.S.[Paolo Sanchez], Orden, L.[Luciano], Berger, K.[Katja], Verrelst, J.[Jochem], Delegido, J.[Jesús],
Quantifying Irrigated Winter Wheat LAI in Argentina Using Multiple Sentinel-1 Incidence Angles,
RS(14), No. 22, 2022, pp. xx-yy.
DOI Link 2212
BibRef

Zheng, J.[Jie], Song, X.Y.[Xiao-Yu], Yang, G.J.[Gui-Jun], Du, X.C.[Xiao-Chu], Mei, X.[Xin], Yang, X.D.[Xiao-Dong],
Remote Sensing Monitoring of Rice and Wheat Canopy Nitrogen: A Review,
RS(14), No. 22, 2022, pp. xx-yy.
DOI Link 2212
BibRef

Qin, W.L.[Wei-Long], Wang, J.[Jian], Ma, L.F.[Long-Fei], Wang, F.[Falv], Hu, N.[Naiyue], Yang, X.Y.[Xian-Yue], Xiao, Y.Y.[Yi-Yang], Zhang, Y.H.[Ying-Hua], Sun, Z.C.[Zhen-Cai], Wang, Z.M.[Zhi-Min], Yu, K.[Kang],
UAV-Based Multi-Temporal Thermal Imaging to Evaluate Wheat Drought Resistance in Different Deficit Irrigation Regimes,
RS(14), No. 21, 2022, pp. xx-yy.
DOI Link 2212
BibRef

Zelazny, W.R.[Wiktor R.], Kusnierek, K.[Krzysztof], Geipel, J.[Jakob],
Gaussian Process Modeling of In-Season Physiological Parameters of Spring Wheat Based on Airborne Imagery from Two Hyperspectral Cameras and Apparent Soil Electrical Conductivity,
RS(14), No. 23, 2022, pp. xx-yy.
DOI Link 2212
BibRef

Ma, X.[Xiao], Chen, P.F.[Peng-Fei], Jin, X.[Xiuliang],
Predicting Wheat Leaf Nitrogen Content by Combining Deep Multitask Learning and a Mechanistic Model Using UAV Hyperspectral Images,
RS(14), No. 24, 2022, pp. xx-yy.
DOI Link 2212
BibRef

Lv, S.H.[Sheng-Hui], Xia, X.S.[Xing-Sheng], Pan, Y.Z.[Yao-Zhong],
Optimization of Characteristic Phenological Periods for Winter Wheat Extraction Using Remote Sensing in Plateau Valley Agricultural Areas in Hualong, China,
RS(15), No. 1, 2023, pp. xx-yy.
DOI Link 2301
BibRef

Li, W.G.[Wei-Guo], Zhang, H.[Hong], Li, W.[Wei], Ma, T.[Tinghuai],
Extraction of Winter Wheat Planting Area Based on Multi-Scale Fusion,
RS(15), No. 1, 2023, pp. xx-yy.
DOI Link 2301
BibRef

Roth, R.T.[Richard T.], Chen, K.[Kanru], Scott, J.R.[John R.], Jung, J.[Jinha], Yang, Y.[Yang], Camberato, J.J.[James J.], Armstrong, S.D.[Shalamar D.],
Prediction of Cereal Rye Cover Crop Biomass and Nutrient Accumulation Using Multi-Temporal Unmanned Aerial Vehicle Based Visible-Spectrum Vegetation Indices,
RS(15), No. 3, 2023, pp. xx-yy.
DOI Link 2302
BibRef

Liao, C.H.[Chun-Hua], Wang, J.F.[Jin-Fei], Shan, B.[Bo], Shang, J.L.[Jia-Li], Dong, T.[Taifeng], He, Y.J.[Yong-Jun],
Near real-time detection and forecasting of within-field phenology of winter wheat and corn using Sentinel-2 time-series data,
PandRS(196), 2023, pp. 105-119.
Elsevier DOI 2302
Crop phenology, BBCH scale, Near real-time, Sentinel-2 time-series, Winter wheat, Corn BibRef

Chen, X.K.[Xiao-Kai], Li, F.[Fenling], Chang, Q.[Qingrui],
Combination of Continuous Wavelet Transform and Successive Projection Algorithm for the Estimation of Winter Wheat Plant Nitrogen Concentration,
RS(15), No. 4, 2023, pp. xx-yy.
DOI Link 2303
BibRef

Chen, S.[Siru], Zhao, W.H.[Wen-Hui], Zhang, R.X.[Ren-Xiang], Sun, X.[Xun], Zhou, Y.Z.[Yang-Zhen], Liu, L.Z.[Lei-Zhen],
Higher Sensitivity of NIRv,Rad in Detecting Net Primary Productivity of C4 Than that of C3: Evidence from Ground Measurements of Wheat and Maize,
RS(15), No. 4, 2023, pp. xx-yy.
DOI Link 2303
BibRef

He, P.[Peng], Bi, R.[Rutian], Xu, L.[Lishuai], Liu, Z.C.[Zheng-Chun], Yang, F.[Fan], Wang, W.B.[Wen-Biao], Cui, Z.N.[Zheng-Nan], Wang, J.S.[Jing-Shu],
Evapotranspiration of Winter Wheat in the Semi-Arid Southeastern Loess Plateau Based on Multi-Source Satellite Data,
RS(15), No. 8, 2023, pp. 2095.
DOI Link 2305
BibRef

Li, Z.P.[Zong-Peng], Zhou, X.G.[Xin-Guo], Cheng, Q.[Qian], Fei, S.P.[Shuai-Peng], Chen, Z.[Zhen],
A Machine-Learning Model Based on the Fusion of Spectral and Textural Features from UAV Multi-Sensors to Analyse the Total Nitrogen Content in Winter Wheat,
RS(15), No. 8, 2023, pp. 2152.
DOI Link 2305
BibRef

Gée, C.[Christelle], Denimal, E.[Emmanuel], de Yparraguirre, M.[Maël], Dujourdy, L.[Laurence], Voisin, A.S.[Anne-Sophie],
Assessment of Nitrogen Nutrition Index of Winter Wheat Canopy from Visible Images for a Dynamic Monitoring of N Requirements,
RS(15), No. 10, 2023, pp. xx-yy.
DOI Link 2306
BibRef

Chen, X.K.[Xiao-Kai], Li, F.L.[Fen-Ling], Shi, B.[Botai], Chang, Q.R.[Qing-Rui],
Estimation of Winter Wheat Plant Nitrogen Concentration from UAV Hyperspectral Remote Sensing Combined with Machine Learning Methods,
RS(15), No. 11, 2023, pp. 2831.
DOI Link 2306
BibRef

Zhu, Y.J.[Yong-Ji], Liu, J.[Jikai], Tao, X.Y.[Xin-Yu], Su, X.X.[Xiang-Xiang], Li, W.Y.[Wen-Yang], Zha, H.[Hainie], Wu, W.[Wenge], Li, X.W.[Xin-Wei],
A Three-Dimensional Conceptual Model for Estimating the Above-Ground Biomass of Winter Wheat Using Digital and Multispectral Unmanned Aerial Vehicle Images at Various Growth Stages,
RS(15), No. 13, 2023, pp. 3332.
DOI Link 2307
BibRef

Yin, Q.[Quan], Zhang, Y.T.[Yu-Ting], Li, W.L.[Wei-Long], Wang, J.J.[Jian-Jun], Wang, W.L.[Wei-Ling], Ahmad, I.[Irshad], Zhou, G.S.[Gui-Sheng], Huo, Z.Y.[Zhong-Yang],
Estimation of Winter Wheat SPAD Values Based on UAV Multispectral Remote Sensing,
RS(15), No. 14, 2023, pp. 3595.
DOI Link 2307
BibRef

Zhai, W.G.[Wei-Guang], Li, C.C.[Chang-Chun], Cheng, Q.[Qian], Mao, B.[Bohan], Li, Z.P.[Zong-Peng], Li, Y.F.[Ya-Feng], Ding, F.[Fan], Qin, S.[Siqing], Fei, S.[Shuaipeng], Chen, Z.[Zhen],
Enhancing Wheat Above-Ground Biomass Estimation Using UAV RGB Images and Machine Learning: Multi-Feature Combinations, Flight Height, and Algorithm Implications,
RS(15), No. 14, 2023, pp. 3653.
DOI Link 2307
BibRef

Yang, G.X.[Gao-Xiang], Li, X.R.[Xing-Rong], Liu, P.Z.[Peng-Zhi], Yao, X.[Xia], Zhu, Y.[Yan], Cao, W.X.[Wei-Xing], Cheng, T.[Tao],
Automated in-season mapping of winter wheat in China with training data generation and model transfer,
PandRS(202), 2023, pp. 422-438.
Elsevier DOI 2308
Crop, Large-scale mapping, Optical and SAR data, Time series, Phenology, Random forest BibRef

Liu, J.H.[Jia-Hao], Wang, H.[Hong], Zhang, Y.[Yao], Zhao, X.[Xili], Qu, T.F.[Teng-Fei], Tian, H.Z.[Hao-Zhe], Lu, Y.T.[Yu-Ting], Su, J.[Jingru], Luo, D.S.[Ding-Sheng], Yang, Y.[Yalei],
A Spatial Distribution Extraction Method for Winter Wheat Based on Improved U-Net,
RS(15), No. 15, 2023, pp. xx-yy.
DOI Link 2308
BibRef

Meng, X.P.[Xiao-Peng], Li, C.C.[Chang-Chun], Li, J.B.[Jing-Bo], Li, X.[Xinyan], Guo, F.[Fuchen], Xiao, Z.[Zhen],
YOLOv7-MA: Improved YOLOv7-Based Wheat Head Detection and Counting,
RS(15), No. 15, 2023, pp. xx-yy.
DOI Link 2308
BibRef

Yin, Q.[Quan], Zhang, Y.T.[Yu-Ting], Li, W.L.[Wei-Long], Wang, J.J.[Jian-Jun], Wang, W.L.[Wei-Ling], Ahmad, I.[Irshad], Zhou, G.S.[Gui-Sheng], Huo, Z.Y.[Zhong-Yang],
Better Inversion of Wheat Canopy SPAD Values before Heading Stage Using Spectral and Texture Indices Based on UAV Multispectral Imagery,
RS(15), No. 20, 2023, pp. 4935.
DOI Link 2310
BibRef

Zhang, Q.X.[Qi-Xia], Wang, G.[Guofu], Wang, G.J.[Guo-Jie], Song, W.C.[Wei-Cheng], Wei, X.[Xikun], Hu, Y.F.[Yi-Fan],
Identifying Winter Wheat Using Landsat Data Based on Deep Learning Algorithms in the North China Plain,
RS(15), No. 21, 2023, pp. 5121.
DOI Link 2311
BibRef

Longmire, A., Poblete, T., Hornero, A., Chen, D., Zarco-Tejada, P.,
Estimation of grain protein content in commercial bread and durum wheat fields via traits inverted by radiative transfer modelling from Sentinel-2 timeseries,
PandRS(206), 2023, pp. 49-62.
Elsevier DOI 2312
Wheat, Grain protein content, Stress detection, Sentinel-2 time series, Radiative transfer model inversion, Machine learning BibRef

Sahoo, R.N.[Rabi N.], Gakhar, S.[Shalini], Rejith, R.G.[Rajan G.], Verrelst, J.[Jochem], Ranjan, R.[Rajeev], Kondraju, T.[Tarun], Meena, M.C.[Mahesh C.], Mukherjee, J.[Joydeep], Daas, A.[Anchal], Kumar, S.[Sudhir], Kumar, M.[Mahesh], Dhandapani, R.[Raju], Chinnusamy, V.[Viswanathan],
Optimizing the Retrieval of Wheat Crop Traits from UAV-Borne Hyperspectral Image with Radiative Transfer Modelling Using Gaussian Process Regression,
RS(15), No. 23, 2023, pp. 5496.
DOI Link 2312
BibRef

Wang, Z.X.[Zhen-Xing], Liu, D.[Dong], Wang, M.[Min],
Mapping Main Grain Crops and Change Analysis in the West Liaohe River Basin with Limited Samples Based on Google Earth Engine,
RS(15), No. 23, 2023, pp. 5515.
DOI Link 2312
BibRef

Li, W.L.[Wei-Long], Wang, J.J.[Jian-Jun], Zhang, Y.T.[Yu-Ting], Yin, Q.[Quan], Wang, W.L.[Wei-Ling], Zhou, G.S.[Gui-Sheng], Huo, Z.Y.[Zhong-Yang],
Combining Texture, Color, and Vegetation Index from Unmanned Aerial Vehicle Multispectral Images to Estimate Winter Wheat Leaf Area Index during the Vegetative Growth Stage,
RS(15), No. 24, 2023, pp. 5715.
DOI Link 2401
BibRef

Roy, B.[Bishal], Sagan, V.[Vasit], Haireti, A.[Alifu], Newcomb, M.[Maria], Tuberosa, R.[Roberto], LeBauer, D.[David], Shakoor, N.[Nadia],
Early Detection of Drought Stress in Durum Wheat Using Hyperspectral Imaging and Photosystem Sensing,
RS(16), No. 1, 2024, pp. xx-yy.
DOI Link 2401
BibRef

Sun, Z.[Zheng], Sun, L.[Liang], Liu, Y.[Yu], Li, Y.W.[Yang-Wei], Crusiol, L.G.T.[Luís Guilherme Teixeira], Chen, R.Q.[Rui-Qing], Wuyun, D.[Deji],
Estimating Fraction of Absorbed Photosynthetically Active Radiation of Winter Wheat Based on Simulated Sentinel-2 Data under Different Varieties and Water Stress,
RS(16), No. 2, 2024, pp. 362.
DOI Link 2402
BibRef

Zhang, R.[Ruinan], Jin, S.C.[Shi-Chao], Zhang, Y.H.[Yuan-Hao], Zang, J.R.[Jing-Rong], Wang, Y.[Yu], Li, Q.[Qing], Sun, Z.Z.[Zhuang-Zhuang], Wang, X.[Xiao], Zhou, Q.[Qin], Cai, J.[Jian], Xu, S.[Shan], Su, Y.J.[Yan-Jun], Wu, J.[Jin], Jiang, D.[Dong],
PhenoNet: A two-stage lightweight deep learning framework for real-time wheat phenophase classification,
PandRS(208), 2024, pp. 136-157.
Elsevier DOI Code:
WWW Link. 2402
Wheat phenology, Dataset, Image classification, Deep learning, Transfer learning, Web application BibRef

Zhang, C.S.[Chang-Sai], Yi, Y.[Yuan], Wang, L.J.[Li-Juan], Zhang, X.W.[Xue-Wei], Chen, S.[Shuo], Su, Z.[Zaixing], Zhang, S.[Shuxia], Xue, Y.[Yong],
Estimation of the Bio-Parameters of Winter Wheat by Combining Feature Selection with Machine Learning Using Multi-Temporal Unmanned Aerial Vehicle Multispectral Images,
RS(16), No. 3, 2024, pp. 469.
DOI Link 2402
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Liu, H.J.[Hong-Jie], Song, W.L.[Wen-Long], Lv, J.[Juan], Gui, R.J.[Rong-Jie], Shi, Y.J.[Yang-Jun], Lu, Y.Z.[Yi-Zhu], Li, M.Y.[Meng-Yi], Chen, L.[Long], Chen, X.[Xiuhua],
Precise Drought Threshold Monitoring in Winter Wheat Using the Unmanned Aerial Vehicle Thermal Method,
RS(16), No. 4, 2024, pp. 710.
DOI Link 2402
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Dellaly, V.[Vetiya], Bellakanji, A.C.[Aicha Chahbi], Chakroun, H.[Hedia], Saadi, S.[Sameh], Boulet, G.[Gilles], Zribi, M.[Mehrez], Chabaane, Z.L.[Zohra Lili],
Water Footprint of Cereals by Remote Sensing in Kairouan Plain (Tunisia),
RS(16), No. 3, 2024, pp. 491.
DOI Link 2402
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Engstrøm, O.C.G.[Ole-Christian Galbo], Dreier, E.S.[Erik Schou], Jespersen, B.M.[Birthe Møller], Pedersen, K.S.[Kim Steenstrup],
Improving Deep Learning on Hyperspectral Images of Grain by Incorporating Domain Knowledge from Chemometrics,
CVPPA23(485-494)
IEEE DOI 2401
BibRef

Harada, S.[Sho], Han, X.H.[Xian-Hua],
Coarse-To-Fine Pyramid Feature Mining for Wheat Head Detection,
ICIP23(1350-1354)
IEEE DOI 2312
BibRef

Liu, R.R.[Rui-Rui], Liu, J.[Jun], Liu, C.[Chuang],
Determination of Protein Content of Wheat Using Partial Least Squares Regression Based on Near-Infrared Spectroscopy Preprocessing,
ICRVC22(7-10)
IEEE DOI 2301
Proteins, Training, Instruments, Computational modeling, Data preprocessing, Predictive models, KS-MC-PLSR algorithm BibRef

Liu, C.X.[Cheng-Xin], Wang, K.W.[Ke-Wei], Lu, H.[Hao], Cao, Z.G.[Zhi-Guo],
Dynamic Color Transform for Wheat Head Detection,
CVPPA21(1278-1283)
IEEE DOI 2112
Head, Uncertainty, Image color analysis, Lighting, Transforms, Detectors BibRef

Bhagat, S.[Sandesh], Kokare, M.[Manesh], Haswani, V.[Vineet], Hambarde, P.[Praful], Kamble, R.[Ravi],
WheatNet-Lite: A Novel Light Weight Network for Wheat Head Detection,
CVPPA21(1332-1341)
IEEE DOI 2112
Deep learning, Head, Convolution, Annotations, Image edge detection, Crops, Feature extraction BibRef

Najafian, K.[Keyhan], Ghanbari, A.[Alireza], Stavness, I.[Ian], Jin, L.L.[Ling-Ling], Shirdel, G.H.[Gholam Hassan], Maleki, F.[Farhad],
A Semi-self-supervised Learning Approach for Wheat Head Detection using Extremely Small Number of Labeled Samples,
CVPPA21(1342-1351)
IEEE DOI 2112
Training, Deep learning, Adaptation models, Head, Computational modeling, Conferences BibRef

Gansukh, B., Batsaikhan, B., Dorjsuren, A., Jamsran, C., Batsaikhan, N.,
Monitoring Wheat Crop Growth Parameters Using Time Series Sentinel-1 And Sentinel-2 Data for Agricultural Application In Mongolia,
ISPRS20(B3:989-994).
DOI Link 2012
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Chauhan, S., Darvishzadeh, R., Lu, Y., Stroppiana, D., Boschetti, M., Pepe, M., Nelson, A.,
Wheat Lodging Assessment Using Multispectral UAV Data,
UAV-g19(235-240).
DOI Link 1912
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Aich, S., Josuttes, A., Ovsyannikov, I., Strueby, K., Ahmed, I., Duddu, H.S., Pozniak, C., Shirtliffe, S., Stavness, I.,
DeepWheat: Estimating Phenotypic Traits from Crop Images with Deep Learning,
WACV18(323-332)
IEEE DOI 1806
crops, deconvolution, feature extraction, image colour analysis, learning (artificial intelligence), regression analysis, Task analysis BibRef

Nakanishi, T., Imai, Y., Morita, T., Akamatsu, Y., Odagawa, S., Takeda, T., Kashimura, O.,
Evaluation Of Wheat Growth Monitoring Methods Based On Hyperspectral Data Of Later Grain Filling And Heading Stages In Western Australia,
ISPRS12(XXXIX-B8:295-300).
DOI Link 1209
BibRef

d'Andrimont, R.[Raphael], Duveiller, G.[Gregory], Defourny, P.[Pierre],
Exploring the capacity to grasp multi-annual seasonal variability of winter wheat in Continental Climates with MODIS,
MultiTemp11(221-224).
IEEE DOI 1109
BibRef

Chacon, M.I.[Mario I.], Manickavasagan, A.[Annamalai], Flores-Tapia, D.[Daniel], Thomas, G.[Gabriel], Jayas, D.S.[Digvir S.],
Segmentation of Wheat Grains in Thermal Images Based on Pulse Coupled Neural Networks,
ICIP07(II: 273-276).
IEEE DOI 0709
BibRef

Guzman-Arenas, A., Seco, R.M.[Rosa Ma], and Sanchez, V.G.[Victor G.],
Computer Analysis of Images for Crop Identification in Mexico,
TRIIMAS, Vol. 7, no. 135, 1976, UNAM. Crop id - wheat/cotton in NW Mexico; standard classification techniques; spectral signature and set of heuristic functions that the user defines. BibRef 7600

Chapter on Remote Sensing General Issue, Land Use, Land Cover continues in
Wheat Yield Estimates, Prediction .


Last update:Mar 16, 2024 at 20:36:19