Research Article Analysis of the Dielectric Constant of Saline …downloads.hindawi.com/journals/tswj/2014/563015.pdf · · 2015-11-23Polarization HH/HV/VH/VV Acquisition mode Fine-Quad-Pol

Research ArticleAnalysis of the Dielectric Constant of Saline-Alkali Soils andthe Effect on Radar Backscattering Coefficient A Case Study ofSoda Alkaline Saline Soils in Western Jilin Province UsingRADARSAT-2 Data

Yang-yang Li12 Kai Zhao1 Jian-hua Ren12 Yan-ling Ding12 and Li-li Wu12

1 Northeast Institute of Geography and Agroecology Chinese Academy of Sciences Changchun 130102 China2Graduate University of the Chinese Academy of Sciences Beijing 100049 China

Correspondence should be addressed to Kai Zhao zzhaokaivipsinacom

Received 26 February 2014 Revised 26 April 2014 Accepted 21 May 2014 Published 1 July 2014

Academic Editor Catherine Ottle

Copyright copy 2014 Yang-yang Li et al This is an open access article distributed under the Creative Commons Attribution Licensewhich permits unrestricted use distribution and reproduction in any medium provided the original work is properly cited

Soil salinity is a global problem especially in developing countries which affects the environment and productivity of agricultureareas Salt has a significant effect on the complex dielectric constant of wet soil However there is no suitable model to describe thevariation in the backscattering coefficient due to changes in soil salinity content The purpose of this paper is to use backscatteringmodels to understand behaviors of the backscattering coefficient in saline soils based on the analysis of its dielectric constantThe effects of moisture and salinity on the dielectric constant by combined Dobson mixing model and seawater dielectric constantmodel are analyzed and the backscattering coefficient is then simulated using the AIEM Simultaneously laboratorymeasurementswere performed on ground samples The frequency effect of the laboratory results was not the same as the simulated resultsThe frequency dependence of the ionic conductivity of an electrolyte solution is influenced by the ionrsquos components Finally thesimulated backscattering coefficients measured from the dielectric constant with the AIEM were analyzed using the extractedbackscattering coefficient from the RADARSAT-2 image The results show that RADARSAT-2 is potentially able to measure soilsalinity however the mixed pixel problem needs to be more thoroughly considered

1 Introduction

Soil salinization is a global environmental problem withsevere economic and social consequences especially in aridand semiarid regions It is one of the main causes of landdegradation and productivity loss Almost 3 of the worldrsquossoil resources the equivalent of 4025million hectares (Mha)are salt-affected due to varying degrees of human-induceddegradation [1] Thus the monitoring of the area and degreeof land salinization is of important value to agriculture

Radar remote sensing is known to be sensitive to severalnatural surface parameters such as surface roughness vege-tation and soil moisture Until now no inversion algorithmsexisted for directly determining the soil salinity content frommicrowave remote sensing data However the measurementof soil moisture by radar systems has beenwidely investigatedand applied over the last two decades [2ndash6] The basic

theory of the soil moisture inversion method is that onbare surfaces the dielectric constant is highly dependent onsoil moisture due to the large difference in the dielectricconstant between dry soil (approximately 2-3) and water(approximately 81) As the moisture of dry soil increasesthe dielectric constant consequently increases which directlyaffects the backscattering coefficient The complex dielectricconstant is composed of two parts the real part and theimaginary part The real part (1205761015840) of the complex dielectricconstant is related to the medium polarization and governsthe velocity of propagation of a wave trough the materialwhich is called the permittivity the imagery part (12057610158401015840) isrelated to the conductivity of the medium and representsthe radar signal attenuation by energy absorption requiredto reach the polarization which is called the loss factoraccording to Lasne et al [7] When comparing the complexdielectric constant of pure water with saline (sea) water

Hindawi Publishing Corporatione Scientific World JournalVolume 2014 Article ID 563015 14 pageshttpdxdoiorg1011552014563015

2 The Scientific World Journal

(cong4969mScm) [8] a minimal difference is observed in thereal part but there is a significant difference in the imaginarypart especially atmicrowave frequencies less thancong7GHz [9]Taylor applied the small perturbation model (SPM) to thePyramid Hill area when the surface soils were fully saturatedA study by Taylor et al [10] showed that variations in thedielectric constant beyond volumetric soil moisture contentof 30 were attributed to changes in the imaginary partUsing RADARSAT-1 SAR data and the laboratory analysisof the dielectric constant with different salt contents Shaoet al [11] showed that the backscattering coefficient of salt-affected soil is more correlated with 120576

10158401015840 than with 1205761015840 Use

of radar data which exhibit sensitivity to the dielectricand geometric characteristics of objects weather indepen-dent imaging capability and potential to acquire subsurfaceinformation is one of the most promising approaches forsalt-affected soils practical for high soil moisture contentconditions However there are rare theoretical and empiricalbackscattering models to describe the relationship betweenthe dielectric constant soil salinity soil moisture contentand the backscattering coefficient The backscattering modelused in soil moisture retrieval algorithms can also be used todetermine soil salinity

Based on the work by Aly et al [13] a theoretical modelAIEM (advanced integral equation model) was used to sim-ulate salinityrsquos effect on the backscattering coefficient of soilsand then the dielectric constant of laboratory measurementscompared to RADARSAT-2 data was analyzed based on thetheoretical simulation In this paper the Dobson mixingmodel combined with a seawater dielectric constant modelis used to simulate the salt-affected soil dielectric constantwhose advantages and disadvantages are then analyzed

2 Study Areas and Measurements

21 Location The study site is in Anrsquoguang [45∘201015840 ndash45∘40N123∘421015840ndash124∘81015840E] of Darsquoan western Jilin Province an areawith soda alkali-saline soil shown in Figure 1 The city ofDarsquoan is located in the hinterland of the Songnen PlainThe development of the saline-alkali soil is a comprehensiveresult of several natural environmental factors including cli-mate geology land formations parent material hydrologicalconditions water chemistry and the freeze-thaw factor Theclimatic zone ranges from temperate semihumid to semiaridThe evaporative capacity is greater than precipitation and thecontinental climate is obvious Spring and autumn are theperiods of salification whereas summer is the salt leachingperiod and a frozen layer appears in the winter Eachclimatic condition contributes to salinization The weath-ering of aluminosilicate magmatic rock contained withinthe Daxinganling Xiaoxingrsquoanling and ChangbaiMountainsresulted in calcium magnesium potassium and sodiumbicarbonate Then the dissolved salt in surface water andgroundwater concentrated in the plains or low-lying areaswhich brought a rich source of soda salt substances Heavy-textured soil parent material produced by the quaternarygeological environment combined with poor drainage and alow local groundwater level formed one of the worldrsquos largestsoda saline-alkali areas

Table 1 Characteristics of the SAR images in the study acquired byRADARSAT-2 sensors

Parameter RADARSAT-2 sensorsFrequency GHz (band) 5405 (C band)Wavelength (cm) 560Polarization HHHVVHVVAcquisition mode Fine-Quad-PolProcessing level SLC (single look complex)Resolutionm (rgrz) 52 lowast 76

Orbit AscendingAcquisition date 28Jun2013Incidence angle interval 39275∘ ndash40975∘

22 Available Data A RADARSAT-2 SAR image from June28 2013 was obtained for the study area in the Fine-Quad-Pol mode with an incident angle of approximately 39∘ ndash41∘The primary information of the SARdataset is shown in Table1 Before using the radar data radiation calibration filterprocessing and a geometric correction should be performedfirst

Coherent processing occurs from the RADARSAT-2 sen-sors which produces a lot of speckle noise Noise removalshould be performed An enhanced Frost filter with 5 times 5windows was used to reduce the effect of noise achieving asatisfactory result Noteworthy is that the image was takenimmediately after a heavy rain event and most of the landsurface was fully saturated therefore it is advantageous toanalyze the salt content from the radar image according tothe work by Taylor et al [10]

Ground sampling data were collected coincidentally withthe RADARSAT-2 overpass on June 28 2013 53 samples werecollected at the soil surface with a depth of 0ndash5 cm accordingto the geomorphologic and pedological characteristics of thearea Real-time soil-moisture ground EC and the temper-ature were simultaneously measured using a WET sensorThe average moisture value was 35 plusmn 10 () For the 53 soilsamples details from 17 points were taken for laboratorydielectric constant analysis using a vectorial network ana-lyzer Surface roughness was measured manually using a 15-m-long pin profiler shown in Figure 2 and there were at least3 repeat measurements of each point Most sample pointsof bare ground in the region were of smooth surfaces Theaverage value of the RMS (root mean square) height (119904) was027 cm and the correlation length (119897) was 35 cm

3 Methodology

31 Soil Dielectric Mixing Models The influence of soil salinedeposits in microwave remote sensing is related to thesolubility behavior and the ionic properties of the mineralsIn the ionic form the weight of dissolved substances perkilogram of solution determines the conductivity of thesolution that is the conductivity is directly related to thepresence of free electrons and ions Under the function ofan extra electric field the distribution of charges is distortedand the barycenters of positive and negative charges nolonger coincide which results in an induced dipole moment

The Scientific World Journal 3

123∘45

9984000998400998400E 123

∘55

9984000998400998400E 124

∘59984000998400998400E

123∘45

9984000998400998400E 123

∘55

9984000998400998400E 124

∘59984000998400998400E

45∘259984000998400998400

N45∘359984000998400998400

N45∘309984000998400998400

N45∘409984000998400998400

N

45∘259984000998400998400

N45∘359984000998400998400

N45∘309984000998400998400

N45∘409984000998400998400

N

W

S

N

E

Figure 1 Location of the study area (the image on the right is the HH polarization of RADARSAT-2)

Figure 2 Measurement of surface roughness

referred to as the polarization vector P There are threetypes of material in the natural world atoms moleculesand ions The presence of such components generates threemicroscopic polarization mechanisms electronic ionic andorientation polarizabilities which are related directly to themedium dielectric properties More importantly is that 12057610158401015840is proportional to the conductivity Because the propagationof the radar signal is primarily governed by the dielectricconstant it is necessary to understand the behavior of boththe real and imaginary parts of the dielectric constant withthe increase in soil salinity

Theoretical semiempirical and empirical mixture mod-els were proposed for determining the dielectric constant ofsoil materials such as themodel byWang and Schmugge [14]Soil not affected by salt is usually considered to be a mixtureof four components soil air free water and bound water Todescribe the dielectric constant of such a mixture Dobson etal [12] developed a semiempiricalmodel for soil Given a bulkdensity 120588

119887and specific density 120588

119904 the model is described as

120576120572

119898= 1 +

120588119887

120588119904

(120576120572

119904minus 1) + 119898

120573

V 120576120572

119891119908minus 119898V (1)

where 120572 = 065 120576119904= (101 + 044120588

119904)2minus 0062 is the dielectric

constant of soil particles 120573 is a coefficient expressed as afunction of sand and clay contents 119898V is the volumetric soilmoisture content and 120576120572

119891119908is the dielectric constant of the free

waterThe electric conductivity of the saturated soil sample used

in the Dobson model is approximately 1 dSm which wasconsidered to be nonsalt-affected soil The criterion betweensalt-affected and nonsalt-affected soil is 4 dS m thus themodel is not suitable for the salt-affected soil To accuratelydescribe the dielectric constant of salt-affected soils Aly etal [13] replaced the dielectric constant of free water withStogrynrsquos saline water model [8] the same method that wealso used in this paper The soil surface temperature is fixedat 23∘C which is acceptable for an average value of samplingsoilsThe bulk density used in the Dobsonmodel is 14 gcm3there was an average value of 53 ground points and thespecific density was assumed to be 265 gcm3

32 Backscattering Model To evaluate the effect of saltson airborne or orbital SAR data the radar backscatteringcoefficients based on the model need to be computed for thedielectric constant values previously simulated

The backscattering models used in nonsalt-affected soilsare also suitable for salt-affected soilsThere are several classicbackscatteringmodels of random rough surfaces proposed inprevious research (theoretical and empirical models) suchas the SPM (small perturbation model) the POM (physicaloptic model) introduced by Ulaby et al in microwave remotesensing [15] the IEM (integral equation model) and AIEM(advanced integral equation model) proposed by Fung et al[16 17] and the DM (Dubois model) proposed by Duboiset al [18] Different models have different application fieldsTable 2 shows the applicability of these models


Table 2 Comparisons of Different Backscattering Coefficient Models

Models DM SPM POM AIEMSurface All Smooth Rough AllRMS (119904) cm 03sim3 119896 sdot 119904 lt 25 119896 sdot 119904 lt 03 119896 sdot 119904 gt 2 AllCorrelation length (119897) mdash 119896 sdot 119897 lt 3 119904119897 lt 03 119896 sdot 119897 gt 6 119897

2gt 276 sdot 119904 sdot 120582 All

Incidence angle (120579) 30∘sim 65∘

gt 35∘sim 40∘

lt35∘ AllFrequency available (GHz) 15sim11 Low Frequency All All120582 is the wavelength of electromagnetic wave where 119896 = 2120587120582 is the wave-number

The SPM assumes that variations in surface height aresmall relative to the wavelength and that the incidence angleis greater than 35∘ ndash40∘ The POM is valid when the RMSsurface slope is small relative to the wavelength and theincidence angle is smaller than 35∘ The Dubois model issuitable for frequencies between 15 GHz and 11 GHz Con-trary to the three models the model based on the surfaceintegral equation (IEMAIEM) is the most suitable model forall surface types

This approachwas reported by Fung andChen [16] wherethe phase of Greenrsquos function in a higher order term wasignored This phase was later retained by Hsieh and Fungby fully including the phase effect in Greenrsquos function toachieve better accuracy in bistatic scattering andmultiple sur-face scattering especially in regions where the incident andscattering angles are not equal which was primarily the casefor the AIEM Therefore we applied the AIEM to simulatethe single backscattering coefficient of salt-affected soil byonly considering the surface scattering term The singlebackscattering coefficient of the AIEMmodel is expressed as

1205900

119901119901=

1198962

4120587

exp (minus411989621199111205902)

times

1003816100381610038161003816100381610038161003816

2119896119911120590 +

120590

4

(1198651199011199011

+ 1198651199011199012)

1003816100381610038161003816100381610038161003816

2

119908 (2119896119909 0)

+

infin

sum

119899=2

1003816100381610038161003816100381610038161003816

(2119896119911120590)119899119891119901119901+

120590

4

1198651199011199011(2119896119911120590)119899minus11003816100381610038161003816100381610038161003816

2

times

119908(119899)(2119896119909 0)

119899

(2)

where 119901 = V or ℎ polarization 120579 is the incident angle 119896119909=

119896 sin 120579 119896119911= 119896 cos 120579 119891VV = 2119877V cos 120579 and 119891ℎℎ = 2119877

ℎ cos 120579

The expressions 119908 and 119908(119899) are the surface spectra corre-

sponding to the two-dimensional Fourier transformations ofthe surface correlation coefficient and its 119899th power

It is apparent that most naturally occurring surfacesland or sea may contain more than one scale of roughnessExponential statistical distribution and Gaussian and the119909-power law distribution can all be used to describe thenatural surface as described by Fung and Chen [16] who alsoshowed that for moderately rough surfaces an exponentialstatistical distribution performs better than the Gaussian

or the 119909-power law distributions (119909 = 15) Consideringthe relatively smooth surface of saline soil the exponentialstatistical distribution was chosen for describing the surfaceof the AIEMmodel [19 20]

The incident angle used in themodel is assumed to be 40∘comparing the incident angles of the RADARSAT-2 image

33 Laboratory Measurement of the Dielectric Constant Todetermine the validity of the previous dielectric mixingmodel and simultaneously assess the impact of salt onthe RADARSAT-2 data we performed dielectric constantmeasurements for 17 samples with different gravimetricwater contents (from dry soil to 50 with a step of5) The volumetric soil moisture was measured using theoven-drying method A vectorial network analyzer (Agilent83630A PNA Analyzer) coupled with an open-ended coaxialprobe technique was used in the measurement of the soildielectric constant [7 11] The measurement frequency wasfrom 05GHz to 40GHz with 200 sampling points

Because the electromagnetic field at the probesampleinterface can be represented by a capacitor a calibrationprocedure had to be performed on which the dielectricconstant and frequency are well known The dielectric con-stant measurement system was calibrated using a standardcalibration procedure provided by the system (air-shortcircuiter-distilled water) and we refreshed the system beforeevery sample was measured

4 Results

41 Analysis of the Simulated Dielectric Constants The soilsoluble salt in the groundwater can rise to the surface as watermoves through capillary action in the soil Then the waterevaporates resulting in salt accumulation which forms salinesoils The particle size of different soil textures can affect thespeed and height of watermovement through capillary actionin the soil In general the capillary water in loamy soil risesrelatively quicker and to a greater height compared to clayand sandy soils The five different soil texture types were allanalyzed and the representative texture types of this regionare sandy and clay soils which were thoroughly analyzed atthree frequencies L band (14 GHz) C band (54GHz) andX band (1065GHz)

411 Salinity and Moisturersquos Effect on the Dielectric ConstantBelow 10GHz the ionic conductivity of salinewatermay have


0 10 20 30 40 50 60 70 80 90 10005

1015202530354045

Salinity (permil)

Real

par

tIncreasing soil moisture from 0 to 55 (5 step)

(a)

05

101520253035404550

Imag

inar

y pa

rt

0 10 20 30 40 50 60 70 80 90 100Salinity (permil)

Increasing soil moisture from 0 to 55 (5 step)

(b)

0 10 20 30 40 50 60Soil moisture ()

Decreasing salinity from 0 to 100permil(10permil step)

05

1015202530354045

Real

par

t

(c)

Imag

inar

y pa

rt

Increasing salinity from 0 to 100permil(10permil step)

0 10 20 30 40 50 60Soil moisture ()

05

1015202530354045

(d)

Figure 3 Effect of salinity and moisture on the sandy loam soil dielectric constant derived from the Dobson model combined with thesaltwater model at 54GHz (a) Salinity effect on the real part (b) salinity effect on the imaginary part (c) soil moisture effect on the real partand (d) soil moisture effect on the imaginary part

a marked effect on the loss factor Consequently high soilsalinity may significantly influence the dielectric propertiesof wet soil In this paper we take sandy loam soil with a fre-quency of 54GHz as an example The results in Figures 3(c)and 3(d) show that both the real and imaginary parts increasesharply with the moisture content however the impact ofsalinity is not the same for 1205761015840 and 12057610158401015840 For the real part theresults presented in Figure 3(a) show that soil salinity haslittle influence on 120576

1015840 As moisture increases the effect ofsalinity increases and the 1205761015840 decreases with increasing salinityConversely the imaginary part 12057610158401015840 is intensely affected by boththe salinity and soil moisture The higher the moisture thestronger the effect of salinity as shown in Figures 3(b) and3(d)The imaginary part of 12057610158401015840 is related to the conductivity ofthemedium and is generally proportional to the conductivityThe behavior of 12057610158401015840 increasing with increasing soil moisturecan be explained by the higher water content (especially thecontent of free water) within the soil leading to a greateramount of salts dissolved in the soil system (soil free waterair dissolved salt and bound water) resulting in an increasein conductivity More precisely for soil with small watercontent the dominant form is bound water in soil withdielectric properties close to ice (approximately 32) whichleads to a weak increase in the dielectric constant For soilwith greater water content the free water component in the

soil becomes much more active and allows more salt to bedissolved in the soil

412 Texture Effect on the Dielectric Constant Soil textureis one of soilrsquos physical properties It refers to the differentcombinations of different mineral particle sizes Soil texturehas a close relationship with soil aeration the protection ofsoil fertilizer water status and farming ease therefore itcannot be neglected when analyzing the dielectric constant ofsoils Soil texture affects the detection of soilmoisture becausethe dielectric constant changes with the relative amount ofsand silt and clay in the soil [12 14] In saline soil the texturecan affect salt and moisturersquos ability to move which candirectly influence the dielectric constant of salt-affected soils

The five different soil texture types were analyzed andthe results are presented in Figure 4 For the oven-driedsoil both the 1205761015840 and 12057610158401015840 are approximately the same for allsoil types The variation of the soil dielectric constant withincreasing soil moisture (119898V) can be divided into two parts(i) between 119898V = 0 and a transition moisture level 119898

119905and

(ii) 119898V ge 119898119905 The transition moisture is a constant for

a given type of soil composition and varies between 003for sands and 01 for clays which represents the boundarybetween the bound water and the free water molecules [14]Between the dry soil and the transition moisture level most


0 5 10 15 20 25 30 35 40 45 50 5505

1015

2025303540

45Re

al p

art

Soil moisture ()

Sandy loamLoamSilty loam

Sandy claySilty clay

(a)

0

5

10

15

20

25

30

40

35

Real

par

t



0 10 20 30 40 50 60Soil moisture ()

(b)

0

2

4

6

8

10

12

14

Imag

inar

y pa

rt

0 10 20 30 40 50 60Soil moisture ()



(c)

0

5

10

15

20

25

30

35

Imag

inar

y pa

rt

0 10 20 30 40 50 60Soil moisture ()



(d)

Figure 4 Effect of soil texture on the dielectric constant in nonsalt-affected soil (on the left) [12] and 60permil in salt-affected soil (on the right)(a) Texture effect on real part (0permil) (b) texture effect on real part (60permil) (c) texture effect on imaginary part (0permil) and (d) texture effect onimaginary part (60permil)

of the water molecules in the soil system are consideredto be at least partially bound to the soil particles by theinfluence of both metrics and osmotic forces Because of themuch smaller dielectric constant of bound water moleculescompared to free water consequently the dielectric constantof the mixture increases only slowly with increasing 119898VBeyond the transition moisture level the water molecules areconsidered to be free particles with a larger dielectric constantthan that of dry soil and thereby a strong influence occurson the soil system The transition moisture depends on thesoil particle surface area per unit volume and is a function ofsoil type Sandy loam soils have the highest 1205761015840 for both salt-affected soil and nonaffected soil followed by sandy clay andthen silt clay The results show that the higher the percentageof sand content in soil particles the higher the real part ofthe soil dielectric constant This is the reason that the sandhas a relatively weak ability to bind the water molecules to

soil particles leavingmore free water in the soil system whichresults in a higher dielectric constant

The effect of texture on the dielectric loss (12057610158401015840) is morecomplicated than the real part The 12057610158401015840 is shown to increasewith soil clay content For nonsalt affected soil at 40 to60GHz 12057610158401015840 is nearly independent of soil texture at allsoil moisture conditions as proposed by Schmugge (1983)However for saline soil the effect of texture at 54GHz isstrong We also confirm that the texture effect increases withan increasing salinity content

413 Frequency Effect on the Dielectric Constant The dielec-tric loss 12057610158401015840 is a parameter that describes the movementsof electric charge (conduction phenomena) The conductioncan arise from an actual transport charge (such as ionicconduction in electrolytes)Thus the observed dielectric lossconsists of two termsmdashthe loss due to a lag in polarization


0

5

10

15

20

25

30

35

40

Imag

inar

y pa

rt

1 2 3 4 5 6 7 8 9 10 115

10

15

20

25

30

35

40

45

Frequency (GHz)1 2 3 4 5 6 7 8 9 10 11

Frequency (GHz)

Real

par

t

Salinity 30permilIncreasing soil moisturefrom 5 to 55 (5 step)

Increasing soil moisturefrom 5 to 55 (5 step)

Salinity 30permil

(a)

0

10

20

30

40

50

60

70

Imag

inar

y pa

rt

5

10

15

20

25

30

35

40

45

Real

par

t

Salinity 60permilSalinity 60permil

Increasing soil moisture from 5 to 55 (5 step) Increasing soil moisture from 5 to 55 (5 step)

1 2 3 4 5 6 7 8 9 10 11Frequency (GHz)

1 2 3 4 5 6 7 8 9 10 11Frequency (GHz)

(b)

Figure 5 Effect of frequency on the dielectric constant at a salinity of 30permil (a) and 60permil (b)

and the conductive loss Both of the terms depend on the fre-quency especially below 10GHzwhere the ionic conductivityof saline water may have a marked effect on the loss factorThus the aim is to assess the frequency effect on the dielectricconstant Four commonly used microwave frequency bandswere analyzedmdashL (14GHz) S (24GHz) C (54GHz) and X(1065GHz)

The frequency variation of the dielectric constant of salt-affected soils is shown in Figure 5 (salinity of 30permil) andFigure 6 (salinity of 60permil) The volumetric water content isin the range of 5 to 55 The real part 1205761015840 slowly decreaseswith an increase of frequency Conversely the imaginary

part 12057610158401015840 rapidly decreases with an increase of frequencyespecially in the low frequency range the value stabilizeswhen the frequency is higher than 7GHz Furthermore Shaoachieved the same 12057610158401015840 variation pattern from experimentalmeasurements performed on NaCl-concentrated solutionsand the results from Lasnersquos combination of the Wang modeland seawater dielectricmodel to simulate the salt-affected soildielectric constant confirmed our studyrsquos conclusion

42 Analysis of the Laboratory Measured Dielectric ConstantSix samples of different salinity content were chosen andthe dielectric constant was then analyzed in the L band


05

1015202530354045

Real

par

t of L

ban

d

123

456

0 10 20 30 40 50 60Soil moisture ()

(a)

0

5

10

15

20

25

30

35

40

Real

par

t of C

ban

d

123

456

0 10 20 30 40 50 60Soil moisture ()

(b)

minus2

0

2

4

6

8

10

12

14

Imag

inar

y pa

rt o

f L b

and

0 10 20 30 40 50 60Soil moisture ()

123

456

(c)

minus2

0

2

4

6

8

10

12

14

Imag

inar

y pa

rt o

f C b

and

123

456

0 10 20 30 40 50 60Soil moisture ()

(d)

Figure 6 Measurement of the dielectric constant of the L band and C band (6 sample points are taken with different salinity contents as anexample)

(143GHz) and C band (54GHz) The results are shown inFigure 6 The salinity contents were increased from sample1 to 6 in turn For the real part both the L and C bandsincreased with the increasing water content and the values inthe L band were slightly greater than the C band In additionthere was a higher salinity content in the lower real part asshown in Figure 6 especially when the water content wasgreater than 20 This phenomenon was the same as themodelrsquos simulated result as presented in the previous sectionThe imaginary part increased with the increasing water con-tent however when the water content was greater than 20the influence of salinity on 12057610158401015840 leads to a strong increase How-ever in instances of low volumetric water content the salinityeffect is unnoticeable for both the real and imaginary partsof the dielectric constant This is because the low volumetricwater content results in a low concentration of ions (namelyconductivity)The results shown in Figure 6 also indicate thatthe C and L bands are highly correlated especially for the real

part The research results of Shao showed that the C and Lbands were favorable for delineating the soil salinity

The measurement results of the sample prepared in thelaboratory were compared with the frequency variation asshown in Figure 7The real part decreasedwith the increasingfrequency especially in instances of high water contentwhere the real part decreased sharply with a variation infrequency The measured results of the frequency effect on 1205761015840were the same according to the results of the mixed model(the Dobson model combined with the seawater dielectricconstant model) However a distinct phenomenon occurredwith the imaginary part At a low frequency (05ndash2GHz)the 120576

10158401015840 decreased sharply with an increasing frequencywhich confirmed the theoretical frequency dependence of12057610158401015840 exhibiting a steep variation rate in the 1-2GHz frequencyrange [7 11] Then an inflection point appeared after whichthe 12057610158401015840 increased with an increasing frequency from 3GHzto 10GHz At frequencies greater than 10GHz the 12057610158401015840 began


0

5

10

15

20

25

30

35

40Re

al p

art

0 5 10 15 20 25 30 35 40Frequency (GHz)

2871117201

272954145485

Volumetric moisture content ()

(a)

0 5 10 15 20 25 30 35 400

2

4

6

8

10

12

14

16

18

20

Frequency (GHz)

Imag

inar

y pa

rt

2871117201

272954145485


(b)

Figure 7 Frequency variations of the real (a) and imaginary (b) parts of the dielectric constant of the sample derived from laboratorymeasurements at different moisture content levels

to decrease This phenomenon was present in all of themeasurement samples prepared in the laboratory When thefrequency was higher than 5GHz the measured results werenot the same as the research of Lasne et al [7] and Shao et al[11] An explanation for the different conclusions follows

The laboratory research of both Shao and Lasnewas basedon a mixture of an NaCl solution and soil and the salinitywater model used in Section 41 was a seawater model whichis also based on the analysis of NaCl solution however thesalt components for this study were Na+ CO

3

2minus andHCO3

minusIn an electrical field the process of a medium changingfrom a state of nonpolarization to polarization or changingfrom one polarization state to another is called the electricpolarization relaxation process and the time of the relaxationprocess is the dielectric relaxation time An investigationwas performed by Chandra and Bagchi [21] that showed thesaturation of a solutionmight be attributed to the influence ofthe relaxation time on the saturated solution In solutions thevariations of 12057610158401015840 with the frequency can be illustrated as thefrequency dependence of ionic conductivity which usuallydescribes the motion ions [22] Different salt componentshave different ionic conductivity properties which results indifferent relaxation times that then influence the frequencyThe relaxation time is also related to the solution temperatureand the concentration

The results presented in Figure 7 show the saline soilin the study area by combining the C band (54GHz) andX band (1065GHz) This conclusion also confirmed thatcombining the Dobson model with the seawater dielectricconstant model was not suitable for all types of salt-affected

soil It is necessary to develop suitable models for differentsaline-alkali lands

43 Analysis of the Simulated BackscatteringCoefficients Basedon the Simulated Dielectric Constant The backscatteringcoefficient model used in the paper is the AIEM modelwhichwas introduced in Section 32 and the band is 54GHzreferred to in the RADARSAT-2 data The input dielectricconstant data were previously simulated by combining theDobson model and seawater model The surfaces of the salt-affected soils are usually smooth Thus an RMS height of027 cmand a correlation length of 35 cmwere set for the datasimulation The simulated results in Figure 8 show that thesensitivity of the backscattering coefficient on the soilrsquos salin-ity depends on the soil moisture content With an increasein soil moisture content the simulated backscattering coeffi-cient increased which was the same effect on salinity Salinitymore slightly affects the HH polarization mode compared tothe other two simulated modes particularly where the soilmoisture content is high For HH polarization the range ofvariation is minus12 dB to minus9 dB whereas the VV polarization isfrom minus162 dB to minus10 dB and from minus373 dB to minus322 dB forHV polarization

There may be two possible explanations for interpretingthese characteristics The first is that soil moisture greatlydominates the dielectric constant for soils with highmoisturecontent therefore when the salinity increases the changein the backscattering coefficient is not obvious The secondexplanation may be that the salt in the soil cannot becompletely dissolved at a low water contentmdashthe greater the


5 10 15 20 25 30 35 40 45 50 55minus17minus16minus15minus14minus13minus12minus11minus10

minus9minus8

Soil moisture ()

HH

bac

ksca

tterin

g co

effici

ent (

dB) Increasing S from 0 to 120permil (30permil step)

(a)

minus17

minus16

minus15

minus14

minus13

minus12

minus11

minus10

minus9

VV

bac

ksca

tterin

g co

effici

ent (

dB)

5 10 15 20 25 30 35 40 45 50 55Soil moisture ()

Increasing S from 0 to 120permil (30permil step)

(b)

minus37minus365

minus36minus355

minus35minus345

minus34minus335

minus33minus325

minus32

HV

bac

ksca

tterin

g co

effici

ent (

dB)

5 10 15 20 25 30 35 40 45 50 55Soil moisture ()


(c)

Figure 8 AIEM simulations of the simulated dielectric constant for the backscattering coefficient at a C band of 40∘ incidence angle with avariation in soil moisture and soil salinity (a) HH polarization (b) VV polarization and (c) HV polarization

water content the more the free ions in the soil system andsubsequently the higher the dielectric constant When thedielectric constant is high enough the Fresnel coefficientschange slowly which is due to radar signal saturation

To interpret this phenomenon a salinity content of 30permilis used as an example to demonstrate the relationship betweenthe Fresnel coefficient and soil moisture and the relationshipbetween the Fresnel coefficient gradient and soil moistureshown in Figure 9 The Fresnel coefficients of H and Vpolarization both increase with increasing soil moisture Thegradient of the Fresnel coefficients sharply decreases with anincrease in water content and the change rate of the Fresnelcoefficients is close to zero when the water content is greaterthan 40 which illustrates that the Fresnel coefficientschange slowly as the water content increases and then reachsome constant If other conditions remain unchanged theradar signal trends towards stable

44 Analysis of the Backscattering Coefficient of the LaboratoryDielectric Constant The dielectric constants of samples weremeasured using anAgilent 83630APNAAnalyzerThe resultsof the measurement are analyzed in Section 42 The mea-sured dielectric constant is an input parameter in the AIEMwith an incident angle of 40∘ (the same for obtaining the radarimage) The roughness parameter of the RMS height (119904) is027 cm and the correlation length (119897) is 35 cm which are

the average values for the research area The backscatteringcoefficients with HH and VV polarization were derived usingthe AIEM with the input parameter described For the sametime period the backscattering coefficients of the samplesin the RADARSAT-2 images were extracted according tothe latitude and longitude coordinates of the samples Thebackscattering coefficient comparisons of model simulationresults and image values of the samples with HH and VVpolarization are shown in Figure 10 ((a) for HH polarizationand (b) for VV polarization) The relationship betweenthe simulated and 120590

0image shown in Figure 10 and the

correlation coefficient is 01518 and 01898 respectively Therelevancy was very poor for themodel value and image valuewhichmay be an influence ofmixed pixelsThe type of saline-alkali soil in this region is in ameadow characterized by grasswith areas of bare soil Figure 11 shows the landscape of theresearch area which shows grass and bare soil distributedrandomly resulting in mixed pixels

To improve the effect of grass in a pixel the semiempiricalwater-cloud model used as a vegetation effect correctionmodel was imported into the correction of the soil backscat-tering coefficient

The water-cloud model is described as

1205900

con (120579) = 1205900

veg (120579) + 1205742

(120579) 1205900

soil (120579) (3)


0 10 20 30 40 50 60Soil moisture ()

0

01

02

03

04

05

06

07

Fres

nel c

oeffi

cien

t

R

Rh

(a)

0 10 20 30 40 50 60Soil moisture ()

0

002

004

006

008

01

012

Gra

dien

t of F

resn

el co

effici

ent

R

Rh

(b)

Figure 9 Relationship between the Fresnel coefficients and the gradient of the Fresnel coefficients with a variation in soil moisture

minus20 minus18 minus16 minus14 minus12 minus10 minus8 minus6 minus4 minus2 0minus30

minus28

minus26

minus24

minus22

minus20

minus18

minus16

minus14

minus12

minus10

minus8

HH polarizationFitting line

RADARSAT-2 1205900 (dB)

Sim

ulat

ed1205900

(dB)

R2= 01518

(a)

minus20 minus18 minus16 minus14 minus12 minus10 minus8 minus6 minus4 minus2 0

VV polarizationFitting line

RADARSAT-21205900 (dB)

minus30

minus28

minus26

minus24

minus22

minus20

minus18

minus16

minus14

minus12

minus10

minus8

Sim

ulat

ed1205900

(dB)

R2= 01898

(b)

Figure 10 Simulated backscattering coefficient compared to the RADARSAT-2 images of the 16 ground samples with HH polarization on(a) and VV polarization on (b)

where 1205900veg(120579) = 119860 cos(120579)[1 minus 1205742(120579)] 1205742(120579) = exp[minus2119861119898V

cos(120579)] and 119898V is the vegetation water content which canbe derived from optical images The parameters of 119860 and 119861are defined according to Table 3 [23] The vegetation infor-mation improved the backscattering coefficient of groundsoil samples The results are shown in Figure 12 The corre-lation coefficients for the simulated 120590

0(calculated from the

laboratory-measured dielectric constant) and the improved1205900(according to the water-cloud model) were 05228 and

06106 respectively for the HH and VV polarization whichwere both improved before However the simulated 120590

0was

higher than the 1205900value extracted from the image The

reason for the difference may be a reflection of the followingtwo aspects (1) The water-cloud model was based on twoassumptions the uniform distribution of scattering particlesof the vegetation layer and the negligence of the multiplescattering between the vegetation layer and the soil surfacehowever the grasslandrsquos interaction with bare saline-alkali


Figure 11 The landscape of saline-alkali soil in the research area

minus30 minus25 minus20 minus15 minus10 minus5 0minus30

minus25

minus20

minus15

minus10

minus5

0

Improved 1205900 (dB)

Sim

ulat

ed1205900

(dB)

HH polarization

R2= 05228

1 1 line

(a)


minus25

minus20

minus15

minus10

minus5

0


Sim

ulat

ed1205900

(dB)

R2= 06106

VV polarization1 1 line

(b)

Figure 12 The improved backscattering coefficient from the water-cloud model compared with the simulated backscattering coefficient ofthe 16 ground samples with HH polarization on (a) and VV polarization on (b)

soil presented a very complicated landscape which cannot beeasily described by the water-cloud model In other words itwas a problem of mixed pixels (2) There may have been anerror in the average values of surface roughness that we usedfor this region

5 Conclusions

The complex dielectric constant for the salt-affected soilwas analyzed using the modified Dobson dielectric mixingmodel Then the backscattering coefficients based on thesimulated complex dielectric model were analyzed Basedon the analysis of the modelrsquos simulated data laboratorymeasurements were performed on the ground samplesThenthe AIEM model was applied to the laboratory dielectricconstants and compared with the backscattering coefficientextracted from radar imagery The conclusions from thepresented work are as follows

(1) The analysis of the simulated dielectric constantconfirmed several dielectric properties of salt-affectedsoils The first is that both the real and imaginaryparts increase with the moisture content The secondis that salinity has little influence on the real part and1205761015840 decreases with increasing salinity especially for soilwith a high moisture content (119898V gt 20) The thirdis that the imaginary part 12057610158401015840 is strongly affected byboth moisture and salinity In particular the higherthemoisture content the stronger the effect of salinityon the imaginary part

(2) The frequency effect on the salt-affected soil of labo-ratory measurement results paints a different picturefor the simulated dielectric constant The 12057610158401015840 sharplydecreases at the low frequency range (05ndash3GHz)and then exhibits an increasing trend form 5GHz to15GHz where the 12057610158401015840 becomes stableThis conclusion


Table 3 Values of vegetation parameters used in the semiempirical model

Item All vegetation Rangelands Cropland GrasslandParameter 119860 00012 00009 00018 00014Parameter 119861 0091 0032 0138 0084

shows that the Dobson model combined with theseawater dielectric model is not suitable for sodasaline-alkaline land

(3) The laboratory results of the frequency effect on thesalinity also reveal that the combination of the C bandand X band may be useful on the inversion of salinityand moisture

(4) The backscattering coefficients of VV and cross-polarization seem to be more sensitive than HHpolarization on the salinity effect

(5) The saline-alkali lands in western Jilin Province arealways mixed pixels with bare soil and grass as pre-sented in the radar image especially during the rainyseasonThe simple water-cloudmodel is not sufficientenough to solve the problem of mixed pixels

Three important things must be done in the futureFirst a suitable dielectric constant model for soda saline-alkali land is urgently needed Second the problem of mixedpixels needs to be solved through theoretical and technicalsupport Finally polarization radar data has two importantparameters the amplitude andphaseThe influence of salinityon the amplitude of the radar backscattering coefficient isinitially considered and the phase parameter as a potentialindicator for soil moisture detection requires attention

Conflict of Interests

The authors declare that there is no conflict of interestsregarding the publication of this paper

References

[1] FAO LandResource Potential andConstraints Statistics at Coun-try and Regional Level Food and Agriculture Organization2010

[2] F T Ulaby ldquoRadarmeasurement of soil moisture contentrdquo IEEETransactions on Antennas and Propagation vol 22 no 2 pp257ndash265 1974

[3] A K Fung Z Li and K S Chen ldquoBackscattering from a rand-omly rough dielectric surfacerdquo IEEE Transactions on Geoscienceand Remote Sensing vol 30 no 2 pp 356ndash369 1992

[4] E T Engman and N Chauhan ldquoStatus of microwave soil mois-ture measurements with remote sensingrdquo Remote Sensing ofEnvironment vol 51 no 1 pp 189ndash198 1995

[5] P C Dubois J van Zyl and T Engman ldquoMeasuring soil mois-ture with imaging radarsrdquo IEEE Transactions on Geoscience andRemote Sensing vol 33 no 4 pp 915ndash926 1995

[6] J Shi J Wang A Y Hsu P E ONeill and E T Engman ldquoEsti-mation of bare surface soil moisture and surface roughness

parameter using L-band SAR image datardquo IEEE Transactionson Geoscience and Remote Sensing vol 35 no 5 pp 1254ndash12661997

[7] Y Lasne P Paillou A Freeman et al ldquoEffect of salinity on thedielectric properties of geological materials implication for soilmoisture detection by means of radar remote sensingrdquo IEEETransactions on Geoscience and Remote Sensing vol 46 no 6pp 1674ndash1688 2008

[8] A Stogryn ldquoEquations for calculating the dielectric constant ofsaline waterrdquo IEEE Transactions onMicrowaveTheory and Tech-niques vol 19 no 8 pp 733ndash736 1971

[9] F T Ulaby R K Moore and A K Fung Microwave RemoteSensing Active and Passive-From Theory To Application-3Artech House Dedham Massachusetts 1983

[10] G R Taylor A H Mah F A Kruse K S Kierein-Young RD Hewson and B A Bennett ldquoCharacterization of saline soilsusing airborne radar imageryrdquo Remote Sensing of Environmentvol 57 no 3 pp 127ndash142 1996

[11] Y Shao Q Hu H Guo Y Lu Q Dong and C Han ldquoEffect ofdielectric properties of moist salinized soils on backscatteringcoefficients extracted from RADARSAT imagerdquo IEEE Transac-tions on Geoscience and Remote Sensing vol 41 no 8 pp 1879ndash1888 2003

[12] M C Dobson F T Ulaby M T Hallikainen and M A El-Rayes ldquoMicrowave dielectric behavior of wet soil-Part II Diele-ctric mixing modelsrdquo IEEE Transactions on Geoscience andRemote Sensing vol 23 no 1 pp 35ndash46 1985

[13] Z Aly F J Bonn and R Magagi ldquoAnalysis of the backscat-tering coefficient of salt-affected soils using modeling andRADARSAT-1 SAR datardquo IEEE Transactions on Geoscience andRemote Sensing vol 45 no 2 pp 332ndash341 2007

[14] J RWang andT J Schmugge ldquoAn empiricalmodel for the com-plex dielectric permittivity of soils as a function of water con-tentrdquo IEEE Transactions on Geoscience and Remote Sensing vol18 no 4 pp 288ndash295 1980

[15] F T Ulaby R K Moore and A K Fung Microwave RemoteSensing vol 2 Artech House Dedham Massachusetts 1982

[16] A K Fung and K S ChenMicrowave Scattering and EmissionModels and Their Applications Artech House Norwood NJUSA 1994

[17] C Y Hsieh A K Fung G Nesti A J Sieber and P Coppo ldquoAfurther study of the IEM surface scatteringmodelrdquoTransactionson Geoscience and Remote Sensing vol 35 no 4 pp 901ndash9091997


[19] R Bindlish and A P Barros ldquoSub-pixel variability of remotelysensed soil moisture an inter-comparison study of SAR andESTARrdquo in Proceedings of the IEEE International Geoscience andRemote Sensing Symposium (IGARSS 99) pp 1917ndash1920 July1999


[20] YWu andWWang ldquoModeling the backscattering coefficient ofsalt-affected soils using AIEM modelrdquo Proceedings of SPIE vol8181 8 pages 2011

[21] A Chandra and B Bagchi ldquoFrequency dependence of ionicconductivity of electrolyte solutionsrdquo The Journal of ChemicalPhysics vol 112 no 4 pp 1876ndash1886 2000

[22] T Yamaguchi T Matsuoka and S Koda ldquoA theoretical studyon the frequency-dependent electric conductivity of electrolytesolutionsrdquo The Journal of Chemical Physics vol 127 no 23Article ID 234501 9 pages 2007

[23] R Bindlish and A P Barros ldquoMultifrequency soil moistureinversion from SAR measurements with the use of IEMrdquoRemote Sensing of Environment vol 71 no 1 pp 67ndash88 2000

Submit your manuscripts athttpwwwhindawicom

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ClimatologyJournal of


(cong4969mScm) [8] a minimal difference is observed in thereal part but there is a significant difference in the imaginarypart especially atmicrowave frequencies less thancong7GHz [9]Taylor applied the small perturbation model (SPM) to thePyramid Hill area when the surface soils were fully saturatedA study by Taylor et al [10] showed that variations in thedielectric constant beyond volumetric soil moisture contentof 30 were attributed to changes in the imaginary partUsing RADARSAT-1 SAR data and the laboratory analysisof the dielectric constant with different salt contents Shaoet al [11] showed that the backscattering coefficient of salt-affected soil is more correlated with 120576

10158401015840 than with 1205761015840 Use

of radar data which exhibit sensitivity to the dielectricand geometric characteristics of objects weather indepen-dent imaging capability and potential to acquire subsurfaceinformation is one of the most promising approaches forsalt-affected soils practical for high soil moisture contentconditions However there are rare theoretical and empiricalbackscattering models to describe the relationship betweenthe dielectric constant soil salinity soil moisture contentand the backscattering coefficient The backscattering modelused in soil moisture retrieval algorithms can also be used todetermine soil salinity

Based on the work by Aly et al [13] a theoretical modelAIEM (advanced integral equation model) was used to sim-ulate salinityrsquos effect on the backscattering coefficient of soilsand then the dielectric constant of laboratory measurementscompared to RADARSAT-2 data was analyzed based on thetheoretical simulation In this paper the Dobson mixingmodel combined with a seawater dielectric constant modelis used to simulate the salt-affected soil dielectric constantwhose advantages and disadvantages are then analyzed

2 Study Areas and Measurements

21 Location The study site is in Anrsquoguang [45∘201015840 ndash45∘40N123∘421015840ndash124∘81015840E] of Darsquoan western Jilin Province an areawith soda alkali-saline soil shown in Figure 1 The city ofDarsquoan is located in the hinterland of the Songnen PlainThe development of the saline-alkali soil is a comprehensiveresult of several natural environmental factors including cli-mate geology land formations parent material hydrologicalconditions water chemistry and the freeze-thaw factor Theclimatic zone ranges from temperate semihumid to semiaridThe evaporative capacity is greater than precipitation and thecontinental climate is obvious Spring and autumn are theperiods of salification whereas summer is the salt leachingperiod and a frozen layer appears in the winter Eachclimatic condition contributes to salinization The weath-ering of aluminosilicate magmatic rock contained withinthe Daxinganling Xiaoxingrsquoanling and ChangbaiMountainsresulted in calcium magnesium potassium and sodiumbicarbonate Then the dissolved salt in surface water andgroundwater concentrated in the plains or low-lying areaswhich brought a rich source of soda salt substances Heavy-textured soil parent material produced by the quaternarygeological environment combined with poor drainage and alow local groundwater level formed one of the worldrsquos largestsoda saline-alkali areas

Table 1 Characteristics of the SAR images in the study acquired byRADARSAT-2 sensors

Parameter RADARSAT-2 sensorsFrequency GHz (band) 5405 (C band)Wavelength (cm) 560Polarization HHHVVHVVAcquisition mode Fine-Quad-PolProcessing level SLC (single look complex)Resolutionm (rgrz) 52 lowast 76

Orbit AscendingAcquisition date 28Jun2013Incidence angle interval 39275∘ ndash40975∘

22 Available Data A RADARSAT-2 SAR image from June28 2013 was obtained for the study area in the Fine-Quad-Pol mode with an incident angle of approximately 39∘ ndash41∘The primary information of the SARdataset is shown in Table1 Before using the radar data radiation calibration filterprocessing and a geometric correction should be performedfirst

Coherent processing occurs from the RADARSAT-2 sen-sors which produces a lot of speckle noise Noise removalshould be performed An enhanced Frost filter with 5 times 5windows was used to reduce the effect of noise achieving asatisfactory result Noteworthy is that the image was takenimmediately after a heavy rain event and most of the landsurface was fully saturated therefore it is advantageous toanalyze the salt content from the radar image according tothe work by Taylor et al [10]

Ground sampling data were collected coincidentally withthe RADARSAT-2 overpass on June 28 2013 53 samples werecollected at the soil surface with a depth of 0ndash5 cm accordingto the geomorphologic and pedological characteristics of thearea Real-time soil-moisture ground EC and the temper-ature were simultaneously measured using a WET sensorThe average moisture value was 35 plusmn 10 () For the 53 soilsamples details from 17 points were taken for laboratorydielectric constant analysis using a vectorial network ana-lyzer Surface roughness was measured manually using a 15-m-long pin profiler shown in Figure 2 and there were at least3 repeat measurements of each point Most sample pointsof bare ground in the region were of smooth surfaces Theaverage value of the RMS (root mean square) height (119904) was027 cm and the correlation length (119897) was 35 cm

3 Methodology

31 Soil Dielectric Mixing Models The influence of soil salinedeposits in microwave remote sensing is related to thesolubility behavior and the ionic properties of the mineralsIn the ionic form the weight of dissolved substances perkilogram of solution determines the conductivity of thesolution that is the conductivity is directly related to thepresence of free electrons and ions Under the function ofan extra electric field the distribution of charges is distortedand the barycenters of positive and negative charges nolonger coincide which results in an induced dipole moment


123∘45

9984000998400998400E 123

∘55

9984000998400998400E 124

∘59984000998400998400E

123∘45

9984000998400998400E 123

∘55

9984000998400998400E 124

∘59984000998400998400E

45∘259984000998400998400

N45∘359984000998400998400

N45∘309984000998400998400

N45∘409984000998400998400

N

45∘259984000998400998400

N45∘359984000998400998400

N45∘309984000998400998400

N45∘409984000998400998400

N

W

S

N

E







120576120572

119898= 1 +

120588119887

120588119904

(120576120572

119904minus 1) + 119898

120573

V 120576120572

119891119908minus 119898V (1)

where 120572 = 065 120576119904= (101 + 044120588











2gt 276 sdot 119904 sdot 120582 All


gt 35∘sim 40∘




1205900

119901119901=

1198962

4120587

exp (minus411989621199111205902)

times

1003816100381610038161003816100381610038161003816

2119896119911120590 +

120590

4

(1198651199011199011

+ 1198651199011199012)

1003816100381610038161003816100381610038161003816

2

119908 (2119896119909 0)

+

infin

sum

119899=2

1003816100381610038161003816100381610038161003816

(2119896119911120590)119899119891119901119901+

120590

4

1198651199011199011(2119896119911120590)119899minus11003816100381610038161003816100381610038161003816

2

times

119908(119899)(2119896119909 0)

119899

(2)



ℎ cos 120579








4 Results




0 10 20 30 40 50 60 70 80 90 10005

1015202530354045

Salinity (permil)

Real

par


(a)

05

101520253035404550

Imag

inar

y pa

rt

0 10 20 30 40 50 60 70 80 90 100Salinity (permil)


(b)

0 10 20 30 40 50 60Soil moisture ()


05

1015202530354045

Real

par

t

(c)

Imag

inar

y pa

rt


0 10 20 30 40 50 60Soil moisture ()

05

1015202530354045

(d)







119905and




0 5 10 15 20 25 30 35 40 45 50 5505

1015

2025303540

45Re

al p

art

Soil moisture ()



(a)

0

5

10

15

20

25

30

40

35

Real

par

t



0 10 20 30 40 50 60Soil moisture ()

(b)

0

2

4

6

8

10

12

14

Imag

inar

y pa

rt

0 10 20 30 40 50 60Soil moisture ()



(c)

0

5

10

15

20

25

30

35

Imag

inar

y pa

rt

0 10 20 30 40 50 60Soil moisture ()



(d)







0

5

10

15

20

25

30

35

40

Imag

inar

y pa

rt

1 2 3 4 5 6 7 8 9 10 115

10

15

20

25

30

35

40

45

Frequency (GHz)1 2 3 4 5 6 7 8 9 10 11

Frequency (GHz)

Real

par

t



Salinity 30permil

(a)

0

10

20

30

40

50

60

70

Imag

inar

y pa

rt

5

10

15

20

25

30

35

40

45

Real

par

t



1 2 3 4 5 6 7 8 9 10 11Frequency (GHz)

1 2 3 4 5 6 7 8 9 10 11Frequency (GHz)

(b)







05

1015202530354045

Real

par

t of L

ban

d

123

456

0 10 20 30 40 50 60Soil moisture ()

(a)

0

5

10

15

20

25

30

35

40

Real

par

t of C

ban

d

123

456

0 10 20 30 40 50 60Soil moisture ()

(b)

minus2

0

2

4

6

8

10

12

14

Imag

inar

y pa

rt o

f L b

and

0 10 20 30 40 50 60Soil moisture ()

123

456

(c)

minus2

0

2

4

6

8

10

12

14

Imag

inar

y pa

rt o

f C b

and

123

456

0 10 20 30 40 50 60Soil moisture ()

(d)







0

5

10

15

20

25

30

35

40Re

al p

art

0 5 10 15 20 25 30 35 40Frequency (GHz)

2871117201

272954145485


(a)

0 5 10 15 20 25 30 35 400

2

4

6

8

10

12

14

16

18

20

Frequency (GHz)

Imag

inar

y pa

rt

2871117201

272954145485


(b)




3

2minus andHCO3








minus9minus8

Soil moisture ()

HH

bac

ksca

tterin

g co

effici

ent (


(a)

minus17

minus16

minus15

minus14

minus13

minus12

minus11

minus10

minus9

VV

bac

ksca

tterin

g co

effici

ent (

dB)

5 10 15 20 25 30 35 40 45 50 55Soil moisture ()


(b)

minus37minus365

minus36minus355

minus35minus345

minus34minus335

minus33minus325

minus32

HV

bac

ksca

tterin

g co

effici

ent (

dB)

5 10 15 20 25 30 35 40 45 50 55Soil moisture ()


(c)










1205900

con (120579) = 1205900

veg (120579) + 1205742

(120579) 1205900

soil (120579) (3)


0 10 20 30 40 50 60Soil moisture ()

0

01

02

03

04

05

06

07

Fres

nel c

oeffi

cien

t

R

Rh

(a)

0 10 20 30 40 50 60Soil moisture ()

0

002

004

006

008

01

012

Gra

dien

t of F

resn

el co

effici

ent

R

Rh

(b)



minus28

minus26

minus24

minus22

minus20

minus18

minus16

minus14

minus12

minus10

minus8



Sim

ulat

ed1205900

(dB)

R2= 01518

(a)




minus30

minus28

minus26

minus24

minus22

minus20

minus18

minus16

minus14

minus12

minus10

minus8

Sim

ulat

ed1205900

(dB)

R2= 01898

(b)







0was






minus25

minus20

minus15

minus10

minus5

0


Sim

ulat

ed1205900

(dB)

HH polarization

R2= 05228

1 1 line

(a)


minus25

minus20

minus15

minus10

minus5

0


Sim

ulat

ed1205900

(dB)

R2= 06106


(b)



5 Conclusions














References






























Journal of












Volume 2014

Advances in









Geophysics















123∘45

9984000998400998400E 123

∘55

9984000998400998400E 124

∘59984000998400998400E

123∘45

9984000998400998400E 123

∘55

9984000998400998400E 124

∘59984000998400998400E

45∘259984000998400998400

N45∘359984000998400998400

N45∘309984000998400998400

N45∘409984000998400998400

N

45∘259984000998400998400

N45∘359984000998400998400

N45∘309984000998400998400

N45∘409984000998400998400

N

W

S

N

E







120576120572

119898= 1 +

120588119887

120588119904

(120576120572

119904minus 1) + 119898

120573

V 120576120572

119891119908minus 119898V (1)

where 120572 = 065 120576119904= (101 + 044120588











2gt 276 sdot 119904 sdot 120582 All


gt 35∘sim 40∘




1205900

119901119901=

1198962

4120587

exp (minus411989621199111205902)

times

1003816100381610038161003816100381610038161003816

2119896119911120590 +

120590

4

(1198651199011199011

+ 1198651199011199012)

1003816100381610038161003816100381610038161003816

2

119908 (2119896119909 0)

+

infin

sum

119899=2

1003816100381610038161003816100381610038161003816

(2119896119911120590)119899119891119901119901+

120590

4

1198651199011199011(2119896119911120590)119899minus11003816100381610038161003816100381610038161003816

2

times

119908(119899)(2119896119909 0)

119899

(2)



ℎ cos 120579








4 Results




0 10 20 30 40 50 60 70 80 90 10005

1015202530354045

Salinity (permil)

Real

par


(a)

05

101520253035404550

Imag

inar

y pa

rt

0 10 20 30 40 50 60 70 80 90 100Salinity (permil)


(b)

0 10 20 30 40 50 60Soil moisture ()


05

1015202530354045

Real

par

t

(c)

Imag

inar

y pa

rt


0 10 20 30 40 50 60Soil moisture ()

05

1015202530354045

(d)







119905and




0 5 10 15 20 25 30 35 40 45 50 5505

1015

2025303540

45Re

al p

art

Soil moisture ()



(a)

0

5

10

15

20

25

30

40

35

Real

par

t



0 10 20 30 40 50 60Soil moisture ()

(b)

0

2

4

6

8

10

12

14

Imag

inar

y pa

rt

0 10 20 30 40 50 60Soil moisture ()



(c)

0

5

10

15

20

25

30

35

Imag

inar

y pa

rt

0 10 20 30 40 50 60Soil moisture ()



(d)







0

5

10

15

20

25

30

35

40

Imag

inar

y pa

rt

1 2 3 4 5 6 7 8 9 10 115

10

15

20

25

30

35

40

45

Frequency (GHz)1 2 3 4 5 6 7 8 9 10 11

Frequency (GHz)

Real

par

t



Salinity 30permil

(a)

0

10

20

30

40

50

60

70

Imag

inar

y pa

rt

5

10

15

20

25

30

35

40

45

Real

par

t



1 2 3 4 5 6 7 8 9 10 11Frequency (GHz)

1 2 3 4 5 6 7 8 9 10 11Frequency (GHz)

(b)







05

1015202530354045

Real

par

t of L

ban

d

123

456

0 10 20 30 40 50 60Soil moisture ()

(a)

0

5

10

15

20

25

30

35

40

Real

par

t of C

ban

d

123

456

0 10 20 30 40 50 60Soil moisture ()

(b)

minus2

0

2

4

6

8

10

12

14

Imag

inar

y pa

rt o

f L b

and

0 10 20 30 40 50 60Soil moisture ()

123

456

(c)

minus2

0

2

4

6

8

10

12

14

Imag

inar

y pa

rt o

f C b

and

123

456

0 10 20 30 40 50 60Soil moisture ()

(d)







0

5

10

15

20

25

30

35

40Re

al p

art

0 5 10 15 20 25 30 35 40Frequency (GHz)

2871117201

272954145485


(a)

0 5 10 15 20 25 30 35 400

2

4

6

8

10

12

14

16

18

20

Frequency (GHz)

Imag

inar

y pa

rt

2871117201

272954145485


(b)




3

2minus andHCO3








minus9minus8

Soil moisture ()

HH

bac

ksca

tterin

g co

effici

ent (


(a)

minus17

minus16

minus15

minus14

minus13

minus12

minus11

minus10

minus9

VV

bac

ksca

tterin

g co

effici

ent (

dB)

5 10 15 20 25 30 35 40 45 50 55Soil moisture ()


(b)

minus37minus365

minus36minus355

minus35minus345

minus34minus335

minus33minus325

minus32

HV

bac

ksca

tterin

g co

effici

ent (

dB)

5 10 15 20 25 30 35 40 45 50 55Soil moisture ()


(c)










1205900

con (120579) = 1205900

veg (120579) + 1205742

(120579) 1205900

soil (120579) (3)


0 10 20 30 40 50 60Soil moisture ()

0

01

02

03

04

05

06

07

Fres

nel c

oeffi

cien

t

R

Rh

(a)

0 10 20 30 40 50 60Soil moisture ()

0

002

004

006

008

01

012

Gra

dien

t of F

resn

el co

effici

ent

R

Rh

(b)



minus28

minus26

minus24

minus22

minus20

minus18

minus16

minus14

minus12

minus10

minus8



Sim

ulat

ed1205900

(dB)

R2= 01518

(a)




minus30

minus28

minus26

minus24

minus22

minus20

minus18

minus16

minus14

minus12

minus10

minus8

Sim

ulat

ed1205900

(dB)

R2= 01898

(b)







0was






minus25

minus20

minus15

minus10

minus5

0


Sim

ulat

ed1205900

(dB)

HH polarization

R2= 05228

1 1 line

(a)


minus25

minus20

minus15

minus10

minus5

0


Sim

ulat

ed1205900

(dB)

R2= 06106


(b)



5 Conclusions














References






























Journal of












Volume 2014

Advances in









Geophysics

















2gt 276 sdot 119904 sdot 120582 All


gt 35∘sim 40∘




1205900

119901119901=

1198962

4120587

exp (minus411989621199111205902)

times

1003816100381610038161003816100381610038161003816

2119896119911120590 +

120590

4

(1198651199011199011

+ 1198651199011199012)

1003816100381610038161003816100381610038161003816

2

119908 (2119896119909 0)

+

infin

sum

119899=2

1003816100381610038161003816100381610038161003816

(2119896119911120590)119899119891119901119901+

120590

4

1198651199011199011(2119896119911120590)119899minus11003816100381610038161003816100381610038161003816

2

times

119908(119899)(2119896119909 0)

119899

(2)



ℎ cos 120579








4 Results




0 10 20 30 40 50 60 70 80 90 10005

1015202530354045

Salinity (permil)

Real

par


(a)

05

101520253035404550

Imag

inar

y pa

rt

0 10 20 30 40 50 60 70 80 90 100Salinity (permil)


(b)

0 10 20 30 40 50 60Soil moisture ()


05

1015202530354045

Real

par

t

(c)

Imag

inar

y pa

rt


0 10 20 30 40 50 60Soil moisture ()

05

1015202530354045

(d)







119905and




0 5 10 15 20 25 30 35 40 45 50 5505

1015

2025303540

45Re

al p

art

Soil moisture ()



(a)

0

5

10

15

20

25

30

40

35

Real

par

t



0 10 20 30 40 50 60Soil moisture ()

(b)

0

2

4

6

8

10

12

14

Imag

inar

y pa

rt

0 10 20 30 40 50 60Soil moisture ()



(c)

0

5

10

15

20

25

30

35

Imag

inar

y pa

rt

0 10 20 30 40 50 60Soil moisture ()



(d)







0

5

10

15

20

25

30

35

40

Imag

inar

y pa

rt

1 2 3 4 5 6 7 8 9 10 115

10

15

20

25

30

35

40

45

Frequency (GHz)1 2 3 4 5 6 7 8 9 10 11

Frequency (GHz)

Real

par

t



Salinity 30permil

(a)

0

10

20

30

40

50

60

70

Imag

inar

y pa

rt

5

10

15

20

25

30

35

40

45

Real

par

t



1 2 3 4 5 6 7 8 9 10 11Frequency (GHz)

1 2 3 4 5 6 7 8 9 10 11Frequency (GHz)

(b)







05

1015202530354045

Real

par

t of L

ban

d

123

456

0 10 20 30 40 50 60Soil moisture ()

(a)

0

5

10

15

20

25

30

35

40

Real

par

t of C

ban

d

123

456

0 10 20 30 40 50 60Soil moisture ()

(b)

minus2

0

2

4

6

8

10

12

14

Imag

inar

y pa

rt o

f L b

and

0 10 20 30 40 50 60Soil moisture ()

123

456

(c)

minus2

0

2

4

6

8

10

12

14

Imag

inar

y pa

rt o

f C b

and

123

456

0 10 20 30 40 50 60Soil moisture ()

(d)







0

5

10

15

20

25

30

35

40Re

al p

art

0 5 10 15 20 25 30 35 40Frequency (GHz)

2871117201

272954145485


(a)

0 5 10 15 20 25 30 35 400

2

4

6

8

10

12

14

16

18

20

Frequency (GHz)

Imag

inar

y pa

rt

2871117201

272954145485


(b)




3

2minus andHCO3








minus9minus8

Soil moisture ()

HH

bac

ksca

tterin

g co

effici

ent (


(a)

minus17

minus16

minus15

minus14

minus13

minus12

minus11

minus10

minus9

VV

bac

ksca

tterin

g co

effici

ent (

dB)

5 10 15 20 25 30 35 40 45 50 55Soil moisture ()


(b)

minus37minus365

minus36minus355

minus35minus345

minus34minus335

minus33minus325

minus32

HV

bac

ksca

tterin

g co

effici

ent (

dB)

5 10 15 20 25 30 35 40 45 50 55Soil moisture ()


(c)










1205900

con (120579) = 1205900

veg (120579) + 1205742

(120579) 1205900

soil (120579) (3)


0 10 20 30 40 50 60Soil moisture ()

0

01

02

03

04

05

06

07

Fres

nel c

oeffi

cien

t

R

Rh

(a)

0 10 20 30 40 50 60Soil moisture ()

0

002

004

006

008

01

012

Gra

dien

t of F

resn

el co

effici

ent

R

Rh

(b)



minus28

minus26

minus24

minus22

minus20

minus18

minus16

minus14

minus12

minus10

minus8



Sim

ulat

ed1205900

(dB)

R2= 01518

(a)




minus30

minus28

minus26

minus24

minus22

minus20

minus18

minus16

minus14

minus12

minus10

minus8

Sim

ulat

ed1205900

(dB)

R2= 01898

(b)







0was






minus25

minus20

minus15

minus10

minus5

0


Sim

ulat

ed1205900

(dB)

HH polarization

R2= 05228

1 1 line

(a)


minus25

minus20

minus15

minus10

minus5

0


Sim

ulat

ed1205900

(dB)

R2= 06106


(b)



5 Conclusions














References






























Journal of












Volume 2014

Advances in









Geophysics















0 10 20 30 40 50 60 70 80 90 10005

1015202530354045

Salinity (permil)

Real

par


(a)

05

101520253035404550

Imag

inar

y pa

rt

0 10 20 30 40 50 60 70 80 90 100Salinity (permil)


(b)

0 10 20 30 40 50 60Soil moisture ()


05

1015202530354045

Real

par

t

(c)

Imag

inar

y pa

rt


0 10 20 30 40 50 60Soil moisture ()

05

1015202530354045

(d)







119905and




0 5 10 15 20 25 30 35 40 45 50 5505

1015

2025303540

45Re

al p

art

Soil moisture ()



(a)

0

5

10

15

20

25

30

40

35

Real

par

t



0 10 20 30 40 50 60Soil moisture ()

(b)

0

2

4

6

8

10

12

14

Imag

inar

y pa

rt

0 10 20 30 40 50 60Soil moisture ()



(c)

0

5

10

15

20

25

30

35

Imag

inar

y pa

rt

0 10 20 30 40 50 60Soil moisture ()



(d)







0

5

10

15

20

25

30

35

40

Imag

inar

y pa

rt

1 2 3 4 5 6 7 8 9 10 115

10

15

20

25

30

35

40

45

Frequency (GHz)1 2 3 4 5 6 7 8 9 10 11

Frequency (GHz)

Real

par

t



Salinity 30permil

(a)

0

10

20

30

40

50

60

70

Imag

inar

y pa

rt

5

10

15

20

25

30

35

40

45

Real

par

t



1 2 3 4 5 6 7 8 9 10 11Frequency (GHz)

1 2 3 4 5 6 7 8 9 10 11Frequency (GHz)

(b)







05

1015202530354045

Real

par

t of L

ban

d

123

456

0 10 20 30 40 50 60Soil moisture ()

(a)

0

5

10

15

20

25

30

35

40

Real

par

t of C

ban

d

123

456

0 10 20 30 40 50 60Soil moisture ()

(b)

minus2

0

2

4

6

8

10

12

14

Imag

inar

y pa

rt o

f L b

and

0 10 20 30 40 50 60Soil moisture ()

123

456

(c)

minus2

0

2

4

6

8

10

12

14

Imag

inar

y pa

rt o

f C b

and

123

456

0 10 20 30 40 50 60Soil moisture ()

(d)







0

5

10

15

20

25

30

35

40Re

al p

art

0 5 10 15 20 25 30 35 40Frequency (GHz)

2871117201

272954145485


(a)

0 5 10 15 20 25 30 35 400

2

4

6

8

10

12

14

16

18

20

Frequency (GHz)

Imag

inar

y pa

rt

2871117201

272954145485


(b)




3

2minus andHCO3








minus9minus8

Soil moisture ()

HH

bac

ksca

tterin

g co

effici

ent (


(a)

minus17

minus16

minus15

minus14

minus13

minus12

minus11

minus10

minus9

VV

bac

ksca

tterin

g co

effici

ent (

dB)

5 10 15 20 25 30 35 40 45 50 55Soil moisture ()


(b)

minus37minus365

minus36minus355

minus35minus345

minus34minus335

minus33minus325

minus32

HV

bac

ksca

tterin

g co

effici

ent (

dB)

5 10 15 20 25 30 35 40 45 50 55Soil moisture ()


(c)










1205900

con (120579) = 1205900

veg (120579) + 1205742

(120579) 1205900

soil (120579) (3)


0 10 20 30 40 50 60Soil moisture ()

0

01

02

03

04

05

06

07

Fres

nel c

oeffi

cien

t

R

Rh

(a)

0 10 20 30 40 50 60Soil moisture ()

0

002

004

006

008

01

012

Gra

dien

t of F

resn

el co

effici

ent

R

Rh

(b)



minus28

minus26

minus24

minus22

minus20

minus18

minus16

minus14

minus12

minus10

minus8



Sim

ulat

ed1205900

(dB)

R2= 01518

(a)




minus30

minus28

minus26

minus24

minus22

minus20

minus18

minus16

minus14

minus12

minus10

minus8

Sim

ulat

ed1205900

(dB)

R2= 01898

(b)







0was






minus25

minus20

minus15

minus10

minus5

0


Sim

ulat

ed1205900

(dB)

HH polarization

R2= 05228

1 1 line

(a)


minus25

minus20

minus15

minus10

minus5

0


Sim

ulat

ed1205900

(dB)

R2= 06106


(b)



5 Conclusions














References






























Journal of












Volume 2014

Advances in









Geophysics















0 5 10 15 20 25 30 35 40 45 50 5505

1015

2025303540

45Re

al p

art

Soil moisture ()



(a)

0

5

10

15

20

25

30

40

35

Real

par

t



0 10 20 30 40 50 60Soil moisture ()

(b)

0

2

4

6

8

10

12

14

Imag

inar

y pa

rt

0 10 20 30 40 50 60Soil moisture ()



(c)

0

5

10

15

20

25

30

35

Imag

inar

y pa

rt

0 10 20 30 40 50 60Soil moisture ()



(d)







0

5

10

15

20

25

30

35

40

Imag

inar

y pa

rt

1 2 3 4 5 6 7 8 9 10 115

10

15

20

25

30

35

40

45

Frequency (GHz)1 2 3 4 5 6 7 8 9 10 11

Frequency (GHz)

Real

par

t



Salinity 30permil

(a)

0

10

20

30

40

50

60

70

Imag

inar

y pa

rt

5

10

15

20

25

30

35

40

45

Real

par

t



1 2 3 4 5 6 7 8 9 10 11Frequency (GHz)

1 2 3 4 5 6 7 8 9 10 11Frequency (GHz)

(b)







05

1015202530354045

Real

par

t of L

ban

d

123

456

0 10 20 30 40 50 60Soil moisture ()

(a)

0

5

10

15

20

25

30

35

40

Real

par

t of C

ban

d

123

456

0 10 20 30 40 50 60Soil moisture ()

(b)

minus2

0

2

4

6

8

10

12

14

Imag

inar

y pa

rt o

f L b

and

0 10 20 30 40 50 60Soil moisture ()

123

456

(c)

minus2

0

2

4

6

8

10

12

14

Imag

inar

y pa

rt o

f C b

and

123

456

0 10 20 30 40 50 60Soil moisture ()

(d)







0

5

10

15

20

25

30

35

40Re

al p

art

0 5 10 15 20 25 30 35 40Frequency (GHz)

2871117201

272954145485


(a)

0 5 10 15 20 25 30 35 400

2

4

6

8

10

12

14

16

18

20

Frequency (GHz)

Imag

inar

y pa

rt

2871117201

272954145485


(b)




3

2minus andHCO3








minus9minus8

Soil moisture ()

HH

bac

ksca

tterin

g co

effici

ent (


(a)

minus17

minus16

minus15

minus14

minus13

minus12

minus11

minus10

minus9

VV

bac

ksca

tterin

g co

effici

ent (

dB)

5 10 15 20 25 30 35 40 45 50 55Soil moisture ()


(b)

minus37minus365

minus36minus355

minus35minus345

minus34minus335

minus33minus325

minus32

HV

bac

ksca

tterin

g co

effici

ent (

dB)

5 10 15 20 25 30 35 40 45 50 55Soil moisture ()


(c)










1205900

con (120579) = 1205900

veg (120579) + 1205742

(120579) 1205900

soil (120579) (3)


0 10 20 30 40 50 60Soil moisture ()

0

01

02

03

04

05

06

07

Fres

nel c

oeffi

cien

t

R

Rh

(a)

0 10 20 30 40 50 60Soil moisture ()

0

002

004

006

008

01

012

Gra

dien

t of F

resn

el co

effici

ent

R

Rh

(b)



minus28

minus26

minus24

minus22

minus20

minus18

minus16

minus14

minus12

minus10

minus8



Sim

ulat

ed1205900

(dB)

R2= 01518

(a)




minus30

minus28

minus26

minus24

minus22

minus20

minus18

minus16

minus14

minus12

minus10

minus8

Sim

ulat

ed1205900

(dB)

R2= 01898

(b)







0was






minus25

minus20

minus15

minus10

minus5

0


Sim

ulat

ed1205900

(dB)

HH polarization

R2= 05228

1 1 line

(a)


minus25

minus20

minus15

minus10

minus5

0


Sim

ulat

ed1205900

(dB)

R2= 06106


(b)



5 Conclusions














References






























Journal of












Volume 2014

Advances in









Geophysics















0

5

10

15

20

25

30

35

40

Imag

inar

y pa

rt

1 2 3 4 5 6 7 8 9 10 115

10

15

20

25

30

35

40

45

Frequency (GHz)1 2 3 4 5 6 7 8 9 10 11

Frequency (GHz)

Real

par

t



Salinity 30permil

(a)

0

10

20

30

40

50

60

70

Imag

inar

y pa

rt

5

10

15

20

25

30

35

40

45

Real

par

t



1 2 3 4 5 6 7 8 9 10 11Frequency (GHz)

1 2 3 4 5 6 7 8 9 10 11Frequency (GHz)

(b)







05

1015202530354045

Real

par

t of L

ban

d

123

456

0 10 20 30 40 50 60Soil moisture ()

(a)

0

5

10

15

20

25

30

35

40

Real

par

t of C

ban

d

123

456

0 10 20 30 40 50 60Soil moisture ()

(b)

minus2

0

2

4

6

8

10

12

14

Imag

inar

y pa

rt o

f L b

and

0 10 20 30 40 50 60Soil moisture ()

123

456

(c)

minus2

0

2

4

6

8

10

12

14

Imag

inar

y pa

rt o

f C b

and

123

456

0 10 20 30 40 50 60Soil moisture ()

(d)







0

5

10

15

20

25

30

35

40Re

al p

art

0 5 10 15 20 25 30 35 40Frequency (GHz)

2871117201

272954145485


(a)

0 5 10 15 20 25 30 35 400

2

4

6

8

10

12

14

16

18

20

Frequency (GHz)

Imag

inar

y pa

rt

2871117201

272954145485


(b)




3

2minus andHCO3








minus9minus8

Soil moisture ()

HH

bac

ksca

tterin

g co

effici

ent (


(a)

minus17

minus16

minus15

minus14

minus13

minus12

minus11

minus10

minus9

VV

bac

ksca

tterin

g co

effici

ent (

dB)

5 10 15 20 25 30 35 40 45 50 55Soil moisture ()


(b)

minus37minus365

minus36minus355

minus35minus345

minus34minus335

minus33minus325

minus32

HV

bac

ksca

tterin

g co

effici

ent (

dB)

5 10 15 20 25 30 35 40 45 50 55Soil moisture ()


(c)










1205900

con (120579) = 1205900

veg (120579) + 1205742

(120579) 1205900

soil (120579) (3)


0 10 20 30 40 50 60Soil moisture ()

0

01

02

03

04

05

06

07

Fres

nel c

oeffi

cien

t

R

Rh

(a)

0 10 20 30 40 50 60Soil moisture ()

0

002

004

006

008

01

012

Gra

dien

t of F

resn

el co

effici

ent

R

Rh

(b)



minus28

minus26

minus24

minus22

minus20

minus18

minus16

minus14

minus12

minus10

minus8



Sim

ulat

ed1205900

(dB)

R2= 01518

(a)




minus30

minus28

minus26

minus24

minus22

minus20

minus18

minus16

minus14

minus12

minus10

minus8

Sim

ulat

ed1205900

(dB)

R2= 01898

(b)







0was






minus25

minus20

minus15

minus10

minus5

0


Sim

ulat

ed1205900

(dB)

HH polarization

R2= 05228

1 1 line

(a)


minus25

minus20

minus15

minus10

minus5

0


Sim

ulat

ed1205900

(dB)

R2= 06106


(b)



5 Conclusions














References






























Journal of












Volume 2014

Advances in









Geophysics















05

1015202530354045

Real

par

t of L

ban

d

123

456

0 10 20 30 40 50 60Soil moisture ()

(a)

0

5

10

15

20

25

30

35

40

Real

par

t of C

ban

d

123

456

0 10 20 30 40 50 60Soil moisture ()

(b)

minus2

0

2

4

6

8

10

12

14

Imag

inar

y pa

rt o

f L b

and

0 10 20 30 40 50 60Soil moisture ()

123

456

(c)

minus2

0

2

4

6

8

10

12

14

Imag

inar

y pa

rt o

f C b

and

123

456

0 10 20 30 40 50 60Soil moisture ()

(d)







0

5

10

15

20

25

30

35

40Re

al p

art

0 5 10 15 20 25 30 35 40Frequency (GHz)

2871117201

272954145485


(a)

0 5 10 15 20 25 30 35 400

2

4

6

8

10

12

14

16

18

20

Frequency (GHz)

Imag

inar

y pa

rt

2871117201

272954145485


(b)




3

2minus andHCO3








minus9minus8

Soil moisture ()

HH

bac

ksca

tterin

g co

effici

ent (


(a)

minus17

minus16

minus15

minus14

minus13

minus12

minus11

minus10

minus9

VV

bac

ksca

tterin

g co

effici

ent (

dB)

5 10 15 20 25 30 35 40 45 50 55Soil moisture ()


(b)

minus37minus365

minus36minus355

minus35minus345

minus34minus335

minus33minus325

minus32

HV

bac

ksca

tterin

g co

effici

ent (

dB)

5 10 15 20 25 30 35 40 45 50 55Soil moisture ()


(c)










1205900

con (120579) = 1205900

veg (120579) + 1205742

(120579) 1205900

soil (120579) (3)


0 10 20 30 40 50 60Soil moisture ()

0

01

02

03

04

05

06

07

Fres

nel c

oeffi

cien

t

R

Rh

(a)

0 10 20 30 40 50 60Soil moisture ()

0

002

004

006

008

01

012

Gra

dien

t of F

resn

el co

effici

ent

R

Rh

(b)



minus28

minus26

minus24

minus22

minus20

minus18

minus16

minus14

minus12

minus10

minus8



Sim

ulat

ed1205900

(dB)

R2= 01518

(a)




minus30

minus28

minus26

minus24

minus22

minus20

minus18

minus16

minus14

minus12

minus10

minus8

Sim

ulat

ed1205900

(dB)

R2= 01898

(b)







0was






minus25

minus20

minus15

minus10

minus5

0


Sim

ulat

ed1205900

(dB)

HH polarization

R2= 05228

1 1 line

(a)


minus25

minus20

minus15

minus10

minus5

0


Sim

ulat

ed1205900

(dB)

R2= 06106


(b)



5 Conclusions














References






























Journal of












Volume 2014

Advances in









Geophysics















0

5

10

15

20

25

30

35

40Re

al p

art

0 5 10 15 20 25 30 35 40Frequency (GHz)

2871117201

272954145485


(a)

0 5 10 15 20 25 30 35 400

2

4

6

8

10

12

14

16

18

20

Frequency (GHz)

Imag

inar

y pa

rt

2871117201

272954145485


(b)




3

2minus andHCO3








minus9minus8

Soil moisture ()

HH

bac

ksca

tterin

g co

effici

ent (


(a)

minus17

minus16

minus15

minus14

minus13

minus12

minus11

minus10

minus9

VV

bac

ksca

tterin

g co

effici

ent (

dB)

5 10 15 20 25 30 35 40 45 50 55Soil moisture ()


(b)

minus37minus365

minus36minus355

minus35minus345

minus34minus335

minus33minus325

minus32

HV

bac

ksca

tterin

g co

effici

ent (

dB)

5 10 15 20 25 30 35 40 45 50 55Soil moisture ()


(c)










1205900

con (120579) = 1205900

veg (120579) + 1205742

(120579) 1205900

soil (120579) (3)


0 10 20 30 40 50 60Soil moisture ()

0

01

02

03

04

05

06

07

Fres

nel c

oeffi

cien

t

R

Rh

(a)

0 10 20 30 40 50 60Soil moisture ()

0

002

004

006

008

01

012

Gra

dien

t of F

resn

el co

effici

ent

R

Rh

(b)



minus28

minus26

minus24

minus22

minus20

minus18

minus16

minus14

minus12

minus10

minus8



Sim

ulat

ed1205900

(dB)

R2= 01518

(a)




minus30

minus28

minus26

minus24

minus22

minus20

minus18

minus16

minus14

minus12

minus10

minus8

Sim

ulat

ed1205900

(dB)

R2= 01898

(b)







0was






minus25

minus20

minus15

minus10

minus5

0


Sim

ulat

ed1205900

(dB)

HH polarization

R2= 05228

1 1 line

(a)


minus25

minus20

minus15

minus10

minus5

0


Sim

ulat

ed1205900

(dB)

R2= 06106


(b)



5 Conclusions














References






























Journal of












Volume 2014

Advances in









Geophysics
















minus9minus8

Soil moisture ()

HH

bac

ksca

tterin

g co

effici

ent (


(a)

minus17

minus16

minus15

minus14

minus13

minus12

minus11

minus10

minus9

VV

bac

ksca

tterin

g co

effici

ent (

dB)

5 10 15 20 25 30 35 40 45 50 55Soil moisture ()


(b)

minus37minus365

minus36minus355

minus35minus345

minus34minus335

minus33minus325

minus32

HV

bac

ksca

tterin

g co

effici

ent (

dB)

5 10 15 20 25 30 35 40 45 50 55Soil moisture ()


(c)










1205900

con (120579) = 1205900

veg (120579) + 1205742

(120579) 1205900

soil (120579) (3)


0 10 20 30 40 50 60Soil moisture ()

0

01

02

03

04

05

06

07

Fres

nel c

oeffi

cien

t

R

Rh

(a)

0 10 20 30 40 50 60Soil moisture ()

0

002

004

006

008

01

012

Gra

dien

t of F

resn

el co

effici

ent

R

Rh

(b)



minus28

minus26

minus24

minus22

minus20

minus18

minus16

minus14

minus12

minus10

minus8



Sim

ulat

ed1205900

(dB)

R2= 01518

(a)




minus30

minus28

minus26

minus24

minus22

minus20

minus18

minus16

minus14

minus12

minus10

minus8

Sim

ulat

ed1205900

(dB)

R2= 01898

(b)







0was






minus25

minus20

minus15

minus10

minus5

0


Sim

ulat

ed1205900

(dB)

HH polarization

R2= 05228

1 1 line

(a)


minus25

minus20

minus15

minus10

minus5

0


Sim

ulat

ed1205900

(dB)

R2= 06106


(b)



5 Conclusions














References






























Journal of












Volume 2014

Advances in









Geophysics















0 10 20 30 40 50 60Soil moisture ()

0

01

02

03

04

05

06

07

Fres

nel c

oeffi

cien

t

R

Rh

(a)

0 10 20 30 40 50 60Soil moisture ()

0

002

004

006

008

01

012

Gra

dien

t of F

resn

el co

effici

ent

R

Rh

(b)



minus28

minus26

minus24

minus22

minus20

minus18

minus16

minus14

minus12

minus10

minus8



Sim

ulat

ed1205900

(dB)

R2= 01518

(a)




minus30

minus28

minus26

minus24

minus22

minus20

minus18

minus16

minus14

minus12

minus10

minus8

Sim

ulat

ed1205900

(dB)

R2= 01898

(b)







0was






minus25

minus20

minus15

minus10

minus5

0


Sim

ulat

ed1205900

(dB)

HH polarization

R2= 05228

1 1 line

(a)


minus25

minus20

minus15

minus10

minus5

0


Sim

ulat

ed1205900

(dB)

R2= 06106


(b)



5 Conclusions














References






























Journal of












Volume 2014

Advances in









Geophysics

















minus25

minus20

minus15

minus10

minus5

0


Sim

ulat

ed1205900

(dB)

HH polarization

R2= 05228

1 1 line

(a)


minus25

minus20

minus15

minus10

minus5

0


Sim

ulat

ed1205900

(dB)

R2= 06106


(b)



5 Conclusions














References






























Journal of












Volume 2014

Advances in









Geophysics
























References






























Journal of












Volume 2014

Advances in









Geophysics























Journal of












Volume 2014

Advances in









Geophysics


















Journal of












Volume 2014

Advances in









Geophysics














Documents

Research Article Analysis of the Dielectric Constant of Saline …downloads.hindawi.com/journals/tswj/2014/563015.pdf · · 2015-11-23Polarization HH/HV/VH/VV Acquisition mode Fine-Quad-Pol