{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,9]],"date-time":"2026-01-09T19:31:49Z","timestamp":1767987109331,"version":"3.49.0"},"reference-count":64,"publisher":"MDPI AG","issue":"23","license":[{"start":{"date-parts":[[2024,12,6]],"date-time":"2024-12-06T00:00:00Z","timestamp":1733443200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"United States Department of Agriculture Forest Service","award":["110789"],"award-info":[{"award-number":["110789"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>A novel Portable L-band radiometer (PoLRa), compatible with tower-, vehicle- and drone-based platforms, can provide gridded soil moisture estimations from a few meters to several hundred meters yet its retrieval accuracy has rarely been examined. This study aims to provide an initial assessment of the performance of PoLRa-derived soil moisture at a spatial resolution of approximately 0.7 m \u00d7 0.7 m at a set of sampling pixels in central Illinois, USA. This preliminary evaluation focuses on (1) the consistency of PoLRa-measured brightness temperatures from different viewing directions over the same area and (2) whether PoLRa-derived soil moisture retrievals are within an acceptable accuracy range. As PoLRa shares many aspects of the L-band radiometer onboard NASA\u2019s Soil Moisture Active Passive (SMAP) mission, two SMAP operational algorithms and the conventional dual-channel algorithm (DCA) were applied to calculate volumetric soil moisture from the measured brightness temperatures. The vertically polarized brightness temperatures from the PoLRa are typically more stable than their horizontally polarized counterparts across all four directions. In each test period, the standard deviations of observed dual-polarization brightness temperatures are generally less than 5 K. By comparing PoLRa-based soil moisture retrievals against the simultaneous moisture values obtained by a handheld capacitance probe, the unbiased root mean square error (ubRMSE) and the Pearson correlation coefficient (R) are mostly below 0.05 m3\/m3 and above 0.7 for various algorithms adopted here. While SMAP models and the DCA algorithm can derive soil moisture from PoLRa observations, no single algorithm consistently outperforms the others. These findings highlight the significant potential of ground- or drone-based PoLRa measurements as a standalone reference for the calibration and validation of spaceborne L-band synthetic aperture radars and radiometers. The accuracy of PoLRa-yielded high-resolution soil moisture can be further improved via standardized operational procedures and appropriate tau-omega parameters.<\/jats:p>","DOI":"10.3390\/rs16234596","type":"journal-article","created":{"date-parts":[[2024,12,9]],"date-time":"2024-12-09T10:11:47Z","timestamp":1733739107000},"page":"4596","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":5,"title":["Evaluation of Soil Moisture Retrievals from a Portable L-Band Microwave Radiometer"],"prefix":"10.3390","volume":"16","author":[{"given":"Runze","family":"Zhang","sequence":"first","affiliation":[{"name":"Department of Civil and Environmental Engineering, University of Illinois Urbana-Champaign, Urbana, IL 61801, USA"}]},{"given":"Abhi","family":"Nayak","sequence":"additional","affiliation":[{"name":"Department of Computer Science, University of Illinois Urbana-Champaign, Urbana, IL 61801, USA"}]},{"given":"Derek","family":"Houtz","sequence":"additional","affiliation":[{"name":"Microwave Remote Sensing, Swiss Federal Institute for Forest, Snow, and Landscape Research, 8903 Birmensdorf, Switzerland"}]},{"given":"Adam","family":"Watts","sequence":"additional","affiliation":[{"name":"Pacific Wildland Fire Sciences Laboratory, United States Forest Service, Wenatchee, WA 98801, USA"}]},{"given":"Elahe","family":"Soltanaghai","sequence":"additional","affiliation":[{"name":"Department of Computer Science, University of Illinois Urbana-Champaign, Urbana, IL 61801, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2018-134X","authenticated-orcid":false,"given":"Mohamad","family":"Alipour","sequence":"additional","affiliation":[{"name":"Department of Civil and Environmental Engineering, University of Illinois Urbana-Champaign, Urbana, IL 61801, USA"}]}],"member":"1968","published-online":{"date-parts":[[2024,12,6]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"1138","DOI":"10.1126\/science.1100217","article-title":"Regions of strong coupling between soil moisture and precipitation","volume":"305","author":"Koster","year":"2004","journal-title":"Science"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"125","DOI":"10.1016\/j.earscirev.2010.02.004","article-title":"Investigating soil moisture\u2013climate interactions in a changing climate: A review","volume":"99","author":"Seneviratne","year":"2010","journal-title":"Earth-Sci. Rev."},{"key":"ref_3","first-page":"229","article-title":"Remote sensing of soil properties in precision agriculture: A review","volume":"5","author":"Ge","year":"2011","journal-title":"Front. Earth Sci."},{"key":"ref_4","doi-asserted-by":"crossref","unstructured":"Petropoulos, G. (2013). Remote Sensing of Energy Fluxes and Soil Moisture Content, CRC press.","DOI":"10.1201\/b15610"},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"345","DOI":"10.1038\/ngeo2141","article-title":"Mega-heatwave temperatures due to combined soil desiccation and atmospheric heat accumulation","volume":"7","author":"Miralles","year":"2014","journal-title":"Nat. Geosci."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"10657","DOI":"10.1029\/2019WR025874","article-title":"Satellite-based assessment of land surface energy partitioning\u2013soil moisture relationships and effects of confounding variables","volume":"55","author":"Feldman","year":"2019","journal-title":"Water Resour. Res."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"1117","DOI":"10.1175\/JHM-386.1","article-title":"A global dataset of Palmer Drought Severity Index for 1870\u20132002: Relationship with soil moisture and effects of surface warming","volume":"5","author":"Dai","year":"2004","journal-title":"J. Hydrometeorol."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"e2022WR033814","DOI":"10.1029\/2022WR033814","article-title":"Remotely sensed soil moisture can capture dynamics relevant to plant water uptake","volume":"59","author":"Feldman","year":"2023","journal-title":"Water Resour. Res."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"927","DOI":"10.1029\/RS016i005p00927","article-title":"A comparison of radiative transfer models for predicting the microwave emission from soils","volume":"16","author":"Schmugge","year":"1981","journal-title":"Radio Sci."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"1549","DOI":"10.1175\/1520-0450(1978)017<1549:RSOSSM>2.0.CO;2","article-title":"Remote sensing of surface soil moisture","volume":"17","author":"Schmugge","year":"1978","journal-title":"J. Appl. Meteorol."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"33","DOI":"10.1109\/TGE.1979.294626","article-title":"Microwave backscatter dependence on surface roughness, soil moisture, and soil texture: Part II-vegetation-covered soil","volume":"17","author":"Ulaby","year":"1979","journal-title":"IEEE Trans. Geosci. Electron."},{"key":"ref_12","unstructured":"Ulaby, F.T., Moore, R.K., and Fung, A.K. (1986). Microwave Remote Sensing: Active and Passive. Volume 3-From Theory to Applications, Artech House."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"101","DOI":"10.1016\/0022-1694(95)02970-2","article-title":"Passive microwave remote sensing of soil moisture","volume":"184","author":"Njoku","year":"1996","journal-title":"J. Hydrol."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"1729","DOI":"10.1109\/36.942551","article-title":"Soil moisture retrieval from space: The Soil Moisture and Ocean Salinity (SMOS) mission","volume":"39","author":"Kerr","year":"2001","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"704","DOI":"10.1109\/JPROC.2010.2043918","article-title":"The soil moisture active passive (SMAP) mission","volume":"98","author":"Entekhabi","year":"2010","journal-title":"Proc. IEEE"},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"215","DOI":"10.1109\/TGRS.2002.808243","article-title":"Soil moisture retrieval from AMSR-E","volume":"41","author":"Njoku","year":"2003","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"5","DOI":"10.1127\/0941-2948\/2013\/0399","article-title":"The ASCAT soil moisture product: A review of its specifications, validation results, and emerging applications","volume":"22","author":"Wagner","year":"2013","journal-title":"Meteorol. Z."},{"key":"ref_18","first-page":"13","article-title":"Instrument performance and calibration of AMSR-E and AMSR2","volume":"38","author":"Imaoka","year":"2010","journal-title":"Int. Arch. Photogramm. Remote Sens. Spat. Inf. Sci."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"9","DOI":"10.1016\/j.rse.2011.05.028","article-title":"GMES Sentinel-1 mission","volume":"120","author":"Torres","year":"2012","journal-title":"Remote Sens. Environ."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"82","DOI":"10.1016\/j.rse.2019.01.015","article-title":"A comprehensive validation of the SMAP Enhanced Level-3 Soil Moisture product using ground measurements over varied climates and landscapes","volume":"223","author":"Zhang","year":"2019","journal-title":"Remote Sens. Environ."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"112126","DOI":"10.1016\/j.rse.2020.112126","article-title":"Identifying relative strengths of SMAP, SMOS-IC, and ASCAT to capture temporal variability","volume":"252","author":"Zhang","year":"2021","journal-title":"Remote Sens. Environ."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"112052","DOI":"10.1016\/j.rse.2020.112052","article-title":"Global scale error assessments of soil moisture estimates from microwave-based active and passive satellites and land surface models over forest and mixed irrigated\/dryland agriculture regions","volume":"251","author":"Kim","year":"2020","journal-title":"Remote Sens. Environ."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"111215","DOI":"10.1016\/j.rse.2019.111215","article-title":"Satellite surface soil moisture from SMAP, SMOS, AMSR2 and ESA CCI: A comprehensive assessment using global ground-based observations","volume":"231","author":"Ma","year":"2019","journal-title":"Remote Sens. Environ."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"100","DOI":"10.1038\/ngeo2868","article-title":"The global distribution and dynamics of surface soil moisture","volume":"10","author":"McColl","year":"2017","journal-title":"Nat. Geosci."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"4826","DOI":"10.1038\/s41467-024-49244-7","article-title":"Global critical soil moisture thresholds of plant water stress","volume":"15","author":"Fu","year":"2024","journal-title":"Nat. Commun."},{"key":"ref_26","doi-asserted-by":"crossref","unstructured":"Bindlish, R., Long, D., Piepmeier, J., and Bailey, M. (2021, January 11\u201316). Global L-band Observatory for water cycle studies (GLOWS): Soil moisture continuity mission. Proceedings of the 2021 IEEE International Geoscience and Remote Sensing Symposium IGARSS, Brussels, Belgium.","DOI":"10.1117\/12.3028882"},{"key":"ref_27","doi-asserted-by":"crossref","unstructured":"Davidson, M.W., and Furnell, R. (2021, January 11\u201316). ROSE-L: Copernicus l-band SAR mission. Proceedings of the 2021 IEEE International Geoscience and Remote Sensing Symposium IGARSS, Brussels, Belgium.","DOI":"10.1109\/IGARSS47720.2021.9554018"},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"584","DOI":"10.3390\/s100100584","article-title":"ELBARA II, an L-band radiometer system for soil moisture research","volume":"10","author":"Schwank","year":"2009","journal-title":"Sensors"},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"1039","DOI":"10.1109\/36.921422","article-title":"Passive active L-and S-band (PALS) microwave sensor for ocean salinity and soil moisture measurements","volume":"39","author":"Wilson","year":"2001","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1109\/TGRS.2023.3238367","article-title":"Toward an Improved Surface Roughness Parameterization Model for Soil Moisture Retrieval in Road Construction","volume":"61","author":"Nguyen","year":"2023","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"739","DOI":"10.5194\/bg-18-739-2021","article-title":"L-band vegetation optical depth as an indicator of plant water potential in a temperate deciduous forest stand","volume":"18","author":"Holtzman","year":"2021","journal-title":"Biogeosciences"},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"8724","DOI":"10.1109\/JSTARS.2024.3388914","article-title":"Calibration of the SMAP Soil Moisture Retrieval Algorithm to Reduce Bias Over the Amazon Rainforest","volume":"17","author":"Cho","year":"2024","journal-title":"IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens."},{"key":"ref_33","doi-asserted-by":"crossref","unstructured":"Brocca, L., Ciabatta, L., Massari, C., Camici, S., and Tarpanelli, A. (2017). Soil moisture for hydrological applications: Open questions and new opportunities. Water, 9.","DOI":"10.3390\/w9020140"},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"112162","DOI":"10.1016\/j.rse.2020.112162","article-title":"A roadmap for high-resolution satellite soil moisture applications\u2013confronting product characteristics with user requirements","volume":"252","author":"Peng","year":"2021","journal-title":"Remote Sens. Environ."},{"key":"ref_35","doi-asserted-by":"crossref","unstructured":"Houtz, D., Naderpour, R., and Schwank, M. (2020). Portable l-band radiometer (polra): Design and characterization. Remote Sens., 12.","DOI":"10.3390\/rs12172780"},{"key":"ref_36","unstructured":"Matzler, C., Weber, D., Wuthrich, M., Schneeberger, K., Stamm, C., Wydler, H., and Fluhler, H. (2003, January 21\u201325). ELBARA, the ETH L-band radiometer for soil-moisture research. Proceedings of the IGARSS 2003. 2003 IEEE International Geoscience and Remote Sensing Symposium. Proceedings (IEEE Cat. No.03CH37477), Toulouse, France."},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"1662","DOI":"10.3390\/rs2071662","article-title":"Design and first results of an UAV-borne L-band radiometer for multiple monitoring purposes","volume":"2","author":"Aguasca","year":"2010","journal-title":"Remote Sens."},{"key":"ref_38","doi-asserted-by":"crossref","unstructured":"McIntyre, E.M., and Gasiewski, A.J. (2007, January 23\u201328). An ultra-lightweight L-band digital Lobe-Differencing Correlation Radiometer (LDCR) for airborne UAV SSS mapping. Proceedings of the 2007 IEEE International Geoscience and Remote Sensing Symposium, Barcelona, Spain.","DOI":"10.1109\/IGARSS.2007.4422992"},{"key":"ref_39","unstructured":"O\u2019Neill, P., Bindlish, R., Chan, S., Chaubell, J., Colliander, A., Njoku, E., and Jackson, T. (2024, March 18). Algorithm Theoretical Basis Document Level 2 & 3 Soil Moisture (Passive) Data Products, Available online: https:\/\/nsidc.org\/sites\/nsidc.org\/files\/technical-references\/L2_SM_P_ATBD_rev_G_final_Oct2021.pdf."},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"102","DOI":"10.1109\/JSTARS.2021.3123932","article-title":"Regularized dual-channel algorithm for the retrieval of soil moisture and vegetation optical depth from SMAP measurements","volume":"15","author":"Chaubell","year":"2021","journal-title":"IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens."},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"16592","DOI":"10.1109\/JSTARS.2024.3457941","article-title":"Inverse Dynamic Parameter Identification for Remote Sensing of Soil Moisture from SMAP Satellite Observations","volume":"17","author":"Zhang","year":"2024","journal-title":"IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens."},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"238","DOI":"10.1016\/j.rse.2017.01.024","article-title":"Modelling the passive microwave signature from land surfaces: A review of recent results and application to the L-band SMOS & SMAP soil moisture retrieval algorithms","volume":"192","author":"Wigneron","year":"2017","journal-title":"Remote Sens. Environ."},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"11229","DOI":"10.1029\/JC087iC13p11229","article-title":"A model for microwave emission from vegetation-covered fields","volume":"87","author":"Mo","year":"1982","journal-title":"J. Geophys. Res. Ocean."},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"1301","DOI":"10.1029\/JC087iC02p01301","article-title":"A parameterization of effective soil temperature for microwave emission","volume":"87","author":"Choudhury","year":"1982","journal-title":"J. Geophys. Res. Ocean."},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"5699","DOI":"10.1029\/JC084iC09p05699","article-title":"Effect of surface roughness on the microwave emission from soils","volume":"84","author":"Choudhury","year":"1979","journal-title":"J. Geophys. Res. Ocean."},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"113458","DOI":"10.1016\/j.rse.2023.113458","article-title":"From field observations to temporally dynamic soil surface roughness retrievals in the U.S. Corn Belt","volume":"287","author":"Walker","year":"2023","journal-title":"Remote Sens. Environ."},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"288","DOI":"10.1109\/TGRS.1980.350304","article-title":"An empirical model for the complex dielectric permittivity of soils as a function of water content","volume":"GE-18","author":"Wang","year":"1980","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_48","doi-asserted-by":"crossref","first-page":"35","DOI":"10.1109\/TGRS.1985.289498","article-title":"Microwave dielectric behavior of wet soil-Part II: Dielectric mixing models","volume":"GE-23","author":"Dobson","year":"1985","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_49","doi-asserted-by":"crossref","first-page":"2059","DOI":"10.1109\/TGRS.2008.2011631","article-title":"Physically and mineralogically based spectroscopic dielectric model for moist soils","volume":"47","author":"Mironov","year":"2009","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_50","doi-asserted-by":"crossref","first-page":"6407","DOI":"10.5194\/hess-25-6407-2021","article-title":"An inverse dielectric mixing model at 50 MHz that considers soil organic carbon","volume":"25","author":"Park","year":"2021","journal-title":"Hydrol. Earth Syst. Sci."},{"key":"ref_51","doi-asserted-by":"crossref","first-page":"203","DOI":"10.1016\/0034-4257(91)90057-D","article-title":"Vegetation effects on the microwave emission of soils","volume":"36","author":"Jackson","year":"1991","journal-title":"Remote Sens. Environ."},{"key":"ref_52","doi-asserted-by":"crossref","first-page":"5734","DOI":"10.3390\/rs70505734","article-title":"Global-scale evaluation of roughness effects on C-band AMSR-E observations","volume":"7","author":"Wang","year":"2015","journal-title":"Remote Sens."},{"key":"ref_53","first-page":"125","article-title":"Global SMOS soil moisture retrievals from the land parameter retrieval model","volume":"45","author":"Kerr","year":"2016","journal-title":"Int. J. Appl. Earth Obs. Geoinf."},{"key":"ref_54","doi-asserted-by":"crossref","first-page":"111968","DOI":"10.1016\/j.rse.2020.111968","article-title":"Landsat 9: Empowering open science and applications through continuity","volume":"248","author":"Masek","year":"2020","journal-title":"Remote Sens. Environ."},{"key":"ref_55","doi-asserted-by":"crossref","first-page":"832","DOI":"10.1175\/2010JHM1223.1","article-title":"Performance metrics for soil moisture retrievals and application requirements","volume":"11","author":"Entekhabi","year":"2010","journal-title":"J. Hydrometeorol."},{"key":"ref_56","doi-asserted-by":"crossref","first-page":"460","DOI":"10.1016\/j.rse.2017.06.037","article-title":"L-band vegetation optical depth and effective scattering albedo estimation from SMAP","volume":"198","author":"Konings","year":"2017","journal-title":"Remote Sens. Environ."},{"key":"ref_57","doi-asserted-by":"crossref","first-page":"7684","DOI":"10.1109\/JSTARS.2024.3382045","article-title":"Precision Soil Moisture Monitoring with Passive Microwave L-band UAS Mapping","volume":"17","author":"Kim","year":"2024","journal-title":"IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens."},{"key":"ref_58","doi-asserted-by":"crossref","first-page":"112921","DOI":"10.1016\/j.rse.2022.112921","article-title":"A new SMAP soil moisture and vegetation optical depth product (SMAP-IB): Algorithm, assessment and inter-comparison","volume":"271","author":"Li","year":"2022","journal-title":"Remote Sens. Environ."},{"key":"ref_59","doi-asserted-by":"crossref","first-page":"112238","DOI":"10.1016\/j.rse.2020.112238","article-title":"SMOS-IC data record of soil moisture and L-VOD: Historical development, applications and perspectives","volume":"254","author":"Wigneron","year":"2021","journal-title":"Remote Sens. Environ."},{"key":"ref_60","doi-asserted-by":"crossref","first-page":"364","DOI":"10.1109\/JSTARS.2021.3124743","article-title":"Validation of Soil Moisture Data Products From the NASA SMAP Mission","volume":"15","author":"Colliander","year":"2022","journal-title":"IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens."},{"key":"ref_61","doi-asserted-by":"crossref","first-page":"108686","DOI":"10.1016\/j.compag.2024.108686","article-title":"Advancements in dielectric soil moisture sensor Calibration: A comprehensive review of methods and techniques","volume":"218","author":"Mane","year":"2024","journal-title":"Comput. Electron. Agric."},{"key":"ref_62","doi-asserted-by":"crossref","first-page":"111662","DOI":"10.1016\/j.rse.2020.111662","article-title":"Microwave retrievals of soil moisture and vegetation optical depth with improved resolution using a combined constrained inversion algorithm: Application for SMAP satellite","volume":"239","author":"Gao","year":"2020","journal-title":"Remote Sens. Environ."},{"key":"ref_63","doi-asserted-by":"crossref","first-page":"111797","DOI":"10.1016\/j.rse.2020.111797","article-title":"SAR-enhanced mapping of live fuel moisture content","volume":"245","author":"Rao","year":"2020","journal-title":"Remote Sens. Environ."},{"key":"ref_64","doi-asserted-by":"crossref","first-page":"113667","DOI":"10.1016\/j.rse.2023.113667","article-title":"A multi-scale algorithm for the NISAR mission high-resolution soil moisture product","volume":"295","author":"Lal","year":"2023","journal-title":"Remote Sens. Environ."}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/16\/23\/4596\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T16:49:10Z","timestamp":1760114950000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/16\/23\/4596"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,12,6]]},"references-count":64,"journal-issue":{"issue":"23","published-online":{"date-parts":[[2024,12]]}},"alternative-id":["rs16234596"],"URL":"https:\/\/doi.org\/10.3390\/rs16234596","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,12,6]]}}}