{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,10]],"date-time":"2026-06-10T16:13:10Z","timestamp":1781107990260,"version":"3.54.1"},"reference-count":29,"publisher":"MDPI AG","issue":"21","license":[{"start":{"date-parts":[[2021,10,28]],"date-time":"2021-10-28T00:00:00Z","timestamp":1635379200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100004837","name":"Spanish Ministry of Science and Innovation","doi-asserted-by":"publisher","award":["TEC2017-85244-C2-1-P"],"award-info":[{"award-number":["TEC2017-85244-C2-1-P"]}],"id":[{"id":"10.13039\/501100004837","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100004837","name":"Spanish Ministry of Science and Innovation","doi-asserted-by":"publisher","award":["PID2020-117303GB-C22"],"award-info":[{"award-number":["PID2020-117303GB-C22"]}],"id":[{"id":"10.13039\/501100004837","id-type":"DOI","asserted-by":"publisher"}]},{"name":"State Agency of Research (AEI)","award":["TEC2017-85244-C2-1-P"],"award-info":[{"award-number":["TEC2017-85244-C2-1-P"]}]},{"name":"State Agency of Research (AEI)","award":["PID2020-117303GB-C22"],"award-info":[{"award-number":["PID2020-117303GB-C22"]}]},{"name":"European Funds for Regional Development (EFRD)","award":["TEC2017-85244-C2-1-P"],"award-info":[{"award-number":["TEC2017-85244-C2-1-P"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>In the last decade, suboptimal Bayesian filtering (BF) techniques, such as Extended Kalman Filtering (EKF) and Particle Filtering (PF), have led to great interest for crop phenology monitoring with Synthetic Aperture Radar (SAR) data. In this study, a novel approach, based on the Grid-Based Filter (GBF), is proposed to estimate crop phenology. Here, phenological scales, which consist of a finite number of discrete stages, represent the one-dimensional state space, and hence GBF provides the optimal phenology estimates. Accordingly, contrarily to literature studies based on EKF and PF, no constraints are imposed on the models and the statistical distributions involved. The prediction model is defined by the transition matrix, while Kernel Density Estimation (KDE) is employed to define the observation model. The approach is applied on dense time series of dual-polarization Sentinel-1 (S1) SAR images, collected in four different years, to estimate the BBCH stages of rice crops. Results show that 0.94 \u2264 R2 \u2264 0.98, 5.37 \u2264 RMSE \u2264 7.9 and 20 \u2264 MAE \u2264 33.<\/jats:p>","DOI":"10.3390\/rs13214332","type":"journal-article","created":{"date-parts":[[2021,10,28]],"date-time":"2021-10-28T23:52:35Z","timestamp":1635465155000},"page":"4332","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":9,"title":["Optimal Grid-Based Filtering for Crop Phenology Estimation with Sentinel-1 SAR Data"],"prefix":"10.3390","volume":"13","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-1989-592X","authenticated-orcid":false,"given":"Lucio","family":"Mascolo","sequence":"first","affiliation":[{"name":"Institute for Computer Research (IUII), University of Alicante, P.O. Box 99, 03080 Alicante, Spain"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Tomas","family":"Martinez-Marin","sequence":"additional","affiliation":[{"name":"Institute for Computer Research (IUII), University of Alicante, P.O. Box 99, 03080 Alicante, Spain"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4216-5175","authenticated-orcid":false,"given":"Juan M.","family":"Lopez-Sanchez","sequence":"additional","affiliation":[{"name":"Institute for Computer Research (IUII), University of Alicante, P.O. Box 99, 03080 Alicante, Spain"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2021,10,28]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"949","DOI":"10.3390\/rs5020949","article-title":"Advances in Remote Sensing of Agriculture: Context Description, Existing Operational Monitoring Systems and Major Information Needs","volume":"5","author":"Atzberger","year":"2013","journal-title":"Remote Sens."},{"key":"ref_2","unstructured":"FAO (2021, October 21). GIEWS Update-Bangladesh. GIEWS, Available online: https:\/\/www.fao.org\/3\/i7876e\/i7876e.pdf."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"1085","DOI":"10.1007\/s11442-017-1423-3","article-title":"Influences of agricultural phenology dynamic on land surface biophysical process and climate feedback","volume":"27","author":"Liu","year":"2017","journal-title":"J. Geogr. Sci."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"2249","DOI":"10.1109\/JSTARS.2016.2639043","article-title":"Radar Remote Sensing of Agricultural Canopies: A Review","volume":"10","author":"McNairn","year":"2017","journal-title":"IEEE J. Sel. Topics Appl. Earth. Observ. Remote Sens."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"4070","DOI":"10.1109\/JSTARS.2020.3008096","article-title":"Time-Series of Sentinel-1 Interferometric Coherence and Backscatter for Crop-Type Mapping","volume":"13","author":"Jacob","year":"2020","journal-title":"IEEE J. Sel. Topics Appl. Earth Observ. Remote Sens."},{"key":"ref_6","doi-asserted-by":"crossref","unstructured":"Yang, H., Pan, B., Li, N., Wang, W., Zhang, J., and Zhang, X. (2021). A systematic method for spatio-temporal phenology estimation of paddy rice using time series Sentinel-1 images. Remote Sens. Environ., 259.","DOI":"10.1016\/j.rse.2021.112394"},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"2020","DOI":"10.1016\/j.rse.2020.111954","article-title":"Dual polarimetric radar vegetation index for crop growth monitoring using Sentinel-1 SAR data","volume":"247","author":"Mandal","year":"2020","journal-title":"Remote Sens. Environ."},{"key":"ref_8","unstructured":"European Space Agency (2013). Sentinel-1 User Handbook, European Space Agency."},{"key":"ref_9","unstructured":"Joint Research Center (2021, September 15). Concept Note: Towards Future Copernicus Service Components in Support to Agriculture?. Available online: https:\/\/www.copernicus.eu\/sites\/default\/files\/2018-10\/AGRI_Conceptnote.pdf."},{"key":"ref_10","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_11","unstructured":"Lopez-Sanchez, J.M., Vicente-Guijalba, F., Ballester-Berman, J.D., and Cloude, S.R. (2013). Estimating phenology of agricultural crops from space. ESA Living Planet Symp., European Space Agency. ESA-SP 722."},{"key":"ref_12","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_13","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_14","doi-asserted-by":"crossref","first-page":"3077","DOI":"10.1080\/01431161.2015.1055608","article-title":"Retrieval of phenological stages of onion fields during the first year of growth by means of C-band polarimetric SAR measurements","volume":"36","author":"Mascolo","year":"2015","journal-title":"Int. J. Remote Sens."},{"key":"ref_15","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_16","doi-asserted-by":"crossref","first-page":"249","DOI":"10.1109\/LGRS.2014.2334371","article-title":"Influence of incidence angle on the coherent copolar polarimetric response of rice at X-band","volume":"12","author":"Cloude","year":"2015","journal-title":"IEEE Geosci. Remote Sens. Lett."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"6505","DOI":"10.1109\/TGRS.2016.2585744","article-title":"A complete procedure for crop phenology estimation with PolSAR data based on the complex Wishart classifier","volume":"54","author":"Mascolo","year":"2016","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_18","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 multitemporal co-polar X-band SAR images","volume":"9","author":"Kucuk","year":"2016","journal-title":"IEEE J. Sel. Topics Appl. Earth Observ. Remote Sens."},{"key":"ref_19","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_20","doi-asserted-by":"crossref","first-page":"3278","DOI":"10.1109\/TGRS.2014.2372897","article-title":"Dynamical approach for real-time monitoring of agricultural crops","volume":"53","year":"2015","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_21","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. Topics Appl. Earth Observ. Remote Sens."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"3512","DOI":"10.1109\/JSTARS.2016.2539498","article-title":"Contribution to real-time estimation of crop phenological states in a dynamical framework based on NDVI time series: Data fusion with SAR and temperature","volume":"9","year":"2016","journal-title":"IEEE J. Sel. Topics Appl. Earth Observ. Remote Sens."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"196","DOI":"10.1016\/j.rse.2018.10.012","article-title":"Estimating canola phenology using synthetic aperture radar","volume":"219","author":"McNairn","year":"2018","journal-title":"Remote Sens. Environ."},{"key":"ref_24","doi-asserted-by":"crossref","unstructured":"De Bernardis, C., Vicente-Guijalba, F., Martinez-Marin, T., and Lopez-Sanchez, J.M. (2016). Particle Filter Approach for Real-Time Estimation of Crop Phenological States Using Time Series of NDVI Images. Remote Sens., 8.","DOI":"10.3390\/rs8070610"},{"key":"ref_25","doi-asserted-by":"crossref","unstructured":"Grewal, M.S., and Andrews, A.P. (2001). Kalman Filtering: Theory and Practice Using MATLAB, Wiley. [2nd ed.].","DOI":"10.1002\/0471266388"},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"174","DOI":"10.1109\/78.978374","article-title":"A tutorial on particle filters for online nonlinear\/non-Gaussian Bayesian tracking","volume":"50","author":"Arulampalam","year":"2002","journal-title":"IEEE Trans. Signal Process."},{"key":"ref_27","unstructured":"Meier, U. (2001). Growth Stages of Mono- and Dicotyledonous Plants. BBCH Monograph, Federal Biological Research Centre for Agriculture and Forestry. [2nd ed.]."},{"key":"ref_28","unstructured":"Bowerman, B.L. (1974). Nonstationary Markov Decision Processes and Related Topics in Nonstationary Markov Chains. [Ph.D. Thesis, Iowa State University]."},{"key":"ref_29","doi-asserted-by":"crossref","unstructured":"Chen, C., H\u00e4rdle, W., and Unwin, A. (2008). Multivariate Visualization by Density Estimation. Handbook of Data Visualization, Springer.","DOI":"10.1007\/978-3-540-33037-0"}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/13\/21\/4332\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T07:22:00Z","timestamp":1760167320000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/13\/21\/4332"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,10,28]]},"references-count":29,"journal-issue":{"issue":"21","published-online":{"date-parts":[[2021,11]]}},"alternative-id":["rs13214332"],"URL":"https:\/\/doi.org\/10.3390\/rs13214332","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021,10,28]]}}}