{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,17]],"date-time":"2026-09-17T17:33:54Z","timestamp":1789666434024,"version":"4.0.1"},"reference-count":35,"publisher":"MDPI AG","issue":"9","license":[{"start":{"date-parts":[[2015,9,7]],"date-time":"2015-09-07T00:00:00Z","timestamp":1441584000000},"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>Validation of satellite-based soil moisture products is necessary to provide users with an assessment of their accuracy and reliability and to ensure quality of information. A key step in the validation process is to upscale point-scale, ground-based soil moisture observations to satellite-scale pixel averages. When soil moisture shows high spatial heterogeneity within pixels, a strategy which captures the spatial characteristics is essential for the upscaling process. In addition, temporal variation in soil moisture must be taken into account when measurement times of ground-based and satellite-based observations are not the same. We applied spatio-temporal regression block kriging (STRBK) to upscale  in situ soil moisture observations collected as time series at multiple locations to pixel averages. STRBK incorporates auxiliary information such as maps of vegetation and land surface temperature to improve predictions and exploits the spatio-temporal correlation structure of the point-scale soil moisture observations. In addition, STRBK also quantifies the uncertainty associated with the upscaled soil moisture which allows bias detection and significance testing of satellite-based soil moisture products. The approach is illustrated with a real-world application for upscaling in situ soil moisture observations for validating the Polarimetric L-band Multi-beam Radiometer (PLMR) retrieved soil moisture product in the Heihe Water Allied Telemetry Experimental Research experiment (HiWATER). The results show that STRBK yields upscaled soil moisture predictions that are sufficiently accurate  for validation purposes. Comparison of the upscaled predictions with PLMR soil moisture observations shows that the root-mean-squared error of the PLMR soil moisture product  is about 0.03 m3\u00b7m\u22123 and can be used as a high-resolution soil moisture product for watershed-scale soil moisture monitoring.<\/jats:p>","DOI":"10.3390\/rs70911372","type":"journal-article","created":{"date-parts":[[2015,9,8]],"date-time":"2015-09-08T11:59:54Z","timestamp":1441713594000},"page":"11372-11388","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":40,"title":["Upscaling In Situ Soil Moisture Observations to Pixel Averages with Spatio-Temporal Geostatistics"],"prefix":"10.3390","volume":"7","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-5333-3827","authenticated-orcid":false,"given":"Jianghao","family":"Wang","sequence":"first","affiliation":[{"name":"State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences & Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China"},{"name":"Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application, Nanjing 210023, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yong","family":"Ge","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences & Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China"},{"name":"Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application, Nanjing 210023, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0959-9358","authenticated-orcid":false,"given":"Gerard","family":"Heuvelink","sequence":"additional","affiliation":[{"name":"Soil Geography and Landscape Group, Wageningen University, Wageningen 6708 PB,  The Netherlands"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Chenghu","family":"Zhou","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences & Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2015,9,7]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Vereecken, H., Huisman, J.A., Bogena, H., Vanderborght, J., Vrugt, J.A., and Hopmans, J.W. (2008). On the value of soil moisture measurements in vadose zone hydrology: A review. Water Resour. Res., 44.","DOI":"10.1029\/2008WR006829"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"63","DOI":"10.1016\/j.jhydrol.2011.12.039","article-title":"Catchment scale soil moisture spatial-temporal variability","volume":"422","author":"Brocca","year":"2012","journal-title":"J. Hydrol."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"80","DOI":"10.1007\/s11430-013-4728-9","article-title":"Characterization, controlling, and reduction of uncertainties in the modeling and observation of land-surface systems","volume":"57","author":"Li","year":"2014","journal-title":"Sci. China Earth Sci."},{"key":"ref_4","doi-asserted-by":"crossref","unstructured":"Crow, W.T., Berg, A.A., Cosh, M.H., Loew, A., Mohanty, B.P., Panciera, R., de Rosnay, P., Ryu, D., and Walker, J.P. (2012). Upscaling sparse ground-based soil moisture observations for the validation of coarse-resolution satellite soil moisture products. Rev. Geophys., 50.","DOI":"10.1029\/2011RG000372"},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"4256","DOI":"10.1109\/TGRS.2010.2051035","article-title":"Validation of advanced microwave scanning radiometer soil moisture products","volume":"48","author":"Jackson","year":"2010","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"874","DOI":"10.1109\/TGRS.2009.2028019","article-title":"Analysis of local variation of soil surface parameters with TerraSAR-X radar data over bare agricultural fields","volume":"48","author":"Anguela","year":"2010","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"215","DOI":"10.1016\/j.rse.2011.11.017","article-title":"Evaluation of remotely sensed and modelled soil moisture products using global ground-based in situ observations","volume":"118","author":"Albergel","year":"2012","journal-title":"Remote Sens. Environ."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.rse.2013.07.003","article-title":"Spatial upscaling of in-situ soil moisture measurements based on MODIS-derived apparent thermal inertia","volume":"138","author":"Qin","year":"2013","journal-title":"Remote Sens. Environ."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"8190","DOI":"10.3390\/rs6098190","article-title":"Evaluation of a global soil moisture product from finer spatial resolution SAR data and ground measurements at Irish sites","volume":"6","author":"Pratola","year":"2014","journal-title":"Remote Sens."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"1","DOI":"10.2136\/vzj2006.0055","article-title":"Upscaling hydraulic properties and soil water flow processes in heterogeneous soils: A review","volume":"6","author":"Vereecken","year":"2007","journal-title":"Vadose Zone J."},{"key":"ref_11","doi-asserted-by":"crossref","unstructured":"Cressie, N.A.C. (1993). Statistics for Spatial Data, Wiley. Revised ed.","DOI":"10.1002\/9781119115151"},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"241","DOI":"10.1016\/j.jhydrol.2009.01.015","article-title":"Multi-scale soil moisture measurements at the Gourma meso-scale site in Mali","volume":"375","author":"Gruhier","year":"2009","journal-title":"J. Hydrol."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.advwatres.2004.10.004","article-title":"Upscaling of field-scale soil moisture measurements using distributed land surface modeling","volume":"28","author":"Crow","year":"2005","journal-title":"Adv. Water Resour."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"1145","DOI":"10.1175\/BAMS-D-12-00154.1","article-title":"Heihe watershed allied telemetry experimental research (HiWATER): Scientific objectives and experimental design","volume":"94","author":"Li","year":"2013","journal-title":"Bull. Am. Meteorol. Soc."},{"key":"ref_15","unstructured":"Jin, R., and Li, D. HiWATER: Dataset of Retrieved Soil Moisture Products Using PLMR Brightness Temperatures in the Middle Reaches of the Heihe River Basin. Available online: http:\/\/card.westgis.ac.cn\/service\/pdf\/uuid\/e48170e3-b4e6-4d75-80f6-39b4abddc862."},{"key":"ref_16","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."},{"key":"ref_17","first-page":"259","article-title":"Soil moisture retrieval from airborne PLMR and MODIS products in the Zhangye oasis of middle stream of Heihe River Basin, China","volume":"29","author":"Li","year":"2014","journal-title":"Adv. Earth Sci."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"2015","DOI":"10.1109\/LGRS.2014.2319085","article-title":"A nested ecohydrological wireless sensor network for capturing the surface heterogeneity in the midstream areas of the Heihe River Basin, China","volume":"11","author":"Jin","year":"2014","journal-title":"IEEE Geosci. Remote Sens. Lett."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"2125","DOI":"10.1109\/LGRS.2014.2321429","article-title":"A geostatistical approach to upscale soil moisture with unequal precision observations","volume":"11","author":"Wang","year":"2014","journal-title":"IEEE Geosci. Remote Sens. Lett."},{"key":"ref_20","doi-asserted-by":"crossref","unstructured":"Qu, W., Bogena, H.R., Huisman, J.A., and Vereecken, H. (2013). Calibration of a novel low-cost soil water content sensor based on a ring oscillator. Vadose Zone J., 12.","DOI":"10.2136\/vzj2012.0139"},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"1002","DOI":"10.2136\/vzj2009.0173","article-title":"Potential of wireless sensor networks for measuring soil water content variability","volume":"9","author":"Bogena","year":"2010","journal-title":"Vadose Zone J."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"656","DOI":"10.1109\/LGRS.2014.2355871","article-title":"Upscaling sensible heat fluxes with area-to-area regression kriging","volume":"12","author":"Ge","year":"2015","journal-title":"IEEE Geosci. Remote Sens. Lett."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"2294","DOI":"10.1002\/2013JD020803","article-title":"Spatio-temporal interpolation of daily temperatures for global land areas at 1 km resolution","volume":"119","author":"Kilibarda","year":"2014","journal-title":"J. Geophys. Res. Atmos."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"265","DOI":"10.1007\/s00704-011-0464-2","article-title":"Spatio-Temporal prediction of daily temperatures using time-series of MODIS LST images","volume":"107","author":"Hengl","year":"2012","journal-title":"Theor. Appl. Climatol."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"161","DOI":"10.1111\/j.1538-4632.2010.00788.x","article-title":"Space\u2013time geostatistics for geography: A case study of radiation monitoring across parts of Germany","volume":"42","author":"Heuvelink","year":"2010","journal-title":"Geogr. Anal."},{"key":"ref_26","unstructured":"Cressie, N.A.C., and Wikle, C.K. (2011). Statistics for Spatio-Temporal Data, Wiley."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"1027","DOI":"10.1080\/02664760903019422","article-title":"Space-Time correlation analysis: A comparative study","volume":"37","year":"2010","journal-title":"J. Appl. Stat."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"310","DOI":"10.1198\/016214504000000854","article-title":"Space-time covariance functions","volume":"100","author":"Stein","year":"2005","journal-title":"J. Am. Stat. Assoc."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"253","DOI":"10.1016\/S0016-7061(02)00310-5","article-title":"Soil water content interpolation using spatio-temporal kriging with external drift","volume":"112","author":"Snepvangers","year":"2003","journal-title":"Geoderma"},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"683","DOI":"10.1016\/j.cageo.2004.03.012","article-title":"Multivariable geostatistics in S: The gstat package","volume":"30","author":"Pebesma","year":"2004","journal-title":"Computat. Geosci."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"1","DOI":"10.18637\/jss.v051.i07","article-title":"Spacetime: spatio-temporal data in R","volume":"51","author":"Pebesma","year":"2012","journal-title":"J. Stat. Softw."},{"key":"ref_32","unstructured":"R Development Core Team (2014). R: A Language and Environment for Statistical Computing, R Foundation for Statistical Computing."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"1","DOI":"10.18637\/jss.v025.c01","article-title":"A method for visualizing multivariate time series data","volume":"25","author":"Peng","year":"2008","journal-title":"J. Stat. Softw."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"472","DOI":"10.1109\/LGRS.2014.2346784","article-title":"Observation on soil moisture of irrigation cropland by cosmic-ray probe","volume":"12","author":"Zhu","year":"2015","journal-title":"IEEE Geosci. Remote Sens. Lett."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"170","DOI":"10.1016\/j.jhydrol.2015.01.061","article-title":"Inter-comparison of spatial upscaling methods for evaluation of satellite-based soil moisture","volume":"523","author":"Qin","year":"2015","journal-title":"J. Hydrol."}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/7\/9\/11372\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T20:48:03Z","timestamp":1760215683000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/7\/9\/11372"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2015,9,7]]},"references-count":35,"journal-issue":{"issue":"9","published-online":{"date-parts":[[2015,9]]}},"alternative-id":["rs70911372"],"URL":"https:\/\/doi.org\/10.3390\/rs70911372","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2015,9,7]]}}}