{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,9,7]],"date-time":"2024-09-07T06:41:54Z","timestamp":1725691314483},"reference-count":44,"publisher":"MDPI AG","issue":"13","license":[{"start":{"date-parts":[[2022,6,29]],"date-time":"2022-06-29T00:00:00Z","timestamp":1656460800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/100000001","name":"National Science Foundation","doi-asserted-by":"publisher","award":["1643004"],"id":[{"id":"10.13039\/100000001","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000104","name":"NASA","doi-asserted-by":"publisher","award":["80NSSC18K0704"],"id":[{"id":"10.13039\/100000104","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Australian Research Council"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"This paper presents a soil moisture retrieval scheme from Cyclone Global Navigation Satellite System (CYGNSS) delay-Doppler maps (DDMs) over land. The proposed inversion method consists of a hybrid global and local optimization method and a physics-based bistatic scattering forward model. The forward model was developed for bare-to-densely vegetated terrains, and it predicts the circularly polarized bistatic radar cross section DDM of the land surface. This method was tested on both simulated DDMs and CYGNSS DDMs over the Soil Moisture Active Passive (SMAP) Yanco core validation site in Australia. About 250 CYGNSS DDMs from 2019 and 2020 over the Yanco site were used for validation. The simulated DDMs were for grassland and forest vegetation types. The vegetation type of the Yanco validation site was grassland. The vegetation water content (VWC) was 0.19\u00a0kgm\u22122 and 4.89\u00a0kgm\u22122 for the grassland and forest terrains, respectively. For the case when the surface roughness is known to the algorithm, the unbiased root mean square error (ubRMSE) of soil moisture estimates was less than 0.03\u00a0m3m\u22123 while it was approximately 0.06\u00a0m3m\u22123 and 0.09\u00a0m3m\u22123 for the validation results from 2019 and 2020, respectively. The retrieval algorithm generally had enhanced performance for smaller values of soil moisture. For the case when both the soil moisture and surface roughness are unknown to the algorithm and only a single DDM is used for retrieval, the validation results showed an expected reduced performance, with an an ubRMSE of less than 0.12\u00a0m3m\u22123.<\/jats:p>","DOI":"10.3390\/rs14133129","type":"journal-article","created":{"date-parts":[[2022,6,30]],"date-time":"2022-06-30T02:43:28Z","timestamp":1656557008000},"page":"3129","source":"Crossref","is-referenced-by-count":6,"title":["GNSS-R Soil Moisture Retrieval for Flat Vegetated Surfaces Using a Physics-Based Bistatic Scattering Model and Hybrid Global\/Local Optimization"],"prefix":"10.3390","volume":"14","author":[{"ORCID":"http:\/\/orcid.org\/0000-0003-0543-8178","authenticated-orcid":false,"given":"Amir","family":"Azemati","sequence":"first","affiliation":[{"name":"Ming Hsieh Department of Electrical and Computer Engineering, University of Southern California, Los Angeles, CA 90089, USA"}]},{"ORCID":"http:\/\/orcid.org\/0000-0002-7078-0845","authenticated-orcid":false,"given":"Amer","family":"Melebari","sequence":"additional","affiliation":[{"name":"Ming Hsieh Department of Electrical and Computer Engineering, University of Southern California, Los Angeles, CA 90089, USA"}]},{"ORCID":"http:\/\/orcid.org\/0000-0001-6774-5275","authenticated-orcid":false,"given":"James D.","family":"Campbell","sequence":"additional","affiliation":[{"name":"Ming Hsieh Department of Electrical and Computer Engineering, University of Southern California, Los Angeles, CA 90089, USA"}]},{"ORCID":"http:\/\/orcid.org\/0000-0002-4817-2712","authenticated-orcid":false,"given":"Jeffrey P.","family":"Walker","sequence":"additional","affiliation":[{"name":"Department of Civil Engineering, Monash University, Clayton, VIC 3800, Australia"}]},{"ORCID":"http:\/\/orcid.org\/0000-0001-5304-2616","authenticated-orcid":false,"given":"Mahta","family":"Moghaddam","sequence":"additional","affiliation":[{"name":"Ming Hsieh Department of Electrical and Computer Engineering, University of Southern California, Los Angeles, CA 90089, USA"}]}],"member":"1968","published-online":{"date-parts":[[2022,6,29]]},"reference":[{"key":"ref_1","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_2","doi-asserted-by":"crossref","first-page":"596","DOI":"10.1109\/TGRS.2003.821065","article-title":"Quantitative Retrieval of Soil Moisture Content and Surface Roughness from Multipolarized Radar Observations of Bare Soil Surfaces","volume":"42","author":"Yisok","year":"2004","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_3","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_4","doi-asserted-by":"crossref","first-page":"1897","DOI":"10.1109\/TGRS.2016.2631126","article-title":"Surface Soil Moisture Retrieval Using the L-Band Synthetic Aperture Radar Onboard the Soil Moisture Active\u2013Passive Satellite and Evaluation at Core Validation Sites","volume":"55","author":"Kim","year":"2017","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_5","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_6","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_7","doi-asserted-by":"crossref","unstructured":"Hensley, S., Michel, T., Van Zyl, J., Muellerschoen, R., Chapman, B., Oveisgharan, S., Haddad, Z.S., Jackson, T., and Mladenova, I. (2011, January 24\u201329). Effect of Soil Moisture on Polarimetric-Interferometric Repeat Pass Observations by UAVSAR during 2010 Canadian Soil Moisture campaign. Proceedings of the 2011 IEEE International Geoscience and Remote Sensing Symposium, Vancouver, BC, Canada.","DOI":"10.1109\/IGARSS.2011.6049379"},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"2630","DOI":"10.1109\/TGRS.2007.898236","article-title":"Microwave Observatory of Subcanopy and Subsurface (MOSS): A Mission Concept for Global Deep Soil Moisture Observations","volume":"45","author":"Moghaddam","year":"2007","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"4513","DOI":"10.1109\/JSTARS.2018.2873218","article-title":"The Polarimetric L-Band Imaging Synthetic Aperture Radar (PLIS): Description, Calibration, and Cross-Validation","volume":"11","author":"Zhu","year":"2018","journal-title":"IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"468","DOI":"10.1109\/TGRS.2008.2004711","article-title":"Using Envisat Asar Global Mode Data for Surface Soil Moisture Retrieval over Oklahoma, USA","volume":"47","author":"Pathe","year":"2009","journal-title":"IEEE Trans. Geosci. Rem. Sens."},{"key":"ref_11","first-page":"295","article-title":"Soil Moisture Retrieval from Airborne PLMR and MODIS Productsinthe ZhangyeOasisof MiddleStream ofHeihe River Basin, China","volume":"29","author":"Dazhi","year":"2014","journal-title":"Adv. Earth Sci."},{"key":"ref_12","doi-asserted-by":"crossref","unstructured":"Azemati, A., and Moghaddam, M. (2017, January 9\u201314). Modeling and Analysis of Bistatic Scattering from Forests in Support of Soil Moisture Retrieval. Proceedings of the 2017 IEEE International Symposium on Antennas and Propagation USNC\/URSI National Radio Science Meeting, San Diego, CA, USA.","DOI":"10.1109\/APUSNCURSINRSM.2017.8072959"},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"3252","DOI":"10.1109\/TGRS.2008.921495","article-title":"Radar Bistatic Configurations for Soil Moisture Retrieval: A Simulation Study","volume":"46","author":"Pierdicca","year":"2008","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"3616","DOI":"10.1109\/TGRS.2009.2030672","article-title":"Soil Moisture Retrieval Using GNSS-R Techniques: Experimental Results Over a Bare Soil Field","volume":"47","author":"Camps","year":"2009","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"537","DOI":"10.1109\/TGRS.2013.2242332","article-title":"Effects of Near-Surface Soil Moisture on GPS SNR Data: Development of a Retrieval Algorithm for Soil Moisture","volume":"52","author":"Chew","year":"2014","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"4730","DOI":"10.1109\/JSTARS.2016.2588467","article-title":"Sensitivity of GNSS-R Spaceborne Observations to Soil Moisture and Vegetation","volume":"9","author":"Camps","year":"2016","journal-title":"IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens."},{"key":"ref_17","doi-asserted-by":"crossref","unstructured":"Shah, R., Zuffada, C., Chew, C., Lavalle, M., Xu, X., and Azemati, A. (2017, January 11\u201315). Modeling Bistatic Scattering Signatures from Sources of Opportunity in P-Ka Bands. Proceedings of the 2017 International Conference on Electromagnetics in Advanced Applications (ICEAA), Verona, Italy.","DOI":"10.1109\/ICEAA.2017.8065616"},{"key":"ref_18","unstructured":"Ruf, C., Chang, P.S., Clarizia, M.P., Gleason, S., Jelenak, Z., Majumdar, S., Morris, M., Murray, J., Musko, S., and Posselt, D. (2016). CYGNSS Handbook, Michigan Publishing."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"2227","DOI":"10.1109\/JSTARS.2019.2895510","article-title":"Analysis of CYGNSS Data for Soil Moisture Retrieval","volume":"12","author":"Clarizia","year":"2019","journal-title":"IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens."},{"key":"ref_20","doi-asserted-by":"crossref","unstructured":"Chew, C., and Small, E. (2020). Description of the UCAR\/CU Soil Moisture Product. Remote Sens., 12.","DOI":"10.3390\/rs12101558"},{"key":"ref_21","doi-asserted-by":"crossref","unstructured":"Senyurek, V., Lei, F., Boyd, D., Kurum, M., Gurbuz, A.C., and Moorhead, R. (2020). Machine Learning-Based CYGNSS Soil Moisture Estimates over ISMN Sites in CONUS. Remote Sens., 12.","DOI":"10.3390\/rs12071168"},{"key":"ref_22","doi-asserted-by":"crossref","unstructured":"Senyurek, V., Lei, F., Boyd, D., Gurbuz, A.C., Kurum, M., and Moorhead, R. (2020). Evaluations of Machine Learning-Based CYGNSS Soil Moisture Estimates against SMAP Observations. Remote Sens., 12.","DOI":"10.3390\/rs12213503"},{"key":"ref_23","first-page":"3003505","article-title":"Soil Moisture Retrievals Using CYGNSS Data in a Time-Series Ratio Method: Progress Update and Error Analysis","volume":"19","author":"Johnson","year":"2021","journal-title":"IEEE Geosci. Remote Sens. Lett."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"4322","DOI":"10.1109\/TGRS.2018.2890646","article-title":"Time-Series Retrieval of Soil Moisture Using CYGNSS","volume":"57","author":"Johnson","year":"2019","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_25","doi-asserted-by":"crossref","unstructured":"Azemati, A., Moghaddam, M., and Bhat, A. (2018, January 22\u201327). Relationship Between Bistatic Radar Scattering Cross Sections and GPS Reflectometry Delay-Doppler Maps Over Vegetated Land in Support of Soil Moisture Retrieval. Proceedings of the IGARSS 2018\u20142018 IEEE International Geoscience and Remote Sensing Symposium, Valencia, Spain.","DOI":"10.1109\/IGARSS.2018.8517345"},{"key":"ref_26","doi-asserted-by":"crossref","unstructured":"Azemati, A., and Moghaddam, M. (2017, January 11\u201315). Circular-Linear Polarization Signatures in Bistatic Scattering Models Applied to Signals of Opportunity. Proceedings of the 2017 International Conference on Electromagnetics in Advanced Applications (ICEAA), Verona, Italy.","DOI":"10.1109\/ICEAA.2017.8065654"},{"key":"ref_27","unstructured":"Azemati, A., Bhat, A., Walker, J., and Moghaddam, M. A Discrete Scatterer Bistatic Radar Scattering Model for Vegetated Land Surface in Support of Soil Moisture Retrieval. IEEE Trans. Geosci. Remote Sens., in-review."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"167","DOI":"10.1109\/JMMCT.2018.2875107","article-title":"Electromagnetic Imaging of Dielectric Objects Using a Multidirectional-Search-Based Simulated Annealing","volume":"3","author":"Etminan","year":"2018","journal-title":"IEEE J. Multiscale Multiphys. Comput. Tech."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"290","DOI":"10.1109\/36.17670","article-title":"Modeling and Observation of the Radar Polarization Signature of Forested Areas","volume":"27","author":"Durden","year":"1989","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"2059","DOI":"10.1109\/TGRS.2008.2011631","article-title":"Physically and Mineralogically Based Spectroscopic Dielectric Model for Moist Soils","volume":"47","author":"Mironov","year":"2009","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"4832","DOI":"10.1109\/TGRS.2011.2172949","article-title":"A Generalized Radar Backscattering Model Based on Wave Theory for Multilayer Multispecies Vegetation","volume":"49","author":"Burgin","year":"2011","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_32","doi-asserted-by":"crossref","unstructured":"Ulaby, F., Long, D., Blackwell, W., Elachi, C., Fung, A., Ruf, C., Sarabandi, K., Zebker, H., and Van Zyl, J. (2014). Microwave Radar and Radiometric Remote Sensing, University of Michigan Press.","DOI":"10.3998\/0472119356"},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"3944","DOI":"10.1109\/TGRS.2016.2532123","article-title":"Generalized Terrain Topography in Radar Scattering Models","volume":"54","author":"Burgin","year":"2016","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_34","unstructured":"Campbell, J.D. (2019). Electromagnetic Scattering Models for Satellite Remote Sensing of Soil Moisture Using Reflectometry from Microwave Signals of Opportunity. [Ph.D. Thesis, University of Southern California]."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"1959","DOI":"10.1109\/TGRS.2017.2771253","article-title":"Bistatic Radar Equation for Signals of Opportunity Revisited","volume":"56","author":"Voronovich","year":"2018","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"1381","DOI":"10.1109\/TGRS.2013.2250980","article-title":"Models of L-Band Radar Backscattering Coefficients Over Global Terrain for Soil Moisture Retrieval","volume":"52","author":"Kim","year":"2014","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_37","doi-asserted-by":"crossref","unstructured":"Smith, A.B., Walker, J.P., Western, A.W., Young, R.I., Ellett, K.M., Pipunic, R.C., Grayson, R.B., 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_38","unstructured":"Young, R., Walker, J., Yeoh, N., Smith, A., Ellett, K., Merlin, O., and Western, A. (2008). Soil Moisture and Meteorological Observations From the Murrumbidgee Catchment, Department of Civil and Environmental Engineering, The University of Melbourne. Technical Report."},{"key":"ref_39","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. Hydrometeorol."},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"347","DOI":"10.1109\/TGRS.2012.2198920","article-title":"Canadian Experiment for Soil Moisture in 2010 (CanEx-SM10): Overview and Preliminary Results","volume":"51","author":"Magagi","year":"2013","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"645","DOI":"10.1109\/TGRS.2014.2326839","article-title":"P-Band Radar Retrieval of Subsurface Soil Moisture Profile as a Second-Order Polynomial: First AirMOSS Results","volume":"53","author":"Tabatabaeenejad","year":"2015","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_42","unstructured":"Tissott, B., and Mueller, N. (2022, June 23). DEA Land Cover 25m, Geoscience Australia, Canberra, Available online: https:\/\/ecat.ga.gov.au\/geonetwork\/srv\/eng\/catalog.search#\/metadata\/146090."},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"1740","DOI":"10.1109\/JSTARS.2020.2981570","article-title":"Modeling the Effects of Topography on Delay-Doppler Maps","volume":"13","author":"Campbell","year":"2020","journal-title":"IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens."},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"560","DOI":"10.1109\/TGRS.2002.1000316","article-title":"Delay-Doppler Analysis of Bistatically Reflected Signals from the Ocean Surface: Theory and Application","volume":"40","author":"Elfouhaily","year":"2002","journal-title":"IEEE Trans. Geosci. Remote Sens."}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/14\/13\/3129\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,8,1]],"date-time":"2024-08-01T07:08:48Z","timestamp":1722496128000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/14\/13\/3129"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,6,29]]},"references-count":44,"journal-issue":{"issue":"13","published-online":{"date-parts":[[2022,7]]}},"alternative-id":["rs14133129"],"URL":"https:\/\/doi.org\/10.3390\/rs14133129","relation":{},"ISSN":["2072-4292"],"issn-type":[{"type":"electronic","value":"2072-4292"}],"subject":[],"published":{"date-parts":[[2022,6,29]]}}}