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Winter wheat, Water-logging, Parcel scale,
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Estimation of LAI in Winter Wheat from Multi-Angular Hyperspectral
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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
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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],
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RS(10), No. 12, 2018, pp. xx-yy.
DOI Link
1901
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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
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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
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Song, Y.[Yang],
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Mapping Winter Wheat Planting Area and Monitoring Its Phenology Using
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1903
BibRef
Upreti, D.[Deepak],
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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.
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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
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RS(11), No. 6, 2019, pp. xx-yy.
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1903
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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
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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
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1905
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Qin, Q.M.[Qi-Ming],
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RS(11), No. 8, 2019, pp. xx-yy.
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1905
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A New Integrated Vegetation Index for the Estimation of Winter Wheat
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RS(11), No. 8, 2019, pp. xx-yy.
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1905
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Crop Sensor-Based In-Season Nitrogen Management of Wheat with Manure
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RS(11), No. 9, 2019, pp. xx-yy.
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1905
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RS(11), No. 9, 2019, pp. xx-yy.
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1905
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Wocher, M.[Matthias],
Mauser, W.[Wolfram],
Hank, T.[Tobias],
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RS(11), No. 10, 2019, pp. xx-yy.
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1906
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Peng, F.[Fanchen],
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RS(11), No. 10, 2019, pp. xx-yy.
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DOI Link
2004
BibRef
Xu, X.O.[Xia-Obin],
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Jin, X.L.[Xiu-Liang],
Song, X.Y.[Xiao-Yu],
Gu, X.H.[Xiao-He],
Casa, R.[Raffaele],
Chen, L.P.[Li-Ping],
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2004
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Elsevier DOI
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Remote sensing, Multi-temporal optical and SAR data,
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IEEE DOI
2005
Soil moisture, Soil measurements, Synthetic aperture radar,
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Combining Genetic Analysis and Multivariate Modeling to Evaluate
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2005
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2101
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Elsevier DOI
2005
Lodging score, Lodging severity, Sentinel-1, RADARSAT-2, PLS-DA,
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Igathinathane, C.,
Naik, D.L.[Dayakar L.],
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2006
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Wang, X.L.[Xin-Lei],
Huang, J.X.[Jian-Xi],
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Winter Wheat Yield Prediction at County Level and Uncertainty
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Aniskevich, S.[Svetlana],
Bobylev, L.[Leonid],
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Caluwaerts, S.[Steven],
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Gnatiuk, N.[Natalia],
Hamdi, R.[Rafiq],
Remedio, A.R.[Armelle Reca],
Sakalli, A.[Abdulla],
van de Vyver, H.[Hans],
van Schaeybroeck, B.[Bert],
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Wheat Yield Estimation from NDVI and Regional Climate Models in
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2007
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2007
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Song, Y.[Yang],
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Shang, J.[Jiali],
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Using UAV-Based SOPC Derived LAI and SAFY Model for Biomass and Yield
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2008
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Sun, J.[Jing],
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Spatiotemporal Dynamics of the Northern Limit of Winter Wheat in
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2008
BibRef
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Waine, T.W.[Toby W.],
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Deriving Wheat Crop Productivity Indicators Using Sentinel-1 Time
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2008
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Zhou, X.F.[Xian-Feng],
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Chen, D.M.[Dong-Mei],
Huang, Y.[Yanbo],
Kong, W.P.[Wei-Ping],
Yuan, L.[Lin],
Ye, H.[Huichun],
Huang, W.J.[Wen-Jiang],
Assessment of Leaf Chlorophyll Content Models for Winter Wheat Using
Landsat-8 Multispectral Remote Sensing Data,
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DOI Link
2008
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Upreti, D.[Deepak],
Pignatti, S.[Stefano],
Pascucci, S.[Simone],
Tolomio, M.[Massimo],
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Casa, R.[Raffaele],
Bayesian Calibration of the Aquacrop-OS Model for Durum Wheat by
Assimilation of Canopy Cover Retrieved from VENµS Satellite Data,
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2008
BibRef
Lang, T.T.[Ting-Ting],
Yang, Y.Z.[Yan-Zhao],
Jia, K.[Kun],
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Remotely-Sensed Imagery and Process-Based Model Simulations,
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2009
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Castellón, A.[Ander],
Aizpurua, A.[Ana],
Wheat Yield Estimation with NDVI Values Using a Proximal Sensing Tool,
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2009
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Rodríguez-Rastrero, M.[Manuel],
Recuero, L.[Laura],
Huesca, M.[Margarita],
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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,
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2009
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Wang, S.[Shuai],
Chen, J.[Jin],
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Liu, L.C.[Li-Cong],
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Elsevier DOI
2009
Spring frost, Winter wheat, Damage assessment, Remote sensing, North China
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Zhu, K.Y.[Kang-Ying],
Sun, Z.G.[Zhi-Gang],
Zhao, F.H.[Feng-Hua],
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Lai, J.B.[Jian-Bin],
Long, B.[Buju],
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Remotely sensed canopy resistance model for analyzing the stomatal
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PandRS(168), 2020, pp. 197-207.
Elsevier DOI
2009
Remote sensing model, Canopy resistance, Stomatal behavior,
Dry-hot wind stress, Salt stress, Winter wheat
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Nutrient Prediction for Tef (Eragrostis tef) Plant and Grain with
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2009
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Lee, T.[Trey],
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Franzluebbers, A.[Alan],
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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
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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
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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
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2010
BibRef
Song, Y.[Yang],
Wang, J.[Jing],
Wang, L.X.[Li-Xin],
Satellite Solar-Induced Chlorophyll Fluorescence Reveals Heat Stress
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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],
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Sun, L.X.[Li-Xin],
A Method for Monitoring and Forecasting the Heading and Flowering
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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,
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2011
BibRef
Liu, L.[Linyi],
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Huang, W.J.[Wen-Jiang],
Du, X.P.[Xiao-Ping],
Ma, H.Q.[Hui-Qin],
Monitoring Wheat Fusarium Head Blight Using Unmanned Aerial Vehicle
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2011
BibRef
Ma, H.Q.[Hui-Qin],
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Dong, Y.Y.[Ying-Ying],
Liu, L.Y.[Lin-Yi],
Guo, A.[Anting],
Using UAV-Based Hyperspectral Imagery to Detect Winter Wheat Fusarium
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RS(13), No. 15, 2021, pp. xx-yy.
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2108
BibRef
Dehkordi, R.H.[Ramin Heidarian],
El Jarroudi, M.[Moussa],
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Monitoring Wheat Leaf Rust and Stripe Rust in Winter Wheat Using
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2011
BibRef
Shawon, A.R.[Ashifur Rahman],
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Jeong, S.[Seungtaek],
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Two-Dimensional Simulation of Barley Growth and Yield Using a Model
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2011
BibRef
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Ben-David, R.[Roi],
Lati, R.N.[Ran N.],
Image-Based High-Throughput Phenotyping of Cereals Early Vigor and
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2012
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Yang, C.[Ce],
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Automatic Evaluation of Wheat Resistance to Fusarium Head Blight
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2101
BibRef
He, L.,
Qi, S.L.,
Duan, J.Z.,
Guo, T.C.,
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Monitoring of Wheat Powdery Mildew Disease Severity Using Multiangle
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IEEE DOI
2101
Diseases, Monitoring, Remote sensing, Indexes, Agriculture,
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Zhu, K.Y.[Kang-Ying],
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Relating Hyperspectral Vegetation Indices with Soil Salinity at
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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],
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2101
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UAV-Thermal imaging and agglomerative hierarchical clustering
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PandRS(173), 2021, pp. 221-237.
Elsevier DOI
2102
Canopy temperature, Plant water stress, Vegetation indices,
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2103
BibRef
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Improved Estimation of Winter Wheat Aboveground Biomass Using
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RS(13), No. 4, 2021, pp. xx-yy.
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2103
BibRef
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2103
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Vegetation Indices Data Clustering for Dynamic Monitoring and
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2103
BibRef
Liu, Y.[Yu],
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RS(13), No. 4, 2021, pp. xx-yy.
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2103
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Outlier Detection at the Parcel-Level in Wheat and Rapeseed Crops
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2103
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A Neural Network Method for Classification of Sunlit and Shaded
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RS(13), No. 5, 2021, pp. xx-yy.
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2103
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RS(13), No. 6, 2021, pp. xx-yy.
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2104
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Comparison of Regional Winter Wheat Mapping Results from Different
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2104
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RS(13), No. 6, 2021, pp. xx-yy.
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2104
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Mapping the Dynamics of Winter Wheat in the North China Plain from
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2104
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Raya-Sereno, M.D.[María D.],
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High-Resolution Airborne Hyperspectral Imagery for Assessing Yield,
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2104
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2104
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2104
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2104
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Agriculture, Remote sensing, Synthetic aperture radar,
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crops, deconvolution, feature extraction, image colour analysis,
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Agriculture, Diseases, Monitoring, Remote sensing,
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Chapter on Remote Sensing General Issue, Land Use, Land Cover continues in
Potato Crop Analysis, Production, Detection, Health, Change .