Yang, H.[Hao],
Li, Z.Y.[Zeng-Yuan],
Chen, E.[Erxue],
Zhao, C.J.[Chun-Jiang],
Yang, G.J.[Gui-Jun],
Casa, R.[Raffaele],
Pignatti, S.[Stefano],
Feng, Q.[Qi],
Temporal Polarimetric Behavior of Oilseed Rape (Brassica napus L.) at
C-Band for Early Season Sowing Date Monitoring,
RS(6), No. 11, 2014, pp. 10375-10394.
DOI Link
1412
BibRef
Fang, S.H.[Sheng-Hui],
Tang, W.C.[Wen-Chao],
Peng, Y.[Yi],
Gong, Y.[Yan],
Dai, C.[Can],
Chai, R.[Ruhui],
Liu, K.[Kan],
Remote Estimation of Vegetation Fraction and Flower Fraction in
Oilseed Rape with Unmanned Aerial Vehicle Data,
RS(8), No. 5, 2016, pp. 416.
DOI Link
1606
BibRef
Han, J.H.[Jia-Hui],
Wei, C.W.[Chuan-Wen],
Chen, Y.L.[Yao-Liang],
Liu, W.W.[Wei-Wei],
Song, P.L.[Pei-Lin],
Zhang, D.D.[Dong-Dong],
Wang, A.Q.[An-Qi],
Song, X.D.[Xiao-Dong],
Wang, X.Z.[Xiu-Zhen],
Huang, J.F.[Jing-Feng],
Mapping Above-Ground Biomass of Winter Oilseed Rape Using High
Spatial Resolution Satellite Data at Parcel Scale under Waterlogging
Conditions,
RS(9), No. 3, 2017, pp. xx-yy.
DOI Link
1704
See also Mapping Water-Logging Damage on Winter Wheat at Parcel Level Using High Spatial Resolution Satellite Data.
BibRef
Wei, C.W.[Chuan-Wen],
Huang, J.F.[Jing-Feng],
Mansaray, L.R.[Lamin R.],
Li, Z.H.[Zhen-Hai],
Liu, W.W.[Wei-Wei],
Han, J.H.[Jia-Hui],
Estimation and Mapping of Winter Oilseed Rape LAI from High Spatial
Resolution Satellite Data Based on a Hybrid Method,
RS(9), No. 5, 2017, pp. xx-yy.
DOI Link
1706
BibRef
Zhang, W.F.[Wang-Fei],
Li, Z.Y.[Zeng-Yuan],
Chen, E.[Erxue],
Zhang, Y.H.[Ya-Hong],
Yang, H.[Hao],
Zhao, L.[Lei],
Ji, Y.J.[Yong-Jie],
Compact Polarimetric Response of Rape (Brassica napus L.) at C-Band:
Analysis and Growth Parameters Inversion,
RS(9), No. 6, 2017, pp. xx-yy.
DOI Link
1706
oil seed crop.
BibRef
Wang, D.[Dong],
Fang, S.H.[Sheng-Hui],
Yang, Z.Z.[Zhen-Zhong],
Wang, L.[Lin],
Tang, W.C.[Wen-Chao],
Li, Y.C.[Yu-Cui],
Tong, C.Y.[Chun-Yan],
A Regional Mapping Method for Oilseed Rape Based on HSV
Transformation and Spectral Features,
IJGI(7), No. 6, 2018, pp. xx-yy.
DOI Link
1806
BibRef
Zhang, W.F.[Wang-Fei],
Chen, E.[Erxue],
Li, Z.Y.[Zeng-Yuan],
Zhao, L.[Lei],
Ji, Y.J.[Yong-Jie],
Zhang, Y.H.[Ya-Hong],
Liu, Z.Q.[Zhi-Qin],
Rape (Brassica napus L.) Growth Monitoring and Mapping Based on
Radarsat-2 Time-Series Data,
RS(10), No. 2, 2018, pp. xx-yy.
DOI Link
1804
BibRef
Wan, L.[Liang],
Li, Y.J.[Yi-Jian],
Cen, H.Y.[Hai-Yan],
Zhu, J.P.[Jiang-Peng],
Yin, W.X.[Wen-Xin],
Wu, W.[Weikang],
Zhu, H.Y.[Hong-Yan],
Sun, D.W.[Da-Wei],
Zhou, W.J.[Wei-Jun],
He, Y.[Yong],
Combining UAV-Based Vegetation Indices and Image Classification to
Estimate Flower Number in Oilseed Rape,
RS(10), No. 9, 2018, pp. xx-yy.
DOI Link
1810
BibRef
Abdalla, A.[Alwaseela],
Cen, H.Y.[Hai-Yan],
Abdel-Rahman, E.[Elfatih],
Wan, L.[Liang],
He, Y.[Yong],
Color Calibration of Proximal Sensing RGB Images of Oilseed Rape
Canopy via Deep Learning Combined with K-Means Algorithm,
RS(11), No. 24, 2019, pp. xx-yy.
DOI Link
1912
BibRef
Ashourloo, D.[Davoud],
Shahrabi, H.S.[Hamid Salehi],
Azadbakht, M.[Mohsen],
Aghighi, H.[Hossein],
Nematollahi, H.[Hamed],
Alimohammadi, A.[Abbas],
Matkan, A.A.[Ali Akbar],
Automatic canola mapping using time series of sentinel 2 images,
PandRS(156), 2019, pp. 63-76.
Elsevier DOI
1909
Precision agriculture, Canola, Flowering date,
Automatic crop mapping, Spectral index, Sentinel-2 time-series
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
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
Zhang, J.[Jian],
Xie, T.J.[Tian-Jin],
Yang, C.H.[Cheng-Hai],
Song, H.B.[Huai-Bo],
Jiang, Z.[Zhao],
Zhou, G.S.[Guang-Sheng],
Zhang, D.Y.[Dong-Yan],
Feng, H.[Hui],
Xie, J.[Jing],
Segmenting Purple Rapeseed Leaves in the Field from UAV RGB Imagery
Using Deep Learning as an Auxiliary Means for Nitrogen Stress
Detection,
RS(12), No. 9, 2020, pp. xx-yy.
DOI Link
2005
BibRef
Jelowicki, L.[Lukasz],
Sosnowicz, K.[Konrad],
Ostrowski, W.[Wojciech],
Osinska-Skotak, K.[Katarzyna],
Bakula, K.[Krzysztof],
Evaluation of Rapeseed Winter Crop Damage Using UAV-Based
Multispectral Imagery,
RS(12), No. 16, 2020, pp. xx-yy.
DOI Link
2008
BibRef
Hussain, S.[Sadeed],
Gao, K.X.[Kai-Xiu],
Din, M.[Mairaj],
Gao, Y.K.[Yong-Kang],
Shi, Z.H.[Zhi-Hua],
Wang, S.Q.[Shan-Qin],
Assessment of UAV-Onboard Multispectral Sensor for Non-Destructive
Site-Specific Rapeseed Crop Phenotype Variable at Different
Phenological Stages and Resolutions,
RS(12), No. 3, 2020, pp. xx-yy.
DOI Link
2002
BibRef
Zang, Y.Z.[Yun-Ze],
Chen, X.H.[Xue-Hong],
Chen, J.[Jin],
Tian, Y.G.[Yu-Gang],
Shi, Y.S.[Yu-Sheng],
Cao, X.[Xin],
Cui, X.H.[Xi-Hong],
Remote Sensing Index for Mapping Canola Flowers Using MODIS Data,
RS(12), No. 23, 2020, pp. xx-yy.
DOI Link
2012
BibRef
Liu, S.[Shishi],
Yang, X.[Xin],
Guan, Q.F.[Qing-Feng],
Lu, Z.F.[Zhi-Feng],
Lu, J.W.[Jian-Wei],
An Ensemble Modeling Framework for Distinguishing Nitrogen,
Phosphorous and Potassium Deficiencies in Winter Oilseed Rape
(Brassica napus L.) Using Hyperspectral Data,
RS(12), No. 24, 2020, pp. xx-yy.
DOI Link
2012
BibRef
Han, J.C.[Ji-Chong],
Zhang, Z.[Zhao],
Cao, J.[Juan],
Developing a New Method to Identify Flowering Dynamics of Rapeseed
Using Landsat 8 and Sentinel-1/2,
RS(13), No. 1, 2021, pp. xx-yy.
DOI Link
2101
BibRef
Zhang, W.F.[Wang-Fei],
Zhang, Y.X.[Yong-Xin],
Yang, Y.[Yue],
Chen, E.[Erxue],
Oilseed Rape (Brassica napus L.) Phenology Estimation by Averaged
Stokes-Related Parameters,
RS(13), No. 14, 2021, pp. xx-yy.
DOI Link
2107
BibRef
Zhang, H.Y.[Hong-Yan],
Liu, W.B.[Wen-Bin],
Zhang, L.P.[Liang-Pei],
Seamless and automated rapeseed mapping for large cloudy regions
using time-series optical satellite imagery,
PandRS(184), 2022, pp. 45-62.
Elsevier DOI
2202
Rapeseed mapping, Time-series optical satellite imagery,
Large cloudy region, Winter Rapeseed Index, Phenology, Machine learning
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
Tian, H.F.[Hai-Feng],
Chen, T.[Ting],
Li, Q.Z.[Qiang-Zi],
Mei, Q.Y.[Qiu-Yi],
Wang, S.[Shuai],
Yang, M.D.[Meng-Dan],
Wang, Y.J.[Yong-Jiu],
Qin, Y.[Yaochen],
A Novel Spectral Index for Automatic Canola Mapping by Using
Sentinel-2 Imagery,
RS(14), No. 5, 2022, pp. xx-yy.
DOI Link
2203
BibRef
Tang, W.C.[Wen-Chao],
Tang, R.X.[Rong-Xin],
Guo, T.[Tao],
Wei, J.B.[Jing-Bo],
Remote Prediction of Oilseed Rape Yield via Gaofen-1 Images and a
Crop Model,
RS(14), No. 9, 2022, pp. xx-yy.
DOI Link
2205
BibRef
Chen, S.M.[Shao-Mei],
Li, Z.F.[Zhao-Fu],
Ji, T.L.[Ting-Li],
Zhao, H.Y.[Hai-Yan],
Jiang, X.S.[Xiao-San],
Gao, X.[Xiang],
Pan, J.J.[Jian-Jun],
Zhang, W.M.[Wen-Min],
Two-Stepwise Hierarchical Adaptive Threshold Method for Automatic
Rapeseed Mapping over Jiangsu Using Harmonized Landsat/Sentinel-2,
RS(14), No. 11, 2022, pp. xx-yy.
DOI Link
2206
BibRef
Fernando, H.[Hansanee],
Ha, T.[Thuan],
Attanayake, A.[Anjika],
Benaragama, D.[Dilshan],
Nketia, K.A.[Kwabena Abrefa],
Kanmi-Obembe, O.[Olakorede],
Shirtliffe, S.J.[Steven J.],
High-Resolution Flowering Index for Canola Yield Modelling,
RS(14), No. 18, 2022, pp. xx-yy.
DOI Link
2209
BibRef
Lukas, V.[Vojtech],
Hunady, I.[Igor],
Kintl, A.[Antonín],
Mezera, J.[Jirí],
Hammerschmiedt, T.[Tereza],
Sobotková, J.[Julie],
Brtnický, M.[Martin],
Elbl, J.[Jakub],
Using UAV to Identify the Optimal Vegetation Index for Yield
Prediction of Oil Seed Rape (Brassica napus L.) at the Flowering
Stage,
RS(14), No. 19, 2022, pp. xx-yy.
DOI Link
2210
BibRef
Yang, Y.[Yang],
Wei, X.[Xinbei],
Wang, J.[Jiang],
Zhou, G.S.[Guang-Sheng],
Wang, J.[Jian],
Jiang, Z.T.[Zi-Tong],
Zhao, J.[Jie],
Ren, Y.[Yilin],
Prediction of Seedling Oilseed Rape Crop Phenotype by Drone-Derived
Multimodal Data,
RS(15), No. 16, 2023, pp. 3951.
DOI Link
2309
BibRef
Maleki, S.[Saeideh],
Baghdadi, N.[Nicolas],
Najem, S.[Sami],
Dantas, C.F.[Cassio Fraga],
Bazzi, H.[Hassan],
Ienco, D.[Dino],
Determining Effective Temporal Windows for Rapeseed Detection Using
Sentinel-1 Time Series and Machine Learning Algorithms,
RS(16), No. 3, 2024, pp. 549.
DOI Link
2402
BibRef
Lussem, U.,
Hütt, C.,
Waldhoff, G.,
Combined Analysis Of Sentinel-1 And Rapideye Data For Improved Crop
Type Classification: An Early Season Approach For Rapeseed And Cereals,
ISPRS16(B8: 959-963).
DOI Link
1610
BibRef
Chapter on Remote Sensing General Issue, Land Use, Land Cover continues in
Pasture, Grassland, Rangeland Analysis .