{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,13]],"date-time":"2026-03-13T07:21:01Z","timestamp":1773386461704,"version":"3.50.1"},"reference-count":67,"publisher":"MDPI AG","issue":"10","license":[{"start":{"date-parts":[[2024,5,8]],"date-time":"2024-05-08T00:00:00Z","timestamp":1715126400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/100000001","name":"National Science Foundation","doi-asserted-by":"publisher","award":["1832065"],"award-info":[{"award-number":["1832065"]}],"id":[{"id":"10.13039\/100000001","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000001","name":"National Science Foundation","doi-asserted-by":"publisher","award":["1940163"],"award-info":[{"award-number":["1940163"]}],"id":[{"id":"10.13039\/100000001","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>To address the issue of estimating soil moisture at a hyper-resolution scale, a methodology referred to as Precision Irrigation Soil Moisture Mapper (PrISMM), that includes three key components, is developed: high-resolution remotely sensed optical and thermal data, surface energy balance modeling, and site-specific soil analysis. An Unmanned Aerial Vehicle\/System (UAV or UAS) collects high-resolution multispectral imagery in the Dallas\u2013Fort Worth metropolitan study area. Orthomosaics are converted to thermal inertia estimates in a spatially distributed format using the remotely sensed data combined with a set of surface energy balance modeling equations. Using thermal and physical properties of soil gained from site-specific soil analysis, thermal inertia estimates were further converted from thermal inertia to daily volumetric soil water content (VSWC) with a horizonal resolution of 8.6 cm. A ground truthing dataset of measured VSWC values taken from a Time Domain Reflectometer was compared with model results, producing a reasonable correlation with an average coefficient of determination of (R2) = 0.79, an average root mean square error (RMSE) = 0.0408, and mean absolute error (MAE) = 0.0308. This study highlights a practical approach of estimating VSWC for irrigation purposes while providing superior spatio-temporal coverage over in situ methods. The authors envision that PrISMM can be implemented in water usage management by relating VSWC with weather forecasts and evapotranspiration rates to develop time-based spatially distributed irrigation management plans.<\/jats:p>","DOI":"10.3390\/rs16101660","type":"journal-article","created":{"date-parts":[[2024,5,8]],"date-time":"2024-05-08T09:58:56Z","timestamp":1715162336000},"page":"1660","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":9,"title":["Precision Irrigation Soil Moisture Mapper: A Thermal Inertia Approach to Estimating Volumetric Soil Water Content Using Unmanned Aerial Vehicles and Multispectral Imagery"],"prefix":"10.3390","volume":"16","author":[{"given":"Kevin J.","family":"Wienhold","sequence":"first","affiliation":[{"name":"Department of Civil Engineering, The University of Texas at Arlington, Arlington, TX 76010, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6032-1805","authenticated-orcid":false,"given":"Dongfeng","family":"Li","sequence":"additional","affiliation":[{"name":"Department of Civil Engineering, The University of Texas at Arlington, Arlington, TX 76010, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9871-8405","authenticated-orcid":false,"given":"Zheng N.","family":"Fang","sequence":"additional","affiliation":[{"name":"Department of Civil Engineering, The University of Texas at Arlington, Arlington, TX 76010, USA"}]}],"member":"1968","published-online":{"date-parts":[[2024,5,8]]},"reference":[{"key":"ref_1","unstructured":"United Nations (2014). Department of Economic and Social Affairs, Population Division, United Nations."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"6312","DOI":"10.1073\/pnas.1011615108","article-title":"Urban Growth, Climate Change, and Freshwater Availability","volume":"108","author":"McDonald","year":"2011","journal-title":"Proc. Natl. Acad. Sci. USA"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"4667","DOI":"10.1038\/s41467-021-25026-3","article-title":"Future Global Urban Water Scarcity and Potential Solutions","volume":"12","author":"He","year":"2021","journal-title":"Nat. Commun."},{"key":"ref_4","unstructured":"Texas Water Development Board (2024, April 01). 2017 Sate Water Plan, Water for Texas, Available online: https:\/\/www.twdb.texas.gov\/waterplanning\/swp\/2017\/doc\/SWP17-Water-for-Texas.pdf."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"14","DOI":"10.21423\/twj.v4i2.6992","article-title":"An Evaluation of Urban Landscape Water Use in Texas","volume":"4","author":"Cabrera","year":"2013","journal-title":"Tex. Water J."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"32","DOI":"10.1016\/j.jhydrol.2007.06.032","article-title":"Evaluation of a Low-Cost Soil Water Content Sensor for Wireless Network Applications","volume":"344","author":"Bogena","year":"2007","journal-title":"J. Hydrol."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"2081","DOI":"10.21273\/HORTSCI.43.7.2081","article-title":"Efficient Water Use in Residential Urban Landscapes","volume":"43","author":"Hilaire","year":"2008","journal-title":"HortScience"},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"4961","DOI":"10.3390\/rs5104961","article-title":"Comparison between SAR Soil Moisture Estimates and Hydrological Model Simulations over the Scrivia Test Site","volume":"5","author":"Santi","year":"2013","journal-title":"Remote Sens."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"166","DOI":"10.1016\/j.rse.2015.01.013","article-title":"An Assessment of Remotely-Sensed Surface and Root Zone Soil Moisture through Active and Passive Sensors in Northeast Asia","volume":"160","author":"Cho","year":"2015","journal-title":"Remote Sens. Environ."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"3095","DOI":"10.1109\/TGRS.2014.2368831","article-title":"Estimation of Hydraulic Properties of a Sandy Soil Using Ground-Based Active and Passive Microwave Remote Sensing","volume":"53","author":"Jonard","year":"2015","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"3262","DOI":"10.3390\/s150203262","article-title":"Estimation of Soil Moisture Content from the Spectral Reflectance of Bare Soils in the 0.4\u20132.5 \u039cm Domain","volume":"15","author":"Fabre","year":"2015","journal-title":"Sensors"},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"76","DOI":"10.1016\/j.jhydrol.2013.11.061","article-title":"On the Spatio-Temporal Dynamics of Soil Moisture at the Field Scale","volume":"516","author":"Vereecken","year":"2014","journal-title":"J. Hydrol."},{"key":"ref_13","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_14","unstructured":"Ulaby, F.T., Moore, R.K., and Fung, A.K. (1986). Microwave Remote Sensing: Active and Passive, from Theory to Applications: 3, Artech House."},{"key":"ref_15","doi-asserted-by":"crossref","unstructured":"Sorooshian, S., Gupta, H.V., and Rodda, J.C. (1997). The Land Surface Processes in Hydrology, Springer.","DOI":"10.1007\/978-3-642-60567-3"},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"614","DOI":"10.1016\/j.rse.2014.07.013","article-title":"Global-Scale Comparison of Passive (SMOS) and Active (ASCAT) Satellite Based Microwave Soil Moisture Retrievals with Soil Moisture Simulations (MERRA-Land)","volume":"152","author":"Wigneron","year":"2014","journal-title":"Remote Sens. Environ."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"173","DOI":"10.1016\/S0034-4257(00)00198-X","article-title":"Modeling Soil Moisture\u2013Reflectance","volume":"76","author":"Muller","year":"2001","journal-title":"Remote Sens. Environ."},{"key":"ref_18","unstructured":"Zeng, Y., Feng, Z., and Xiang, N. (2004, January 20\u201324). Assessment of Soil Moisture Using Landsat ETM+ Temperature\/Vegetation Index in Semiarid Environment. Proceedings of the IGARSS 2004. In Proceedings of the 2004 IEEE International Geoscience and Remote Sensing Symposium, Anchorage, AK, USA."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"45","DOI":"10.1016\/0002-1571(81)90032-7","article-title":"Normalizing the Stress-Degree-Day Parameter for Environmental Variability","volume":"24","author":"Idso","year":"1981","journal-title":"Agric. Meteorol."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"655","DOI":"10.1175\/1520-0477(1995)076<0655:DOTLIT>2.0.CO;2","article-title":"Droughts of the Late 1980s in the United States as Derived from NOAA Polar-Orbiting Satellite Data","volume":"76","author":"Kogan","year":"1995","journal-title":"Bull. Am. Meteorol. Soc."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"69","DOI":"10.1016\/S0378-3774(00)00096-2","article-title":"Use of Crop Water Stress Index for Monitoring Water Status and Scheduling Irrigation in Wheat","volume":"47","author":"Alderfasi","year":"2001","journal-title":"Agric. Water Manag."},{"key":"ref_22","first-page":"144","article-title":"Deriving Moisture Availability from Time Series Remote Sensing for Ecohydrological Applications: Development of a Prototype near Real-Time Operational System","volume":"37","author":"McVicar","year":"2007","journal-title":"CSIRO Land Water Sci. Rep."},{"key":"ref_23","first-page":"147","article-title":"Thermal Inertia Mapping from Satellite\u2014Discrimination of Geologic Units in Oman","volume":"2","author":"Pohn","year":"1974","journal-title":"J. Res. U.S. Geol. Surv."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"26","DOI":"10.1029\/GL003i001p00026","article-title":"Thermal Inertia Imaging: A New Geologic Mapping Tool","volume":"3","author":"Kahle","year":"1976","journal-title":"Geophys. Res. Lett."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"2582","DOI":"10.1029\/JC082i018p02582","article-title":"Thermal Inertia Mapping: A New View of the Earth","volume":"82","author":"Price","year":"1977","journal-title":"J. Geophys. Res."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"67","DOI":"10.1175\/1520-0450(1981)020<0067:SEOTSE>2.0.CO;2","article-title":"Satellite Estimation of the Surface Energy Balance, Moisture Availability and Thermal Inertia","volume":"20","author":"Carlson","year":"1981","journal-title":"J. Appl. Meteorol. Climatol."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"1681","DOI":"10.1190\/1.1441317","article-title":"Regional Thermal-inertia Mapping from an Experimental Satellite","volume":"47","author":"Watson","year":"1982","journal-title":"Geophysics"},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"229","DOI":"10.1016\/j.jhydrol.2009.09.055","article-title":"High Resolution Remote Estimation of Soil Surface Water Content by a Thermal Inertia Approach","volume":"379","author":"Minacapilli","year":"2009","journal-title":"J. Hydrol."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"1144","DOI":"10.1080\/02626667.2013.802322","article-title":"Critical Analysis of Thermal Inertia Approaches for Surface Soil Water Content Retrieval","volume":"58","author":"Maltese","year":"2013","journal-title":"Hydrol. Sci. J."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"197","DOI":"10.1080\/02757258609532069","article-title":"Regional-scale Estimates of Surface Moisture Availability and Thermal Inertia Using Remote Thermal Measurements","volume":"1","author":"Carlson","year":"1986","journal-title":"Remote Sens. Rev."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"1673","DOI":"10.1029\/JB082i011p01673","article-title":"A Simple Thermal Model of the Earths Surface for Geologic Mapping by Remote Sensing","volume":"82","author":"Kahle","year":"1977","journal-title":"J. Geophys. Res."},{"key":"ref_32","doi-asserted-by":"crossref","unstructured":"Ghilain, N., Arboleda, A., Batelaan, O., Ard\u00f6, J., Trigo, I., Barrios, J.-M., and Gellens-Meulenberghs, F. (2019). A New Retrieval Algorithm for Soil Moisture Index from Thermal Infrared Sensor On-Board Geostationary Satellites over Europe and Africa and Its Validation. Remote Sens., 11.","DOI":"10.3390\/rs11171968"},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"1119","DOI":"10.1080\/01431169308904400","article-title":"On the Relationship between Thermal Emissivity and the Normalized Difference Vegetation Index for Natural Surfaces","volume":"14","author":"Owe","year":"1993","journal-title":"Int. J. Remote Sens."},{"key":"ref_34","first-page":"1","article-title":"Spatial distribution and structure of remotely sensed surface water content estimated by a thermal inertia approach","volume":"Volume 316","author":"Owe","year":"2007","journal-title":"Remote Sensing for Environmental Monitoring and Change Detection"},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"3729","DOI":"10.3390\/rs5083729","article-title":"Remote Sensing of Soil Moisture in Vineyards Using Airborne and Ground-Based Thermal Inertia Data","volume":"5","author":"Soliman","year":"2013","journal-title":"Remote Sens."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"04016025","DOI":"10.1061\/(ASCE)SU.1943-5428.0000206","article-title":"Accuracy of Digital Surface Models and Orthophotos Derived from Unmanned Aerial Vehicle Photogrammetry","volume":"143","year":"2017","journal-title":"J. Surv. Eng."},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"15852","DOI":"10.1016\/j.ifacol.2020.12.240","article-title":"Soil Moisture Retrieval from Airborne Multispectral and Infrared Images Using Convolutional Neural Network","volume":"53","author":"Seo","year":"2020","journal-title":"IFAC-PapersOnLine"},{"key":"ref_38","unstructured":"Zhuang, R., Manfreda, S., Zeng, Y., Su, Z., Ben Dor, E., and Petropoulos, G.P. (2023). Unmanned Aerial Systems for Monitoring Soil, Vegetation, and Riverine Environments, Elsevier."},{"key":"ref_39","unstructured":"(2007). Standard Test Method for Density and Unit Weight of Soil in Place by Sand-Cone Method (Standard No. ASTM DD1556\/D1556M-15). Available online: https:\/\/webstore.ansi.org\/standards\/astm\/astmd1556d1556m15."},{"key":"ref_40","doi-asserted-by":"crossref","unstructured":"Klute, A., Gee, G.W., and Bauder, J.W. (1986). SSSA Book Series: Methods of Soil Analysis: Part 1\u2014Physical and Mineralogical Methods, ASA.","DOI":"10.2136\/sssabookser5.1.2ed"},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"112315","DOI":"10.1016\/j.rse.2021.112315","article-title":"Information Depth of NIR\/SWIR Soil Reflectance Spectroscopy","volume":"256","author":"Norouzi","year":"2021","journal-title":"Remote Sens. Environ."},{"key":"ref_42","unstructured":"(2014). Standard Test Method for Sand Equivalent Value of Soils and Fine Aggregate (Standard No. ASTM D2419-14). Available online: https:\/\/webstore.ansi.org\/standards\/astm\/astmd241914."},{"key":"ref_43","unstructured":"(2019). Standard Test Methods for Laboratory Determination of Water (Moisture) Content of Soil and Rock by Mass (Standard No. ASTM D2216-19). Available online: https:\/\/www.astm.org\/d2216-19.html."},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"811","DOI":"10.1175\/1520-0450(1976)015<0811:CFEVIT>2.0.CO;2","article-title":"Compensating for Environmental Variability in the Thermal Inertia Approach to Remote Sensing of Soil Moisture","volume":"15","author":"Idso","year":"1976","journal-title":"J. Appl. Meteorol."},{"key":"ref_45","unstructured":"Menenti, M. (1984). Physical Aspects and Determination of Evaporation in Deserts Applying Remote Sensing Techniques, EV."},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"87","DOI":"10.1016\/S0022-1694(99)00202-4","article-title":"SEBAL-Based Sensible and Latent Heat Fluxes in the Irrigated Gediz Basin, Turkey","volume":"229","author":"Bastiaanssen","year":"2000","journal-title":"J. Hydrol."},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"380","DOI":"10.1061\/(ASCE)0733-9437(2007)133:4(380)","article-title":"Satellite-Based Energy Balance for Mapping Evapotranspiration with Internalized Calibration (METRIC)\u2014Model","volume":"133","author":"Allen","year":"2007","journal-title":"J. Irrig. Drain. Eng."},{"key":"ref_48","doi-asserted-by":"crossref","first-page":"3776","DOI":"10.3390\/rs5083776","article-title":"Application of Landsat to Evaluate Effects of Irrigation Forbearance","volume":"5","author":"Cuenca","year":"2013","journal-title":"Remote Sens."},{"key":"ref_49","doi-asserted-by":"crossref","first-page":"273","DOI":"10.1061\/(ASCE)0733-9437(2008)134:3(273)","article-title":"Application of SEBAL Model for Mapping Evapotranspiration and Estimating Surface Energy Fluxes in South-Central Nebraska","volume":"134","author":"Singh","year":"2008","journal-title":"J. Irrig. Drain. Eng."},{"key":"ref_50","doi-asserted-by":"crossref","first-page":"851","DOI":"10.1175\/1520-0450(2003)042<0851:DCISHF>2.0.CO;2","article-title":"Diurnal Covariation in Soil Heat Flux and Net Radiation","volume":"42","author":"Santanello","year":"2003","journal-title":"J. Appl. Meteorol."},{"key":"ref_51","doi-asserted-by":"crossref","first-page":"697","DOI":"10.5194\/hess-20-697-2016","article-title":"Estimating Evaporation with Thermal UAV Data and Two-Source Energy Balance Models","volume":"20","author":"Hoffmann","year":"2016","journal-title":"Hydrol. Earth Syst. Sci."},{"key":"ref_52","doi-asserted-by":"crossref","first-page":"795","DOI":"10.1016\/j.pce.2004.05.007","article-title":"Spatiotemporal Dynamics of Land Surface Parameters in the Red River of the North Basin","volume":"29","author":"Melesse","year":"2004","journal-title":"Phys. Chem. Earth Parts A\/B\/C"},{"key":"ref_53","doi-asserted-by":"crossref","unstructured":"Liang, S. (2004). Quantitative Remote Sensing of Land Surfaces, Wiley-Interscience.","DOI":"10.1002\/047172372X"},{"key":"ref_54","doi-asserted-by":"crossref","unstructured":"Campbell, G.S., and Norman, J.M. (1998). Introduction to Environmental Biophysics, Springer.","DOI":"10.1007\/978-1-4612-1626-1"},{"key":"ref_55","doi-asserted-by":"crossref","first-page":"742","DOI":"10.1029\/WR011i005p00742","article-title":"On a Derivable Formula for Long-wave Radiation from Clear Skies","volume":"11","author":"Brutsaert","year":"1975","journal-title":"Water Resour. Res."},{"key":"ref_56","unstructured":"Chow, V.T., Maidment, D.R., and Mays, L.W. (2013). Applied Hydrology, McGraw-Hill Professional."},{"key":"ref_57","unstructured":"Carslaw, H.S., and Jaeger, J.C. (1959). Conduction of Heat in Solids, Oxford University Press."},{"key":"ref_58","unstructured":"Vries, D.A. (1963). Physics of Plant Environment, US Army Corps of Engineers, Cold Regions Research and Engineering Laboratory."},{"key":"ref_59","unstructured":"Johansen, O. (1975). Thermal Conductivity of Soils. [Ph.D. Thesis, Norwegian University of Science and Technology]."},{"key":"ref_60","doi-asserted-by":"crossref","first-page":"8","DOI":"10.2136\/sssaj2006.0041","article-title":"An Improved Model for Predicting Soil Thermal Conductivity from Water Content at Room Temperature","volume":"71","author":"Lu","year":"2007","journal-title":"Soil Sci. Soc. Am. J."},{"key":"ref_61","doi-asserted-by":"crossref","unstructured":"Frodella, W., Lazzeri, G., Moretti, S., Keizer, J., and Verheijen, F.G.A. (2020). Applying Infrared Thermography to Soil Surface Temperature Monitoring: Case Study of a High-Resolution 48 h Survey in a Vineyard (Anadia, Portugal). Sensors, 20.","DOI":"10.3390\/s20092444"},{"key":"ref_62","doi-asserted-by":"crossref","first-page":"449","DOI":"10.1175\/1520-0450(1998)037<0449:SSEFAR>2.0.CO;2","article-title":"Simulating Surface Energy Fluxes and Radiometric Surface Temperatures for Two Arid Vegetation Communities Using the SHAW Model","volume":"37","author":"Flerchinger","year":"1998","journal-title":"J. Appl. Meteorol. Climatol."},{"key":"ref_63","unstructured":"Murphy, J.A. (2002). Best Management Practices for Irrigating Golf Course Turf, Rutgers Cooperative Extension, Rutgers NJAES Cooperative Extension."},{"key":"ref_64","doi-asserted-by":"crossref","unstructured":"Ge, X., Ding, J., Jin, X., Wang, J., Chen, X., Li, X., Liu, J., and Xie, B. (2021). Estimating Agricultural Soil Moisture Content through UAV-Based Hyperspectral Images in the Arid Region. Remote Sens., 13.","DOI":"10.3390\/rs13081562"},{"key":"ref_65","doi-asserted-by":"crossref","first-page":"107262","DOI":"10.1016\/j.compag.2022.107262","article-title":"UAV-Based Multispectral and Thermal Cameras to Predict Soil Water Content\u2014A Machine Learning Approach","volume":"200","author":"Bertalan","year":"2022","journal-title":"Comput. Electron. Agric."},{"key":"ref_66","doi-asserted-by":"crossref","first-page":"2739","DOI":"10.5194\/hess-25-2739-2021","article-title":"Advances in Soil Moisture Retrieval from Multispectral Remote Sensing Using Unoccupied Aircraft Systems and Machine Learning Techniques","volume":"25","author":"Araya","year":"2021","journal-title":"Hydrol. Earth Syst. Sci."},{"key":"ref_67","doi-asserted-by":"crossref","first-page":"2020JD033661","DOI":"10.1029\/2020JD033661","article-title":"A Soil Moisture-Dependent Model to Simulate Water Table Depth and Proportions of Surface and Subsurface Runoff and Its Validation at the Basin Scale","volume":"126","author":"Lv","year":"2021","journal-title":"JGR Atmos."}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/16\/10\/1660\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T14:41:39Z","timestamp":1760107299000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/16\/10\/1660"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,5,8]]},"references-count":67,"journal-issue":{"issue":"10","published-online":{"date-parts":[[2024,5]]}},"alternative-id":["rs16101660"],"URL":"https:\/\/doi.org\/10.3390\/rs16101660","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,5,8]]}}}