Widespread occurrence of anomalous C-band backscatter signals in arid environments caused by subsurface scattering

Download

Preview

Text (Open Access) - Published Version
· Available under License Creative Commons Attribution.
· Please see our End User Agreement before downloading. | Preview

Available under license: Creative Commons Attribution

Advice

Please see our End User Agreement.

It is advisable to refer to the publisher's version if you intend to cite from this work. See Guidance on citing.

Tools

Lists

Wagner, W., Lindorfer, R., Melzer, T., Hahn, S., Bauer-Marschallinger, B., Morrison, K. ORCID: https://orcid.org/0000-0002-8075-0316, Calvet, J.-C., Hobbs, S., Quast, R., Greimeister-Pfeil, I. and Vreugdenhil, M. (2022) Widespread occurrence of anomalous C-band backscatter signals in arid environments caused by subsurface scattering. Remote Sensing of Environment, 276. 113025. ISSN 0034-4257 doi: 10.1016/j.rse.2022.113025

Abstract/Summary

Backscatter measured by scatterometers and Synthetic Aperture Radars is sensitive to the dielectric properties of the soil and normally increases with increasing soil moisture content. However, when the soil is dry, the radar waves penetrate deeper into the soil, potentially sensing subsurface scatterers such as near-surface rocks and stones. In this paper we propose an exponential model to describe the impact of such subsurface scatterers on CBand backscatter measurements acquired by the Advanced Scatterometer (ASCAT) on board of the METOP satellites. The model predicts an increase of the subsurface scattering contributions with decreasing soil wetness that may counteract the signal from the soil surface. This may cause anomalous backscatter signals that deteriorate soil moisture retrievals from ASCAT. We test whether this new model is able to explain ASCAT observations better than a bare soil backscatter model without a subsurface scattering term, using k-fold cross validation and the Bayesian Information Criterion for model selection. We find that arid landscapes with Leptosols and Arenosols represent ideal environmental conditions for the occurrence of subsurface scattering. Nonetheless, subsurface scattering may also become important in more humid environments during dry spells. We conclude that subsurface scattering is a widespread phenomenon that (i) needs to be accounted for in active microwave soil moisture retrievals and (ii) has a potential for soil mapping, particularly in arid and semi-arid environments.

Altmetric Badge

Item Type	Article
URI	https://reading-clone.eprints-hosting.org/id/eprint/105203
Identification Number/DOI	10.1016/j.rse.2022.113025
Refereed	Yes
Divisions	Science > School of Mathematical, Physical and Computational Sciences > Department of Meteorology
Uncontrolled Keywords	ASCAT Radar backscatter Scattering Deserts Arid environments
Publisher	Elsevier
Download/View statistics	View download statistics for this item

Download Statistics

Downloads

Downloads per month over past year

Deposit Details

Date Deposited:	19 May 2022 10:55	Date item deposited into CentAUR
Last Modified:	23 Jun 2024 05:31	Date item last modified

References

Anderson et al., 2017 C. Anderson, J. Figa-Saldana, J.J.W. Wilson, F. Ticconi Validation and cross-validation methods for ASCAT IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens., 10 (2017), pp. 2232-2239 URL View Record in ScopusGoogle Scholar Attema and Ulaby, 1978 E.P.W. Attema, F.T. Ulaby Vegetation modeled as a water cloud Radio Sci., 13 (1978), pp. 357-364, 10.1029/RS013i002p00357 View PDFView Record in ScopusGoogle Scholar Bahar, 1981 E. Bahar Scattering cross sections for composite random surfaces: full wave analysis Radio Sci., 16 (1981), pp. 1327-1335, 10.1029/RS016i006p01327 View PDFView Record in ScopusGoogle Scholar Bartalis et al., 2006 Z. Bartalis, K. Scipal, W. Wagner Azimuthal anisotropy of scatterometer measurements over land IEEE Trans. Geosci. Remote Sens., 44 (2006), pp. 2083-2092 URL http://ieeexplore.ieee.org/document/1661797/ https://doi.org/10.1109/TGRS.2006.872084 View PDFCrossRefView Record in ScopusGoogle Scholar Bartalis et al., 2007 Z. Bartalis, W. Wagner, V. Naeimi, S. Hasenauer, K. Scipal, H. Bonekamp, J. Figa, C. Anderson Initial soil moisture retrievals from the METOP-A Advanced Scatterometer (ASCAT) Geophys. Res. Lett., 34 (2007), p. L20401, 10.1029/2007GL031088 View PDFView Record in ScopusGoogle Scholar Bauer-Marschallinger et al., 2019 B. Bauer-Marschallinger, V. Freeman, S. Cao, C. Paulik, S. Schaufler, T. Stachl, S. Modanesi, C. Massari, L. Ciabatta, L. Brocca, W. Wagner Toward global soil moisture monitoring with Sentinel-1: harnessing assets and overcoming obstacles IEEE Trans. Geosci. Remote Sens., 57 (2019), pp. 520-539 URL View PDFCrossRefView Record in ScopusGoogle Scholar Beck et al., 2018 H.E. Beck, N.E. Zimmermann, T.R. McVicar, N. Vergopolan, A. Berg, E.F. Wood Present and future Köppen-Geiger climate classification maps at 1-km resolution Sci. Data, 5 (2018), p. 180214 URL http://www.nature.com/articles/sdata2018214 https://doi.org/10.1038/sdata.2018.214 View Record in ScopusGoogle Scholar Branch et al., 1999 M.A. Branch, T.F. Coleman, Y. Li A subspace, interior, and conjugate gradient method for large-scale bound-constrained minimization problems SIAM J. Sci. Comput., 21 (1999), pp. 1-23, 10.1137/S1064827595289108 View PDFView Record in ScopusGoogle Scholar Chen et al., 2017 Z. Chen, A.S. Auler, M. Bakalowicz, D. Drew, F. Griger, J. Hartmann, G. Jiang, N. Moosdorf, A. Richts, Z. Stevanovic, G. Veni, N. Goldscheider The world karst aquifer mapping project: concept, mapping procedure and map of Europe Hydrogeol. J., 25 (2017), pp. 771-785, 10.1007/s10040-016-1519-3 View PDFGoogle Scholar Crow et al., 2010 W.T. Crow, W. Wagner, V. Naeimi The impact of radar incidence angle on soil-moisture-retrieval skill IEEE Geosci. Remote Sens. Lett., 7 (2010), pp. 501-505, 10.1109/LGRS.2010.2040134 View PDFView Record in ScopusGoogle Scholar de Jeu et al., 2008 R.A.M. de Jeu, W. Wagner, T.R.H. Holmes, A.J. Dolman, N.C. van de Giesen, J. Friesen Global soil moisture patterns observed by space borne microwave radiometers and scatterometers Surv. Geophys., 29 (2008), pp. 399-420, 10.1007/s10712-008-9044-0 View PDFGoogle Scholar Dobson and Ulaby, 1986 M. Dobson, F. Ulaby Active microwave soil moisture research IEEE Trans. Geosci. Remote Sens., GE-24 (1986), pp. 23-36 URL View PDFCrossRefView Record in ScopusGoogle Scholar Dobson et al., 1985 M. Dobson, F. Ulaby, M. Hallikainen, M. El-rayes Microwave dielectric behavior of wet soil-part II: dielectric mixing models IEEE Trans. Geosci. Remote Sens., GE-23 (1985), pp. 35-46 URL View Record in ScopusGoogle Scholar Dorigo et al., 2010 W.A. Dorigo, K. Scipal, R.M. Parinussa, Y.Y. Liu, W. Wagner, R.A.M. de Jeu, V. Naeimi Error characterisation of global active and passive microwave soil moisture datasets Hydrol. Earth Syst. Sci., 14 (2010), pp. 2605-2616 URL View PDFCrossRefView Record in ScopusGoogle Scholar Dubois et al., 1995 P. Dubois, J. van Zyl, T. Engman Measuring soil moisture with imaging radars IEEE Trans. Geosci. Remote Sens., 33 (1995), pp. 915-926 URL http://ieeexplore.ieee.org/document/406677/ https://doi.org/10.1109/36.406677 View Record in ScopusGoogle Scholar Entekhabi et al., 2010 D. Entekhabi, E.G. Njoku, P.E. O'Neill, K.H. Kellogg, W.T. Crow, W.N. Edelstein, J.K. Entin, S.D. Goodman, T.J. Jackson, J. Johnson, J. Kimball, J.R. Piepmeier, R.D. Koster, N. Martin, K.C. McDonald, M. Moghaddam, S. Moran, R. Reichle, J.C. Shi, M.W. Spencer, S.W. Thurman, L. Tsang, J. Van Zyl The soil moisture active passive (SMAP) mission Proc. IEEE, 98 (2010), pp. 704-716 URL View Record in ScopusGoogle Scholar ESA, 2017 ESA ESA Land Cover CCI Product User Guide - v2.0 - CCI-LC-PUGv2 URL https://www.esa-landcover-cci.org/?q=webfm_send/112 (2017) Google Scholar Escorihuela and Quintana-Seguí, 2016 M.J. Escorihuela, P. Quintana-Seguí Comparison of remote sensing and simulated soil moisture datasets in Mediterranean landscapes Remote Sens. Environ., 180 (2016), pp. 99-114 URL https://linkinghub.elsevier.com/retrieve/pii/S0034425716300748 https://doi.org/10.1016/j.rse.2016.02.046 ArticleDownload PDFView Record in ScopusGoogle Scholar Fascetti et al., 2016 F. Fascetti, N. Pierdicca, L. Pulvirenti, R. Crapolicchio, J. Muñoz-Sabater A comparison of ASCAT and SMOS soil moisture retrievals over Europe and Northern Africa from 2010 to 2013 Int. J. Appl. Earth Obs. Geoinf., 45 (2016), pp. 135-142 URL https://linkinghub.elsevier.com/retrieve/pii/S0303243415300313 https://doi.org/10.1016/j.jag.2015.09.008 ArticleDownload PDFView Record in ScopusGoogle Scholar Figa-Saldaña et al., 2002 J. Figa-Saldaña, J.J.W. Wilson, E.P.W. Attema, R. Gelsthorpe, M.R. Drinkwater, A. Stoffelen The advanced scatterometer (ASCAT) on the meteorological operational (MetOp) platform: a follow on for European wind scatterometers Can. J. Remote. Sens., 28 (2002), pp. 404-412, 10.5589/m02-035 View PDFGoogle Scholar Frießenbichler, 2020 M. Frießenbichler An Analysis of the Radar Subsurface Scattering Phenomenon Observed in the Metop ASCAT Soil Moisture Product over South Africa Ph.D. thesis Technische Universität Wien, Vienna, Austria (2020) Google Scholar Fung et al., 2002 A. Fung, W. Liu, K. Chen, M. Tsay An improved IEM model for bistatic scattering from rough surfaces J. Electromagnet. Wave Appl., 16 (2002), pp. 689-702, 10.1163/156939302X01119 View PDFView Record in ScopusGoogle Scholar Hahn et al., 2017 S. Hahn, C. Reimer, M. Vreugdenhil, T. Melzer, W. Wagner Dynamic characterization of the incidence angle dependence of backscatter using Metop ASCAT IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens., 10 (2017), pp. 2348-2359 URL View Record in ScopusGoogle Scholar Hahn et al., 2021 S. Hahn, W. Wagner, S.C. Steele-Dunne, M. Vreugdenhil, T. Melzer Improving ASCAT soil moisture retrievals with an enhanced spatially variable vegetation parameterization IEEE Trans. Geosci. Remote Sens., 59 (2021), pp. 8241-8256 URL View PDFCrossRefView Record in ScopusGoogle Scholar Hastie et al., 2009 T. Hastie, R. Tibshirani, J. Friedman The Elements of Statistical Learning. Springer Series in Statistics Springer New York, New York, NY (2009), 10.1007/978-0-387-84858-7 View PDFGoogle Scholar Hengl et al., 2017 T. Hengl, J. Mendes de Jesus, G.B.M. Heuvelink, M. Ruiperez Gonzalez, M. Kilibarda, A. Blagotić, W. Shangguan, M.N. Wright, X. Geng, B. Bauer-Marschallinger, M.A. Guevara, R. Vargas, R.A. MacMillan, N.H. Batjes, J.G.B. Leenaars, E. Ribeiro, I. Wheeler, S. Mantel, B. Kempen SoilGrids250m: global gridded soil information based on machine learning PLoS One, 12 (2017), Article e0169748, 10.1371/journal.pone.0169748 View PDFView Record in ScopusGoogle Scholar Hersbach et al., 2020 H. Hersbach, B. Bell, P. Berrisford, S. Hirahara, A. Horányi, J. Muñoz-Sabater, J. Nicolas, C. Peubey, R. Radu, D. Schepers, A. Simmons, C. Soci, S. Abdalla, X. Abellan, G. Balsamo, P. Bechtold, G. Biavati, J. Bidlot, M. Bonavita, G. Chiara, P. Dahlgren, D. Dee, M. Diamantakis, R. Dragani, J. Flemming, R. Forbes, M. Fuentes, A. Geer, L. Haimberger, S. Healy, R.J. Hogan, E. Hólm, M. Janisková, S. Keeley, P. Laloyaux, P. Lopez, C. Lupu, G. Radnoti, P. Rosnay, I. Rozum, F. Vamborg, S. Villaume, J. Thépaut The ERA5 global reanalysis Q. J. R. Meteorol. Soc., 146 (2020), pp. 1999-2049, 10.1002/qj.3803 View PDFView Record in ScopusGoogle Scholar Jaruwatanadilok and Stiles, 2014 S. Jaruwatanadilok, B.W. Stiles Trends and variation in Ku-band backscatter of natural targets on land observed in QuikSCAT data IEEE Trans. Geosci. Remote Sens., 52 (2014), pp. 4383-4390 URL View Record in ScopusGoogle Scholar Kerr et al., 2012 Y.H. Kerr, P. Waldteufel, P. Richaume, J.P. Wigneron, P. Ferrazzoli, A. Mahmoodi, A. Al Bitar, F. Cabot, C. Gruhier, S.E. Juglea, D. Leroux, A. Mialon, S. Delwart The SMOS soil moisture retrieval algorithm IEEE Trans. Geosci. Remote Sens., 50 (2012), pp. 1384-1403 URL Google Scholar Kim and van Zyl, 2009 Y. Kim, J. van Zyl A time-series approach to estimate soil moisture using polarimetric radar data IEEE Trans. Geosci. Remote Sens., 47 (2009), pp. 2519-2527 URL View Record in ScopusGoogle Scholar Liu et al., 2016 P.W. Liu, J. Judge, R.D. DeRoo, A.W. England, T. Bongiovanni, A. Luke Dominant backscattering mechanisms at L-band during dynamic soil moisture conditions for sandy soils Remote Sens. Environ., 178 (2016), pp. 104-112 URL https://linkinghub.elsevier.com/retrieve/pii/S0034425716300918 https://doi.org/10.1016/j.rse.2016.02.062 ArticleDownload PDFView Record in ScopusGoogle Scholar Magagi and Kerr, 1997 R.D. Magagi, Y.H. Kerr Retrieval of soil moisture and vegetation characteristics by use of ERS-1 wind scatterometer over arid and semi-arid areas J. Hydrol., 188-189 (1997), pp. 361-384 URL https://www.sciencedirect.com/science/article/pii/S0022169496031666 https://doi.org/10.1016/S0022-1694(96)03166-6 ArticleDownload PDFView Record in ScopusGoogle Scholar McCauley et al., 1982 J.F. McCauley, G.G. Schaber, C.S. Breed, M.J. Grolier, C.V. Haynes, B. Issawi, C. Elachi, R. Blom Subsurface valleys and geoarcheology of the eastern Sahara revealed by shuttle radar Science, 218 (1982), pp. 1004-1020, 10.1126/science.218.4576.1004 View PDFView Record in ScopusGoogle Scholar McColl et al., 2014 K.A. McColl, D. Entekhabi, M. Piles Uncertainty analysis of soil moisture and vegetation indices using aquarius scatterometer observations IEEE Trans. Geosci. Remote Sens., 52 (2014), pp. 4259-4272 URL View Record in ScopusGoogle Scholar Miyaoka et al., 2017 K. Miyaoka, A. Gruber, F. Ticconi, S. Hahn, W. Wagner, J. Figa-Saldana, C. Anderson Triple collocation analysis of soil moisture from Metop-a ASCAT and SMOS against JRA-55 and ERA-interim IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens., 10 (2017), pp. 2274-2284 URL View Record in ScopusGoogle Scholar Morrison and Wagner, 2020 K. Morrison, W. Wagner Explaining anomalies in SAR and scatterometer soil moisture retrievals from dry soils with subsurface scattering IEEE Trans. Geosci. Remote Sens., 58 (2020), pp. 2190-2197 URL View PDFCrossRefView Record in ScopusGoogle Scholar Morrison and Wagner, 2022 K. Morrison, W. Wagner A novel DInSAR algorithm for the retrieval of soil moisture and soil depth over arid regions of the world Can. J. Remote. Sens. (2022) submitted Google Scholar Mousa and Shu, 2020 B.G. Mousa, H. Shu Spatial evaluation and assimilation of SMAP, SMOS, and ASCAT satellite soil moisture products over Africa using statistical techniques Earth Space Sci., 7 (2020), 10.1029/2019EA000841 View PDFGoogle Scholar Muñoz-Sabater et al., 2021 J. Muñoz-Sabater, E. Dutra, A. Agustí-Panareda, C. Albergel, G. Arduini, G. Balsamo, S. Boussetta, M. Choulga, S. Harrigan, H. Hersbach, B. Martens, D.G. Miralles, M. Piles, N.J. Rodríguez-Fernández, E. Zsoter, C. Buontempo, J.N. Thépaut ERA5-land: a state-of-the-art global reanalysis dataset for land applications Earth Syst. Sci. Data, 13 (2021), pp. 4349-4383 URL View PDFCrossRefView Record in ScopusGoogle Scholar Oh et al., 1992 Y. Oh, K. Sarabandi, F. Ulaby An empirical model and an inversion technique for radar scattering from bare soil surfaces IEEE Trans. Geosci. Remote Sens., 30 (1992), pp. 370-381 URL http://ieeexplore.ieee.org/document/134086/ https://doi.org/10.1109/36.134086 View Record in ScopusGoogle Scholar Petropoulos et al., 2015 G.P. Petropoulos, G. Ireland, B. Barrett Surface soil moisture retrievals from remote sensing: current status, products & future trends Phys. Chem. Earth Part A/B/C, 83-84 (2015), pp. 36-56 URL ArticleDownload PDFView Record in ScopusGoogle Scholar Quast et al., 2019 R. Quast, C. Albergel, J.C. Calvet, W. Wagner A generic first-order radiative transfer modelling approach for the inversion of soil and vegetation parameters from scatterometer observations Remote Sens., 11 (2019), 10.3390/rs11030285 View PDFGoogle Scholar Schaber et al., 1986 G. Schaber, J. McCauley, C. Breed, G. Olhoeft Shuttle imaging radar: physical controls on signal penetration and subsurface scattenng in the eastern Sahara IEEE Trans. Geosci. Remote Sens., GE-24 (1986), pp. 603-623 URL View PDFCrossRefView Record in ScopusGoogle Scholar Schanda, 1986 E. Schanda Physical Fundamentals of Remote Sensing Springer Berlin Heidelberg, Berlin, Heidelberg (1986), 10.1007/978-3-642-48733-0 View PDFGoogle Scholar Shamambo et al., 2019 D. Shamambo, B. Bonan, J.C. Calvet, C. Albergel, S. Hahn Interpretation of ASCAT radar scatterometer observations over land: a case study over southwestern France Remote Sens., 11 (2019), p. 2842 URL View PDFCrossRefView Record in ScopusGoogle Scholar Steele-Dunne et al., 2017 S.C. Steele-Dunne, H. McNairn, A. Monsivais-Huertero, J. Judge, P.W. Liu, K. Papathanassiou Radar remote sensing of agricultural canopies: a review IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens., 10 (2017), pp. 2249-2273 URL View Record in ScopusGoogle Scholar Steele-Dunne et al., 2019 S.C. Steele-Dunne, S. Hahn, W. Wagner, M. Vreugdenhil Investigating vegetation water dynamics and drought using Metop ASCAT over the North American Grasslands Remote Sens. Environ., 224 (2019), pp. 219-235 URL https://www.sciencedirect.com/science/article/pii/S0034425719300045 https://doi.org/10.1016/j.rse.2019.01.004 ArticleDownload PDFView Record in ScopusGoogle Scholar Stoffelen et al., 2017 A. Stoffelen, S. Aaboe, J.C. Calvet, J. Cotton, G. De Chiara, J.F. Saldana, A.A. Mouche, M. Portabella, K. Scipal, W. Wagner Scientific developments and the EPS-SG scatterometer IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens., 10 (2017), pp. 2086-2097 URL View Record in ScopusGoogle Scholar Ulaby et al., 1978 F.T. Ulaby, P.P. Batlivala, M.C. Dobson Microwave backscatter dependence on surface roughness, soil moisture, and soil texture: part I-bare soil IEEE Trans. Geosci. Electron., 16 (1978), pp. 286-295 URL View Record in ScopusGoogle Scholar Ulaby et al., 1981 F.T. Ulaby, R.K. Moore, A.K. Fung Microwave Remote Sensing: Active and Passive. Volume 1 Microwave Remote Sensing Fundamentals and Radiometry Artech House Inc (1981) Google Scholar Ullmann et al., 2019 T. Ullmann, K. Serfas, C. Büdel, M. Padashi, R. Baumhauer Data processing, feature extraction, and time-series analysis of Sentinel-1 synthetic aperture radar (SAR) imagery: examples from Damghan and Bajestan Playa (Iran) Z. Geomorphol. (2019), pp. 9-39, 10.1127/zfg_suppl/2019/0524 Supplementary Issues 62. place: Stuttgart, Germany Publisher: Schweizerbart Science Publishers View PDFView Record in ScopusGoogle Scholar Verhoest et al., 2008 N. Verhoest, H. Lievens, W. Wagner, J. Álvarez Mozos, M. Moran, F. Mattia On the soil roughness parameterization problem in soil moisture retrieval of bare surfaces from synthetic aperture radar Sensors, 8 (2008), pp. 4213-4248 URL View PDFCrossRefView Record in ScopusGoogle Scholar Wagner et al., 1999 W. Wagner, G. Lemoine, M. Borgeaud, H. Rott A study of vegetation cover effects on ERS scatterometer data IEEE Trans. Geosci. Remote Sens., 37 (1999), pp. 938-948 URL http://ieeexplore.ieee.org/document/752212/ https://doi.org/10.1109/36.752212 View Record in ScopusGoogle Scholar Wagner et al., 2013 W. Wagner, S. Hahn, R. Kidd, T. Melzer, Z. Bartalis, S. Hasenauer, J. Figa-Saldaña, P. de Rosnay, A. Jann, S. Schneider, J. Komma, G. Kubu, K. Brugger, C. Aubrecht, J. Züger, U. Gangkofner, S. Kienberger, L. Brocca, Y. Wang, G. Blöschl, J. Eitzinger, K. Steinnocher The ASCAT soil moisture product: a review of its specifications, validation results, and emerging applications Meteorol. Z., 22 (2013), pp. 5-33 URL View PDFCrossRefView Record in ScopusGoogle Scholar Wanders et al., 2012 N. Wanders, D. Karssenberg, M. Bierkens, R. Parinussa, R. de Jeu, J. van Dam, S. de Jong Observation uncertainty of satellite soil moisture products determined with physically-based modeling Remote Sens. Environ., 127 (2012), pp. 341-356 URL https://linkinghub.elsevier.com/retrieve/pii/S0034425712003574 https://doi.org/10.1016/j.rse.2012.09.004 ArticleDownload PDFView Record in ScopusGoogle Scholar Wegmuller et al., 1994 U. Wegmuller, C. Matzler, R. Huppi, E. Schanda Active and passive microwave signature catalog on bare soil (2-12 GHz) IEEE Trans. Geosci. Remote Sens., 32 (1994), pp. 698-702 URL http://ieeexplore.ieee.org/document/297987/ https://doi.org/10.1109/36.297987 View Record in ScopusGoogle Scholar Williams and Greeley, 2001 K. Williams, R. Greeley Radar attenuation by sand: laboratory measurements of radar transmission IEEE Trans. Geosci. Remote Sens., 39 (2001), pp. 2521-2526 URL http://ieeexplore.ieee.org/document/964990/ https://doi.org/10.1109/36.964990 View Record in ScopusGoogle Scholar Wu et al., 2021 K. Wu, D. Ryu, L. Nie, H. Shu Time-variant error characterization of SMAP and ASCAT soil moisture using triple collocation analysis Remote Sens. Environ., 256 (2021), p. 112324 URL ArticleDownload PDFView Record in ScopusGoogle Scholar Zhang et al., 2021 R. Zhang, S. Kim, A. Sharma, V. Lakshmi Identifying relative strengths of SMAP, SMOS-IC, and ASCAT to capture temporal variability Remote Sens. Environ., 252 (2021), p. 112126 URL https://linkinghub.elsevier.com/retrieve/pii/S0034425720304995 https://doi.org/10.1016/j.rse.2020.112126 ArticleDownload PDFView Record in ScopusGoogle Scholar Zribi et al., 2014 M. Zribi, A. Gorrab, N. Baghdadi, Z. Lili-Chabaane, B. Mougenot Inuence of radar frequency on the relationship between bare surface soil moisture vertical profile and radar backscatter IEEE Geosci. Remote Sens. Lett., 11 (2014), pp. 848-852 URL View Record in ScopusGoogle Scholar Zribi et al., 2021 M. Zribi, M. Foucras, N. Baghdadi, J. Demarty, S. Muddu A new reflectivity index for the retrieval of surface soil moisture from radar data IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens., 14 (2021), pp. 818-826 URL View PDFCrossRefView Record in ScopusGoogle Scholar Zwieback et al., 2015 S. Zwieback, S. Hensley, I. Hajnsek A polarimetric first-order model of soil moisture effects on the DInSAR coherence Remote Sens., 7 (2015), pp. 7571-7596 URL View PDFCrossRefView Record in ScopusGoogle Scholar

University Staff: Request a correction | Centaur Editors: Update this record

Search Google Scholar