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
Sun, C.M.[Chang-Ming],
Berman, M.[Mark],
Coward, D.[David],
Osborne, B.[Brian],
Thickness measurement and crease detection of wheat grains using stereo
vision,
PRL(28), No. 12, 1 September 2007, pp. 1501-1508.
Elsevier DOI
0707
Grain thickness measurement; Grain crease detection; Stereo vision
BibRef
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
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
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.[Xinping],
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
Yuan, L.[Lin],
Zhang, J.C.[Jing-Cheng],
Shi, Y.[Yeyin],
Nie, C.W.[Chen-Wei],
Wei, L.G.[Li-Guang],
Wang, J.[Jihua],
Damage Mapping of Powdery Mildew in Winter Wheat with High-Resolution
Satellite Image,
RS(6), No. 5, 2014, pp. 3611-3623.
DOI Link
1407
BibRef
Ashourloo, D.[Davoud],
Mobasheri, M.R.[Mohammad Reza],
Huete, A.[Alfredo],
Developing Two Spectral Disease Indices for Detection of Wheat Leaf
Rust (Pucciniatriticina),
RS(6), No. 6, 2014, pp. 4723-4740.
DOI Link
1407
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
Ashourloo, D.[Davoud],
Mobasheri, M.R.[Mohammad Reza],
Huete, A.[Alfredo],
Evaluating the Effect of Different Wheat Rust Disease Symptoms on
Vegetation Indices Using Hyperspectral Measurements,
RS(6), No. 6, 2014, pp. 5107-5123.
DOI Link
1407
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
Bendig, J.[Juliane],
Bolten, A.[Andreas],
Bennertz, S.[Simon],
Broscheit, J.[Janis],
Eichfuss, S.[Silas],
Bareth, G.[Georg],
Estimating Biomass of Barley Using Crop Surface Models (CSMs) Derived
from UAV-Based RGB Imaging,
RS(6), No. 11, 2014, pp. 10395-10412.
DOI Link
1412
BibRef
Brocks, S.[Sebastian],
Bareth, G.[Georg],
Estimating Barley Biomass with Crop Surface Models from Oblique RGB
Imagery,
RS(10), No. 2, 2018, pp. xx-yy.
DOI Link
1804
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
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
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
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
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
Tilly, N.[Nora],
Aasen, H.[Helge],
Bareth, G.[George],
Fusion of Plant Height and Vegetation Indices for the Estimation of
Barley Biomass,
RS(7), No. 9, 2015, pp. 11449.
DOI Link
1511
BibRef
And:
Correction:
RS(7), No. 12, 2015, pp. 15878.
DOI Link
1601
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
Zheng, Y.[Yang],
Zhang, M.[Miao],
Zhang, X.[Xin],
Zeng, H.W.[Hong-Wei],
Wu, B.[Bingfang],
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
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
Jain, M.[Meha],
Srivastava, A.K.[Amit K.],
Balwinder-Singh,
Joon, R.K.[Rajiv K.],
McDonald, A.[Andrew],
Royal, K.[Keitasha],
Lisaius, M.C.[Madeline C.],
Lobell, D.B.[David B.],
Mapping Smallholder Wheat Yields and Sowing Dates Using
Micro-Satellite Data,
RS(8), No. 10, 2016, pp. 860.
DOI Link
1609
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
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.[Haikuan],
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
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
Jin, X.L.[Xiu-Liang],
Li, Z.H.[Zhen-Hai],
Yang, G.J.[Gui-Jun],
Yang, H.[Hao],
Feng, H.[Haikuan],
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.[Zhenhai],
Yang, G.[Guijun],
Huang, W.[Wenjiang],
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
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
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
Yue, J.[Jibo],
Feng, H.[Haikuan],
Yang, G.[Guijun],
Li, Z.[Zhenhai],
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.[Yongchao],
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.[Guijun],
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
Jin, X.[Xiu],
Jie, L.[Lu],
Wang, S.[Shuai],
Qi, H.J.[Hai Jun],
Li, S.W.[Shao Wen],
Classifying Wheat Hyperspectral Pixels of Healthy Heads and Fusarium
Head Blight Disease Using a Deep Neural Network in the Wild Field,
RS(10), No. 3, 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
Shi, Y.[Yue],
Huang, W.[Wenjiang],
González-Moreno, P.[Pablo],
Luke, B.[Belinda],
Dong, Y.Y.[Ying-Ying],
Zheng, Q.[Qiong],
Ma, H.Q.[Hui-Qin],
Liu, L.[Linyi],
Wavelet-Based Rust Spectral Feature Set (WRSFs): A Novel Spectral
Feature Set Based on Continuous Wavelet Transformation for Tracking
Progressive Host-Pathogen Interaction of Yellow Rust on Wheat,
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.[Jinhai],
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, W.W.[Wei-Wei],
Huang, J.F.[Jing-Feng],
Wei, C.W.[Chuan-Wen],
Wang, X.Z.[Xiu-Zhen],
Mansaray, L.R.[Lamin R.],
Han, J.[Jiahui],
Zhang, D.D.[Dong-Dong],
Chen, Y.[Yaoliang],
Mapping Water-Logging Damage on Winter Wheat at Parcel Level Using
High Spatial Resolution Satellite Data,
PandRS(142), 2018, pp. 243-256.
Elsevier DOI
1807
Winter wheat, Water-logging, Parcel scale,
High resolution satellite data, Biophysical parameters
See also Mapping Above-Ground Biomass of Winter Oilseed Rape Using High Spatial Resolution Satellite Data at Parcel Scale under Waterlogging Conditions.
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
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
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.[Hanyue],
Huang, W.[Wenjiang],
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
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
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.[Huiqin],
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.[Guijun],
Tian, Q.J.[Qing-Jiu],
Feng, H.[Haikuan],
Xu, K.[Kaijian],
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.[Wenjiang],
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.[Keqi],
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
Yue, J.[Jibo],
Tian, Q.J.[Qing-Jiu],
Dong, X.Y.[Xin-Yu],
Xu, K.J.[Kai-Jian],
Zhou, C.Q.[Cheng-Quan],
Using Hyperspectral Crop Residue Angle Index to Estimate Maize and
Winter-Wheat Residue Cover: A Laboratory Study,
RS(11), No. 7, 2019, pp. xx-yy.
DOI Link
1904
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.[Linyi],
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
Wang, Y.[Yulong],
Xu, X.G.[Xin-Gang],
Huang, L.[Linsheng],
Yang, G.[Guijun],
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
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
Cai, W.[Wenting],
Zhao, S.[Shuhe],
Wang, Y.[Yamei],
Peng, F.[Fanchen],
Heo, J.[Joon],
Duan, Z.[Zheng],
Estimation of Winter Wheat Residue Coverage Using Optical and SAR
Remote Sensing Images,
RS(11), No. 10, 2019, pp. xx-yy.
DOI Link
1906
BibRef
Yang, Y.[Yanjun],
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.[Jinfei],
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.[Linghui],
Gao, J.B.[Jiang-Bo],
Hao, C.Y.[Cheng-Yuan],
Zhang, L.L.[Lin-Lin],
Wu, S.H.[Shao-Hong],
Xiao, X.[Xiangming],
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.[Jiali],
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.[Chuanjie],
Liu, Q.S.[Qing-Sheng],
Guan, S.[Shiying],
Liu, G.[Gaohuan],
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
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
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
Zhang, D.Y.[Dong-Yan],
Wang, D.Y.[Dao-Yong],
Gu, C.Y.[Chun-Yan],
Jin, N.[Ning],
Zhao, H.T.[Hai-Tao],
Chen, G.[Gao],
Liang, H.Y.[Hong-Yi],
Liang, D.[Dong],
Using Neural Network to Identify the Severity of Wheat Fusarium Head
Blight in the Field Environment,
RS(11), No. 20, 2019, pp. xx-yy.
DOI Link
1910
BibRef
Zhu, W.[Wanxue],
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.[Xiaohan],
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
Bohnenkamp, D.[David],
Behmann, J.[Jan],
Mahlein, A.K.[Anne-Katrin],
In-Field Detection of Yellow Rust in Wheat on the Ground Canopy and
UAV Scale,
RS(11), No. 21, 2019, pp. xx-yy.
DOI Link
1911
BibRef
Tuvdendorj, B.[Battsetseg],
Wu, B.[Bingfang],
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
Fitzgerald, G.J.[Glenn J.],
Perry, E.M.[Eileen M.],
Flower, K.C.[Ken C.],
Callow, J.N.[J. Nikolaus],
Boruff, B.[Bryan],
Delahunty, A.[Audrey],
Wallace, A.[Ashley],
Nuttall, J.[James],
Frost Damage Assessment in Wheat Using Spectral Mixture Analysis,
RS(11), No. 21, 2019, pp. xx-yy.
DOI Link
1911
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
Qiu, R.[Ruicheng],
Yang, C.[Ce],
Moghimi, A.[Ali],
Zhang, M.[Man],
Steffenson, B.J.[Brian J.],
Hirsch, C.D.[Cory D.],
Detection of Fusarium Head Blight in Wheat Using a Deep Neural
Network and Color Imaging,
RS(11), No. 22, 2019, pp. xx-yy.
DOI Link
1911
BibRef
Jia, M.[Min],
Li, D.[Dong],
Colombo, R.[Roberto],
Wang, Y.[Ying],
Wang, X.[Xue],
Cheng, T.[Tao],
Zhu, Y.[Yan],
Yao, X.[Xia],
Xu, C.J.[Chang-Jun],
Ouer, G.[Geli],
Li, H.Y.[Hong-Ying],
Zhang, C.[Chaokun],
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
BibRef
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
BibRef
Meng, S.[Shiyao],
Zhong, Y.F.[Yan-Fei],
Luo, C.[Chang],
Hu, X.[Xin],
Wang, X.Y.[Xin-Yu],
Huang, S.X.[Sheng-Xiang],
Optimal Temporal Window Selection for Winter Wheat and Rapeseed
Mapping with Sentinel-2 Images: A Case Study of Zhongxiang in China,
RS(12), No. 2, 2020, pp. xx-yy.
DOI Link
2001
BibRef
Han, J.C.[Ji-Chong],
Zhang, Z.[Zhao],
Cao, J.[Juan],
Luo, Y.C.[Yu-Chuan],
Zhang, L.L.[Liang-Liang],
Li, Z.[Ziyue],
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.[Ziyue],
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
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
BibRef
Xing, N.C.[Nai-Chen],
Huang, W.J.[Wen-Jiang],
Xie, Q.Y.[Qiao-Yun],
Shi, Y.[Yue],
Ye, H.[Huichun],
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
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.[Yawen],
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
Li, F.[Feng],
Zhang, C.M.[Cheng-Ming],
Zhang, W.W.[Wen-Wen],
Xu, Z.G.[Zhi-Gang],
Wang, S.[Shouyi],
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
BibRef
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
BibRef
Song, Y.[Yang],
Wang, J.[Jing],
Yu, Q.A.[Qi-Ang],
Huang, J.[Jianxi],
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
BibRef
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
BibRef
And:
Erratum:
RS(12), No. 10, 2020, pp. xx-yy.
DOI Link
2006
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
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
BibRef
Mercier, A.[Audrey],
Betbeder, J.[Julie],
Baudry, J.[Jacques],
Le Roux, V.[Vincent],
Spicher, F.[Fabien],
Lacoux, J.[Jérôme],
Roger, D.[David],
Hubert-Moy, L.[Laurence],
Evaluation of Sentinel-1 and 2 time series for predicting wheat and
rapeseed phenological stages,
PandRS(163), 2020, pp. 231-256.
Elsevier DOI
2005
Remote sensing, Multi-temporal optical and SAR data,
Polarimetry, C-band, Crop phenology
BibRef
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
Guo, A.T.[An-Ting],
Huang, W.J.[Wen-Jiang],
Ye, H.[Huichun],
Dong, Y.Y.[Ying-Ying],
Ma, H.Q.[Hui-Qin],
Ren, Y.[Yu],
Ruan, C.[Chao],
Identification of Wheat Yellow Rust Using Spectral and Texture
Features of Hyperspectral Images,
RS(12), No. 9, 2020, pp. xx-yy.
DOI Link
2005
BibRef
Guo, A.T.[An-Ting],
Huang, W.J.[Wen-Jiang],
Dong, Y.Y.[Ying-Ying],
Ye, H.C.[Hui-Chun],
Ma, H.Q.[Hui-Qin],
Liu, B.[Bo],
Wu, W.B.[Wen-Bin],
Ren, Y.[Yu],
Ruan, C.[Chao],
Geng, Y.[Yun],
Wheat Yellow Rust Detection Using UAV-Based Hyperspectral Technology,
RS(13), No. 1, 2021, pp. xx-yy.
DOI Link
2101
BibRef
Zhang, X.[Xin],
Han, L.X.[Liang-Xiu],
Dong, Y.Y.[Ying-Ying],
Shi, Y.[Yue],
Huang, W.J.[Wen-Jiang],
Han, L.H.[Liang-Hao],
González-Moreno, P.[Pablo],
Ma, H.Q.[Hui-Qin],
Ye, H.C.[Hui-Chun],
Sobeih, T.[Tam],
A Deep Learning-Based Approach for Automated Yellow Rust Disease
Detection from High-Resolution Hyperspectral UAV Images,
RS(11), No. 13, 2019, pp. xx-yy.
DOI Link
1907
BibRef
Chauhan, S.[Sugandh],
Darvishzadeh, R.[Roshanak],
Boschetti, M.[Mirco],
Nelson, A.[Andrew],
Discriminant analysis for lodging severity classification in wheat
using RADARSAT-2 and Sentinel-1 data,
PandRS(164), 2020, pp. 138-151.
Elsevier DOI
2005
Lodging score, Lodging severity, Sentinel-1, RADARSAT-2, PLS-DA,
Sustainable agriculture
BibRef
Zhang, Z.[Zhao],
Flores, P.[Paulo],
Igathinathane, C.,
Naik, D.L.[Dayakar L.],
Kiran, R.[Ravi],
Ransom, J.K.[Joel K.],
Wheat Lodging Detection from UAS Imagery Using Machine Learning
Algorithms,
RS(12), No. 11, 2020, pp. xx-yy.
DOI Link
2006
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.[Jinfei],
Shang, J.[Jiali],
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
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
BibRef
Zhou, X.F.[Xian-Feng],
Zhang, J.C.[Jing-Cheng],
Chen, D.M.[Dong-Mei],
Huang, Y.[Yanbo],
Kong, W.P.[Wei-Ping],
Yuan, L.[Lin],
Ye, H.[Huichun],
Huang, W.[Wenjiang],
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.[Wenjiang],
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
BibRef
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
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
Cicuéndez, V.[Víctor],
Rodríguez-Rastrero, M.[Manuel],
Recuero, L.[Laura],
Huesca, M.[Margarita],
Schmid, T.[Thomas],
Inclán, R.[Rosa],
Litago, J.[Javier],
Sánchez-Girón, V.[Víctor],
Palacios-Orueta, A.[Alicia],
First Insights on Soil Respiration Prediction across the Growth
Stages of Rainfed Barley Based on Simulated MODIS and Sentinel-2
Spectral Indices,
RS(12), No. 17, 2020, pp. xx-yy.
DOI Link
2009
BibRef
Wang, S.[Shuai],
Chen, J.[Jin],
Rao, Y.H.[Yu-Han],
Liu, L.C.[Li-Cong],
Wang, W.Q.[Wen-Qing],
Dong, Q.[Qi],
Response of winter wheat to spring frost from a remote sensing
perspective: Damage estimation and influential factors,
PandRS(168), 2020, pp. 221-235.
Elsevier DOI
2009
Spring frost, Winter wheat, Damage assessment, Remote sensing, North China
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
BibRef
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
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
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
Xiao, Y.X.[Ying-Xin],
Dong, Y.Y.[Ying-Ying],
Huang, W.J.[Wen-Jiang],
Liu, L.Y.[Lin-Yi],
Ma, H.Q.[Hui-Qin],
Ye, H.C.[Hui-Chun],
Wang, K.[Kun],
Dynamic Remote Sensing Prediction for Wheat Fusarium Head Blight by
Combining Host and Habitat Conditions,
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
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
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.[Jianxi],
Li, X.[Xuecao],
Wang, J.[Jian],
Zhou, B.[Boyan],
Qin, Y.[Yaochen],
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
Liu, L.[Linyi],
Dong, Y.[Yingying],
Huang, W.[Wenjiang],
Du, X.P.[Xiao-Ping],
Ma, H.[Huiqin],
Monitoring Wheat Fusarium Head Blight Using Unmanned Aerial Vehicle
Hyperspectral Imagery,
RS(12), No. 22, 2020, pp. xx-yy.
DOI Link
2011
BibRef
Dehkordi, R.H.[Ramin Heidarian],
El Jarroudi, M.[Moussa],
Kouadio, L.[Louis],
Meersmans, J.[Jeroen],
Beyer, M.[Marco],
Monitoring Wheat Leaf Rust and Stripe Rust in Winter Wheat Using
High-Resolution UAV-Based Red-Green-Blue Imagery,
RS(12), No. 22, 2020, pp. xx-yy.
DOI Link
2011
BibRef
Shawon, A.R.[Ashifur Rahman],
Ko, J.[Jonghan],
Jeong, S.[Seungtaek],
Shin, T.[Taehwan],
Lee, K.D.[Kyung Do],
Shim, S.I.[Sang In],
Two-Dimensional Simulation of Barley Growth and Yield Using a Model
Integrated with Remote-Controlled Aerial Imagery,
RS(12), No. 22, 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
BibRef
Su, W.H.[Wen-Hao],
Zhang, J.[Jiajing],
Yang, C.[Ce],
Page, R.[Rae],
Szinyei, T.[Tamas],
Hirsch, C.D.[Cory D.],
Steffenson, B.J.[Brian J.],
Automatic Evaluation of Wheat Resistance to Fusarium Head Blight
Using Dual Mask-RCNN Deep Learning Frameworks in Computer Vision,
RS(13), No. 1, 2021, pp. xx-yy.
DOI Link
2101
BibRef
He, L.,
Qi, S.L.,
Duan, J.Z.,
Guo, T.C.,
Feng, W.,
He, D.X.,
Monitoring of Wheat Powdery Mildew Disease Severity Using Multiangle
Hyperspectral Remote Sensing,
GeoRS(59), No. 2, February 2021, pp. 979-990.
IEEE DOI
2101
Diseases, Monitoring, Remote sensing, Indexes, Agriculture,
Correlation, Vegetation mapping, Band combination,
wheat
BibRef
Zhu, K.Y.[Kang-Ying],
Sun, Z.G.[Zhi-Gang],
Zhao, F.[Fenghua],
Yang, T.[Ting],
Tian, Z.[Zhenrong],
Lai, J.B.[Jian-Bin],
Zhu, W.[Wanxue],
Long, B.[Buju],
Relating Hyperspectral Vegetation Indices with Soil Salinity at
Different Depths for the Diagnosis of Winter Wheat Salt Stress,
RS(13), No. 2, 2021, pp. xx-yy.
DOI Link
2101
BibRef
Zheng, Q.[Qiong],
Ye, H.C.[Hui-Chun],
Huang, W.J.[Wen-Jiang],
Dong, Y.Y.[Ying-Ying],
Jiang, H.[Hao],
Wang, C.Y.[Chong-Yang],
Li, D.[Dan],
Wang, L.[Li],
Chen, S.[Shuisen],
Integrating Spectral Information and Meteorological Data to Monitor
Wheat Yellow Rust at a Regional Scale: A Case Study,
RS(13), No. 2, 2021, pp. xx-yy.
DOI Link
2101
BibRef
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.[Guijun],
Song, X.Y.[Xiao-Yu],
Li, Z.H.[Zhen-Hong],
Xu, X.G.[Xin-Gang],
Feng, H.[Haikuan],
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
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
Liu, Y.[Yu],
Hatou, K.[Kenji],
Aihara, T.[Takanori],
Kurose, S.[Sakuya],
Akiyama, T.[Tsutomu],
Kohno, Y.S.[Yasu-Shi],
Lu, S.[Shan],
Omasa, K.[Kenji],
A Robust Vegetation Index Based on Different UAV RGB Images to
Estimate SPAD Values of Naked Barley Leaves,
RS(13), No. 4, 2021, pp. xx-yy.
DOI Link
2103
BibRef
Mouret, F.[Florian],
Albughdadi, M.[Mohanad],
Duthoit, S.[Sylvie],
Kouamé, D.[Denis],
Rieu, G.[Guillaume],
Tourneret, J.Y.[Jean-Yves],
Outlier Detection at the Parcel-Level in Wheat and Rapeseed Crops
Using Multispectral and SAR Time Series,
RS(13), No. 5, 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.[Jinha],
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.[Shangrong],
Zhao, H.W.[Hong-Wei],
Zhang, N.[Ningdan],
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
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
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
BibRef
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
BibRef
Wu, B.[Bin],
Huang, W.[Wenjiang],
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
BibRef
Pour, M.K.[Majid Khak],
Fotouhi, R.[Reza],
Hucl, P.[Pierre],
Zhang, Q.[Qianwei],
Development of a Mobile Platform for Field-Based High-Throughput
Wheat Phenotyping,
RS(13), No. 8, 2021, pp. xx-yy.
DOI Link
2104
BibRef
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
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
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
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
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
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
Xiao, Y.X.[Ying-Xin],
Dong, Y.Y.[Ying-Ying],
Huang, W.[Wenjiang],
Liu, L.[Linyi],
Ma, H.Q.[Hui-Qin],
Wheat Fusarium Head Blight Detection Using UAV-Based Spectral and
Texture Features in Optimal Window Size,
RS(13), No. 13, 2021, pp. xx-yy.
DOI Link
2107
BibRef
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
BibRef
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
Wellens, J.,
Sallah, A.H.,
Tychon, B.,
Piccard, I.,
Gobin, A.,
Curnel, Y.,
Leclef, A.,
Goffart, D.,
Planchon, V.,
Goffart, J.P.,
Delloye, C.,
Defourny, P.,
Assessment of AquaCrop for winter wheat using satellite derived
fCover data,
MultiTemp17(1-3)
IEEE DOI
1712
crops, mean square error methods, remote sensing,
AquaCrop assessment, AquaCrop plug-in model, Belgium,
yield estimate
BibRef
Pryzant, R.,
Ermon, S.,
Lobell, D.,
Monitoring Ethiopian Wheat Fungus with Satellite Imagery and Deep
Feature Learning,
EarthVision17(1524-1532)
IEEE DOI
1709
Agriculture, Diseases, Monitoring, Remote sensing,
Satellites, Spatial, resolution
BibRef
Siricharoen, P.[Punnarai],
Scotney, B.[Bryan],
Morrow, P.[Philip],
Parr, G.[Gerard],
Automated Wheat Disease Classification Under Controlled and
Uncontrolled Image Acquisition,
ICIAR15(456-464).
Springer DOI
1507
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
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.
HTML Version.
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
Cataltepe, Z.,
Cetin, E.,
Pearson, T.,
Identification of insect damaged wheat kernels using transmittance
images,
ICIP04(V: 2917-2920).
IEEE DOI
0505
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
Potato Crop Analysis, Production, Detection, Health, Change .