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Received：31 May 2021，
Published：07 October 2022
移动端阅览
冬小麦是中国的主要粮食作物且种植面积年际变化较大，及时准确掌握冬小麦种植面积变化有利于国家和相关部门科学决策。遥感技术是获取大范围冬小麦种植面积数据的最有效手段。前期研究多利用多时相中低分辨率影像（如MODIS）的归一化植被指数NDVI（Normalized Difference Vegetation Index）开展大范围冬小麦种植区提取，因分辨率低导致精度难以令人满意。Sentinel-2卫星是唯一能获取3个红边波段影像的米级分辨率传感器，但应用其红边波段进行大范围冬小麦提取的研究几乎没有。本文分析了红边位置指数REPI（Red-Edge Position Index）与NDVI各自在冬小麦提取中的优势，并基于冬小麦物候特征与JM距离研究关键时相，提出一种综合多时相Sentinel-2 PERI、NDVI的大范围冬小麦提取方法，将其应用于2020年京津冀地区的冬小麦种植区提取，冬小麦总面积提取误差为-2.57%。提取结果与Google Earth高分辨率光学影像的解译结果进行比较，总体精度为94.24%，Kappa系数为0.88，相较于已有大范围冬小麦提取研究精度有明显提升，表明了本文方法的有效性。
As the main grain crop in China
winter wheat planting area has great inter-annual variations. Remote Sensing (RS) technology is the most effective method to obtain the planting area data of winter wheat over wide areas. The Normalized Difference Vegetation Index (NDVI) parameter derived from multi-temporal RS images with medium and low resolution
such as MODIS imagery
is frequently used for such purpose. But the accuracy of obtained winter wheat planting area is usually unsatisfactory due to the limited spatial resolution of the used RS images. Sentinel-2A and Sentine-2B
which were launched in 2015 and 2017 respectively
are currently the only spaceborne sensors capable of acquiring images in three red-edge spectral bands with meter-level spatial resolution. Red-edge bands have great potential in discriminating vegetation types and evaluating vegetation health condition
because these bands are sensitive to the chlorophyll and the nitrogen contents of vegetation. However
there are few studies on winter wheat extraction over wide area using the red-edge bands of Sentinel-2 data. In this paper
a wide-area winter wheat extraction method based on the Red-Edge Position Index (REPI) and the NDVI data derived from multi-temporal Sentinel-2 images is proposed
which is then applied to extract the winter wheat planting area in the Beijing-Tianjin-Hebei region for the year of 2020. Firstly
the temporal REPI and NDVI are extracted from Sentinel-2 data. Secondly
the key temporal phases for discriminating winter wheat are studied
and the decision rules based on temporal REPI and NDVI features for winter wheat discrimination are constructed. Finally
the winter wheat planting area in the Beijin-Tianjin-Hebei region in 2020 is extracted using the constructed decision rules. The extracted winter wheat area is validated by two kinds of reference data. It shows an error of -2.57% when compared with the winter wheat planting area data published by the National Bureau of Statistics. Additionally
the overall accuracy of the extracted winter wheat area is 94.24% and the Kappa coefficient is 0.88 in comparison with the visual interpretation results of Google Earth high-resolution images. The conclusions are: (1) REPI changes with the change of chlorophyll concentration during the growth period of winter wheat
and gradually increases with the growth of winter wheat seedlings after sowing period
until reaching the first peak (about 722 nm) at the emergence stage (November). During the overwintering period
it falls below 715 nm. The second peak is reached at heading stage (April-May)
with the corresponding value greater than 730 nm. The REPI value in the mature stage drops below 720 nm. Especially
the REPI at heading stage provides excellent separability between winter wheat and woodland
while NDVI has a serious commission error when distinguishing winter wheat from woodland. (2) It can not achieve satisfactory result when either parameter (REPI or NDVI) of single date is used to extract winter wheat over wide areas. However
the decision tree classifier constructed based on the combination of REPI and NDVI parameters derived from multi-temporal Sentinel-2 data can extract winter wheat area with very high accuracy over wide areas
because other land cover types can be well excluded by the specific features presented by either REPI or NDVI of the key temporal phases
thus the effect of “different cover types with similar pectrum” associate with wide-area classification can be largely mitigated. This research demonstrates the significance of the red-edge bands of Sentinel-2 in discriminating winter wheat of wide-area.
Bi K Y , Niu Z , Huang N , Kang J and Pei J . 2017 . Identifying vegetation with decision tree model based on object-oriented method using multi-temporal Sentinel-2A images . Geography and Geo-Information Science , 33 ( 5 ): 16 - 20 , 27
毕恺艺 , 牛铮 , 黄妮 , 康峻 , 裴杰 . 2017 . 基于Sentinel-2A时序数据和面向对象决策树方法的植被识别 . 地理与地理信息科学 , 33 ( 5 ): 16- 20 , 27 [ DOI: 10.3969/j.issn.1672-0504.2017.05.003 http://dx.doi.org/10.3969/j.issn.1672-0504.2017.05.003 ]
Deng S B . 2014 . Remote Sensing Image Processing Method of ENVI(2nd) . Beijing : Higher Education Press : 136 .
邓书斌 . 2014 . ENVI遥感图像处理方法(2版) . 北京 ： 高等教育出版社 : 136
Drusch M , del Bello U , Carlier S , Colin O , Fernandez V , Gascon F , Hoersch B , Isola C , Laberinti P , Martimort P , Meygret A , Spoto F , Sy O , Marchese F and Bargellini P . 2012 . Sentinel-2: ESA’s optical high-resolution mission for GMES operational services . Remote Sensing of Environment , 120 ( none ): 25 - 36 [ DOI: 10.1016/j.rse.2011.11.026 http://dx.doi.org/10.1016/j.rse.2011.11.026 ]
Du J B , Zhang J , Wang Z M , Mao D H , Zhang M and Wu B F . 2019 . Crop mapping based on Sentinel-2A NDVI time series using object-oriented classification and decision tree model . Journal of Geo-Information Science , 21 ( 5 ): 740 - 751
杜保佳 , 张晶 , 王宗明 , 毛德华 , 张淼 , 吴炳方 . 2019 . 应用Sentinel-2A NDVI时间序列和面向对象决策树方法的农作物分类 . 地球信息科学学报 , 21 ( 5 ): 740 - 751 [ DOI: 10.12082/dqxxkx.2019.180412 http://dx.doi.org/10.12082/dqxxkx.2019.180412 ]
Frampton W J , Dash J , Watmough G and Milton E J . 2013 . Evaluating the capabilities of Sentinel-2 for quantitative estimation of biophysical variables in vegetation . ISPRS Journal of Photogrammetry and Remote Sensing , 82 ( none ): 83 - 92 [ DOI: 10.1016/j.isprsjprs.2013.04.007 http://dx.doi.org/10.1016/j.isprsjprs.2013.04.007 ]
Guo Y K , Liu Y L , Xu M and Zhang X J . 2021 . Modeling and analysis of red edge index estimated by leaf area index in road vegetation . Science of Surveying and Mapping , 46 ( 1 ): 93 - 98
郭云开 , 刘雨玲 , 许敏 , 张晓炯 . 2021 . 植被叶面积指数估算的红边指数建模分析 . 测绘科学 , 46 ( 1 ): 93 - 98 [ DOI: 10.16251/j.cnki.1009-2307.2021.01.012 http://dx.doi.org/10.16251/j.cnki.1009-2307.2021.01.012 ]
Guo Y L , Li L T , Chen W Q , Cui J Q and Wang Y L . 2020 . Research on the estimation of winter wheat chlorophyll content based on red edge spectral and XGBoost algorithm . Infrared , 41 ( 11 ): 33 - 43
郭宇龙 , 李岚涛 , 陈伟强 , 崔佳琪 , 王宜伦 . 2020 . 基于红边光谱特征和XGBoost算法的冬小麦叶绿素浓度估算研究 . 红外 , 41 ( 11 ): 33 - 43 [ DOI: 10.3969/j.issn.1672-8785.2020.11.006 http://dx.doi.org/10.3969/j.issn.1672-8785.2020.11.006 ]
Guo Y S , Liu Q S , Liu G H and Huang C . 2017 . Extraction of main crops in yellow river delta based on MODIS NDVI time series . Journal of Natural Resources , 32 ( 10 ): 1808 - 1818
郭昱杉 , 刘庆生 , 刘高焕 , 黄翀 . 2017 . 基于MODIS时序NDVI主要农作物种植信息提取研究 . 自然资源学报 , 32 ( 10 ): 1808 - 1818 [ DOI: 10.11849/zrzyxb.20160943 http://dx.doi.org/10.11849/zrzyxb.20160943 ]
Guyot G and Baret F . 1988 . Utilisation de la haute resolution spectrale pour suivre l’etat des couverts vegetaux . Spectral Signatures of Objects in Remote Sensing , 287 ( 287 ): 279 - 286 .[ http://hal.inrae.fr/hal-02780265 http://hal.inrae.fr/hal-02780265 ]
Hu Q , Wu W B , Song Q , Yu Q Y , Yang P and Tang H J . 2015 . Recent progresses in research of crop patterns mapping by using remote sensing . Scientia Agricultura Sinica , 48 ( 10 ): 1900 - 1914
胡琼 , 吴文斌 , 宋茜 , 余强毅 , 杨鹏 , 唐华俊 . 2015 . 农作物种植结构遥感提取研究进展 . 中国农业科学 , 48 ( 10 ): 1900 - 1914 [ DOI: 10.3864/j.issn.0578-1752.2015.10.004 http://dx.doi.org/10.3864/j.issn.0578-1752.2015.10.004 ]
Hunt M L , Blackburn G A , Carrasco L , Redhead J W and Rowland C S . 2019 . High resolution wheat yield mapping using Sentinel-2 . Remote Sensing of Environment , 233 ( none ): 111410 - 111425 [ DOI: 10.1016/j.rse.2019.111410 http://dx.doi.org/10.1016/j.rse.2019.111410 ]
Koukoulas S and Blackburn G A . 2001 . Introducing new indices for accuracy evaluation of classified images representing semi-natural woodland environments . Photogrammetric Engineering & Remote Sensing , 67 ( 4 ): 499 - 510 [ DOI： doi:10.1007/s001900000153 http://dx.doi.org/doi:10.1007/s001900000153 ]
Liang J , Zheng Z W , Xia S T , Zhang X T and Tang Y Y . 2020 . Crop recognition and evaluation using red edge features of GF-6 satellite . Journal of Remote Sensing , 24 ( 10 ): 1168 - 1179
梁继 , 郑镇炜 , 夏诗婷 , 张晓彤 , 唐媛媛 . 2020 . 高分六号红边特征的农作物识别与评估 . 遥感学报 , 24 ( 10 ): 1168 - 1179 [ DOI: 10.11834/jrs.20209289 http://dx.doi.org/10.11834/jrs.20209289 ]
Main-Knorn M , Pflug B , Debaecker V and Louis J . 2015 . Calibration and validation plan for the L2A processor and products of the Sentinel-2 mission . The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, XL-7-W 3 : 1249 - 1255 [ DOI: 10.5194/isprsarchives-XL-7-W3-1249-2015 http://dx.doi.org/10.5194/isprsarchives-XL-7-W3-1249-2015 ]
Majasalmi T and Rautiainen M . 2016 . The potential of Sentinel-2 data for estimating biophysical variables in a boreal forest: a simulation study . Remote Sensing Letters , 7 ( 5 ): 427 - 436 [ DOI: 10.1080/2150704X.2016.1149251 http://dx.doi.org/10.1080/2150704X.2016.1149251 ]
Massey R , Sankey T T , Congalton R G , Yadav K , Thenkabail P S , Ozdogan M and Sánchez Meador A J . 2017 . MODIS phenology-derived, multi-year distribution of conterminous U.S. crop types . Remote Sensing of Environment , 198 ( none ): 490 - 503 [ DOI: 10.1016/j.rse.2017.06.033 http://dx.doi.org/10.1016/j.rse.2017.06.033 ]
Nasrallah A , Baghdadi N , Mhawej M , Faour G , Darwish T , Belhouchette H and Darwich S . 2018 . A novel approach for mapping wheat areas using high resolution Sentinel-2 images . Sensors , 18 ( 7 ): 2089 [ DOI: 10.3390/s18072089 http://dx.doi.org/10.3390/s18072089 ]
Saini R and Ghosh S K . 2018 . Exploring capabilities of Sentinel-2 for vegetation mapping using random forest . The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, XLII-3 : 1499 - 1502 [ DOI: 10.5194/isprs-archives-XLII-3-1499-2018 http://dx.doi.org/10.5194/isprs-archives-XLII-3-1499-2018 ]
Tavakoli H , Mohtasebi S S , Alimardani R and Gebbers R . 2014 . Evaluation of different sensing approaches concerning to nondestructive estimation of Leaf Area Index (LAI) for winter wheat . International Journal on Smart Sensing and Intelligent Systems , 7 ( 1 ): 337 - 359 [ DOI: 10.21307/ijssis-2017-659 http://dx.doi.org/10.21307/ijssis-2017-659 ]
Tian H F , Pei J , Huang J X , Li X C , Wang J , Zhou B Y , Qin Y C and Wang L . 2020 . Garlic and winter wheat identification based on active and passive satellite imagery and the Google Earth engine in Northern China . Remote Sensing , 12 ( 21 ): 3539 - 3556 [ DOI: 10.3390/rs12213539 http://dx.doi.org/10.3390/rs12213539 ]
Tian Y , Chen Z Q , Hui F M , Cheng X and Ouyang L X . 2019 . ESA Sentinel-2A/B satellite: characteristics and applications . Journal of Beijing Normal University (Natural Science) , 55 ( 1 ): 57 - 65
田颖 , 陈卓奇 , 惠凤鸣 , 程晓 , 欧阳伦曦 . 2019 . 欧空局哨兵卫星Sentinel-2A/B数据特征及应用前景分析 . 北京师范大学学报(自然科学版) , 55 ( 1 ): 57 - 65 [ DOI: 10.16360/j.cnki.jbnuns.2019.01.007 http://dx.doi.org/10.16360/j.cnki.jbnuns.2019.01.007 ]
Wang J , Liu L , Li C , Xiang T F , Zheng S L , Ding S B and Liu P J . 2017 . The study for formation mechanism of spectral red edge of green vegetation . Spectroscopy and Spectral Analysis , 37 ( 12 ): 3940 - 3946 [ DOI: 10.3964/j.issn.1000-0593(2017)12-3940-07 http://dx.doi.org/10.3964/j.issn.1000-0593(2017)12-3940-07 ]
Wang L M , Liu J , Yang F G , Yang L B , Yao B M and Wang X L . 2018 . Acguisition of winter wheat area in the Beijing-Tianjin-Hebei region with GF-1 satellite data . Acta Agronomica Sinica , 44 ( 5 ): 762 - 773
王利民 , 刘佳 , 杨福刚 , 杨玲波 , 姚保民 , 王小龙 . 2018 . 基于GF-1卫星遥感数据识别京津冀冬小麦面积 . 作物学报 , 44 ( 5 ): 762 - 773 [ DOI: 10.3724/SP.J.1006.2018.00762 http://dx.doi.org/10.3724/SP.J.1006.2018.00762 ]
Wang R , Feng M C , Yang W D and Zhang M J . 2019 . Remote sensing monitoring of winter wheat planting area in county based on Sentinel-2A imagery . Journal of Shanxi Agricultural Sciences , 47 ( 5 ): 854 - 860
王蓉 , 冯美臣 , 杨武德 , 张美俊 . 2019 . 基于Sentinel-2A影像的县域冬小麦种植面积遥感监测 . 山西农业科学 , 47 ( 5 ): 854 - 860 [ DOI: 10.3969/j.issn.1002-2481.2019.05.34 http://dx.doi.org/10.3969/j.issn.1002-2481.2019.05.34 ]
Wei M F , Qiao B J , Zhao J H and Zuo X Y . 2020 . The area extraction of winter wheat in mixed planting area based on Sentinel-2 a remote sensing satellite images . International Journal of Parallel, Emergent and Distributed Systems , 35 ( 3 ): 297 - 308 [ DOI: 10.1080/17445760.2019.1597084 http://dx.doi.org/10.1080/17445760.2019.1597084 ]
Wu B F , Fan J L , Tian Y C , Li Q Z , Zhang L , Liu Z L , Zhang G L , He L H , Huang J L , Jiang X B , Yan C Z , Xu A and Zhang W Q . 2004 . A method for crop planting structure inventory and its application . Journal of Remote Sensing , 8 ( 6 ): 618 - 627
吴炳方 , 范锦龙 , 田亦陈 , 李强子 , 张磊 , 刘兆礼 , 张广录 , 何隆华 , 黄进良 , 江晓波 , 颜长珍 , 许安 , 张维奇 . 2004 . 全国作物种植结构快速调查技术与应用 . 遥感学报 , 8 ( 6 ): 618 - 627 [ DOI: 10.11834/jrs.20040612 http://dx.doi.org/10.11834/jrs.20040612 ]
Wu F H , Lang T T , Jiang D , Ding F Y and Zhang Z P . 2019 . Study on rapid extraction technology of winter wheat planting area in Beijing-Tianjin-Hebei region . Jiangsu Agricultural Sciences , 47 ( 16 ): 224 - 229
吴风华 , 郎婷婷 , 江东 , 丁方宇 , 张紫萍 . 2019 . 京津冀地区冬小麦播种面积快速提取技术研究 . 江苏农业科学 , 47 ( 16 ): 224 - 229 [ DOI: 10.15889/j.issn.1002-1302.2019.16.050 http://dx.doi.org/10.15889/j.issn.1002-1302.2019.16.050 ]
Xiao L J , Yang W D , Feng M C , Sun H and Wang C . 2020 . Effects of drought stress on canopy spectra and red edge parameters of winter wheat . Journal of Shanxi Agricultural University (Natural Science Edition) , 40 ( 5 ): 92 - 98
肖璐洁 , 杨武德 , 冯美臣 , 孙慧 , 王超 . 2020 . 干旱胁迫对冬小麦冠层光谱及红边参数的影响 . 山西农业大学学报(自然科学版) , 40 ( 5 ): 92 - 98 [ DOI: 10.13842/j.cnki.issn1671-8151.202004034 http://dx.doi.org/10.13842/j.cnki.issn1671-8151.202004034 ]
Yang Y J , Zhan Y L , Tian Q J , Gu X F , Yu T and Wang L . 2015 . Crop classification based on GF-1/WFV NDVI time series . Transactions of the Chinese Society of Agricultural Engineering , 31 ( 24 ): 155 - 161 .
杨闫君 , 占玉林 , 田庆久 , 顾行发 , 余涛 , 王磊 . 2015 . 基于GF-1/WFVNDVI时间序列数据的作物分类 . 农业工程学报 , 31 ( 24 ): 155 - 161 [ DOI: 10.11975/j.issn.1002-6819.2015.24.024 http://dx.doi.org/10.11975/j.issn.1002-6819.2015.24.024 ]
Yue Z G . 2015 . European sentinel-2a satellite is about to sstrut it’s stuff—The brief introduction of Copernicus earth Programme (Part 1 ). Infrared , 36 ( 8 ): 34 - 48
岳桢干 . 2015 . 欧洲Sentinel-2A卫星即将大显身手——“哥白尼”对地观测计划简介(上) . 红外 , 36 ( 8 ): 32 - 36 [ DOI: 10.3969/j.issn.1672-8785.2015.08.008 http://dx.doi.org/10.3969/j.issn.1672-8785.2015.08.008 ]
Zhang J S , Zhao G Z , Hong Y T , Sun Z H and Duan Y M . 2020 . Spatial extraction of winter wheat in Hebei in growing season using pixel-wise phenological curve . Transactions of the Chinese Society of Agricultural Engineering , 36 ( 23 ): 193 - 200
张锦水 , 赵光政 , 洪友堂 , 孙智虎 , 段雅鸣 . 2020 . 基于像元物候曲线匹配的生长季内河北省冬小麦空间分布识别 . 农业工程学报 , 36 ( 23 ): 193 - 200 [ DOI: 10.11975/j.issn.1002-6819.2020.23.022 http://dx.doi.org/10.11975/j.issn.1002-6819.2020.23.022 ]
Zhang S , Zhang J H , Bai Y and Yao F M . 2018 . Extracting winter wheat area in Huanghuaihai Plain using MODIS-EVI data and phenology difference avoiding threshold . Transactions of the Chinese Society of Agricultural Engineering , 34 ( 11 ): 150 - 158
张莎 , 张佳华 , 白雲 , 姚凤梅 . 2018 . 基于MODIS-EVI及物候差异免阈值提取黄淮海平原冬小麦面积 . 农业工程学报 , 34 ( 11 ): 150 - 158 [ DOI: 10.11975/j.issn.1002-6819.2018.11.019 http://dx.doi.org/10.11975/j.issn.1002-6819.2018.11.019 ]
Zhao C J , Wang Z J , Wang J H and Huang W J . 2012 . Relationships of leaf nitrogen concentration and canopy nitrogen density with spectral features parameters and narrow-band spectral indices calculated from field winter wheat ( Triticum aestivum L.) spectra . International Journal of Remote Sensing , 33 ( 11 ): 3472 - 3491 [ DOI: 10.1080/01431161.2011.604052 http://dx.doi.org/10.1080/01431161.2011.604052 ]
Zhao Y S . 2013 . The Principle and Method of Analysis of Remote Sensing Application(2nd) . Beijing : Science Press: 34 , 360 - 362
赵英时 . 2013 . 遥感应用分析原理与方法(2版) . 北京 : 科学出版社: 34 ： 360 - 362
Zhen X J , Zhang X H , Wu M G , Fu X Y , He Y and Hong C Q . 2019 . Identification of winter wheat based on Sentinel-2A NDVI times series data . Jiangsu Agricultural Sciences , 47 ( 16 ): 239 - 245
甄晓菊 , 张雪红 , 吴国明 , 傅晓艺 , 何泱 , 洪长桥 . 2019 . 基于Sentinel-2A NDVI时间序列数据的冬小麦识别 . 江苏农业科学 , 47 ( 16 ): 239 - 245 [ DOI: 10.15889/j.issn.1002-1302.2019.16.053 http://dx.doi.org/10.15889/j.issn.1002-1302.2019.16.053 ]
Zou H Y and Zheng H P . 2010 . The effect and method of quantitative analysis of “Red Edge”of vegetation . Remote Sensing Information , 5 ( 4 ): 112 - 116
邹红玉 , 郑红平 . 2010 . 浅述植被“红边”效应及其定量分析方法 . 遥感信息 , 5 ( 4 ): 112 - 116 [ DOI： CNKI:SUN:YGXX.0.2010-04-028 http://dx.doi.org/CNKI:SUN:YGXX.0.2010-04-028 ]
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