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
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, 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.[Qiuyi],
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.[Jingbo],
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
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 and Change .