{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,8]],"date-time":"2026-03-08T18:13:28Z","timestamp":1772993608182,"version":"3.50.1"},"reference-count":56,"publisher":"MDPI AG","issue":"9","license":[{"start":{"date-parts":[[2020,4,25]],"date-time":"2020-04-25T00:00:00Z","timestamp":1587772800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["41771470;41961059"],"award-info":[{"award-number":["41771470;41961059"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Xinjiang University Excellent Doctoral Innovation Project","award":["XJUBSCX-2016013"],"award-info":[{"award-number":["XJUBSCX-2016013"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>In the earth ecosystem, surface soil moisture is an important factor in the process of energy exchange between land and atmosphere, which has a strong control effect on land surface evapotranspiration, water migration, and carbon cycle. Soil moisture is particularly important in an oasis region because of its fragile ecological environment. Accordingly, a soil moisture retrieval model was conducted based on Dubois model and ratio model. Based on the Dubois model, the in situ soil roughness was used to simulate the backscattering coefficient of bare soil, and the empirical relationship was established with the measured soil moisture. The ratio model was used to eliminate the backscattering contribution of vegetation, in which three vegetation indices were used to characterize vegetation growth. The results were as follows: (1) the Dubois model was used to calibrate the unknown parameters of the ratio model and verified the feasibility of the ratio model to simulate the backscattering coefficient. (2) All three vegetation indices (Normalized Difference Vegetation Index (NDVI), Vegetation Water Content (VWC), and Enhanced Vegetation Index (EVI)) can represent the scattering characteristics of vegetation in an oasis region, but the VWC vegetation index is more suitable than the others. (3) Based on the Dubois model and ratio model, the soil moisture retrieval model was conducted, and the in situ soil moisture was used to analyze the accuracy of the simulated soil moisture, which found that the soil moisture retrieval accuracy is the highest under VWC vegetation index, and the coefficient of determination is 0.76. The results show that the soil moisture retrieval model conducted on the Dubois model and ratio model is feasible.<\/jats:p>","DOI":"10.3390\/rs12091358","type":"journal-article","created":{"date-parts":[[2020,4,28]],"date-time":"2020-04-28T10:30:58Z","timestamp":1588069858000},"page":"1358","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":21,"title":["The Capability of Integrating Optical and Microwave Data for Detecting Soil Moisture in an Oasis Region"],"prefix":"10.3390","volume":"12","author":[{"given":"Shuai","family":"Huang","sequence":"first","affiliation":[{"name":"College of Resources and Environment Sciences, Xinjiang University, Urumqi 830046, China"},{"name":"Key Laboratory of Oasis Ecology under Ministry of Education, Xinjiang University, Urumqi 830046, China"}]},{"given":"Jianli","family":"Ding","sequence":"additional","affiliation":[{"name":"College of Resources and Environment Sciences, Xinjiang University, Urumqi 830046, China"},{"name":"Key Laboratory of Oasis Ecology under Ministry of Education, Xinjiang University, Urumqi 830046, China"}]},{"given":"Bohua","family":"Liu","sequence":"additional","affiliation":[{"name":"College of Resources and Environment Sciences, Xinjiang University, Urumqi 830046, China"},{"name":"Key Laboratory of Oasis Ecology under Ministry of Education, Xinjiang University, Urumqi 830046, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7855-6525","authenticated-orcid":false,"given":"Xiangyu","family":"Ge","sequence":"additional","affiliation":[{"name":"College of Resources and Environment Sciences, Xinjiang University, Urumqi 830046, China"},{"name":"Key Laboratory of Oasis Ecology under Ministry of Education, Xinjiang University, Urumqi 830046, China"}]},{"given":"Jinjie","family":"Wang","sequence":"additional","affiliation":[{"name":"College of Resources and Environment Sciences, Xinjiang University, Urumqi 830046, China"},{"name":"Key Laboratory of Oasis Ecology under Ministry of Education, Xinjiang University, Urumqi 830046, China"}]},{"given":"Jie","family":"Zou","sequence":"additional","affiliation":[{"name":"College of Resources and Environment Sciences, Xinjiang University, Urumqi 830046, China"},{"name":"Key Laboratory of Oasis Ecology under Ministry of Education, Xinjiang University, Urumqi 830046, China"}]},{"given":"Junyong","family":"Zhang","sequence":"additional","affiliation":[{"name":"College of Resources and Environment Sciences, Xinjiang University, Urumqi 830046, China"},{"name":"Key Laboratory of Oasis Ecology under Ministry of Education, Xinjiang University, Urumqi 830046, China"}]}],"member":"1968","published-online":{"date-parts":[[2020,4,25]]},"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","first-page":"97","article-title":"Advances in Study on Microwave Remote Sensing of Soil Moisture","volume":"16","author":"Gao","year":"2001","journal-title":"Remote Sens. Technol. Appl."},{"key":"ref_3","doi-asserted-by":"crossref","unstructured":"Proch\u00e1zka, P., H\u00f6nig, V., Maitah, M., Plju\u010darsk\u00e1, I., and Kleindienst, J. (2018). Evaluation of Water Scarcity in Selected Countries of the Middle East. Water, 10.","DOI":"10.3390\/w10101482"},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"101","DOI":"10.1016\/j.compag.2013.08.029","article-title":"A near-infrared reflectance sensor for soil surface moisture measurement","volume":"99","author":"Zhe","year":"2013","journal-title":"Comput. Electron. Agric."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"301","DOI":"10.1002\/grl.50108","article-title":"Irrigation in California\u2019s Central Valley strengthens the southwestern US water cycle","volume":"40","author":"Lo","year":"2013","journal-title":"Geophys. Res. Lett."},{"key":"ref_6","doi-asserted-by":"crossref","unstructured":"Hong, Z., Zhang, W., Yu, C., Zhang, D., Li, L., and Meng, L. (2018). SWCTI: Surface Water Content Temperature Index for Assessment of Surface Soil Moisture Status. Sensors, 18.","DOI":"10.3390\/s18092875"},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"301","DOI":"10.1007\/s00704-018-2487-4","article-title":"Analysis of trend in temperature and rainfall time series of an Indian arid region: Comparative evaluation of salient techniques","volume":"136","author":"Machiwal","year":"2019","journal-title":"Theor. Appl. Climatol."},{"key":"ref_8","doi-asserted-by":"crossref","unstructured":"Jin, H., Zhu, Q., Zhao, X., and Zhang, Y. (2016). Simulation and Prediction of Climate Variability and Assessment of the Response of Water Resources in a Typical Watershed in China. Water, 8.","DOI":"10.3390\/w8110490"},{"key":"ref_9","doi-asserted-by":"crossref","unstructured":"Sorooshian, S., Li, J., Hsu, K.L., and Gao, X. (2011). How significant is the impact of irrigation on the local hydroclimate in California\u2019s Central Valley? Comparison of model results with ground and remote-sensing data. J. Geophys. Res. Atmos., 116.","DOI":"10.1029\/2010JD014775"},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"2618","DOI":"10.1002\/2016WR020175","article-title":"The Future of Evapotranspiration: Global requirements for ecosystem functioning, carbon and climate feedbacks, agricultural management, and water resources","volume":"53","author":"Fisher","year":"2017","journal-title":"Water Resour. Res."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"1781","DOI":"10.1016\/j.rse.2011.02.019","article-title":"Improvements to a MODIS global terrestrial evapotranspiration algorithm","volume":"115","author":"Qiaozhen","year":"2011","journal-title":"Remote Sens. Environ."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"111622","DOI":"10.1016\/j.rse.2019.111622","article-title":"Data assimilation of high-resolution thermal and radar remote sensing retrievals for soil moisture monitoring in a drip-irrigated vineyard","volume":"239","author":"Lei","year":"2020","journal-title":"Remote Sens. Environ."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"111605","DOI":"10.1016\/j.rse.2019.111605","article-title":"A robust spectral-spatial approach to identifying heterogeneous crops using remote sensing imagery with high spectral and spatial resolutions","volume":"239","author":"Zhao","year":"2020","journal-title":"Remote Sens. Environ."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"111322","DOI":"10.1016\/j.rse.2019.111322","article-title":"Land-cover classification with high-resolution remote sensing images using transferable deep models","volume":"237","author":"Tong","year":"2020","journal-title":"Remote Sens. Environ."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"85","DOI":"10.1016\/j.wse.2019.06.001","article-title":"Using multi-satellite microwave remote sensing observations for retrieval of daily surface soil moisture across China","volume":"12","author":"Zhang","year":"2019","journal-title":"Water Sci. Eng."},{"key":"ref_16","doi-asserted-by":"crossref","unstructured":"Meyer, T., Weiherm\u00fcller, L., Vereecken, H., and Jonard, F. (2018). Vegetation Optical Depth and Soil Moisture Retrieved from L-Band Radiometry over the Growth Cycle of a Winter Wheat. Remote Sens., 10.","DOI":"10.3390\/rs10101637"},{"key":"ref_17","doi-asserted-by":"crossref","unstructured":"Bai, X., He, B., Li, X., Zeng, J., Wang, X., Wang, Z., Zeng, Y., and Su, Z. (2017). First Assessment of Sentinel-1A Data for Surface Soil Moisture Estimations Using a Coupled Water Cloud Model and Advanced Integral Equation Model over the Tibetan Plateau. Remote Sens., 9.","DOI":"10.3390\/rs9070714"},{"key":"ref_18","doi-asserted-by":"crossref","unstructured":"Zhang, L., Meng, Q., Yao, S., Wang, Q., Zeng, J., Zhao, S., and Ma, J. (2018). Soil Moisture Retrieval from the Chinese GF-3 Satellite and Optical Data over Agricultural Fields. Sensors, 18.","DOI":"10.3390\/s18082675"},{"key":"ref_19","doi-asserted-by":"crossref","unstructured":"Rahman, M.S., Di, L., Yu, E., Lin, L., Zhang, C., and Tang, J. (2019). Rapid Flood Progress Monitoring in Cropland with NASA SMAP. Remote Sens., 11.","DOI":"10.3390\/rs11020191"},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"33","DOI":"10.1016\/j.rse.2010.07.011","article-title":"Soil moisture retrieval over agricultural fields from multi-polarized and multi-angular RADARSAT-2 SAR data","volume":"115","author":"Gherboudj","year":"2011","journal-title":"Remote Sens. Environ."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"1279","DOI":"10.3390\/rs70201279","article-title":"Modeling and Mapping Soil Moisture of Plateau Pasture Using RADARSAT-2 Imagery","volume":"7","author":"Chai","year":"2015","journal-title":"Remote Sens."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"15388","DOI":"10.3390\/rs71115388","article-title":"Quality Assessment of the CCI ECV Soil Moisture Product Using ENVISAT ASAR Wide Swath Data over Spain, Ireland and Finland","volume":"7","author":"Pratola","year":"2015","journal-title":"Remote Sens."},{"key":"ref_23","doi-asserted-by":"crossref","unstructured":"Dabrowska-Zielinska, K., Budzynska, M., Tomaszewska, M., Malinska, A., Gatkowska, M., Bartold, M., and Malek, I. (2016). Assessment of Carbon Flux and Soil Moisture in Wetlands Applying Sentinel-1 Data. Remote Sens., 8.","DOI":"10.20944\/preprints201609.0046.v1"},{"key":"ref_24","doi-asserted-by":"crossref","unstructured":"Alexakis, D.D., Mexis, F.-D.K., Vozinaki, A.-E.K., Daliakopoulos, I.N., and Tsanis, I.K. (2017). Soil Moisture Content Estimation Based on Sentinel-1 and Auxiliary Earth Observation Products. A Hydrological Approach. Sensors, 17.","DOI":"10.3390\/s17061455"},{"key":"ref_25","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_26","doi-asserted-by":"crossref","unstructured":"Liu, Z., Li, P., and Yang, J. (2017). Soil Moisture Retrieval and Spatiotemporal Pattern Analysis Using Sentinel-1 Data of Dahra, Senegal. Remote Sens., 9.","DOI":"10.3390\/rs9111197"},{"key":"ref_27","doi-asserted-by":"crossref","unstructured":"Huang, S., Ding, J., Zou, J., Liu, B., and Chen, W. (2019). Soil Moisture Retrival Based on Sentinel-1 Imagery under Sparse Vegetation Coverage. Sensors, 19.","DOI":"10.3390\/s19030589"},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"10098","DOI":"10.3390\/rs70810098","article-title":"Retrieval of Both Soil Moisture and Texture Using TerraSAR-X Images","volume":"7","author":"Azza","year":"2015","journal-title":"Remote Sens."},{"key":"ref_29","doi-asserted-by":"crossref","unstructured":"Wang, C., Zhang, Z., Paloscia, S., Zhang, H., Wu, F., and Wu, Q. (2018). Permafrost Soil Moisture Monitoring Using Multi-Temporal TerraSAR-X Data in Beiluhe of Northern Tibet, China. Remote Sens., 10.","DOI":"10.3390\/rs10101577"},{"key":"ref_30","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_31","doi-asserted-by":"crossref","first-page":"915","DOI":"10.1109\/36.406677","article-title":"Measuring soil moisture with imaging radars","volume":"33","author":"Dubois","year":"1995","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_32","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_33","doi-asserted-by":"crossref","first-page":"2928","DOI":"10.3390\/rs5062928","article-title":"The Intercomparison of X-Band SAR Images from COSMO? SkyMed and TerraSAR-X Satellites: Case Studies","volume":"5","author":"Pettinato","year":"2013","journal-title":"Remote Sens."},{"key":"ref_34","doi-asserted-by":"crossref","unstructured":"Choker, M., Baghdadi, N., Zribi, M., El Hajj, M., Paloscia, S., Verhoest, N.E.C., Lievens, H., and Mattia, F. (2017). Evaluation of the Oh, Dubois and IEM Backscatter Models Using a Large Dataset of SAR Data and Experimental Soil Measurements. Water, 9.","DOI":"10.3390\/w9010038"},{"key":"ref_35","first-page":"2040","article-title":"A transition model for the reflection coefficient in surface scattering","volume":"39","author":"Wu","year":"1998","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"2589","DOI":"10.1109\/TGRS.2017.2648502","article-title":"Simulation and SMAP Observation of Sun-Glint over the Land Surface at the L-Band","volume":"55","author":"He","year":"2017","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"90","DOI":"10.1109\/TGRS.2002.807587","article-title":"Emission of rough surfaces calculated by the integral equation method with comparison to three-dimensional moment method simulations","volume":"41","author":"Chen","year":"2003","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"740","DOI":"10.1109\/LGRS.2011.2106109","article-title":"On the Retrieval of Soil Moisture in Wheat Fields from L-Band SAR Based on Water Cloud Modeling, the IEM, and Effective Roughness Parameters","volume":"8","author":"Lievens","year":"2011","journal-title":"IEEE Geosci. Remote Sens. Lett."},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"10966","DOI":"10.3390\/rs61110966","article-title":"A Synergistic Methodology for Soil Moisture Estimation in an Alpine Prairie Using Radar and Optical Satellite Data","volume":"6","author":"He","year":"2014","journal-title":"Remote Sens."},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"6827","DOI":"10.1080\/01431160802270123","article-title":"Biophysical estimation in tropical forests using JERS-1 SAR and VNIR imagery. II. Aboveground woody biomass","volume":"29","author":"Wang","year":"2008","journal-title":"Int. J. Remote Sens."},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"925","DOI":"10.1109\/TGRS.2006.872287","article-title":"Use of radar and optical remotely sensed data for soil moisture retrieval over vegetated areas","volume":"44","author":"Notarnicola","year":"2006","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"1404","DOI":"10.1109\/TGRS.2011.2179051","article-title":"A combined optical\u2013microwave method to retrieve soil moisture over vegetated areas","volume":"50","author":"Mattar","year":"2012","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_43","doi-asserted-by":"crossref","unstructured":"Xu, C., Qu, J.J., Hao, X., and Wu, D. (2020). Monitoring Surface Soil Moisture Content over the Vegetated Area by Integrating Optical and SAR Satellite Observations in the Permafrost Region of Tibetan Plateau. Remote Sens., 12.","DOI":"10.3390\/rs12010183"},{"key":"ref_44","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_45","doi-asserted-by":"crossref","unstructured":"Li, J., and Wang, S. (2018). Using SAR-Derived Vegetation Descriptors in a Water Cloud Model to Improve Soil Moisture Retrieval. Remote Sens., 10.","DOI":"10.3390\/rs10091370"},{"key":"ref_46","doi-asserted-by":"crossref","unstructured":"Attarzadeh, R., Amini, J., Notarnicola, C., and Greifeneder, F. (2018). Synergetic Use of Sentinel-1 and Sentinel-2 Data for Soil Moisture Mapping at Plot Scale. Remote Sens., 10.","DOI":"10.3390\/rs10081285"},{"key":"ref_47","doi-asserted-by":"crossref","unstructured":"Bousbih, S., Zribi, M., El Hajj, M., Baghdadi, N., Lili-Chabaane, Z., Gao, Q., and Fanise, P. (2018). Soil Moisture and Irrigation Mapping in A Semi-Arid Region, Based on the Synergetic Use of Sentinel-1 and Sentinel-2 Data. Remote Sens., 10.","DOI":"10.3390\/rs10121953"},{"key":"ref_48","doi-asserted-by":"crossref","first-page":"286","DOI":"10.1109\/TGE.1978.294586","article-title":"Microwave Backscatter Dependence on Surface Roughness, Soil Moisture, and Soil Texture: Part I-Bare Soil","volume":"16","author":"Ulaby","year":"1978","journal-title":"IEEE Trans. Geosci. Electron."},{"key":"ref_49","doi-asserted-by":"crossref","first-page":"4966","DOI":"10.1109\/TGRS.2013.2286203","article-title":"Evaluation of IEM, Dubois, and Oh radar backscatter models using airborne L-band SAR","volume":"52","author":"Panciera","year":"2013","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_50","doi-asserted-by":"crossref","first-page":"S274","DOI":"10.5589\/m10-055","article-title":"Evaluation of the Dubois, Oh, and IEM radar backscatter models over agricultural fields using C-band RADARSAT-2 SAR image data","volume":"36","author":"Merzouki","year":"2010","journal-title":"Can. J. Remote Sens."},{"key":"ref_51","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_52","doi-asserted-by":"crossref","first-page":"574","DOI":"10.1029\/WR016i003p00574","article-title":"Electromagnetic determination of soil water content: Measurements in coaxial transmission lines","volume":"16","author":"Topp","year":"1980","journal-title":"Water Resour. Res."},{"key":"ref_53","doi-asserted-by":"crossref","first-page":"2365","DOI":"10.1109\/TGRS.2008.917214","article-title":"Soil moisture retrieval during a corn growth cycle using L-band (1.6 GHz) radar observations","volume":"46","author":"Joseph","year":"2008","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_54","doi-asserted-by":"crossref","first-page":"2417","DOI":"10.1016\/j.rse.2010.05.017","article-title":"Effects of corn on C-and L-band radar backscatter: A correction method for soil moisture retrieval","volume":"114","author":"Joseph","year":"2010","journal-title":"Remote Sens. Environ."},{"key":"ref_55","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":"2011","journal-title":"IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens."},{"key":"ref_56","doi-asserted-by":"crossref","first-page":"2802","DOI":"10.1109\/TGRS.2014.2364914","article-title":"A Modified Water-Cloud Model with Leaf Angle Parameters for Microwave Backscattering from Agricultural Fields","volume":"53","author":"Kweon","year":"2015","journal-title":"IEEE Trans. Geosci. Remote Sens."}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/12\/9\/1358\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,13]],"date-time":"2025-10-13T14:09:20Z","timestamp":1760364560000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/12\/9\/1358"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,4,25]]},"references-count":56,"journal-issue":{"issue":"9","published-online":{"date-parts":[[2020,5]]}},"alternative-id":["rs12091358"],"URL":"https:\/\/doi.org\/10.3390\/rs12091358","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2020,4,25]]}}}