{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,17]],"date-time":"2026-06-17T16:28:48Z","timestamp":1781713728399,"version":"3.54.5"},"reference-count":56,"publisher":"MDPI AG","issue":"4","license":[{"start":{"date-parts":[[2015,3,30]],"date-time":"2015-03-30T00:00:00Z","timestamp":1427673600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Data disaggregation (or downscaling) is becoming a recognized modeling framework to improve the spatial resolution of available surface soil moisture satellite products. However, depending on the quality of the scale change modeling and on the uncertainty in its input data, disaggregation may improve or degrade soil moisture information at high resolution. Hence, defining a relevant metric for evaluating such methodologies is crucial before disaggregated data can be eventually used in fine-scale studies. In this paper, a new metric, named GDOWN, is proposed to assess the potential gain provided by disaggregation relative to the non-disaggregation case. The performance metric is tested during a four-year period by comparing 1-km resolution disaggregation based on physical and theoretical scale change (DISPATCH) data with the soil moisture measurements collected by six stations in central Morocco. DISPATCH data are obtained every 2\u20133 days from 40-km resolution SMOS (Soil Moisture Ocean Salinity) and 1-km resolution optical MODIS (Moderate Resolution Imaging Spectroradiometer) data. The correlation coefficient between GDOWN and the disaggregation gain in time series correlation, mean bias and bias in the slope of the linear fit ranges from 0.5 to 0.8. The new metric is found to be a good indicator of the overall performance of DISPATCH. Especially, the sign of GDOWN (positive in the case of effective disaggregation and negative in the opposite case) is independent of the uncertainties in SMOS data and of the representativeness of localized in situ measurements at the downscaling (1 km) resolution. In contrast, the traditional root mean square difference between disaggregation output and in situ measurements is poorly correlated (correlation coefficient of about 0.0) with the disaggregation gain in terms of both time series correlation and bias in the slope of the linear fit. The GDOWN approach is generic and thus could help test a range of downscaling methods dedicated to soil moisture and to other geophysical variables.<\/jats:p>","DOI":"10.3390\/rs70403783","type":"journal-article","created":{"date-parts":[[2015,3,30]],"date-time":"2015-03-30T10:50:23Z","timestamp":1427712623000},"page":"3783-3807","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":82,"title":["Performance Metrics for Soil Moisture Downscaling Methods: Application to DISPATCH Data in Central Morocco"],"prefix":"10.3390","volume":"7","author":[{"given":"Olivier","family":"Merlin","sequence":"first","affiliation":[{"name":"Facult\u00e9 des Sciences Semlalia Marrakech (FSSM), Avenue Prince Moulay Abdellah, BP 2390,Marrakech 40000, Morocco"},{"name":"Centre d'Etudes Spatiales de la Biosph\u00e8re (CESBIO), 18 Avenue, Edouard Belin, bpi 2801, Toulouse 31401, France"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yoann","family":"Malb\u00e9teau","sequence":"additional","affiliation":[{"name":"Centre d'Etudes Spatiales de la Biosph\u00e8re (CESBIO), 18 Avenue, Edouard Belin, bpi 2801, Toulouse 31401, France"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Youness","family":"Notfi","sequence":"additional","affiliation":[{"name":"Facult\u00e9 des Sciences et Techniques (FST), Avenue Abdelkarim Khettabi, BP 549, Marrakech 40000, Morocco"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Stefan","family":"Bacon","sequence":"additional","affiliation":[{"name":"Centre d'Etudes Spatiales de la Biosph\u00e8re (CESBIO), 18 Avenue, Edouard Belin, bpi 2801, Toulouse 31401, France"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3309-9935","authenticated-orcid":false,"given":"Salah","family":"Khabba","sequence":"additional","affiliation":[{"name":"Facult\u00e9 des Sciences Semlalia Marrakech (FSSM), Avenue Prince Moulay Abdellah, BP 2390,Marrakech 40000, Morocco"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Lionel","family":"Jarlan","sequence":"additional","affiliation":[{"name":"Facult\u00e9 des Sciences Semlalia Marrakech (FSSM), Avenue Prince Moulay Abdellah, BP 2390,Marrakech 40000, Morocco"},{"name":"Centre d'Etudes Spatiales de la Biosph\u00e8re (CESBIO), 18 Avenue, Edouard Belin, bpi 2801, Toulouse 31401, France"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2015,3,30]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"1643","DOI":"10.1109\/36.942542","article-title":"A methodology for surface soil moisture and vegetation optical depth retrieval using the microwave polarization difference index","volume":"39","author":"Owe","year":"2001","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"1655","DOI":"10.1109\/36.942543","article-title":"A multifrequency algorithm for the retrieval of soil moisture on a large scale using microwave data from SMMR and SSM\/I satellites","volume":"39","author":"Paloscia","year":"2001","journal-title":"IEEE Trans. Geosci Remote Sens."},{"key":"ref_3","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_4","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_5","doi-asserted-by":"crossref","first-page":"1999","DOI":"10.1109\/TGRS.2008.2011617","article-title":"An improved soil moisture retrieval algorithm for ERS and METOP scatterometer observations","volume":"47","author":"Naeimi","year":"2009","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"666","DOI":"10.1109\/JPROC.2010.2043032","article-title":"The SMOS mission: new tool for monitoring key elements of the global water cycle","volume":"98","author":"Kerr","year":"2010","journal-title":"Proc. IEEE"},{"key":"ref_7","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_8","doi-asserted-by":"crossref","first-page":"4599","DOI":"10.1080\/0143116031000156837","article-title":"Spaceborne soil moisture estimation at high resolution: A microwave-optical\/IR synergistic approach","volume":"24","author":"Chauhan","year":"2003","journal-title":"Int. J. Remote Sens."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"326","DOI":"10.1109\/36.992792","article-title":"Subpixel variability of remotely sensed soil moisture: An inter-comparison study of SAR and ESTAR","volume":"40","author":"Bindlish","year":"2002","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"112","DOI":"10.1016\/S0022-1694(03)00066-0","article-title":"A disaggregation scheme for soil moisture based on topography and soil depth","volume":"276","author":"Pellenq","year":"2003","journal-title":"J. Hydrol."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"2018","DOI":"10.1109\/TGRS.2013.2257605","article-title":"Tests of the SMAP combined radar and radiometer algorithm using airborne field campaign observations and simulated data","volume":"52","author":"Das","year":"2014","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_12","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. Hydrometeor."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"259","DOI":"10.1016\/j.rse.2012.05.009","article-title":"A microwave-optical\/infrared disaggregation for improving spatial representation of soil moisture using AMSR-E and MODIS products","volume":"124","author":"Choi","year":"2012","journal-title":"Remote Sens. Environ."},{"key":"ref_14","doi-asserted-by":"crossref","unstructured":"Fang, B., Lakshmi, V., Bindlish, R., Jackson, T.J., Cosh, M., and Basara, J. (2013). Passive microwave soil moisture downscaling using vegetation index and skin surface temperature. Vadose Zone J, 12.","DOI":"10.2136\/vzj2013.05.0089er"},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"408","DOI":"10.1029\/2012WR012379","article-title":"An unmixing algorithm for remotely sensed soil moisture","volume":"49","author":"Ines","year":"2013","journal-title":"Water Resour. Res."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"446","DOI":"10.1109\/TGRS.2011.2161318","article-title":"Improving spatial soil moisture representation through integration of AMSR-E and MODIS products","volume":"50","author":"Kim","year":"2012","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"1556","DOI":"10.1109\/TGRS.2011.2175000","article-title":"Disaggregation of SMOS soil moisture in southeastern Australia","volume":"50","author":"Merlin","year":"2012","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"25","DOI":"10.1016\/j.rse.2012.11.008","article-title":"Self-calibrated evaporation-based disaggregation of SMOS soil moisture: an evaluation study at 3 km and 100 m resolution in Catalunya, Spain","volume":"130","author":"Merlin","year":"2013","journal-title":"Remote Sens. Environ."},{"key":"ref_19","doi-asserted-by":"crossref","unstructured":"Parinussa, R., Yilmaz, M., Anderson, M., Hain, C., and de Jeu, R. (2013). An intercomparison of remotely sensed soil moisture products at various spatial scales over the Iberian Peninsula. Hydrol. Process., 130.","DOI":"10.1002\/hyp.9975"},{"key":"ref_20","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_21","doi-asserted-by":"crossref","first-page":"273","DOI":"10.1016\/j.jhydrol.2013.12.047","article-title":"Combining SMOS with visible and near\/shortwave\/thermal infrared satellite data for high resolution soil moisture estimates","volume":"516","author":"Piles","year":"2014","journal-title":"J. Hydrol."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"6208","DOI":"10.1002\/wrcr.20495","article-title":"Development of a deterministic downscaling algorithm for remote sensing soil moisture footprint using soil and vegetation classifications","volume":"49","author":"Shin","year":"2013","journal-title":"Water Resour. Res."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"935","DOI":"10.1109\/JSTARS.2013.2272053","article-title":"Retrieving righ-resolution surface soil moisture by downscaling AMSR-E brightness temperature using MODIS LST and NDVI data","volume":"7","author":"Song","year":"2014","journal-title":"IEEE J. Select Top. Appl. Earth Obs. Remote Sens."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"5069","DOI":"10.1007\/s11269-013-0337-9","article-title":"Data fusion techniques for improving soil moisture deficit using SMOS satellite and WRF-NOAH land surface model","volume":"27","author":"Srivastava","year":"2013","journal-title":"Water Resour. Manag."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"3127","DOI":"10.1007\/s11269-013-0337-9","article-title":"Machine learning techniques for downscaling SMOS satellite soil moisture using MODIS land surface Temperature for Hydrological Application","volume":"27","author":"Srivastava","year":"2013","journal-title":"Water Resour. Manag."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"6790","DOI":"10.3390\/rs5126790","article-title":"A downscaling method for improving the spatial resolution of AMSR-E derived soil moisture product based on MSG-SEVIRI data","volume":"5","author":"Zhao","year":"2013","journal-title":"Remote Sens."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"1864","DOI":"10.1109\/TGRS.2011.2169802","article-title":"Multi-dimensional disaggregation of land surface temperature using high-resolution red, near-infrared, shortwave-infrared and microwave-L bands","volume":"50","author":"Merlin","year":"2012","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"545","DOI":"10.1016\/j.rse.2006.10.006","article-title":"A vegetation index based technique for spatial sharpening of thermal imagery","volume":"107","author":"Agam","year":"2007","journal-title":"Remote Sens. Environ."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"118","DOI":"10.1016\/j.rse.2013.03.023","article-title":"Development and verification of a non-linear disaggregation method (NL-DisTrad) to downscale MODIS land surface temperature to the spatial scale of Landsat thermal data to estimate evapotranspiration","volume":"135","author":"Bindhu","year":"2013","journal-title":"Remote Sens. Environ."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"2131","DOI":"10.1002\/2013JD020354","article-title":"Genetic particle filter application to land surface temperature downscaling","volume":"119","author":"Mechri","year":"2014","journal-title":"J. Geophys. Res.: Atmos."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"2500","DOI":"10.1016\/j.rse.2010.05.025","article-title":"Disaggregation of MODIS surface temperature over an agricultural area using a time series of Formosat-2 Images","volume":"114","author":"Merlin","year":"2010","journal-title":"Remote Sens. Environ."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"119","DOI":"10.1016\/j.rse.2012.12.014","article-title":"Disaggregation of remotely sensed land surface temperature: Literature survey, taxonomy, issues, and caveats","volume":"131","author":"Zhan","year":"2013","journal-title":"Remote Sens. Environ."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"1444","DOI":"10.1016\/j.advwatres.2008.01.018","article-title":"The NAFE\u201906 data set: towards soil moisture retrieval at intermediate resolution","volume":"31","author":"Merlin","year":"2008","journal-title":"Adv. Water Resour."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"1697","DOI":"10.5194\/hess-16-1697-2012","article-title":"The AACES field experiments: SMOS calibration and validation across the Murrumbidgee River catchment","volume":"16","author":"Peischl","year":"2012","journal-title":"Hydrol. Earth Syst. Sci."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.agwat.2005.02.013","article-title":"Monitoring wheat phenology and irrigation in central Morocco: on the use of relationships between evapotranspiration, crops coefficients, leaf area index and remotely-sensed vegetation indices","volume":"79","author":"Duchemin","year":"2006","journal-title":"Agr. Water Manag."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"41","DOI":"10.1016\/j.agwat.2006.02.004","article-title":"Combining FAO-56 model and ground-based remote sensing to estimate water consumptions of wheat crops in a semi-arid region","volume":"87","author":"Chehbouni","year":"2007","journal-title":"Agr. Water Manag."},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"5161","DOI":"10.1080\/01431160802036417","article-title":"An integrated modelling and remote sensing approach for hydrological study in arid and semi-arid regions: the SUDMED Programme","volume":"29","author":"Chehbouni","year":"2008","journal-title":"Int. J. Remote Sens."},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"524","DOI":"10.1016\/j.proenv.2013.06.059","article-title":"The SudMed program and the Joint International Laboratory TREMA: A decade of water transfer study in the Soil-Plant-Atmosphere system over irrigated crops in semi-arid area","volume":"19","author":"Khabba","year":"2013","journal-title":"Proced. Environ. Sci."},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"2028","DOI":"10.3390\/s7102028","article-title":"A wetness index using terrain-corrected surface temperature and Normalized Difference Vegetation Index derived from standard MODIS products: an evaluation of its use in a humid forest-dominated region of eastern Canada","volume":"7","author":"Hassan","year":"2007","journal-title":"Sensors"},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"585","DOI":"10.1016\/j.isprsjprs.2009.04.003","article-title":"The influence of topography on the forest surface temperature retrieved from Landsat TM, ETM + and ASTER thermal channels","volume":"64","author":"Hais","year":"2009","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_41","doi-asserted-by":"crossref","unstructured":"Van doninck, J., Peters, J., de Baets, B., de Clercq, E.M., Ducheyne, E., and Verhoest, N.E.C. (2012). Influence of topographic normalization on the vegetation index-surface temperature relationship. J. Appl. Remote Sens., 6.","DOI":"10.1117\/1.JRS.6.063518"},{"key":"ref_42","unstructured":"Allen, R.G., Pereira, L.S., Raes, D., and Smith, M. (1998). Crop Evapotranspiration\u2014Guidelines for Computing Crop Water Requirements, FAO."},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"719","DOI":"10.1029\/91WR00075","article-title":"A semiempirical model of bare soil evaporation for crop simulation models","volume":"7","author":"Brisson","year":"1991","journal-title":"Water Resour. Res."},{"key":"ref_44","doi-asserted-by":"crossref","unstructured":"Cosby, B.J., Hornberger, G.M., Clapp, R.B., and Ginn, T.R. (1984). A statistical exploration of the relationships of soil moisture characteristics to the physical properties of soils. Water Resour. Res., 20.","DOI":"10.1029\/WR020i006p00682"},{"key":"ref_45","unstructured":"Kerr, Y., Jacquette, E., al Bitar, A., Cabot, F., Mialon, A., Richaume, P., Quesney, A., and Berthon, L. (2013). CATDS SMOS L3 Soil Moisture Retrieval Processor: Algorithm Theoretical Baseline Document (ATBD), CESBIO."},{"key":"ref_46","unstructured":"Berthon, L., Mialon, A., Cabot, F., al Bitar, A., Richaume, P., Kerr, Y., Leroux, D., Bircher, S., Lawrence, H., and Quesney, A. (2012). CATDS Level 3 Data Product Description\u2014Soil Moisture and Brightness Temperature Part, CESBIO."},{"key":"ref_47","doi-asserted-by":"crossref","unstructured":"Malb\u00e9teau, Y., Merlin, O., Molero, B., R\u00fcdiger, C., and Bacon, S. (2015). DISPATCH as a tool for improving validation strategies of coarse-scale remotely sensed soil moisture: Application to SMOS and AMSR-E data in Southeastern Australia. Int. J. Appl. Earth Obs. GeoInf., sudmitted.","DOI":"10.1016\/j.jag.2015.10.002"},{"key":"ref_48","unstructured":"Budyko, M.I. (1956). Heat Balance of the Earth\u2019s Surface, Gidrometeoizdat."},{"key":"ref_49","doi-asserted-by":"crossref","unstructured":"Reichle, R.H., Koster, R.D., Liu, P., Mahanama, S.P.P., Njoku, E.G., and Owe, M. (2007). Comparison and assimilation of global soil moisture retrievals from the Advanced Microwave Scanning Radiometer for the Earth Observing System (AMSR-E) and the Scanning Multichannel Microwave Radiometer (SMMR). J. Geophys. Res., 112.","DOI":"10.1029\/2006JD008033"},{"key":"ref_50","doi-asserted-by":"crossref","first-page":"3395","DOI":"10.1002\/grl.50655","article-title":"GRACE satellite monitoring of large depletion in water storage in response to the 2011 drought in Texas","volume":"40","author":"Long","year":"2013","journal-title":"Geophys. Res. Lett."},{"key":"ref_51","doi-asserted-by":"crossref","first-page":"1131","DOI":"10.1002\/2013WR014581","article-title":"Uncertainty in evapotranspiration from land surface modeling, remote sensing, and GRACE satellites","volume":"50","author":"Long","year":"2014","journal-title":"Water Resour. Res."},{"key":"ref_52","doi-asserted-by":"crossref","unstructured":"Xia, Y., Mitchell, K., Ek, M., Sheffield, J., Cosgrove, B., Wood, E., Luo, L., Alonge, C., Wei, H., and Meng, J. (2012). Continental-scale water and energy flux analysis and validation for the North American Land Data Assimilation System project phase 2 (NLDAS-2): 1. Intercomparison and application of model products. J. Geophys. Res.: Atmos., 117.","DOI":"10.1029\/2011JD016048"},{"key":"ref_53","doi-asserted-by":"crossref","unstructured":"Xia, Y., Mitchell, K., Ek, M., Cosgrove, B., Sheffield, J., Luo, L., Alonge, C., Wei, H., Meng, J., and Livneh, B. (2012). Continental-scale water and energy flux analysis and validation for North American Land Data Assimilation System project phase 2 (NLDAS-2): 2. Validation of model-simulated streamflow. J. Geophys. Res.: Atmos., 117.","DOI":"10.1029\/2011JD016051"},{"key":"ref_54","doi-asserted-by":"crossref","first-page":"194","DOI":"10.1175\/JHM571.1","article-title":"From near-surface to root-zone soil moisture using different assimilation techniques","volume":"8","author":"Sabater","year":"2007","journal-title":"J. Hydrometeor."},{"key":"ref_55","doi-asserted-by":"crossref","first-page":"1308","DOI":"10.1175\/JHM552.1","article-title":"Assimilation of disaggregated microwave soil moisture into a hydrologic model using coarse-scale meterological data","volume":"7","author":"Merlin","year":"2006","journal-title":"J. Hydrometeor."},{"key":"ref_56","doi-asserted-by":"crossref","unstructured":"Bandara, R., Walker, J.P., R\u00fcdiger, C., and Merlin, O. (2015). Towards soil property retrieval from space: An application with disaggregated satellite observations. J. Hydrol.","DOI":"10.1016\/j.jhydrol.2015.01.018"}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/7\/4\/3783\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T20:44:08Z","timestamp":1760215448000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/7\/4\/3783"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2015,3,30]]},"references-count":56,"journal-issue":{"issue":"4","published-online":{"date-parts":[[2015,4]]}},"alternative-id":["rs70403783"],"URL":"https:\/\/doi.org\/10.3390\/rs70403783","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2015,3,30]]}}}