{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,25]],"date-time":"2026-09-25T02:24:27Z","timestamp":1790303067305,"version":"4.1.0"},"reference-count":51,"publisher":"MDPI AG","issue":"1","license":[{"start":{"date-parts":[[2017,1,8]],"date-time":"2017-01-08T00:00:00Z","timestamp":1483833600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"the Nature Science Foundation Innovation Group Project of Hubei Province, China","award":["No. 2016CFA003"],"award-info":[{"award-number":["No. 2016CFA003"]}]},{"name":"the National High Technology Research and Development Program of China (863 Program)","award":["No. 2013AA01A608"],"award-info":[{"award-number":["No. 2013AA01A608"]}]},{"name":"the National Nature Science Foundation of China (NSFC) Program","award":["No. 41301441"],"award-info":[{"award-number":["No. 41301441"]}]},{"name":"the China Scholarship Council (CSC) under the State Scholarship Fund","award":["No. 201506270080"],"award-info":[{"award-number":["No. 201506270080"]}]}],"content-domain":{"domain":["www.mdpi.com"],"crossmark-restriction":true},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>To meet the demand of regional hydrological and agricultural applications, a new method named near infrared-red (NIR-red) spectra-based disaggregation (NRSD) was proposed to perform a disaggregation of Soil Moisture Active Passive (SMAP) products from 36 km to 250 m resolution. The NRSD combined proposed normalized soil moisture index (NSMI) with SMAP data to obtain 250 m resolution soil moisture mapping. This NRSD method was validated with the data from in situ OzNet network in May and September 2015. Results showed that NRSD performed a decent downscaling (root-mean-square error (RMSE) = 0.04 m3\/m3 and 0.12 m3\/m3 in May and September, respectively). Based on the validation, it was found that the proposed NSMI was a new alternative indicator for denoting the heterogeneity of soil moisture at sub-kilometer scales. Attributed to the excellent performance of the NSMI, NRSD has a higher overall accuracy, finer spatial representation within SMAP pixels and wider applicable scope on usability tests for land cover, vegetation density and drought condition than the disaggregation based on physical and theoretical scale change (DISPATCH) has at 250 m resolution. This revealed that the NRSD method is expected to provide soil moisture mapping at 250-resolution for large-scale hydrological and agricultural studies.<\/jats:p>","DOI":"10.3390\/rs9010051","type":"journal-article","created":{"date-parts":[[2017,1,9]],"date-time":"2017-01-09T11:03:23Z","timestamp":1483959803000},"page":"51","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":29,"title":["NIR-Red Spectra-Based Disaggregation of SMAP Soil Moisture to 250 m Resolution Based on OzNet in Southeastern Australia"],"prefix":"10.3390","volume":"9","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-3521-9972","authenticated-orcid":false,"given":"Nengcheng","family":"Chen","sequence":"first","affiliation":[{"name":"State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan 430079, China"},{"name":"Collaborative Innovation Center of Geospatial Technology, Wuhan University, Wuhan 430079, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1517-6186","authenticated-orcid":false,"given":"Yuqi","family":"He","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan 430079, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1017-742X","authenticated-orcid":false,"given":"Xiang","family":"Zhang","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan 430079, China"},{"name":"Department of Agronomy, Purdue University, West Lafayette, IN 47907, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2017,1,8]]},"reference":[{"key":"ref_1","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_2","doi-asserted-by":"crossref","unstructured":"Entekhabi, D., Jackson, T.J., Njoku, E.G., Oneill, P., and Entin, J.K. (2008, January 10\u201314). Soil moisture active\/passive (SMAP) mission concept. Proceedings of the Society of Photographic Instrumentation Engineers Conference on Optical Engineering+ Applications, San Diego, CA, USA.","DOI":"10.1109\/IGARSS.2008.4779267"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"2136","DOI":"10.1109\/36.789610","article-title":"Soil moisture mapping at regional scales using microwave radiometry: The southern great plains hydrology experiment","volume":"37","author":"Jackson","year":"1999","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"317","DOI":"10.1016\/j.jhydrol.2013.12.053","article-title":"Regional scale spatio-temporal variability of soil moisture and its relationship with meteorological factors over the Korean Peninsula","volume":"516","author":"Cho","year":"2014","journal-title":"J. Hydrol."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"59","DOI":"10.1016\/j.isprsjprs.2014.02.005","article-title":"Soil moisture retrieval from airborne L-band passive microwave using high resolution multispectral data","volume":"91","author":"Hasan","year":"2014","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"3403","DOI":"10.1007\/s00382-014-2112-x","article-title":"Using soil moisture forecasts for sub-seasonal summer temperature predictions in Europe","volume":"43","author":"Orth","year":"2014","journal-title":"Clim. Dyn."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"905","DOI":"10.1016\/S1464-1895(99)00134-9","article-title":"Climate change and soil moisture: A case study","volume":"24","author":"Huszar","year":"1999","journal-title":"Phys. Chem. Earth Part A Solid Earth Ge\u0301od."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"3257","DOI":"10.1175\/2011JCLI3733.1","article-title":"Soil moisture drought in China, 1950\u20132006","volume":"24","author":"Wang","year":"2011","journal-title":"J. Clim."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"227","DOI":"10.1016\/j.jhydrol.2013.03.015","article-title":"Increasing river flood preparedness by real-time warning based on wetness state conditions","volume":"489","author":"Willems","year":"2013","journal-title":"J. Hydrol."},{"key":"ref_10","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_11","doi-asserted-by":"crossref","first-page":"2073","DOI":"10.1175\/2007JTECHA930.1","article-title":"The USDA natural resources conservation service soil climate analysis network (SCAN)","volume":"24","author":"Schaefer","year":"2007","journal-title":"J. Atmos. Ocean. Technol."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"309","DOI":"10.1016\/S0034-4257(99)00087-5","article-title":"Soil moisture (water-content) assessment by an airborne scatterometer: The Chernobyl disaster area and the Negev Desert","volume":"71","author":"Blumberg","year":"2000","journal-title":"Remote Sens. Environ."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"490","DOI":"10.1109\/TGRS.2013.2241774","article-title":"The soil moisture active passive experiments (SMAPEx): Toward soil moisture retrieval from the SMAP mission","volume":"52","author":"Panciera","year":"2014","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"1530","DOI":"10.1109\/TGRS.2011.2168533","article-title":"Validation of soil moisture and ocean salinity (SMOS) soil moisture over watershed networks in the U.S.","volume":"50","author":"Jackson","year":"2012","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"4994","DOI":"10.1109\/TGRS.2016.2561938","article-title":"Assessment of the SMAP passive soil moisture product","volume":"54","author":"Chan","year":"2016","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"181","DOI":"10.1016\/j.rse.2014.04.006","article-title":"Global-scale evaluation of two satellite-based passive microwave soil moisture datasets (SMOS and AMSR-E) with respect to land data assimilation system estimates","volume":"149","author":"Alyaari","year":"2014","journal-title":"Remote Sens. Environ."},{"key":"ref_17","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":"Alyaari","year":"2014","journal-title":"Remote Sens. Environ."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"40","DOI":"10.1016\/j.rse.2016.02.042","article-title":"Overview of SMOS performance in terms of global soil moisture monitoring after six years in operation","volume":"180","author":"Kerr","year":"2016","journal-title":"Remote Sens. Environ."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"761","DOI":"10.1109\/TGRS.2013.2281266","article-title":"Radio-frequency interference mitigation for the soil moisture active passive microwave radiometer","volume":"52","author":"Piepmeier","year":"2014","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"393","DOI":"10.1016\/S0034-4257(02)00014-7","article-title":"Space-time characterization of soil moisture from passive microwave remotely sensed imagery and ancillary data","volume":"81","author":"Kim","year":"2002","journal-title":"Remote Sens. Environ."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"400","DOI":"10.1016\/S0034-4257(02)00044-5","article-title":"Downscaling of remotely sensed soil moisture with a modified fractal interpolation method using contraction mapping and ancillary data","volume":"83","author":"Kim","year":"2002","journal-title":"Remote Sens. Environ."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"2353","DOI":"10.1029\/2001WR000475","article-title":"Downscaling of radio brightness measurements for soil moisture estimation: A four-dimensional variational data assimilation approach","volume":"37","author":"Reichle","year":"2001","journal-title":"Water Resour. Res."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"1504","DOI":"10.1109\/TGRS.2010.2089526","article-title":"An algorithm for merging SMAP radiometer and radar data for high-resolution soil-moisture retrieval","volume":"49","author":"Das","year":"2011","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"210","DOI":"10.1016\/j.rse.2014.08.021","article-title":"Evaluation of the SMAP brightness temperature downscaling algorithm using active\u2013passive microwave observations","volume":"155","author":"Wu","year":"2014","journal-title":"Remote Sens. Environ."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"846","DOI":"10.1109\/LGRS.2014.2364049","article-title":"Effect of land-cover type on the SMAP active\/passive soil moisture downscaling algorithm performance","volume":"12","author":"Wu","year":"2015","journal-title":"IEEE Geosci. Remote Sens. Lett."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"2275","DOI":"10.1016\/j.rse.2009.06.012","article-title":"A sequential model for disaggregating near-surface soil moisture observations using multi-resolution thermal sensors","volume":"113","author":"Merlin","year":"2009","journal-title":"Remote Sens. Environ."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"2305","DOI":"10.1016\/j.rse.2010.05.007","article-title":"An improved algorithm for disaggregating microwave-derived soil moisture based on red, near-infrared and thermal-infrared data","volume":"114","author":"Merlin","year":"2010","journal-title":"Remote Sens. Environ."},{"key":"ref_28","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_29","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_30","doi-asserted-by":"crossref","first-page":"361","DOI":"10.1016\/j.rse.2016.02.045","article-title":"SMOS disaggregated soil moisture product at 1 km resolution: Processor overview and first validation results","volume":"180","author":"Molero","year":"2016","journal-title":"Remote Sens. Environ."},{"key":"ref_31","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_32","doi-asserted-by":"crossref","first-page":"161","DOI":"10.1080\/02757259409532220","article-title":"A method to make use of thermal infrared temperature and NDVI measurements to infer surface soil water content and fractional vegetation cover","volume":"9","author":"Carlson","year":"1994","journal-title":"Remote Sens. Rev."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"1612","DOI":"10.3390\/s7081612","article-title":"An overview of the \"triangle method\" for estimating surface evapotranspiration and soil moisture from satellite imagery","volume":"7","author":"Carlson","year":"2007","journal-title":"Sensors"},{"key":"ref_34","first-page":"1541","article-title":"Distinguishing vegetation from soil background information","volume":"43","author":"Richardson","year":"1977","journal-title":"Photogramm. Eng. Remote Sens."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"37","DOI":"10.1016\/0034-4257(85)90111-7","article-title":"Spectral response of a plant canopy with different soil backgrounds","volume":"17","author":"Huete","year":"1985","journal-title":"Remote Sens. Environ."},{"key":"ref_36","first-page":"1045","article-title":"Designing of the perpendicular drought index","volume":"52","author":"Ghulam","year":"2006","journal-title":"Environ. Earth Sci."},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"150","DOI":"10.1016\/j.isprsjprs.2007.03.002","article-title":"Modified perpendicular drought index (MPDI): A real-time drought monitoring method","volume":"62","author":"Abduwasit","year":"2007","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_38","first-page":"176","article-title":"Two new soil moisture indices based on the NIR-red triangle space of Landsat-8 data","volume":"50","author":"Amani","year":"2016","journal-title":"Int. J. Appl. Earth Obs. Geoinform."},{"key":"ref_39","doi-asserted-by":"crossref","unstructured":"Smith, A.B., Walker, J.P., Western, A.W., Young, R., Ellett, K.M., Pipunic, R., Grayson, R., Siriwardena, L., Chiew, F.H.S., and Richter, H. (2012). The Murrumbidgee soil moisture monitoring network data set. Water Resour. Res., 48.","DOI":"10.1029\/2012WR011976"},{"key":"ref_40","unstructured":"SMAPEx Project. Available online: www.smapex.monash.edu.au."},{"key":"ref_41","unstructured":"NASA Distributed Active Archive Center at NSIDC. Available online: https:\/\/nsidc.org\/daac\/."},{"key":"ref_42","unstructured":"NASA Reverb, Available online: https:\/\/reverb.echo.nasa.gov."},{"key":"ref_43","unstructured":"OzNet Hydrological Monitoring Network. Available online: www.oznet.org.au."},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"141","DOI":"10.1016\/0034-4257(95)00136-O","article-title":"The robustness of canopy gap fraction estimates from red and near-infrared reflectances : A comparison of approaches","volume":"54","author":"Baret","year":"1995","journal-title":"Remote Sens. Environ."},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"155","DOI":"10.1016\/0034-4257(84)90043-9","article-title":"Soil spectral effects on 4-space vegetation discrimination","volume":"15","author":"Huete","year":"1984","journal-title":"Remote Sens. Environ."},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"166","DOI":"10.1016\/S0034-4257(97)00135-1","article-title":"Variability of laboratory measured soil lines of soils from southeastern Brazil","volume":"63","author":"Galvao","year":"1998","journal-title":"Remote Sens. Environ."},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"65","DOI":"10.1080\/02757259309532166","article-title":"The soil line concept in remote sensing","volume":"7","author":"Baret","year":"1993","journal-title":"Remote Sens. Rev."},{"key":"ref_48","doi-asserted-by":"crossref","first-page":"545","DOI":"10.3390\/rs2020545","article-title":"Soil line influences on two-band vegetation indices and vegetation isolines: A numerical study","volume":"2","author":"Yoshioka","year":"2010","journal-title":"Remote Sens."},{"key":"ref_49","doi-asserted-by":"crossref","first-page":"478","DOI":"10.1080\/15481603.2015.1055540","article-title":"A parametric method for estimation of leaf area index using Landsat ETM+ data","volume":"52","author":"Amani","year":"2015","journal-title":"Gisci. Remote Sens."},{"key":"ref_50","doi-asserted-by":"crossref","first-page":"246","DOI":"10.1016\/0034-4257(94)90020-5","article-title":"Estimating crop water deficit using the relation between surface-air temperature and spectral vegetation index","volume":"49","author":"Moran","year":"1994","journal-title":"Remote Sens. Environ."},{"key":"ref_51","doi-asserted-by":"crossref","first-page":"536","DOI":"10.1175\/1520-0493(1989)117<0536:ASPOLS>2.0.CO;2","article-title":"A simple parameterization of land surface processes for meteorological models","volume":"117","author":"Noilhan","year":"1989","journal-title":"Mon. Weather Rev."}],"updated-by":[{"DOI":"10.3390\/rs9040321","type":"correction","label":"Correction","source":"publisher","updated":{"date-parts":[[2017,1,8]],"date-time":"2017-01-08T00:00:00Z","timestamp":1483833600000}}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/9\/1\/51\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,8,3]],"date-time":"2025-08-03T23:21:07Z","timestamp":1754263267000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/9\/1\/51"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2017,1,8]]},"references-count":51,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2017,1]]}},"alternative-id":["rs9010051"],"URL":"https:\/\/doi.org\/10.3390\/rs9010051","relation":{"correction":[{"id-type":"doi","id":"10.3390\/rs9040321","asserted-by":"object"}]},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2017,1,8]]}}}