Widespread occurrence of anomalous C-band backscatter signals in arid environments caused by subsurface scatteringWagner, 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
It is advisable to refer to the publisher's version if you intend to cite from this work. See Guidance on citing. To link to this item DOI: 10.1016/j.rse.2022.113025 Abstract/SummaryBackscatter 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.
DownloadsDownloads per month over past year
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 |