{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,17]],"date-time":"2026-06-17T15:43:11Z","timestamp":1781710991207,"version":"3.54.5"},"reference-count":42,"publisher":"MDPI AG","issue":"8","license":[{"start":{"date-parts":[[2020,4,17]],"date-time":"2020-04-17T00:00:00Z","timestamp":1587081600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"the National Key Research and Development Program of China","award":["No. 2017YFD0300201"],"award-info":[{"award-number":["No. 2017YFD0300201"]}]},{"name":"the Science and Technology Facilities Council of UK- Newton Agritech Programme","award":["Sentinels of Wheat"],"award-info":[{"award-number":["Sentinels of Wheat"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Accurate mapping of winter wheat over a large area is of great significance for guiding policy formulation related to food security, farmland management, and the international food trade. Due to the complex phenological features of winter wheat, the cloud contamination in time-series imagery, and the influence of the soil\/snow background on vegetation indices, there remains no effective method for mapping winter wheat at a medium spatial resolution (10\u201330 m). In this study, we proposed a novel method called phenology-time weighted dynamic time warping (PT-DTW) for identifying winter wheat based on Sentinel 2A\/B time-series data. The main advantages of PT-DTW include (1) the use of phenological features in two periods, i.e., the greenness increase before winter and greenness decrease after heading, which are common to all winter wheat and are distinct from the features of other land cover types, and (2) the use of the normalized differential phenology index (NDPI) instead of traditional vegetation indices to provide more robust vegetation information and to suppress the adverse impacts of soil and snow cover, especially during the before-winter growth period. The proposed PT-DTW method was employed for winter wheat mapping based on Sentinel 2A\/B data on the Huang-Huai Plain, China. Validation with visually interpreted samples showed that the produced winter wheat map achieved an overall classification accuracy of 89.98% and a kappa coefficient of 0.7978, outperforming previous winter wheat classification methods. Moreover, the planting area derived from PT-DTW agreed well with census data at the municipal level, with a coefficient of determination of 0.8638, indicating that the winter wheat map produced at 20 m resolution was reliable overall. Therefore, the PT-DTW method is recommended for winter wheat mapping over large areas.<\/jats:p>","DOI":"10.3390\/rs12081274","type":"journal-article","created":{"date-parts":[[2020,4,21]],"date-time":"2020-04-21T04:49:38Z","timestamp":1587444578000},"page":"1274","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":75,"title":["Mapping Winter Wheat in North China Using Sentinel 2A\/B Data: A Method Based on Phenology-Time Weighted Dynamic Time Warping"],"prefix":"10.3390","volume":"12","author":[{"given":"Qi","family":"Dong","sequence":"first","affiliation":[{"name":"Key Laboratory of Earth Surface Processes and Resource Ecology, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xuehong","family":"Chen","sequence":"additional","affiliation":[{"name":"Key Laboratory of Earth Surface Processes and Resource Ecology, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China"},{"name":"Beijing Engineering Research Center for Global Land Remote Sensing Products, Institute of Remote Sensing Science and Engineering, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jin","family":"Chen","sequence":"additional","affiliation":[{"name":"Key Laboratory of Earth Surface Processes and Resource Ecology, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China"},{"name":"Beijing Engineering Research Center for Global Land Remote Sensing Products, Institute of Remote Sensing Science and Engineering, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Chishan","family":"Zhang","sequence":"additional","affiliation":[{"name":"Key Laboratory of Earth Surface Processes and Resource Ecology, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Licong","family":"Liu","sequence":"additional","affiliation":[{"name":"Key Laboratory of Earth Surface Processes and Resource Ecology, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xin","family":"Cao","sequence":"additional","affiliation":[{"name":"Key Laboratory of Earth Surface Processes and Resource Ecology, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China"},{"name":"Beijing Engineering Research Center for Global Land Remote Sensing Products, Institute of Remote Sensing Science and Engineering, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yunze","family":"Zang","sequence":"additional","affiliation":[{"name":"Key Laboratory of Earth Surface Processes and Resource Ecology, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6660-2034","authenticated-orcid":false,"given":"Xiufang","family":"Zhu","sequence":"additional","affiliation":[{"name":"Key Laboratory of Earth Surface Processes and Resource Ecology, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China"},{"name":"Beijing Engineering Research Center for Global Land Remote Sensing Products, Institute of Remote Sensing Science and Engineering, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xihong","family":"Cui","sequence":"additional","affiliation":[{"name":"Key Laboratory of Earth Surface Processes and Resource Ecology, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China"},{"name":"Beijing Engineering Research Center for Global Land Remote Sensing Products, Institute of Remote Sensing Science and Engineering, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2020,4,17]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"291","DOI":"10.1007\/s12571-013-0263-y","article-title":"Crops that feed the world 10. Past successes and future challenges to the role played by wheat in global food security","volume":"5","author":"Shiferaw","year":"2013","journal-title":"Food Secur."},{"key":"ref_2","unstructured":"Jin, S. (1996). Wheat in China, China Agricultural Press."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"1672","DOI":"10.1007\/s11442-018-1536-3","article-title":"Spatio-temporal analysis of the geographical centroids for three major crops in China from 1949 to 2014","volume":"28","author":"Fan","year":"2018","journal-title":"J. Geogr. Sci."},{"key":"ref_4","first-page":"190","article-title":"Remote sensing monitoring of changes in winter wheat area in North China Plain from 2001 to 2011","volume":"31","author":"Wang","year":"2015","journal-title":"Trans. Chin. Soc. Agric. Eng."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"573","DOI":"10.1117\/1.JRS.7.073576","article-title":"Crop classification using HJ satellite multispectral data in the North China Plain","volume":"7","author":"Jia","year":"2013","journal-title":"J. Appl. Remote Sens."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"2403","DOI":"10.1016\/S2095-3119(15)61319-3","article-title":"Monitoring of winter wheat distribution and phenological phases based on MODIS time-series: A case study in the Yellow River Delta, China","volume":"15","author":"Chu","year":"2016","journal-title":"J. Integr. Agric."},{"key":"ref_7","first-page":"573","article-title":"Application of HJ-1A\/B-CCD Images in Extracting the Distribution of Winter Wheat and Rape in Hubei Province","volume":"33","author":"Liang","year":"2012","journal-title":"Chin. J. Agrometeorol."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"232","DOI":"10.1016\/j.rse.2011.10.011","article-title":"Winter wheat area estimation from MODIS-EVI time series data using the Crop Proportion Phenology Index","volume":"119","author":"Pan","year":"2012","journal-title":"Remote Sens. Environ."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"5026","DOI":"10.1080\/01431161.2012.657366","article-title":"Winter wheat mapping using temporal signatures of MODIS vegetation index data","volume":"33","author":"Sun","year":"2012","journal-title":"Int. J. Remote Sens."},{"key":"ref_10","first-page":"26","article-title":"Identification and mapping of winter wheat by integrating temporal change information and Kullback\u2013Leibler divergence","volume":"76","author":"Zhang","year":"2019","journal-title":"Int. J. Appl. Earth Obs. Geoinf."},{"key":"ref_11","first-page":"476","article-title":"Winter wheat mapping by soft and hard land use\/cover change detection","volume":"18","author":"Zhu","year":"2014","journal-title":"J. Remote. Sens."},{"key":"ref_12","first-page":"1379","article-title":"Winter Wheat Area Estimation with MODIS-NDVI Time Series Based on Parcel","volume":"31","author":"Li","year":"2011","journal-title":"Guang Pu Xue Yu Guang Pu Fen Xi"},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"30","DOI":"10.1016\/j.compag.2012.07.015","article-title":"Crop type mapping using spectral\u2013temporal profiles and phenological information","volume":"89","author":"Foerster","year":"2012","journal-title":"Comput. Electron. Agric."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"35","DOI":"10.1016\/j.isprsjprs.2016.09.016","article-title":"Winter wheat mapping combining variations before and after estimated heading dates","volume":"123","author":"Qiu","year":"2017","journal-title":"ISPRS-J. Photogramm. Remote Sens."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"44","DOI":"10.1016\/j.agrformet.2011.08.007","article-title":"Spatio-temporal patterns of phenological development in Germany in relation to temperature and day length","volume":"152","author":"Siebert","year":"2012","journal-title":"Agric. For. Meteorol."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"1096","DOI":"10.1016\/j.rse.2007.07.019","article-title":"Large-area crop mapping using time-series MODIS 250 m NDVI data: An assessment for the U.S. Central Great Plains","volume":"112","author":"Wardlow","year":"2008","journal-title":"Remote Sens. Environ."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"290","DOI":"10.1016\/j.rse.2006.11.021","article-title":"Analysis of Time-Series MODIS 250 m Vegetation Index Data for Crop Classification in the U.S. Central Great Plains","volume":"108","author":"Wardlow","year":"2007","journal-title":"Remote Sens. Environ."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.rse.2017.04.031","article-title":"A snow-free vegetation index for improved monitoring of vegetation spring green-up date in deciduous ecosystems","volume":"196","author":"Wang","year":"2017","journal-title":"Remote Sens. Environ."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"348","DOI":"10.1016\/S2095-3119(15)61304-1","article-title":"Mapping winter wheat using phenological feature of peak before winter on the North China Plain based on time-series MODIS data","volume":"16","author":"Tao","year":"2017","journal-title":"J. Integr. Agric."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"221","DOI":"10.1016\/j.isprsjprs.2014.12.013","article-title":"Fusion of high spatial resolution WorldView-2 imagery and LiDAR pseudo-waveform for object-based image analysis","volume":"101","author":"Zhou","year":"2015","journal-title":"ISPRS-J. Photogramm. Remote Sens."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"43","DOI":"10.1109\/TASSP.1978.1163055","article-title":"Dynamic-programming algorithm optimization for spoken word recognition","volume":"26","author":"Sakoe","year":"1978","journal-title":"IEEE Trans. Signal Process."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"1299","DOI":"10.1109\/LGRS.2018.2831914","article-title":"Spatio-Temporal Segmentation Applied to Optical Remote Sensing Image Time Series","volume":"15","author":"Costa","year":"2018","journal-title":"IEEE Geosci. Remote. Sens. Lett."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"3081","DOI":"10.1109\/TGRS.2011.2179050","article-title":"Satellite Image Time Series Analysis under Time Warping","volume":"50","author":"Petitjean","year":"2012","journal-title":"IEEE Trans. Geosci. Remote. Sens."},{"key":"ref_24","doi-asserted-by":"crossref","unstructured":"Weber, J., Petitjean, F., and Ganarski, P. (2012, January 22\u201327). Towards efficient satellite image time series analysis: Combination of dynamic time warping and quasi-flat zones. Proceedings of the 2012 IEEE International Geoscience and Remote Sensing Symposium, Munich, Germany.","DOI":"10.1109\/IGARSS.2012.6350401"},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"1142","DOI":"10.1109\/JSTARS.2013.2294956","article-title":"Phenology-Driven Land Cover Classification and Trend Analysis Based on Long-term Remote Sensing Image Series","volume":"7","author":"Xue","year":"2014","journal-title":"IEEE J. Sel. Top. Appl. Earth Observ. Remote Sens."},{"key":"ref_26","doi-asserted-by":"crossref","unstructured":"Petitjean, F., Inglada, J., and Gancarski, P. (2012, January 22\u201327). Introducing prior knowledge in temporal distances for Satellite Image Time Series analysis. Proceedings of the 2012 IEEE International Geoscience and Remote Sensing Symposium, Munich, Germany.","DOI":"10.1109\/IGARSS.2012.6352379"},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"3729","DOI":"10.1109\/JSTARS.2016.2517118","article-title":"A Time-Weighted Dynamic Time Warping Method for Land-Use and Land-Cover Mapping","volume":"9","author":"Maus","year":"2016","journal-title":"IEEE J. Sel. Top. Appl. Earth Observ. Remote Sens."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"509","DOI":"10.1016\/j.rse.2017.10.005","article-title":"Sentinel-2 cropland mapping using pixel-based and object-based time-weighted dynamic time warping analysis","volume":"204","author":"Belgiu","year":"2018","journal-title":"Remote Sens. Environ."},{"key":"ref_29","doi-asserted-by":"crossref","unstructured":"Guan, X., Huang, C., Liu, G., Meng, X., and Liu, Q. (2016). Mapping Rice Cropping Systems in Vietnam Using an NDVI-Based Time-Series Similarity Measurement Based on DTW Distance. Remote Sens., 8.","DOI":"10.3390\/rs8010019"},{"key":"ref_30","doi-asserted-by":"crossref","unstructured":"Maus, V., C\u00e2mara, G., Cartaxo, R., Ramos, F.M., Sanchez, A., and Ribeiro, G.Q. (2015, January 26\u201331). Open boundary dynamic time warping for satellite image time series classification. Proceedings of the 2015 IEEE International Geoscience and Remote Sensing Symposium (IGARSS), Milan, Italy.","DOI":"10.1109\/IGARSS.2015.7326536"},{"key":"ref_31","doi-asserted-by":"crossref","unstructured":"Petitjean, F., Puissant, A., and Gancarski, P. (2012, January 22\u201327). Monitoring urban sprawl from satellite image time series. Proceedings of the 2012 IEEE International Geoscience and Remote Sensing Symposium, Munich, Germany.","DOI":"10.1109\/IGARSS.2012.6352250"},{"key":"ref_32","doi-asserted-by":"crossref","unstructured":"Chen, X., Guo, Z., Chen, J., Yang, W., Yao, Y., Zhang, C., Cui, X., and Cao, X. (2019). Replacing the Red Band with the Red-SWIR Band (0.74\u03c1red+0.26\u03c1swir) Can Reduce the Sensitivity of Vegetation Indices to Soil Background. Remote Sens., 11.","DOI":"10.3390\/rs11070851"},{"key":"ref_33","first-page":"403","article-title":"Regional yield estimation for winter wheat with MODIS-NDVI data in Shandong, China","volume":"10","author":"Ren","year":"2008","journal-title":"Int. J. Appl. Earth. Obs. Geoinf."},{"key":"ref_34","first-page":"577","article-title":"Theory and Practice on Cultivation of Super High Yield of Winter Wheat in the Wheat Fields of Yellow River and Huaihe River Districts","volume":"28","author":"Yu","year":"2002","journal-title":"Zuo Wu Xue Bao"},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"332","DOI":"10.1016\/j.rse.2004.03.014","article-title":"A simple method for reconstructing a high-quality NDVI time-series data set based on the Savitzky\u2013Golay filter","volume":"91","author":"Chen","year":"2004","journal-title":"Remote Sens. Environ."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"165","DOI":"10.1016\/j.rse.2005.02.011","article-title":"A new index for mapping lichen-dominated biological soil crusts in desert areas","volume":"96","author":"Chen","year":"2005","journal-title":"Remote Sens. Environ."},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"267","DOI":"10.1016\/S0034-4257(98)00037-6","article-title":"Mapping chaparral in the Santa Monica Mountains using multiple endmember spectral mixture models","volume":"65","author":"Roberts","year":"1998","journal-title":"Remote Sens. Environ."},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"578","DOI":"10.1080\/2150704X.2018.1452057","article-title":"A new index for mapping the \u2018blue steel tile\u2019 roof dominated industrial zone from Landsat imagery","volume":"9","author":"Guo","year":"2018","journal-title":"Remote Sens. Lett."},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"672","DOI":"10.1109\/36.297984","article-title":"Detection of forests using mid-nir reflectance\u2014An application for aerosol studies","volume":"32","author":"Kaufman","year":"1994","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_40","unstructured":"(2016). The Implementation Plan of Agricultural Project for Comprehensive Management of Groundwater Overexploitation in Hebei Province, Department of Agriculture and Rural Affairs of Hebei Province."},{"key":"ref_41","unstructured":"(2016). The Implementation Plan of Hebei Province\u2019s Seasonal Fallow System in 2016, Department of Agriculture and Rural Affairs of Hebei Province."},{"key":"ref_42","doi-asserted-by":"crossref","unstructured":"Song, Y., and Wang, J. (2019). Mapping Winter Wheat Planting Area and Monitoring Its Phenology Using Sentinel-1 Backscatter Time Series. Remote Sens., 11.","DOI":"10.3390\/rs11040449"}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/12\/8\/1274\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,13]],"date-time":"2025-10-13T13:21:20Z","timestamp":1760361680000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/12\/8\/1274"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,4,17]]},"references-count":42,"journal-issue":{"issue":"8","published-online":{"date-parts":[[2020,4]]}},"alternative-id":["rs12081274"],"URL":"https:\/\/doi.org\/10.3390\/rs12081274","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2020,4,17]]}}}