{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,21]],"date-time":"2026-07-21T14:32:07Z","timestamp":1784644327164,"version":"3.55.0"},"reference-count":63,"publisher":"MDPI AG","issue":"8","license":[{"start":{"date-parts":[[2018,8,15]],"date-time":"2018-08-15T00:00:00Z","timestamp":1534291200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100008798","name":"Ministry of Science Research and Technology","doi-asserted-by":"publisher","award":["1"],"award-info":[{"award-number":["1"]}],"id":[{"id":"10.13039\/501100008798","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>This paper presents an approach for retrieval of soil moisture content (SMC) by coupling single polarization C-band synthetic aperture radar (SAR) and optical data at the plot scale in vegetated areas. The study was carried out at five different sites with dominant vegetation cover located in Kenya. In the initial stage of the process, different features are extracted from single polarization mode (VV polarization) SAR and optical data. Subsequently, proper selection of the relevant features is conducted on the extracted features. An advanced state-of-the-art machine learning regression approach, the support vector regression (SVR) technique, is used to retrieve soil moisture. This paper takes a new look at soil moisture retrieval in vegetated areas considering the needs of practical applications. In this context, we tried to work at the object level instead of the pixel level. Accordingly, a group of pixels (an image object) represents the reality of the land cover at the plot scale. Three approaches, a pixel-based approach, an object-based approach, and a combination of pixel- and object-based approaches, were used to estimate soil moisture. The results show that the combined approach outperforms the other approaches in terms of estimation accuracy (4.94% and 0.89 compared to 6.41% and 0.62 in terms of root mean square error (RMSE) and R2), flexibility on retrieving the level of soil moisture, and better quality of visual representation of the SMC map.<\/jats:p>","DOI":"10.3390\/rs10081285","type":"journal-article","created":{"date-parts":[[2018,8,15]],"date-time":"2018-08-15T10:40:07Z","timestamp":1534329607000},"page":"1285","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":95,"title":["Synergetic Use of Sentinel-1 and Sentinel-2 Data for Soil Moisture Mapping at Plot Scale"],"prefix":"10.3390","volume":"10","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-9573-9531","authenticated-orcid":false,"given":"Reza","family":"Attarzadeh","sequence":"first","affiliation":[{"name":"School of Surveying and Geospatial Engineering, College of Engineering, University of Tehran, Tehran 1439957131, Iran"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jalal","family":"Amini","sequence":"additional","affiliation":[{"name":"School of Surveying and Geospatial Engineering, College of Engineering, University of Tehran, Tehran 1439957131, Iran"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1968-0125","authenticated-orcid":false,"given":"Claudia","family":"Notarnicola","sequence":"additional","affiliation":[{"name":"Institute for Earth Observation, Eurac Research, 39100 Bolzano-Bozen, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0756-9024","authenticated-orcid":false,"given":"Felix","family":"Greifeneder","sequence":"additional","affiliation":[{"name":"Institute for Earth Observation, Eurac Research, 39100 Bolzano-Bozen, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2018,8,15]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"460","DOI":"10.1016\/j.jhydrol.2012.10.044","article-title":"Advances in soil moisture retrieval from synthetic aperture radar and hydrological applications","volume":"476","author":"Kornelsen","year":"2013","journal-title":"J. Hydrol."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"977","DOI":"10.1029\/RS015i005p00977","article-title":"The dielectric properties of soil-water mixtures at microwave frequencies","volume":"15","author":"Wang","year":"1980","journal-title":"Radio Sci."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"666","DOI":"10.1109\/JPROC.2010.2043032","article-title":"The SMOS Mission: New Tool for Monitoring Key Elements ofthe Global Water Cycle","volume":"98","author":"Kerr","year":"2010","journal-title":"Proc. IEEE"},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"1354","DOI":"10.1109\/TGRS.2012.2187666","article-title":"ESA\u2019s Soil Moisture and Ocean Salinity Mission: Mission Performance and Operations","volume":"50","author":"Mecklenburg","year":"2012","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_5","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_6","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_7","unstructured":"Entekhabi, D., Yueh, S., O\u2019Neill, P., Kellogg, K., Allen, A., Bindlish, R., Brown, M., Chan, S., Colliander, A., and Crow, T.W. (2014). SMAP Handbook, Jet Propulsion Laboratory. JPL Publication JPL 400-1567."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"191","DOI":"10.1016\/S0034-4257(99)00036-X","article-title":"A Method for Estimating Soil Moisture from ERS Scatterometer and Soil Data","volume":"70","author":"Wagner","year":"1999","journal-title":"Remote Sens. Environ."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"L20401","DOI":"10.1029\/2007GL031088","article-title":"Initial soil moisture retrievals from the METOP-A Advanced Scatterometer (ASCAT)","volume":"34","author":"Bartalis","year":"2007","journal-title":"Geophys. Res. Lett."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"117","DOI":"10.1109\/JSTARS.2010.2076336","article-title":"Soil Moisture Retrieval from AMSR-E Data in Xinjiang (China): Models and Validation","volume":"4","author":"Zhang","year":"2011","journal-title":"IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"9","DOI":"10.1002\/hyp.6609","article-title":"Operational performance of current synthetic aperture radar sensors in mapping soil surface characteristics in agricultural environments: Application to hydrological and erosion modelling","volume":"22","author":"Baghdadi","year":"2008","journal-title":"Hydrol. Process."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"2647","DOI":"10.1109\/TGRS.2002.806994","article-title":"Soil moisture estimation from ERS\/SAR data: Toward an operational methodology","volume":"40","author":"Zribi","year":"2002","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"439","DOI":"10.1109\/JSTARS.2010.2052916","article-title":"Dense Temporal Series of C- and L-band SAR Data for Soil Moisture Retrieval Over Agricultural Crops","volume":"4","author":"Balenzano","year":"2011","journal-title":"IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"128","DOI":"10.1109\/JSTARS.2011.2116769","article-title":"Mapping Soil Moisture Using RADARSAT-2 Data and Local Autocorrelation Statistics","volume":"4","author":"Merzouki","year":"2011","journal-title":"IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"42","DOI":"10.1016\/S0034-4257(02)00069-X","article-title":"A new empirical model to retrieve soil moisture and roughness from C-band radar data","volume":"84","author":"Zribi","year":"2003","journal-title":"Remote Sens. Environ."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"689","DOI":"10.1163\/156939302X01119","article-title":"An Improved Iem Model for Bistatic Scattering from Rough Surfaces","volume":"16","author":"Fung","year":"2002","journal-title":"J. Electromagn. Waves Appl."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"357","DOI":"10.1029\/RS013i002p00357","article-title":"Vegetation modeled as a water cloud","volume":"13","author":"Attema","year":"1978","journal-title":"Radio Sci."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"1348","DOI":"10.1109\/TGRS.2002.800232","article-title":"Semi-empirical model of the ensemble-averaged differential Mueller matrix for microwave backscattering from bare soil surfaces","volume":"40","author":"Oh","year":"2002","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"596","DOI":"10.1109\/TGRS.2003.821065","article-title":"Quantitative Retrieval of Soil Moisture Content and Surface Roughness from Multipolarized Radar Observations of Bare Soil Surfaces","volume":"42","author":"Oh","year":"2004","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"915","DOI":"10.1109\/36.406677","article-title":"Corrections to \u2018Measuring Soil Moisture with Imaging Radars\u2019","volume":"33","author":"Dubois","year":"1995","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"356","DOI":"10.1109\/36.134085","article-title":"Backscattering from a Randomly Rough Dielectric Surface","volume":"30","author":"Fung","year":"1992","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"256","DOI":"10.1016\/S0034-4257(96)00158-7","article-title":"Backscattering behavior and simulation comparison over bare soils using SIR-C\/X-SAR and ERASME 1994 data over Orgeval","volume":"59","author":"Zribi","year":"1997","journal-title":"Remote Sens. Environ."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"805","DOI":"10.1080\/01431160500212278","article-title":"Calibration of the Integral Equation Model for SAR data in C-band and HH and VV polarizations","volume":"27","author":"Baghdadi","year":"2006","journal-title":"Int. J. Remote Sens."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"3831","DOI":"10.1080\/01431160600658123","article-title":"Evaluation of radar backscatter models IEM, OH and Dubois using experimental observations","volume":"27","author":"Baghdadi","year":"2006","journal-title":"Int. J. Remote Sens."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"2575","DOI":"10.1080\/0143116031000072948","article-title":"Estimation of the moisture content of bare soil from RADARSAT-1 SAR using simple empirical models","volume":"24","author":"Sahebi","year":"2003","journal-title":"Int. J. Remote Sens."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"370","DOI":"10.1109\/36.134086","article-title":"An empirical model and an inversion technique for radar scattering from bare soil surfaces","volume":"30","author":"Oh","year":"1992","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_27","first-page":"3479","article-title":"Soil moisture retrieval through a merging of multi-temporal L-band SAR data and hydrologic modelling","volume":"5","author":"Mattia","year":"2008","journal-title":"Hydrol. Earth Syst. Sci. Discuss."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"196","DOI":"10.1109\/JSTARS.2011.2169236","article-title":"A fusion approach to retrieve soil moisture with SAR and optical data","volume":"5","author":"Prakash","year":"2012","journal-title":"IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"1229","DOI":"10.1109\/JSTARS.2015.2464698","article-title":"Coupling SAR C-Band and Optical Data for Soil Moisture and Leaf Area Index Retrieval over Irrigated Grasslands","volume":"9","author":"Baghdadi","year":"2016","journal-title":"IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens."},{"key":"ref_30","doi-asserted-by":"crossref","unstructured":"Gao, Q., Zribi, M., Escorihuela, M.J., and Baghdadi, N. (2017). Synergetic use of sentinel-1 and sentinel-2 data for soil moisture mapping at 100 m resolution. Sensors, 17.","DOI":"10.3390\/s17091966"},{"key":"ref_31","doi-asserted-by":"crossref","unstructured":"El Hajj, M., Baghdadi, N., Zribi, M., and Bazzi, H. (2017). Synergic use of Sentinel-1 and Sentinel-2 images for operational soil moisture mapping at high spatial resolution over agricultural areas. Remote Sens., 9.","DOI":"10.3390\/rs9121292"},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"117","DOI":"10.1016\/j.rse.2017.01.015","article-title":"Merging active and passive microwave observations in soil moisture data assimilation","volume":"191","author":"Kolassa","year":"2017","journal-title":"Remote Sens. Environ."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"202","DOI":"10.1016\/j.rse.2017.04.020","article-title":"Soil moisture retrieval from AMSR-E and ASCAT microwave observation synergy. Part 2: Product evaluation","volume":"195","author":"Kolassa","year":"2017","journal-title":"Remote Sens. Environ."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"736","DOI":"10.1109\/TGRS.2007.915403","article-title":"The NAFE\u201905\/CoSMOS Data Set: Toward SMOS Soil Moisture Retrieval, Downscaling, and Assimilation","volume":"46","author":"Panciera","year":"2008","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"3935","DOI":"10.1016\/j.rse.2008.06.012","article-title":"Towards deterministic downscaling of SMOS soil moisture using MODIS derived soil evaporative efficiency","volume":"112","author":"Merlin","year":"2008","journal-title":"Remote Sens. Environ."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"3156","DOI":"10.1109\/TGRS.2011.2120615","article-title":"Downscaling SMOS-Derived Soil Moisture Using MODIS Visible\/Infrared Data","volume":"49","author":"Piles","year":"2011","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"558","DOI":"10.1109\/TGRS.2015.2462074","article-title":"Spatial Downscaling of Satellite Soil Moisture Data Using a Vegetation Temperature Condition Index","volume":"54","author":"Peng","year":"2016","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_38","unstructured":"(2018, January 02). NASA Focused on Sentinel as Replacement for SMAP Radar. Available online: http:\/\/spacenews.com\/nasa-focused-on-sentinel-as-replacement-for-smap-radar\/."},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"2107","DOI":"10.1109\/LGRS.2017.2753203","article-title":"Spatial Downscaling of SMAP Soil Moisture Using MODIS Land Surface Temperature and NDVI During SMAPVEX15","volume":"14","author":"Colliander","year":"2017","journal-title":"IEEE Geosci. Remote Sens. Lett."},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"85","DOI":"10.1109\/TGRS.2014.2318699","article-title":"Downscaling Satellite-Based Soil Moisture in Heterogeneous Regions Using High-Resolution Remote Sensing Products and Information Theory: A Synthetic Study","volume":"53","author":"Chakrabarti","year":"2015","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"2663","DOI":"10.1109\/JSTARS.2017.2690220","article-title":"A Method for Upscaling In Situ Soil Moisture Measurements to Satellite Footprint Scale Using Random Forests","volume":"10","author":"Clewley","year":"2017","journal-title":"IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens."},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"1813","DOI":"10.1109\/JSTARS.2017.2649219","article-title":"Characterization of the Spatial Variability of In-Situ Soil Moisture Measurements for Upscaling at the Spatial Resolution of RADARSAT-2","volume":"10","author":"Gherboudj","year":"2017","journal-title":"IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens."},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"900","DOI":"10.1109\/JSTARS.2012.2220124","article-title":"Gonzalez-sosa Toward an Operational Bare Soil Moisture Mapping Using TerraSAR-X Data Acquired Over Agricultural Areas","volume":"6","author":"Aubert","year":"2013","journal-title":"IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens."},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"234","DOI":"10.1016\/j.rse.2013.02.027","article-title":"Soil moisture mapping using Sentinel-1 images: Algorithm and preliminary validation","volume":"134","author":"Paloscia","year":"2013","journal-title":"Remote Sens. Environ."},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"262","DOI":"10.1109\/JSTARS.2014.2378795","article-title":"Estimation of soil moisture in mountain areas using SVR technique applied to multiscale active radar images at C-band","volume":"8","author":"Pasolli","year":"2015","journal-title":"IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens."},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"359","DOI":"10.1111\/j.1467-7679.1992.tb00020.x","article-title":"Environment, Population Growth and Productivity in Kenya: A Case Study of Machakos District","volume":"10","author":"Tiffen","year":"1992","journal-title":"Dev. Policy Rev."},{"key":"ref_47","unstructured":"(2018, June 25). Kenya. Sustainable Development Knowledge Platform. Available online: https:\/\/sustainabledevelopment.un.org\/memberstates\/kenya."},{"key":"ref_48","doi-asserted-by":"crossref","unstructured":"El Hajj, M., Baghdadi, N., Zribi, M., and Angelliaume, S. (2016). Analysis of Sentinel-1 Radiometric Stability and Quality for Land Surface Applications. Remote Sens., 8.","DOI":"10.3390\/rs8050406"},{"key":"ref_49","unstructured":"Louis, J., Debaecker, V., Pflug, B., Main-Knorn, M., Bieniarz, J., Mueller-Wilm, U., Cadau, E., and Gascon, F. (2016). Sentinel-2 SEN2COR: L2A Processor for Users, European Space Agency. (Special Publication) ESA SP-740."},{"key":"ref_50","doi-asserted-by":"crossref","first-page":"610","DOI":"10.1109\/TSMC.1973.4309314","article-title":"Textural Features for Image Classification","volume":"SMC-3","author":"Haralick","year":"1973","journal-title":"IEEE Trans. Syst. Man. Cybern."},{"key":"ref_51","doi-asserted-by":"crossref","first-page":"1170","DOI":"10.1109\/36.469481","article-title":"Evaluation of textural and multipolarization radar features for crop classification","volume":"33","author":"Anys","year":"1995","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_52","doi-asserted-by":"crossref","first-page":"780","DOI":"10.1109\/36.752194","article-title":"Texture analysis of SAR sea ice imagery using gray level co-occurrence matrices","volume":"37","author":"Soh","year":"1999","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_53","doi-asserted-by":"crossref","first-page":"970","DOI":"10.1109\/JSTARS.2012.2195713","article-title":"Decision Fusion of Textural Features Derived From Polarimetric Data for Levee Assessment","volume":"5","author":"Cui","year":"2012","journal-title":"IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens."},{"key":"ref_54","unstructured":"STEP (2018, February 24). Documentation. Available online: http:\/\/step.esa.int\/main\/doc\/."},{"key":"ref_55","unstructured":"Arbib, M.A. (1998). The Handbook of Brain Theory and Neural Networks, MIT Press."},{"key":"ref_56","doi-asserted-by":"crossref","first-page":"389","DOI":"10.1023\/A:1012487302797","article-title":"Gene Selection for Cancer Classification using Support Vector Machines","volume":"46","author":"Guyon","year":"2002","journal-title":"Mach. Learn."},{"key":"ref_57","doi-asserted-by":"crossref","first-page":"3669","DOI":"10.1080\/01431160802609718","article-title":"Feature selection for hyperspectral data based on recursive support vector machines","volume":"30","author":"Zhang","year":"2009","journal-title":"Int. J. Remote Sens."},{"key":"ref_58","unstructured":"Baatz, M., Benz, U., Dehghani, S., Heynen, M., Holtje, A., Hofmann, P., Lingenfelder, I., Mimler, M., Sohlbach, M., and Weber, M. (2004). eCognition Professional: User Guide 4, Definiens Imaging GmbH."},{"key":"ref_59","doi-asserted-by":"crossref","first-page":"239","DOI":"10.1016\/j.isprsjprs.2003.10.002","article-title":"Multi-resolution, object-oriented fuzzy analysis of remote sensing data for GIS-ready information","volume":"58","author":"Benz","year":"2004","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_60","unstructured":"Nussbaum, S., and Menz, G. (2008). Object-Based Image Analysis and Treaty Verification: New Approaches in Remote Sensing\u2014Applied to Nuclear Facilities in Iran, Springer."},{"key":"ref_61","doi-asserted-by":"crossref","first-page":"1080","DOI":"10.1109\/LGRS.2011.2156759","article-title":"Estimating soil moisture with the support vector regression technique","volume":"8","author":"Pasolli","year":"2011","journal-title":"IEEE Geosci. Remote Sens. Lett."},{"key":"ref_62","doi-asserted-by":"crossref","first-page":"159","DOI":"10.1109\/TGRS.2004.839818","article-title":"Robust multiple estimator systems for the analysis of biophysical parameters from remotely sensed data","volume":"43","author":"Bruzzone","year":"2005","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_63","doi-asserted-by":"crossref","unstructured":"Vapnik, V.N. (2000). The Nature of Statistical Learning Theory, Springer.","DOI":"10.1007\/978-1-4757-3264-1"}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/10\/8\/1285\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T15:18:50Z","timestamp":1760195930000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/10\/8\/1285"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2018,8,15]]},"references-count":63,"journal-issue":{"issue":"8","published-online":{"date-parts":[[2018,8]]}},"alternative-id":["rs10081285"],"URL":"https:\/\/doi.org\/10.3390\/rs10081285","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2018,8,15]]}}}