{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,19]],"date-time":"2025-12-19T10:07:28Z","timestamp":1766138848394,"version":"3.37.3"},"reference-count":98,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","license":[{"start":{"date-parts":[[2024,1,1]],"date-time":"2024-01-01T00:00:00Z","timestamp":1704067200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE J. Sel. Top. Appl. Earth Observations Remote Sensing"],"published-print":{"date-parts":[[2024]]},"DOI":"10.1109\/jstars.2024.3448625","type":"journal-article","created":{"date-parts":[[2024,8,23]],"date-time":"2024-08-23T17:53:45Z","timestamp":1724435625000},"page":"15463-15479","source":"Crossref","is-referenced-by-count":2,"title":["RTM-Based Downscaling of Medium Resolution Soil Moisture Using Sentinel-1 Data Over Agricultural Fields"],"prefix":"10.1109","volume":"17","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-5278-8379","authenticated-orcid":false,"given":"Thomas","family":"Wei\u00df","sequence":"first","affiliation":[{"name":"Department of Geography, Ludwig-Maximilians-Universit&#x00E4;t of Munich, Munich, Germany"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1760-2425","authenticated-orcid":false,"given":"Thomas","family":"Jagdhuber","sequence":"additional","affiliation":[{"name":"German Aerospace Center, Microwaves and Radar Institute, We&#x00DF;ling, Germany"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5322-4540","authenticated-orcid":false,"given":"Thomas","family":"Ramsauer","sequence":"additional","affiliation":[{"name":"Department of Geography, Ludwig-Maximilians-Universit&#x00E4;t of Munich, Munich, Germany"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2636-3438","authenticated-orcid":false,"given":"Alexander","family":"L\u00f6w","sequence":"additional","affiliation":[{"name":"Department of Geography, Ludwig-Maximilians-Universit&#x00E4;t of Munich, Munich, Germany"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6294-120X","authenticated-orcid":false,"given":"Philip","family":"Marzahn","sequence":"additional","affiliation":[{"name":"Faculty of Agricultural and Environmental Sciences, University of Rostock, Rostock, Germany"}]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1109\/JSTARS.2012.2192416"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1175\/bams-d-11-00254.1"},{"issue":"2","key":"ref3","article-title":"Soil moisture for hydrological applications: Open questions and new opportunities","volume-title":"Water","volume":"9","author":"Brocca","year":"2017"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1029\/2009wr008016"},{"key":"ref5","first-page":"436","article-title":"Spatial-temporal variability of soil moisture: Addressing the monitoring at the catchment scale","volume-title":"J. Hydrol.","volume":"570","author":"Dari","year":"2019"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1080\/14498596.2020.1833769"},{"key":"ref7","article-title":"Estimation and evaluation of high-resolution soil moisture from merged model and earth observation data in the Great Britain","volume-title":"Remote Sens. Environ.","volume":"264","author":"Peng","year":"2021"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1002\/2016rg000543"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1109\/TGRS.2015.2462074"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1109\/TGRS.2018.2858004"},{"key":"ref11","article-title":"The SMAP and copernicus sentinel 1 A\/B microwave active-passive high resolution surface soil moisture product","volume-title":"Remote Sen\/s. Environ.","volume":"233","author":"Das","year":"2019"},{"article-title":"RADOLAN_API - A soil moisture data set derived from weather radar data","year":"2021","author":"Ramsauer","key":"ref12"},{"issue":"7","key":"ref13","first-page":"3053","article-title":"Daily soil moisture mapping at 1 km resolution based on SMAP data for desertification areas in northern China","volume-title":"Earth Syst. Sci. Data","volume":"14","author":"Rao","year":"2022"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1109\/IGARSS.2013.6723284"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1109\/TGRS.2019.2920995"},{"issue":"1","key":"ref16","article-title":"Field-scale soil moisture retrieval using PALSAR-2 polarimetric decomposition and machine learning","volume-title":"Agronomy","volume":"11","author":"Huang","year":"2021"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1080\/0143116031000156837"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1109\/TGRS.2007.914800"},{"issue":"12","key":"ref19","article-title":"Synergic use of Sentinel-1 and Sentinel-2 images for operational soil moisture mapping at high spatial resolution over agricultural areas","volume-title":"Remote Sens.","volume":"9","author":"Hajj","year":"2017"},{"issue":"18","key":"ref20","article-title":"Evaluation of different radiative transfer models for microwave backscatter estimation of wheat fields","volume-title":"Remote Sens.","volume":"12","author":"Wei","year":"2020"},{"issue":"16","key":"ref21","article-title":"On the radiative transfer model for soil moisture across space, time and hydro-climates","volume-title":"Remote Sens.","volume":"12","author":"Neelam","year":"2020"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1109\/36.942542"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1175\/JHM-D-12-092.1"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1109\/36.134086"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1109\/TGRS.2003.821065"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1109\/36.406677"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1163\/156939302x01119"},{"issue":"2","key":"ref28","article-title":"Potential of Sentinel-1 images for estimating the soil roughness over bare agricultural soils","volume-title":"Water","volume":"10","author":"Baghdadi","year":"2018"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1029\/RS013i002p00357"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1109\/36.917912"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.3998\/0472119356"},{"issue":"14","key":"ref32","article-title":"Retrieval of high-resolution soil moisture through combination of Sentinel-1 and Sentinel-2 data","volume-title":"Remote Sens.","volume":"12","author":"Ma","year":"2020"},{"issue":"1","key":"ref33","article-title":"Penetration analysis of SAR signals in the C and L bands for wheat, maize, and grasslands","volume-title":"Remote Sens.","volume":"11","author":"Hajj","year":"2019"},{"issue":"11","key":"ref34","article-title":"Detecting irrigation events over semi-arid and temperate climatic areas using Sentinel-1 data: Case of several summer crops","volume-title":"Agronomy","volume":"12","author":"Bazzi","year":"2022"},{"issue":"20","key":"ref35","article-title":"Estimating gravimetric water content of a winter wheat field from L-band vegetation optical depth","volume-title":"Remote Sens.","volume":"11","author":"Meyer","year":"2019"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1117\/1.JRS.13.014516"},{"issue":"18","key":"ref37","article-title":"Global monitoring of the vegetation dynamics from the vegetation optical depth (VOD): A review","volume-title":"Remote Sens.","volume":"12","author":"Frappart","year":"2020"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1109\/JSTARS.2014.2323705"},{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.1109\/JSTARS.2015.2398034"},{"key":"ref40","article-title":"An evaluation of landsat, Sentinel-2, Sentinel-1 and MODIS data for crop type mapping","volume-title":"Sci. Remote Sens.","volume":"3","author":"Song","year":"2021"},{"issue":"9","key":"ref41","article-title":"Synergetic use of Sentinel-1 and Sentinel-2 data for soil moisture mapping at 100 m resolution","volume-title":"Sensors","volume":"17","author":"Gao","year":"2017"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.1109\/IGARSS.2018.8518170"},{"key":"ref43","doi-asserted-by":"publisher","DOI":"10.3390\/rs10121924"},{"key":"ref44","doi-asserted-by":"publisher","DOI":"10.3390\/rs11101150"},{"key":"ref45","doi-asserted-by":"publisher","DOI":"10.21105\/joss.03337"},{"key":"ref46","first-page":"202","article-title":"Soil moisture retrieval over irrigated grassland using X-band SAR data","volume-title":"Remote Sens. Environ.","volume":"176","author":"Hajj","year":"2016"},{"issue":"9","key":"ref47","article-title":"Calibration of the water cloud model at C-band for winter crop fields and grasslands","volume-title":"Remote Sens.","volume":"9","author":"Baghdadi","year":"2017"},{"key":"ref48","doi-asserted-by":"publisher","DOI":"10.1109\/36.581987"},{"key":"ref49","first-page":"166","article-title":"Py6S: A python interface to the 6S radiative transfer model","volume-title":"Comput. Geosci.","volume":"51","author":"Wilson","year":"2013"},{"issue":"9","key":"ref50","article-title":"RADOLAN_API: An hourly soil moisture data set based on weather radar, soil properties and reanalysis temperature data","volume-title":"Remote Sens.","volume":"13","author":"Ramsauer","year":"2021"},{"article-title":"Projekt RADOLAN. Routineverfahren zur Online-A neichung der Radarniederschlagsdaten mit Hilfe von Automatischen Boden- niederschlagsstationen (Ombrometer)","year":"2004","author":"Bartels","key":"ref51"},{"key":"ref52","first-page":"132","article-title":"An overview of the new radar-based precipitation climatology of the Deutscher Wetterdienstdata, methods, products","volume-title":"Proc. 11th Int. Workshop Precipitation Urban Areas Rainfall Monit. Modelling Forecasting Urban Environ.","author":"Winterrath","year":"2019"},{"key":"ref53","volume":"30","author":"Kohler","year":"1951","journal-title":"Predicting the Runoff from Storm Rainfall"},{"key":"ref54","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pone.0169748"},{"year":"2018","key":"ref55","article-title":"CORINE land cover 2018"},{"key":"ref56","doi-asserted-by":"publisher","DOI":"10.1109\/TGRS.2002.800232"},{"issue":"3","key":"ref57","first-page":"203","article-title":"Vegetation effects on the microwave emission of soils","volume-title":"Remote Sens. Environ.","volume":"36","author":"Jackson","year":"1991"},{"key":"ref58","doi-asserted-by":"publisher","DOI":"10.1109\/IGARSS47720.2021.9555117"},{"key":"ref59","article-title":"A spatial and temporal evaluation of the SMAP cropland b-parameter across the U.S. Corn Belt","volume-title":"Remote Sens. Environ.","volume":"297","author":"Hartman","year":"2023"},{"issue":"12","key":"ref60","article-title":"Sentinel-1 backscatter analysis and radiative transfer modeling of dense winter wheat time series","volume-title":"Remote Sens.","volume":"13","author":"Wei","year":"2021"},{"issue":"4","key":"ref61","first-page":"475","article-title":"Vegetation water content mapping using landsat data derived normalized difference water index for corn and soybeans","volume-title":"Remote Sens. Environ.","volume":"92","author":"Jackson","year":"2004"},{"key":"ref62","first-page":"297","article-title":"A multi-sensor approach for high resolution airborne soil moisture mapping","volume-title":"Proc. 30th Hydrol. Water Resour. Symp.","author":"Maggioni","year":"2006"},{"key":"ref63","doi-asserted-by":"publisher","DOI":"10.1109\/IGARSS.2011.6049711"},{"year":"2024","key":"ref64","article-title":"SciPy: Open source scientific tools for Python"},{"key":"ref65","first-page":"219","article-title":"An earth observation land data assimilation system (EO-LDAS)","volume-title":"Remote Sens. Environ.","volume":"120","author":"Lewis","year":"2012"},{"key":"ref66","doi-asserted-by":"publisher","DOI":"10.1080\/19479832.2022.2149629"},{"issue":"2","key":"ref67","first-page":"41","article-title":"The BBCH system to coding the phenological growth stages of plantshistory and publications","volume-title":"J. fr Kulturpflanzen","volume":"61","author":"Meier","year":"2009"},{"key":"ref68","article-title":"A roadmap for high-resolution satellite soil moisture applicationsconfronting product characteristics with user requirements","volume-title":"Remote Sens. Environ.","volume":"252","author":"Peng","year":"2021"},{"issue":"10","key":"ref69","article-title":"Hybrid methodology using Sentinel-1\/Sentinel-2 for soil moisture estimation","volume-title":"Remote Sens.","volume":"14","author":"Nativel","year":"2022"},{"issue":"1","key":"ref70","article-title":"Retrieving soil moisture from Sentinel-1: Limitations over certain crops and sensitivity to the first soil thin layer","volume-title":"Water","volume":"16","author":"Bazzi","year":"2024"},{"key":"ref71","first-page":"178","article-title":"Vegetation optical depth and scattering albedo retrieval using time series of dual-polarized L-band radiometer observations","volume-title":"Remote Sens. Environ.","volume":"172","author":"Konings","year":"2016"},{"key":"ref72","doi-asserted-by":"publisher","DOI":"10.1109\/IGARSS.2018.8518975"},{"issue":"1","key":"ref73","article-title":"Vegetation water content mapping in a diverse agricultural landscape: National Airborne Field Experiment 2006","volume-title":"J. Appl. Remote Sens.","volume":"4","author":"Cosh","year":"2010"},{"key":"ref74","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-90673-3_4"},{"key":"ref75","doi-asserted-by":"publisher","DOI":"10.1117\/1.JRS.13.4.044503"},{"issue":"9","key":"ref76","article-title":"High spatial and temporal soil moisture retrieval in agricultural areas using multi-orbit and vegetation adapted Sentinel-1 SAR time series","volume-title":"Remote Sens.","volume":"15","author":"Mengen","year":"2023"},{"key":"ref77","article-title":"Robust retrieval of soil moisture at field scale across wide-ranging SAR incidence angles for soybean, wheat, forage, oat and grass","volume-title":"Remote Sens. Environ.","volume":"266","author":"Kim","year":"2021"},{"key":"ref78","doi-asserted-by":"publisher","DOI":"10.1080\/01431161.2022.2162351"},{"issue":"3","key":"ref79","article-title":"Assessment of multi-scale SMOS and SMAP soil moisture products across the iberian peninsula","volume-title":"Remote Sens.","volume":"12","author":"Portal","year":"2020"},{"issue":"2","key":"ref80","first-page":"267","article-title":"Concept of dealing with uncertainty in radar-based data for hydrological purpose","volume-title":"Natural Hazards Earth Syst. Sci.","volume":"8","author":"Szturc","year":"2008"},{"key":"ref81","doi-asserted-by":"publisher","DOI":"10.1002\/joc.6514"},{"key":"ref82","article-title":"Monitoring soil moisture at the catchment scaleA novel approach combining antecedent precipitation index and radar-derived rainfall data","volume-title":"J. Hydrol.","volume":"589","author":"Schoener","year":"2020"},{"key":"ref83","article-title":"Estimating the global number and distribution of maize and wheat farms","volume-title":"Glob. Food Secur.","volume":"30","author":"Erenstein","year":"2021"},{"article-title":"Soil parameter retrieval under vegetation cover using SAR polarimetry","year":"2012","author":"Jagdhuber","key":"ref84"},{"key":"ref85","doi-asserted-by":"crossref","DOI":"10.1117\/12.693946","article-title":"How far SAR has fulfilled its expectation for soil moisture retrieval","volume-title":"Microwave Remote Sensing of the Atmosphere and Environment V","volume":"6410","author":"Srivastava","year":"2006"},{"issue":"10","key":"ref86","article-title":"Green area index and soil moisture retrieval in maize fields using multi-polarized C- and L-band SAR data and the water cloud model","volume-title":"Remote Sens.","volume":"14","author":"Bouchat","year":"2022"},{"issue":"11","key":"ref87","first-page":"2417","article-title":"Effects of corn on c- and l-band radar backscatter: A correction method for soil moisture retrieval","volume-title":"Remote Sens. Environ.","volume":"114","author":"Joseph","year":"2010"},{"key":"ref88","doi-asserted-by":"publisher","DOI":"10.1117\/1.JRS.10.026008"},{"key":"ref89","doi-asserted-by":"publisher","DOI":"10.1109\/TGRS.2003.813531"},{"issue":"9","key":"ref90","article-title":"Analysis of L-band SAR data for soil moisture estimations over agricultural areas in the tropics","volume-title":"Remote Sens.","volume":"11","author":"Zribi","year":"2019"},{"key":"ref91","doi-asserted-by":"publisher","DOI":"10.1109\/AERO47225.2020.9172638"},{"issue":"1","key":"ref92","article-title":"Operational high resolution land cover map production at the country scale using satellite image time series","volume-title":"Remote Sens.","volume":"9","author":"Inglada","year":"2017"},{"issue":"17","key":"ref93","article-title":"Crop type classification using fusion of Sentinel-1 and Sentinel-2 data: Assessing the impact of feature selection, optical data availability, and parcel sizes on the accuracies","volume-title":"Remote Sens.","volume":"12","author":"Orynbaikyzy","year":"2020"},{"issue":"22","key":"ref94","article-title":"Crop type mapping from optical and radar time series using attention-based deep learning","volume-title":"Remote Sens.","volume":"13","author":"Ofori-Ampofo","year":"2021"},{"key":"ref95","article-title":"Mapping of crop types and crop sequences with combined time series of Sentinel-1, Sentinel-2 and Landsat 8 data for Germany","volume-title":"Remote Sens. Environ.","volume":"269","author":"Blickensdrfer","year":"2022"},{"key":"ref96","doi-asserted-by":"publisher","DOI":"10.1007\/978-94-007-1670-4_8"},{"issue":"2","key":"ref97","article-title":"Agronomic basis and strategies for precision water management: A review","volume-title":"Agronomy","volume":"9","author":"Neupane","year":"2019"},{"key":"ref98","doi-asserted-by":"publisher","DOI":"10.1080\/10934529.2020.1724503"}],"container-title":["IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx8\/4609443\/10330207\/10645061.pdf?arnumber=10645061","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,9,11]],"date-time":"2024-09-11T04:56:58Z","timestamp":1726030618000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/10645061\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024]]},"references-count":98,"URL":"https:\/\/doi.org\/10.1109\/jstars.2024.3448625","relation":{},"ISSN":["1939-1404","2151-1535"],"issn-type":[{"type":"print","value":"1939-1404"},{"type":"electronic","value":"2151-1535"}],"subject":[],"published":{"date-parts":[[2024]]}}}