{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,29]],"date-time":"2026-09-29T12:19:20Z","timestamp":1790684360185,"version":"4.1.0"},"reference-count":42,"publisher":"MDPI AG","issue":"11","license":[{"start":{"date-parts":[[2018,11,20]],"date-time":"2018-11-20T00:00:00Z","timestamp":1542672000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100002830","name":"Centre National d\u2019Etudes Spatiales","doi-asserted-by":"publisher","award":["No Number"],"award-info":[{"award-number":["No Number"]}],"id":[{"id":"10.13039\/501100002830","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100000844","name":"European Space Agency","doi-asserted-by":"publisher","award":["No Number"],"award-info":[{"award-number":["No Number"]}],"id":[{"id":"10.13039\/501100000844","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Global soil moisture (SM) products are currently available thanks to microwave remote sensing techniques. Validation of these satellite-based SM products over different vegetation and climate conditions is a crucial step. INRA (National Institute of Agricultural Research) has set up the AQUI SM and soil temperature in situ network (composed of three main sites Bouron, Bilos, and Hermitage), over a flat area of dense pine forests, in South-Western France (the Bordeaux\u2013Aquitaine region) to validate the Soil Moisture and Ocean salinity (SMOS) satellite SM products. SMOS was launched in 2009 by the European Space Agency (ESA). The aims of this study are to present the AQUI network and to evaluate the SMOS SM product (in the new SMOS-IC version) along with other microwave SM products such as the active ASCAT (Advanced Scatterometer) and the ESA combined (passive and active) CCI (Climate Change Initiative) SM retrievals. A first comparison, using Pearson correlation, Bias, RMSE (Root Mean Square Error), and Un biased RMSE (ubRMSE) scores, between the 0\u20135 cm AQUI network and ASCAT, CCI, and SMOS SM products was conducted. In general all the three products were able to reproduce the annual cycle of the AQUI in situ observations. CCI and ASCAT had best and similar correlations (R~0.72) over the Bouron and Bilos sites. All had comparable correlations over the Hermitage sites with overall average values of 0.74, 0.68, and 0.69 for CCI, SMOS-IC, and ASCAT, respectively. Considering anomalies, correlation values decreased for all products with best ability to capture day to day variations obtained by ASCAT. CCI (followed by SMOS-IC) had the best ubRMSE values (mostly &lt; 0.04 m3\/m3) over most of the stations. Although the region is highly impacted by radio frequency interferences, SMOS-IC followed correctly the in situ SM dynamics. All the three remotely-sensed SM products (except SMOS-IC over some stations) overestimated the AQUI in situ SM observations. These results demonstrate that the AQUI network is likely to be well-suited for satellite microwave remote sensing evaluations\/validations.<\/jats:p>","DOI":"10.3390\/rs10111839","type":"journal-article","created":{"date-parts":[[2018,11,21]],"date-time":"2018-11-21T11:23:27Z","timestamp":1542799407000},"page":"1839","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":49,"title":["The AQUI Soil Moisture Network for Satellite Microwave Remote Sensing Validation in South-Western France"],"prefix":"10.3390","volume":"10","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-7530-6088","authenticated-orcid":false,"given":"A.","family":"Al-Yaari","sequence":"first","affiliation":[{"name":"INRA, UMR1391 ISPA, CS 20032 33882 Villenave d\u2019Ornon, France"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"S.","family":"Dayau","sequence":"additional","affiliation":[{"name":"INRA, UMR1391 ISPA, CS 20032 33882 Villenave d\u2019Ornon, France"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"C.","family":"Chipeaux","sequence":"additional","affiliation":[{"name":"INRA, UMR1391 ISPA, CS 20032 33882 Villenave d\u2019Ornon, France"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"C.","family":"Aluome","sequence":"additional","affiliation":[{"name":"INRA, UMR1391 ISPA, CS 20032 33882 Villenave d\u2019Ornon, France"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"A.","family":"Kruszewski","sequence":"additional","affiliation":[{"name":"INRA, UMR1391 ISPA, CS 20032 33882 Villenave d\u2019Ornon, France"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"D.","family":"Loustau","sequence":"additional","affiliation":[{"name":"INRA, UMR1391 ISPA, CS 20032 33882 Villenave d\u2019Ornon, France"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"J.-P.","family":"Wigneron","sequence":"additional","affiliation":[{"name":"INRA, UMR1391 ISPA, CS 20032 33882 Villenave d\u2019Ornon, France"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2018,11,20]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"7976","DOI":"10.1175\/JCLI-D-13-00591.1","article-title":"Impact of Soil Moisture\u2013Atmosphere Interactions on Surface Temperature Distribution","volume":"27","author":"Berg","year":"2014","journal-title":"J. Clim."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"125","DOI":"10.1016\/j.earscirev.2010.02.004","article-title":"Investigating soil moisture\u2013climate interactions in a changing climate: A review","volume":"99","author":"Seneviratne","year":"2010","journal-title":"Earth-Sci. Rev."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"274","DOI":"10.1016\/j.jhydrol.2008.08.023","article-title":"Flash flood warning based on rainfall thresholds and soil moisture conditions: An assessment for gauged and ungauged basins","volume":"362","author":"Norbiato","year":"2008","journal-title":"J. Hydrol."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"57","DOI":"10.1109\/JSTARS.2009.2037163","article-title":"Evaluating the Utility of Remotely Sensed Soil Moisture Retrievals for Operational Agricultural Drought Monitoring","volume":"3","author":"Bolten","year":"2010","journal-title":"IEEE J. Sel. Top. Appl. Earth Observ. 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":"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_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":"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_9","doi-asserted-by":"crossref","first-page":"1675","DOI":"10.5194\/hess-15-1675-2011","article-title":"The International Soil Moisture Network: A data hosting facility for global in situ soil moisture measurements","volume":"15","author":"Dorigo","year":"2011","journal-title":"Hydrol. Earth Syst. Sci."},{"key":"ref_10","doi-asserted-by":"crossref","unstructured":"Dorigo, W.A., Xaver, A., Vreugdenhil, M., Gruber, A., Hegyiov\u00e1, A., Sanchis-Dufau, A.D., Zamojski, D., Cordes, C., Wagner, W., and Drusch, M. (2013). Global Automated Quality Control of In Situ Soil Moisture Data from the International Soil Moisture Network. Vadose Zone J., 12.","DOI":"10.2136\/vzj2012.0097"},{"key":"ref_11","doi-asserted-by":"crossref","unstructured":"Wigneron, J.P., Dayan, S., Kruszewski, A., Aluome, C., AI-Yaari, M.G.E.A., Fan, L., Guven, S., Chipeaux, C., Moisy, C., and Guyon, D. (2018, January 26\u201330). The Aqui Network: Soil Moisture Sites in the \u201cLes Landes\u201d Forest and Graves Vineyards (Bordeaux Aquitaine Region). Proceedings of the 2018 IEEE International Geoscience and Remote Sensing Symposium (IGARSS 2018), Valancia, Spain.","DOI":"10.1109\/IGARSS.2018.8517392"},{"key":"ref_12","doi-asserted-by":"crossref","unstructured":"Motte, E., Zribi, M., Fanise, P., Egido, A., Darrozes, J., Al-Yaari, A., Baghdadi, N., Baup, F., Dayau, S., and Fieuzal, R. (2016). GLORI: A GNSS-R Dual Polarization Airborne Instrument for Land Surface Monitoring. Sensors, 16.","DOI":"10.3390\/s16050732"},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"2024","DOI":"10.1109\/TGRS.2005.853568","article-title":"A forest geometric description of a maritime pine forest suitable for discrete microwave models","volume":"43","author":"Saleh","year":"2005","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"403","DOI":"10.1109\/36.134089","article-title":"Relating forest biomass to SAR data","volume":"30","author":"Toan","year":"1992","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"164","DOI":"10.1016\/j.isprsjprs.2014.07.008","article-title":"Automated retrieval of forest structure variables based on multi-scale texture analysis of VHR satellite imagery","volume":"96","author":"Beguet","year":"2014","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_16","doi-asserted-by":"crossref","unstructured":"Zribi, M., Motte, E., Baghdadi, N., Baup, F., Dayau, S., Fanise, P., Guyon, D., Huc, M., and Wigneron, J. (2018). Potential Applications of GNSS-R Observations over Agricultural Areas: Results from the GLORI Airborne Campaign. Remote Sens., 10.","DOI":"10.3390\/rs10081245"},{"key":"ref_17","doi-asserted-by":"crossref","unstructured":"Zribi, M., Guyon, D., Motte, E., Wigneron, J.-P., Dayau, S., Baghdadi, N., and Pierdicca, N. (2019). Performances of GNSS-R GLORI data over Landes forest in France. Int. J. Appl. Earth Obs. Geoinf., 74.","DOI":"10.1016\/j.jag.2018.09.010"},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"1051","DOI":"10.1046\/j.1365-2486.2003.00627.x","article-title":"The annual carbon budget of a French pine forest (Pinus pinaster) following harvest","volume":"9","author":"Kowalski","year":"2003","journal-title":"Glob. Change Biol."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"669","DOI":"10.5194\/bg-15-669-2018","article-title":"Hydro-ecological controls on dissolved carbon dynamics in groundwater and export to streams in a temperate pine forest","volume":"15","author":"Deirmendjian","year":"2018","journal-title":"Biogeosciences"},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"1427","DOI":"10.1109\/TGRS.2012.2182775","article-title":"SMOS Radio Frequency Interference Scenario: Status and Actions Taken to Improve the RFI Environment in the 1400\u20131427-MHz Passive Band","volume":"50","author":"Oliva","year":"2012","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"64","DOI":"10.1016\/j.rse.2016.01.013","article-title":"Status of Radio Frequency Interference (RFI) in the 1400\u20131427 MHz passive band based on six years of SMOS mission","volume":"180","author":"Oliva","year":"2016","journal-title":"Remote Sens. Environ."},{"key":"ref_22","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_23","doi-asserted-by":"crossref","first-page":"639","DOI":"10.1016\/j.rse.2006.10.014","article-title":"L-band Microwave Emission of the Biosphere (L-MEB) Model: Description and calibration against experimental data sets over crop fields","volume":"107","author":"Wigneron","year":"2007","journal-title":"Remote Sens. Environ."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"238","DOI":"10.1016\/j.rse.2017.01.024","article-title":"Modelling the passive microwave signature from land surfaces: A review of recent results and application to the L-band SMOS & SMAP soil moisture retrieval algorithms","volume":"192","author":"Wigneron","year":"2017","journal-title":"Remote Sens. Environ."},{"key":"ref_25","doi-asserted-by":"crossref","unstructured":"Al-Yaari, A., Mialon, A., Dorigo, W., Colliander, A., Fan, L., Kerr, Y., Pellarin, T., and Wigneron, J.-P. (2018, January 26\u201330). Validation of satellite microwave retrieved soil moisture with global ground-based measurements. Proceedings of the 2018 IEEE International Geoscience and Remote Sensing Symposium (IGARSS 2018), Valancia, Spain.","DOI":"10.1109\/IGARSS.2018.8517557"},{"key":"ref_26","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":"Wigneron","year":"2014","journal-title":"Remote Sens. Environ."},{"key":"ref_27","doi-asserted-by":"crossref","unstructured":"Fernandez-Moran, R., Al-Yaari, A., Mialon, A., Mahmoodi, A., Al Bitar, A., De Lannoy, G., Rodriguez-Fernandez, N., Lopez-Baeza, E., Kerr, Y., and Wigneron, J.-P. (2017). SMOS-IC: An Alternative SMOS Soil Moisture and Vegetation Optical Depth Product. Remote Sens., 9.","DOI":"10.20944\/preprints201703.0145.v1"},{"key":"ref_28","first-page":"27","article-title":"A new calibration of the effective scattering albedo and soil roughness parameters in the SMOS SM retrieval algorithm","volume":"62","author":"Wigneron","year":"2017","journal-title":"Int. J. Appl. Earth Obs. Geoinf."},{"key":"ref_29","unstructured":"PUM (2018, May 09). Product User Manual (PUM) Soil Moisture Data Records, Metop ASCAT Soil Moisture Time Series. Available online: http:\/\/hsaf.meteoam.it\/documents\/PUM\/SSM_ASCAT_DR_PUM_v0.4.pdf."},{"key":"ref_30","first-page":"1","article-title":"Validation of the ASCAT Soil Water Index using in situ data from the International Soil Moisture Network","volume":"30","author":"Paulik","year":"2014","journal-title":"Int. J. Appl. Earth Obs. Geoinf."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"280","DOI":"10.1016\/j.rse.2012.03.014","article-title":"Trend-preserving blending of passive and active microwave soil moisture retrievals","volume":"123","author":"Liu","year":"2012","journal-title":"Remote Sens. Environ."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"185","DOI":"10.1016\/j.rse.2017.07.001","article-title":"ESA CCI Soil Moisture for improved Earth system understanding: State-of-the art and future directions","volume":"203","author":"Dorigo","year":"2017","journal-title":"Remote Sens. Environ."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"381","DOI":"10.1175\/BAMS-85-3-381","article-title":"The Global Land Data Assimilation System","volume":"85","author":"Rodell","year":"2004","journal-title":"Bull. Am. Meteorol. Soc."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"115","DOI":"10.5194\/hess-13-115-2009","article-title":"An evaluation of ASCAT surface soil moisture products with in-situ observations in Southwestern France","volume":"13","author":"Albergel","year":"2009","journal-title":"Hydrol. Earth Syst. Sci."},{"key":"ref_35","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":"Wigneron","year":"2014","journal-title":"Remote Sens. Environ."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"3390","DOI":"10.1016\/j.rse.2011.08.003","article-title":"Soil moisture estimation through ASCAT and AMSR-E sensors: An intercomparison and validation study across Europe","volume":"115","author":"Brocca","year":"2011","journal-title":"Remote Sens. Environ."},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"827","DOI":"10.1038\/s41559-018-0530-6","article-title":"Satellite passive microwaves reveal recent climate-induced carbon losses in African drylands","volume":"2","author":"Brandt","year":"2018","journal-title":"Nat. Ecol. Evol."},{"key":"ref_38","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_39","doi-asserted-by":"crossref","unstructured":"Rodr\u00edguez-Fern\u00e1ndez, J.N., Kerr, H.Y., van der Schalie, R., Al-Yaari, A., Wigneron, J.-P., de Jeu, R., Richaume, P., Dutra, E., Mialon, A., and Drusch, M. (2016). Long Term Global Surface Soil Moisture Fields Using an SMOS-Trained Neural Network Applied to AMSR-E Data. Remote Sens., 8.","DOI":"10.3390\/rs8110959"},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"1562","DOI":"10.1109\/TGRS.2013.2252468","article-title":"Comparison Between SMOS, VUA, ASCAT, and ECMWF Soil Moisture Products Over Four Watersheds in U.S","volume":"52","author":"Leroux","year":"2013","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"257","DOI":"10.1016\/j.rse.2017.03.010","article-title":"Evaluating soil moisture retrievals from ESA\u2019s SMOS and NASA\u2019s SMAP brightness temperature datasets","volume":"193","author":"Wigneron","year":"2017","journal-title":"Remote Sens. Environ."},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"995","DOI":"10.1016\/j.rse.2009.12.011","article-title":"Effective soil moisture sampling depth of L-band radiometry: A case study","volume":"114","author":"Escorihuela","year":"2010","journal-title":"Remote Sens. Environ."}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/10\/11\/1839\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T15:30:56Z","timestamp":1760196656000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/10\/11\/1839"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2018,11,20]]},"references-count":42,"journal-issue":{"issue":"11","published-online":{"date-parts":[[2018,11]]}},"alternative-id":["rs10111839"],"URL":"https:\/\/doi.org\/10.3390\/rs10111839","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2018,11,20]]}}}