{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,5]],"date-time":"2026-05-05T12:29:33Z","timestamp":1777984173232,"version":"3.51.4"},"reference-count":37,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","license":[{"start":{"date-parts":[[2025,1,1]],"date-time":"2025-01-01T00:00:00Z","timestamp":1735689600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2025,1,1]],"date-time":"2025-01-01T00:00:00Z","timestamp":1735689600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2025,1,1]],"date-time":"2025-01-01T00:00:00Z","timestamp":1735689600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"DOI":"10.13039\/501100002347","name":"Bundesministerium f?r Bildung und Forschung","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100002347","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100000844","name":"European Space Agency","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100000844","id-type":"DOI","asserted-by":"publisher"}]},{"name":"S?chsisches Staatsministerium f?r Wissenschaft, Kultur und Tourismus"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. Geosci. Remote Sensing"],"published-print":{"date-parts":[[2025]]},"DOI":"10.1109\/tgrs.2025.3593051","type":"journal-article","created":{"date-parts":[[2025,7,28]],"date-time":"2025-07-28T19:49:54Z","timestamp":1753732194000},"page":"1-13","source":"Crossref","is-referenced-by-count":0,"title":["PATCH-FILL: Multiscale Gap Filling for Earth System Data Cubes"],"prefix":"10.1109","volume":"63","author":[{"ORCID":"https:\/\/orcid.org\/0009-0006-3093-2468","authenticated-orcid":false,"given":"Charly","family":"Zimmer","sequence":"first","affiliation":[{"name":"Center for Scalable Data Analytics and Artificial Intelligence (ScaDS.AI) Dresden\/Leipzig, Leipzig University, Leipzig, Germany"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0009-8959-2746","authenticated-orcid":false,"given":"Anja","family":"Neumann","sequence":"additional","affiliation":[{"name":"Center for Scalable Data Analytics and Artificial Intelligence (ScaDS.AI) Dresden\/Leipzig, Leipzig University, Leipzig, Germany"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3031-613X","authenticated-orcid":false,"given":"Miguel D.","family":"Mahecha","sequence":"additional","affiliation":[{"name":"Institute for Earth System Science and Remote Sensing, Leipzig University, Leipzig, Germany"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6108-432X","authenticated-orcid":false,"given":"Josefine","family":"Umlauft","sequence":"additional","affiliation":[{"name":"Center for Scalable Data Analytics and Artificial Intelligence (ScaDS.AI) Dresden\/Leipzig, Leipzig University, Leipzig, Germany"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"issue":"1","key":"ref1","first-page":"282","article-title":"Introduction to remote sensing. Fifth edition. By James B. Campbell and Randolph H. Wynne, TheGuilford Press, 2011; 662 pages. ISBN 978-1-60918-176-5","volume-title":"Remote Sens.","volume":"5","author":"Lin","year":"2013"},{"issue":"23","key":"ref2","doi-asserted-by":"crossref","first-page":"3865","DOI":"10.3390\/rs12233865","article-title":"A machine learning approach for remote sensing data gap-filling with open-source implementation: An example regarding Land Surface Temperature, surface albedo and NDVI","volume":"12","author":"Sarafanov","year":"2020","journal-title":"Remote Sens."},{"issue":"3","key":"ref3","doi-asserted-by":"crossref","first-page":"61","DOI":"10.1109\/MGRS.2015.2441912","article-title":"Missing information reconstruction of remote sensing data: A technical review","volume":"3","author":"Shen","year":"2015","journal-title":"IEEE Geosci. Remote Sens. Mag."},{"issue":"1","key":"ref4","doi-asserted-by":"crossref","first-page":"201","DOI":"10.5194\/esd-11-201-2020","article-title":"Earth system data cubes unravel global multivariate dynamics","volume":"11","author":"Mahecha","year":"2020","journal-title":"Earth Syst. Dyn."},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1017\/eds.2024.22"},{"issue":"3","key":"ref6","doi-asserted-by":"crossref","first-page":"1196","DOI":"10.1016\/j.rse.2007.08.011","article-title":"The availability of cloud-free Landsat ETM+ data over the conterminous United States and globally","volume":"112","author":"Ju","year":"2008","journal-title":"Remote Sens. Environ."},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1002\/2016jd026144"},{"issue":"4","key":"ref8","doi-asserted-by":"crossref","first-page":"1053","DOI":"10.1016\/j.rse.2010.12.010","article-title":"A simple and effective method for filling gaps in Landsat ETM+ SLC-off images","volume":"115","author":"Chen","year":"2011","journal-title":"Remote Sens. Environ."},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.5194\/npg-21-203-2014"},{"issue":"1","key":"ref10","doi-asserted-by":"crossref","first-page":"25","DOI":"10.1109\/MCG.2023.3321989","article-title":"Lexcube: Interactive visualization of large Earth system data cubes","volume":"44","author":"S\u00f6chting","year":"2024","journal-title":"IEEE Comput. Graph. Appl."},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1080\/20964471.2025.2471646"},{"issue":"4","key":"ref12","doi-asserted-by":"crossref","first-page":"1500","DOI":"10.31018\/jans.v14i4.4095","article-title":"Development of a simplified technique for gap filling of normalize difference vegetation index (NDVI) time series data","volume":"14","author":"Faisal","year":"2022","journal-title":"J. Appl. Natural Sci."},{"key":"ref13","doi-asserted-by":"crossref","first-page":"139","DOI":"10.1016\/j.envsoft.2011.10.015","article-title":"A three-dimensional gap filling method for large geophysical datasets: Application to global satellite soil moisture observations","volume":"30","author":"Wang","year":"2012","journal-title":"Environ. Model. Softw."},{"key":"ref14","doi-asserted-by":"crossref","DOI":"10.1016\/j.jenvman.2020.110228","article-title":"Comprehensive evaluation of a spatio-temporal gap filling algorithm: Using remotely sensed precipitation, LST and ET data","volume":"261","author":"Siabi","year":"2020","journal-title":"J. Environ. Manage."},{"key":"ref15","first-page":"3105","article-title":"Assessing the interest of a multi-modal gap-filling strategy for monitoring changes in grassland parcels","volume-title":"Proc. IEEE Int. Geosci. Remote Sens. Symp.","author":"Garioud"},{"key":"ref16","first-page":"218","article-title":"Optical image gap filling using deep convolutional autoencoder from optical and radar images","volume-title":"Proc. IEEE Int. Geosci. Remote Sens. Symp.","author":"Cresson"},{"key":"ref17","doi-asserted-by":"crossref","first-page":"380","DOI":"10.1016\/j.isprsjprs.2022.03.007","article-title":"Multi-modal spatio-temporal meteorological forecasting with deep neural network","volume":"188","author":"Zhang","year":"2022","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref18","first-page":"2758","article-title":"Filling cloud gaps in satellite AOD retrievals using an LSTM CNN-autoencoder model","volume-title":"Proc. IEEE Int. Geosci. Remote Sens. Symp.","author":"Daniels"},{"issue":"19","key":"ref19","doi-asserted-by":"crossref","first-page":"4692","DOI":"10.3390\/rs14194692","article-title":"Gap-filling and missing information recovery for time series of MODIS data using deep learning-based methods","volume":"14","author":"Wang","year":"2022","journal-title":"Remote Sens."},{"issue":"1","key":"ref20","doi-asserted-by":"crossref","first-page":"32","DOI":"10.1016\/0034-4257(94)90057-4","article-title":"Kriging in the shadows: Geostatistical interpolation for remote sensing","volume":"49","author":"Rossi","year":"1994","journal-title":"Remote Sens. Environ."},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1080\/01431169208904172"},{"issue":"8","key":"ref22","doi-asserted-by":"crossref","first-page":"833","DOI":"10.1016\/j.cageo.2004.05.006","article-title":"TIMESAT\u2014A program for analyzing time-series of satellite sensor data","volume":"30","author":"J\u00f6nsson","year":"2004","journal-title":"Comput. Geosci."},{"issue":"1","key":"ref23","doi-asserted-by":"crossref","first-page":"60","DOI":"10.1109\/LGRS.2007.907971","article-title":"An algorithm to produce temporally and spatially continuous MODIS-LAI time series","volume":"5","author":"Gao","year":"2008","journal-title":"IEEE Geosci. Remote Sens. Lett."},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1080\/01431160512331326693"},{"key":"ref25","doi-asserted-by":"crossref","first-page":"106","DOI":"10.1016\/j.isprsjprs.2014.10.001","article-title":"An effective approach for gap-filling continental scale remotely sensed time-series","volume":"98","author":"Weiss","year":"2014","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"issue":"5","key":"ref26","doi-asserted-by":"crossref","first-page":"2841","DOI":"10.1109\/TGRS.2017.2785240","article-title":"Predicting missing values in spatio-temporal remote sensing data","volume":"56","author":"Gerber","year":"2018","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"issue":"8","key":"ref27","doi-asserted-by":"crossref","first-page":"4274","DOI":"10.1109\/TGRS.2018.2810208","article-title":"Missing data reconstruction in remote sensing image with a unified spatial\u2013temporal\u2013spectral deep convolutional neural network","volume":"56","author":"Zhang","year":"2018","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref28","first-page":"802","article-title":"Convolutional LSTM network: A machine learning approach for precipitation nowcasting","volume-title":"Proc. 29th Int. Conf. Neural Inf. Process. Syst. (NIPS)","volume":"1","author":"Shi"},{"issue":"16","key":"ref29","doi-asserted-by":"crossref","first-page":"9174","DOI":"10.3390\/su13169174","article-title":"An ensemble 3D convolutional neural network for spatiotemporal soil temperature forecasting","volume":"13","author":"Yu","year":"2021","journal-title":"Sustainability"},{"issue":"6","key":"ref30","doi-asserted-by":"crossref","first-page":"569","DOI":"10.3390\/atmos11060569","article-title":"Strong spatiotemporal radar echo nowcasting combining 3DCNN and bi-directional convolutional LSTM","volume":"11","author":"Chen","year":"2020","journal-title":"Atmosphere"},{"key":"ref31","article-title":"A guide to convolution arithmetic for deep learning","author":"Dumoulin","year":"2016","journal-title":"arXiv:1603.07285"},{"issue":"2","key":"ref32","doi-asserted-by":"crossref","first-page":"425","DOI":"10.5194\/hess-15-425-2011","article-title":"Developing an improved soil moisture dataset by blending passive and active microwave satellite-based retrievals","volume":"15","author":"Liu","year":"2011","journal-title":"Hydrol. Earth Syst. Sci."},{"issue":"1","key":"ref33","doi-asserted-by":"crossref","first-page":"22","DOI":"10.1016\/S0169-5347(98)01533-X","article-title":"Spatial autocorrelation of ecological phenomena","volume":"14","author":"Koenig","year":"1999","journal-title":"Trends Ecol. Evol."},{"issue":"4","key":"ref34","doi-asserted-by":"crossref","first-page":"2959","DOI":"10.5194\/essd-12-2959-2020","article-title":"An update of IPCC climate reference regions for subcontinental analysis of climate model data: Definition and aggregated datasets","volume":"12","author":"Iturbide","year":"2020","journal-title":"Earth Syst. Sci. Data"},{"issue":"1","key":"ref35","doi-asserted-by":"crossref","first-page":"4540","DOI":"10.1038\/s41467-020-18321-y","article-title":"Spatial validation reveals poor predictive performance of large-scale ecological mapping models","volume":"11","author":"Ploton","year":"2020","journal-title":"Nature Commun."},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1111\/ecog.02881"},{"issue":"13","key":"ref37","doi-asserted-by":"crossref","first-page":"1309","DOI":"10.1016\/j.quascirev.2008.12.020","article-title":"Evaluation of transfer functions in spatially structured environments","volume":"28","author":"Telford","year":"2009","journal-title":"Quaternary Sci. Rev."}],"container-title":["IEEE Transactions on Geoscience and Remote Sensing"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx8\/36\/10807682\/11097902.pdf?arnumber=11097902","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,8,9]],"date-time":"2025-08-09T04:47:44Z","timestamp":1754714864000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/11097902\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025]]},"references-count":37,"URL":"https:\/\/doi.org\/10.1109\/tgrs.2025.3593051","relation":{"has-review":[{"id-type":"doi","id":"10.1109\/TGRS.2025.3593051\/v2\/decision1","asserted-by":"object"},{"id-type":"doi","id":"10.1109\/TGRS.2025.3593051\/v2\/response1","asserted-by":"object"},{"id-type":"doi","id":"10.1109\/TGRS.2025.3593051\/v1\/review1","asserted-by":"object"},{"id-type":"doi","id":"10.1109\/TGRS.2025.3593051\/v1\/review2","asserted-by":"object"},{"id-type":"doi","id":"10.1109\/TGRS.2025.3593051\/v2\/review1","asserted-by":"object"},{"id-type":"doi","id":"10.1109\/TGRS.2025.3593051\/v1\/decision1","asserted-by":"object"}],"has-preprint":[{"id-type":"doi","id":"10.36227\/techrxiv.174430600.07997354\/v1","asserted-by":"object"}]},"ISSN":["0196-2892","1558-0644"],"issn-type":[{"value":"0196-2892","type":"print"},{"value":"1558-0644","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025]]}}}