{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,21]],"date-time":"2026-06-21T04:45:14Z","timestamp":1782017114737,"version":"3.54.5"},"reference-count":45,"publisher":"MDPI AG","issue":"2","license":[{"start":{"date-parts":[[2018,2,23]],"date-time":"2018-02-23T00:00:00Z","timestamp":1519344000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"the National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["41471294"],"award-info":[{"award-number":["41471294"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100012226","name":"Fundamental Research Funds for the Central Universities","doi-asserted-by":"publisher","award":["ZYGX2015J112"],"award-info":[{"award-number":["ZYGX2015J112"]}],"id":[{"id":"10.13039\/501100012226","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Accurate estimation and monitoring of rice phenology is necessary for the management and yield prediction of rice. The radar backscattering coefficient, one of the most direct and accessible parameters has been proved to be capable of retrieving rice growth parameters. This paper aims to investigate the possibility of monitoring the rice phenology (i.e., transplanting, vegetative, reproductive, and maturity) using the backscattering coefficients or their simple combinations of multi-temporal RADARSAT-2 datasets only. Four RADARSAT-2 datasets were analyzed at 30 sample plots in Meishan City, Sichuan Province, China. By exploiting the relationships of the backscattering coefficients and their combinations versus the phenology of rice, HH\/VV, VV\/VH, and HH\/VH ratios were found to have the greatest potential for phenology monitoring. A decision tree classifier was applied to distinguish the four phenological phases, and the classifier was effective. The validation of the classifier indicated an overall accuracy level of 86.2%. Most of the errors occurred in the vegetative and reproductive phases. The corresponding errors were 21.4% and 16.7%, respectively.<\/jats:p>","DOI":"10.3390\/rs10020340","type":"journal-article","created":{"date-parts":[[2018,2,23]],"date-time":"2018-02-23T12:41:40Z","timestamp":1519389700000},"page":"340","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":69,"title":["Monitoring Rice Phenology Based on Backscattering Characteristics of Multi-Temporal RADARSAT-2 Datasets"],"prefix":"10.3390","volume":"10","author":[{"given":"Ze","family":"He","sequence":"first","affiliation":[{"name":"School of Resources and Environment, University of Electronic Science and Technology of China, No. 2006, Xiyuan Ave, West Hi-Tech Zone, Chengdu 611731, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Shihua","family":"Li","sequence":"additional","affiliation":[{"name":"School of Resources and Environment, University of Electronic Science and Technology of China, No. 2006, Xiyuan Ave, West Hi-Tech Zone, Chengdu 611731, China"},{"name":"Center for Information Geoscience, University of Electronic Science and Technology of China, No. 2006, Xiyuan Ave, West Hi-Tech Zone, Chengdu 611731, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yong","family":"Wang","sequence":"additional","affiliation":[{"name":"Department of Geography, Planning, and Environment, East Carolina University, Greenville, NC 27858, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Leiyu","family":"Dai","sequence":"additional","affiliation":[{"name":"School of Resources and Environment, University of Electronic Science and Technology of China, No. 2006, Xiyuan Ave, West Hi-Tech Zone, Chengdu 611731, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Sen","family":"Lin","sequence":"additional","affiliation":[{"name":"School of Resources and Environment, University of Electronic Science and Technology of China, No. 2006, Xiyuan Ave, West Hi-Tech Zone, Chengdu 611731, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2018,2,23]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"292","DOI":"10.1016\/j.asr.2011.09.011","article-title":"Monitoring of rice cropping intensity in the upper Mekong Delta, Vietnam using time-series MODIS data","volume":"49","author":"Chen","year":"2012","journal-title":"Adv. Space Res."},{"key":"ref_2","unstructured":"McLean, J., Hardy, B., and Hettel, G. (2013). Rice Almanac, International Rice Research Institute. [4th ed.]."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"366","DOI":"10.1016\/j.rse.2005.03.008","article-title":"A crop phenology detection method using time-series MODIS data","volume":"96","author":"Sakamoto","year":"2005","journal-title":"Remote Sens. Environ."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"123","DOI":"10.1016\/j.ecolmodel.2014.10.001","article-title":"Deriving phenology of barley with imaging hyperspectral remote sensing","volume":"295","author":"Lausch","year":"2015","journal-title":"Ecol. Model."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"2695","DOI":"10.1109\/TGRS.2011.2176740","article-title":"Rice phenology monitoring by means of SAR polarimetry at X-band","volume":"50","author":"Cloude","year":"2012","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"2977","DOI":"10.1109\/TGRS.2013.2268319","article-title":"Polarimetric response of rice fields at C-band: Analysis and phenology retrieval","volume":"52","author":"Cloude","year":"2014","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"1081","DOI":"10.1109\/LGRS.2013.2286214","article-title":"Crop phenology estimation using a multitemporal model and a Kalman filtering strategy","volume":"11","year":"2014","journal-title":"IEEE Geosci. Remote Sens. Lett."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"2841","DOI":"10.3390\/su7032841","article-title":"Detection and modeling of vegetation phenology spatiotemporal characteristics in the middle part of the Huai river region in China","volume":"7","author":"Xu","year":"2015","journal-title":"Sustainability"},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"1300","DOI":"10.1002\/2014RS005498","article-title":"Rice growth monitoring using simulated compact polarimetric C band SAR","volume":"49","author":"Yang","year":"2014","journal-title":"Radio Sci."},{"key":"ref_10","doi-asserted-by":"crossref","unstructured":"Zhang, Y., Li, L., Wang, H., Zhang, Y., Wang, N., and Chen, J. (2017). Land surface phenology of Northeast China during 2000-2015: temporal changes and relationships with climate changes. Environ Monit Assess., 189.","DOI":"10.1007\/s10661-017-6247-1"},{"key":"ref_11","first-page":"28","article-title":"Monitoring paddy rice phenology using time series MODIS data over Jiangxi Province, China","volume":"7","author":"Li","year":"2014","journal-title":"Int. J. Agric. & Biol. Eng."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"1388","DOI":"10.1016\/j.rse.2010.01.021","article-title":"The use of MERIS Terrestrial Chlorophyll Index to study spatio-temporal variation in vegetation phenology over India","volume":"114","author":"Dash","year":"2010","journal-title":"Remote Sens. Environ."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"633","DOI":"10.1080\/01431161.2015.1131902","article-title":"A study of the use of COSMO-SkyMed SAR PingPong polarimetric mode for rice growth monitoring","volume":"37","author":"Corcione","year":"2016","journal-title":"Int. J. Remote Sens."},{"key":"ref_14","first-page":"13","article-title":"Detection and estimation of mixed paddy rice cropping patterns with MODIS data","volume":"13","author":"Peng","year":"2011","journal-title":"Int. J. Appl. Earth Obs. Geoinf."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"4343","DOI":"10.1080\/01431160802549369","article-title":"Evaluation of optical satellite remote sensing for rice paddy phenology in monsoon Asia using a continuous in situ dataset","volume":"30","author":"Motohka","year":"2009","journal-title":"Int. J. Remote Sens."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"215","DOI":"10.1029\/2008JD011645","article-title":"Strategies for the fusion of satellite fire radiative power with burned area data for fire radiative energy derivation","volume":"114","author":"Boschetti","year":"2009","journal-title":"J. Geophys. Res. Atmos."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"1905","DOI":"10.1080\/01431161.2011.603378","article-title":"Rice heading date retrieval based on multi-temporal MODIS data and polynomial fitting","volume":"33","author":"Wang","year":"2012","journal-title":"Int. J. Remote Sens."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"832","DOI":"10.1631\/jzus.B1500087","article-title":"Estimation of rice phenology date using integrated HJ-1 CCD and Landsat-8 OLI vegetation indices time-series images","volume":"16","author":"Wang","year":"2015","journal-title":"J. Zhejiang Univ. Sci. B"},{"key":"ref_19","first-page":"170","article-title":"Retrieving canopy height and density of paddy rice from Radarsat-2 images with a canopy scattering model","volume":"28","author":"Zhang","year":"2014","journal-title":"Int. J. Appl. Earth Obs. Geoinf."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"517","DOI":"10.1109\/TGRS.2008.2007963","article-title":"Monitoring of the rice cropping system in the Mekong delta using ENVISAT\/ASAR dual polarization data","volume":"47","author":"Bouvet","year":"2009","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"1218","DOI":"10.1109\/LGRS.2015.2388953","article-title":"Rice Growth monitoring by means of X-Band co-polar SAR: Feature clustering and BBCH scale","volume":"12","author":"Yuzugullu","year":"2015","journal-title":"IEEE Geosci. Remote Sens. Lett."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"2509","DOI":"10.1109\/JSTARS.2016.2547843","article-title":"Paddy-rice phenology classification based on machine-learning methods using multi-temporal co-polar X-Band SAR images","volume":"9","author":"Erten","year":"2016","journal-title":"IEEE J. Sel. Top. Appl. Earth Observ. Remote Sens."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"1008","DOI":"10.1109\/JSTARS.2014.2372898","article-title":"Estimation of key dates and stages in rice crops using dual-polarization SAR time series and a particle filtering approach","volume":"8","year":"2015","journal-title":"IEEE J. Sel. Top. Appl. Earth Observ. Remote Sens."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"130","DOI":"10.1016\/j.rse.2016.10.007","article-title":"Retrieval of agricultural crop height from space: A comparison of SAR techniques","volume":"187","author":"Erten","year":"2017","journal-title":"Remote Sens. Environ."},{"key":"ref_25","first-page":"568","article-title":"Rice monitoring with multi-temporal and dual-polarimetric TerraSAR-X data","volume":"21","author":"Koppe","year":"2013","journal-title":"Int. J. Appl. Earth Obs. Geoinf."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"184","DOI":"10.1016\/j.rse.2017.04.016","article-title":"An improved scheme for rice phenology estimation based on time-series multispectral HJ-1A\/B and polarimetric RADARSAT-2 data","volume":"195","author":"Yang","year":"2017","journal-title":"Remote Sens. Environ."},{"key":"ref_27","unstructured":"Francis, C., Shang, J., Liu, J., Huang, X., Ma, B., Jiao, X., Geng, X., John, M.K., and Dan, W. (2017). Tracking crop phenological development using multi-temporal polarimetric Radarsat-2 data. Remote Sens. Environ."},{"key":"ref_28","doi-asserted-by":"crossref","unstructured":"Tian, H., Wu, M., Wang, L., and Niu, Z. (2018). Mapping early, middle and late rice extent using sentinel-1A and Landsat-8 data in the poyang lake plain, China. Sensors, 18.","DOI":"10.3390\/s18010185"},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"194","DOI":"10.1016\/S0034-4257(01)00343-1","article-title":"Season-long daily measurements of multifrequency (Ka, Ku, X, C, and L) and full-polarization backscatter signatures over paddy rice field and their relationship with biological variables","volume":"81","author":"Inoue","year":"2002","journal-title":"Remote Sens. Environ."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"196","DOI":"10.1109\/LGRS.2010.2055830","article-title":"Rice crop monitoring in South China with RADARSAT-2 quad-polarization SAR data","volume":"8","author":"Wu","year":"2011","journal-title":"IEEE Geosci. Remote Sens. Lett."},{"key":"ref_31","doi-asserted-by":"crossref","unstructured":"Li, S., Ni, P., Cui, G., He, P., Liu, H., Li, L., and Liang, Z. (2015, January 5\u20139). Estimation of rice biophysical parameters using multitemporal RADARSAT-2 images. Proceedings of the Symposium of the International Society for Digital Earth (ISDE), Halifax, NS, Canada.","DOI":"10.1088\/1755-1315\/34\/1\/012019"},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"65","DOI":"10.1109\/LGRS.2011.2160613","article-title":"Interpreting RADARSAT-2 quad-polarization SAR signatures from rice paddy based on experiments","volume":"9","author":"Yang","year":"2012","journal-title":"IEEE Geosci. Remote Sens. Lett."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"113","DOI":"10.1016\/0034-4257(84)90010-5","article-title":"Relating the microwave backscattering coefficient to leaf area index","volume":"14","author":"Ulaby","year":"1984","journal-title":"Remote Sens. Environ."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"193","DOI":"10.1016\/0034-4257(91)90081-G","article-title":"Crop parameter estimation from ground-based X-band (3-cm wave) radar backscattering data","volume":"37","author":"Bouman","year":"1991","journal-title":"Remote Sens. Environ."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"288","DOI":"10.1080\/2150704X.2012.725482","article-title":"Relationship between X-band backscattering coefficients from high-resolution satellite SAR and biophysical variables in paddy rice","volume":"4","author":"Inoue","year":"2013","journal-title":"Remote Sens. Lett."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"257","DOI":"10.1016\/j.rse.2013.09.001","article-title":"Capability of C-band backscattering coefficients from high-resolution satellite SAR sensors to assess biophysical variables in paddy rice","volume":"140","author":"Inoue","year":"2014","journal-title":"Remote Sens. Environ."},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"194","DOI":"10.1109\/JSTARS.2016.2575362","article-title":"Estimation of rice crop height from X- and C-Band PolSAR by Metamodel-Based optimization","volume":"10","author":"Yuzugullu","year":"2017","journal-title":"IEEE J. Sel. Top. Appl. Earth Observ. Remote Sens."},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"415","DOI":"10.1111\/j.1365-3180.1974.tb01084.x","article-title":"A decimal code for the growth stages of cereals","volume":"14","author":"Zadoks","year":"1974","journal-title":"Weed Res."},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"900","DOI":"10.1109\/TGRS.2014.2330377","article-title":"Paddy-rice monitoring using TanDEM-X","volume":"53","author":"Rossi","year":"2015","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"554","DOI":"10.1016\/S0034-4257(03)00132-9","article-title":"An assessment of the effectiveness of decision tree methods for land cover classification","volume":"86","author":"Pal","year":"2003","journal-title":"Remote Sens. Environ."},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"221","DOI":"10.1080\/01431161.2011.559288","article-title":"ALOS PALSAR L-band polarimetric SAR data and in situ measurements for leaf area index assessment","volume":"3","author":"Francis","year":"2012","journal-title":"Remote Sens. Lett."},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"321","DOI":"10.1071\/WF01031","article-title":"Accuracy assessment and validation of remotely sensed and other spatial information","volume":"10","author":"Congalton","year":"2001","journal-title":"Int. J. Wildland Fire."},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"68","DOI":"10.1109\/36.551935","article-title":"An entropy based classification scheme for land applications of polarimetric SAR","volume":"35","author":"Cloude","year":"1997","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_44","doi-asserted-by":"crossref","unstructured":"Pacheco, A., McNairn, H., Li, Y., Lampropoulos, G., and Powers, J. (2016). Using RADARSAT-2 and TerraSAR-X satellite data for the identification of canola crop phenology. SPIE Remote Sens., 9998.","DOI":"10.1117\/12.2240789"},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"153","DOI":"10.2528\/PIER04080601","article-title":"Electromagetic scattering model for rice canopy based on Monte Carlo simulation","volume":"52","author":"Wang","year":"2005","journal-title":"Prog. Electromagn. Res."}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/10\/2\/340\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T14:56:02Z","timestamp":1760194562000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/10\/2\/340"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2018,2,23]]},"references-count":45,"journal-issue":{"issue":"2","published-online":{"date-parts":[[2018,2]]}},"alternative-id":["rs10020340"],"URL":"https:\/\/doi.org\/10.3390\/rs10020340","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2018,2,23]]}}}