Jeu, R.A.M. de

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RETRIEVAL OF LAND
SURFACE PARAMETERS USING
PASSIVE MICROWAVE
REMOTE SENSING
Richard A.M. de Jeu
Cover: Earth rising above the Moon’s horizon. Photo was taken during the famous
Apollo-11 mission where astronaut Neal Armstrong stepped onto the lunar surface
for the ﬁrst time.
Photo Credit: NASA
c© Richard A.M. de Jeu, 2003
This study was partly funded by the NASA Seasonal-to-Interannual Prediction Project
(NSIPP) and was carried out at the Hydrological Sciences Branch (MC 974) at NASA
Goddard Space Flight Center, Greenbelt, MD, USA, and the Department of Geo-
Environmental Sciences, Faculty of Earth and Life Sciences, Vrije Universiteit Ams-
terdam, the Netherlands.
The full text of this thesis and additional background information are available on
the internet at http://www.geo.vu.nl/∼geomil
Retrieval of land surface parameters using passive microwave remote sensing.
Richard de Jeu, Ph.D. Thesis Vrije Universiteit Amsterdam.
ISBN 09-9016430-8
NUR-code: 934
Subject headings:
Passive Microwave Remote Sensing ′ SMMR ′ Soil Moisture ′ Soil Temperature ′
Vegetation Indices
This thesis was printed by: PrintPartners Ipskamp, Enschede, the Netherlands
VRIJE UNIVERSITEIT
Retrieval of Land Surface Parameters using Passive
Microwave Remote Sensing
ACADEMISCH PROEFSCHRIFT
ter verkrijging van de graad van doctor aan
de Vrije Universiteit Amsterdam,
op gezag van de rector magniﬁcus
prof.dr. T. Sminia,
in het openbaar te verdedigen
ten overstaan van de promotiecommissie
van de faculteit der Aard- en Levenswetenschappen
op dinsdag 4 februari 2003 om 15.45 uur
in het auditorium van de universiteit,
De Boelelaan 1105
door
Richard Adrianus Maria de Jeu
geboren te Alkemade
promotor: prof.dr. H.F. Vugts
copromotor: dr. M. Owe
Contents
1 General Introduction 1
1.1 Background . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1
1.2 Thesis Objective and Approach . . . . . . . . . . . . . . . . . . . . . . 2
1.3 Thesis Outline . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2
2 Microwave Theory 3
2.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3
2.2 Dielectric Constant . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4
2.3 Soil Physical Properties . . . . . . . . . . . . . . . . . . . . . . . . . . 5
2.4 Thermal Sampling Depth . . . . . . . . . . . . . . . . . . . . . . . . . 6
2.5 Surface Roughness . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7
2.6 Vegetation Eﬀects . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8
2.7 Dependence of Polarization on Vegetation . . . . . . . . . . . . . . . . 12
2.8 Atmosphere . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13
3 Description of Data Sets 15
3.1 Satellite Data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15
3.1.1 Nimbus-SMMR . . . . . . . . . . . . . . . . . . . . . . . . . . . 15
3.1.2 TRMM . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16
3.1.3 NOAA-AVHRR . . . . . . . . . . . . . . . . . . . . . . . . . . . 17
3.2 Land Surface Data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17
3.2.1 Vegetation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17
3.2.2 Soil Properties . . . . . . . . . . . . . . . . . . . . . . . . . . . 18
3.2.3 Soil Temperature . . . . . . . . . . . . . . . . . . . . . . . . . . 19
3.2.4 Soil Moisture . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20
3.3 Atmospheric Data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22
3.3.1 Precipitation . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22
3.3.2 Clouds . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22
4 Derivation of Surface Soil Temperatures 25
4.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25
4.2 Atmospheric Eﬀects . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26
4.3 Surface Soil Temperature Model . . . . . . . . . . . . . . . . . . . . . 30
– i –
4.4 Validation of the Model . . . . . . . . . . . . . . . . . . . . . . . . . . 33
4.5 Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 34
4.6 Conclusions and Discussion . . . . . . . . . . . . . . . . . . . . . . . . 36
5 Retrieval of Soil Moisture and Vegetation Optical Depth 37
5.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 37
5.2 Modelling Approach . . . . . . . . . . . . . . . . . . . . . . . . . . . . 38
5.3 Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 42
5.4 Summary and Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . 44
6 Limitations of the Land Surface Parameter Retrievals 49
6.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 49
6.2 Error Propagation Analysis . . . . . . . . . . . . . . . . . . . . . . . . 50
6.2.1 Theory . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 50
6.2.2 Application to the Test Sites . . . . . . . . . . . . . . . . . . . 51
6.3 Masking Routine . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 56
6.3.1 General . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 56
6.3.2 Snow and Frozen Soil . . . . . . . . . . . . . . . . . . . . . . . 56
6.3.3 Vegetation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 56
6.4 Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 58
7 Land Surface Parameters derived from 18 GHz 59
7.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 59
7.2 Model Modiﬁcation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 60
7.3 Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 61
7.3.1 Vegetation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 61
7.3.2 Soil Moisture . . . . . . . . . . . . . . . . . . . . . . . . . . . . 61
7.3.3 Interrelationships and Errors . . . . . . . . . . . . . . . . . . . 61
7.4 Conclusions and Recommendations . . . . . . . . . . . . . . . . . . . . 62
8 Applications 67
8.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 67
8.2 Global Vegetation Monitoring . . . . . . . . . . . . . . . . . . . . . . . 67
8.2.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . 67
8.2.2 Global Vegetation Mapping . . . . . . . . . . . . . . . . . . . . 68
8.2.3 Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 74
8.3 Soil Moisture Dynamics . . . . . . . . . . . . . . . . . . . . . . . . . . 75
8.3.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . 75
8.3.2 The Indian Monsoon . . . . . . . . . . . . . . . . . . . . . . . . 75
8.3.3 Annual Soil Moisture Changes versus Monsoon Circulation . . 78
8.3.4 Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 78
8.4 Time Series Analysis on the Surface Soil Temperatures . . . . . . . . . 79
8.4.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . 79
8.4.2 Time Series Analysis . . . . . . . . . . . . . . . . . . . . . . . . 79
8.4.3 Application to the Continental United States . . . . . . . . . . 82
– ii –
Contents
9 Summary and Conclusions 87
9.1 General . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 87
9.2 Soil Temperature . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 88
9.3 Soil Moisture and Vegetation Optical Depth . . . . . . . . . . . . . . . 88
9.4 Model Sensitivity . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 89
9.5 Wavelength Eﬀects . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 90
9.6 Applications . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 90
9.7 Follow-up Studies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 91
10 Samenvatting en Conclusies 93
10.1 Algemeen . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 93
10.2 Bodemtemperatuur . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 94
10.3 Bodemvocht en Vegetatie . . . . . . . . . . . . . . . . . . . . . . . . . 94
10.4 Gevoeligheid van het Model . . . . . . . . . . . . . . . . . . . . . . . . 95
10.5 Golﬂengte Eﬀecten . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 96
10.6 Toepassingen . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 96
10.7 Vervolgstudies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 97
Bibliography 99
Appendix A: Wang-Schmugge Model 109
Appendix B: Acronyms and Symbols 111
Acknowledgements 115
Publications and Reports 117
– iii –
– iv –
List of Figures
2.1 Comparison of horizontal and vertical polarized emissivity calculated
for an average soil at the SMMR wavelength and incidence angle with
no canopy cover. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4
2.2 Comparison of the soil dielectric constants for typical sand, loam, and
clay soils. The real part is designated by ε′ and the imaginary part by
ε′′. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6
2.3 Horizontal polarized brightness temperature calculated for a range of
roughness values using Equation 2.4. . . . . . . . . . . . . . . . . . . . 7
2.4 Schematic representation of the partitioning of microwave radiation
from a vegetation covered surface in terms of the brightness tempera-
ture (From Van de Griend and Owe (1993)). . . . . . . . . . . . . . . . 9
2.5 The eﬀect of the vegetation optical depth on the emissivity. At H-
polarization, the sensitivity of the above canopy emissivity is severly
reduced at an optical depth of about 0.75 (Γ = 0.3). . . . . . . . . . . 10
2.6 The eﬀect of the single scattering albedo on the soil moisture bright-
ness temperature relationship. . . . . . . . . . . . . . . . . . . . . . . . 11
2.7 Locations of SMMR footprints used to calculate the vertical and hor-
izontal optical depth at saturated conditions. . . . . . . . . . . . . . . 12
2.8 Relationship between vertical and horizontal optical depth. . . . . . . 13
3.1 Location maps of the ﬁeld stations. Figure (A) is a global overview,
(B) shows the U.S. sites, (C) the African site and (D) the Eurasian sites. 23
4.1 Time series of the brightness temperature ratio (-o-) at diﬀerent wave-
lengths and the precipitable water (-) for the Mongolia test site . . . . 27
4.2 Time series of the brightness temperature ratio (-o-) at diﬀerent wave-
lengths and the precipitable water (-) for the Libya test site . . . . . . 28
4.3 Time series of the vertical (top) and horizontal (bottom) emissivity at
37 GHz (-o-) and the precipitable water (-) for the Mongolia test site . 29
4.4 Time series of the vertical (top) and horizontal (bottom) emissivity at
37 GHz (-o-) and the precipitable water (-) for the Libya test site . . . 30
4.5 Relation between the vertical polarized brightness temperature at 37
GHz and the soil temperature at 5 cm depth for diﬀerent soil mois-
ture conditions. Note that the inﬂuence of soil moisture on the linear
relationship does have a random character. . . . . . . . . . . . . . . . 31
– v –
Contents
4.6 The relationship between soil temperature at 5 cm depth and 1.25
cm depth according to ﬁeld observations in Botswana and the U.S.
(BARC) and model simulations (between the two dotted lines). . . . . 32
4.7 Average monthly composites of 1983 of day-time (A, C, E, and G)
and night-time (B, D, F, and H) soil temperature at 5 cm depth of
North America. A and B represent January, C and D April, E and F
July and G and H October. The snow cover is also included and is
indicated with black dots. . . . . . . . . . . . . . . . . . . . . . . . . . 35
5.1 The theoretical relationship between MPDI and the vegetation optical
depth for a range of soil dielectric constants (h = 0, ω = 0.06, and
u = 50.3◦). Typical soil moisture values of 0 m3 m−3, 0.18 m3 m−3,
0.26 m3 m−3, 0.34 m3 m−3, and 0.41 m3 m−3 would correspond to
dielectric constants of k = 3, 8, 13, 18, and 23. . . . . . . . . . . . . . 39
5.2 A graphical presentation of the relationship between the absolute value
of the dielectric constant of the soil (k) and the ﬁtting parameters C1,
C2, C3 and C4. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 40
5.3 Veriﬁcation comparing the MPDI-optical depth relationship derived
from the radiative transfer equation to calculation from simulated data
(h = 0, ω = 0.06, and u = 50.3◦). . . . . . . . . . . . . . . . . . . . . 41
5.4 A simpliﬁed diagram of the soil moisture retrieval methodology . . . . 42
5.5 Time series of satellite derived day-time (◦) and night-time (+) soil
moisture and ground observations (∗) for the test sites. For comparison
the precipitation is included for the American sites. . . . . . . . . . . . 46
5.6 Time series of satellite derived day-time (◦) and night-time (+) vege-
tation optical depth and NDVI (−) for the test sites. For comparison
the precipitation is included for the American sites. . . . . . . . . . . . 47
6.1 The standard deviation of the soil moisture as related the vegetation
optical depth. Note the diﬀerent relations for diﬀerent moisture regimes 52
6.2 The Coeﬃcient of Variation (CV) of the soil moisture as related to
the vegetation optical depth. The relationship is separated in two
diﬀerent soil moisture classes, where (A) represents the dry soils with
soil moisture values below 0.2 m3 m−3 and (B) represents the wet soils
with soil moisture values between 0.2 and 0.5 m3 m−3. In Figure A
the thick dots represent dry soils with soil moisture values below 0.1
m3 m−3 and the thin dots soil moisture values between 0.1 and 0.2 m3
m−3. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 53
6.3 The standard deviation of the vegetation optical depth as related to
the soil moisture. Note the diﬀerent relations for diﬀerent vegetation
types. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 54
6.4 The coeﬃcient of variation of the vegetation optical depth as related
to the soil moisture. The relationship is separated in two diﬀerent
vegetation classes, where (A) represents sparse vegetation with opti-
cal depth values below 0.4, and (B) represents dense vegetation with
optical depth values between 0.4 and 0.8. . . . . . . . . . . . . . . . . 55
– vi –
Contents
7.1 Time series of the soil moisture from 6.6 GHz and 18 GHz for the 5
test sites. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 63
7.2 Time series of the vegetation optical depth derived from 6.6 GHz and
18 GHz for the 5 test site. . . . . . . . . . . . . . . . . . . . . . . . . . 64
7.3 The soil moisture derived from the 6.6 GHz signals versus the soil
moisture from 18 GHz. R2 = 0.60, S.E.E. = 0.06 m3 m−3 for 1614 (n)
points. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 65
7.4 The vegetation optical depth derived from the 6.6 GHz signals versus
the vegetation optical depth from 18 GHz. The dotted line indicates
the 1:1 relation and the solid line the regression line. R2 = 0.81, S.E.E.
= 0.06 for 1614 (n) points. . . . . . . . . . . . . . . . . . . . . . . . . . 65
7.5 The standard deviation of the vegetation optical depth as related to
the soil moisture. These values are derived from the 5 test sites with
the 18 GHz brightness temperatures. . . . . . . . . . . . . . . . . . . . 66
7.6 The standard deviation of the soil moisture as related to the vegetation
optical depth. These values are derived from the 5 test sites with the
18 GHz brightness temperatures. . . . . . . . . . . . . . . . . . . . . . 66
8.1 A monthly composite of the vegetation optical depth for Australia
during July 1983. This image clearly illustrates the boundary eﬀect
with the masked pixels (gray) along the coastlines and surrounding
Lake Eyre in the south central site of Australia. . . . . . . . . . . . . . 69
8.2 Global monthly composites of vegetation optical depth (A and B),
NDVI (C and D), and LAI (E and F) representing January, and April
respectively for 1983. Missing data are represented by the color gray . 70
8.3 Global monthly composites of vegetation optical depth (A and B),
NDVI (C and D), and LAI (E and F) representing July, and October
respectively for 1983. Missing data are represented by the color gray . 71
8.4 The land cover classiﬁcation map developed by Defries and Townshend
(1994) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 72
8.5 Mean monthly precipitation (A, B, C, G, H and I) and soil moisture
(D, E, F, J, K and L) composites from the Indian peninsula of 1983.
This Figure represents the ﬁrst six months. . . . . . . . . . . . . . . . 76
8.6 Mean monthly precipitation (A, B, C, G, H and I) and soil moisture
(D, E, F, J, K and L) composites from the Indian peninsula of 1983.
This Figure represents the last six months. . . . . . . . . . . . . . . . 77
8.7 Results of a statistical time series analysis of surface soil temperature
(5 cm) retrievals from satellite microwave observations for the conti-
nental U.S. during the period 1978 to 1987. The left and right panels
correspond with day-time and night-time observations respectively.
Maps A and B illustrate the 9-year average temperature in Kelvin; C
and D the seasonal amplitude of the mean monthly annual course in
Kelvin; E and F the phase-shift (time of peak) with the unit being the
date; G and H the long term trend (slope) in Kelvin per year. Five
pixels (numbered) were selected for more detailed analysis. . . . . . . 80
– vii –
List of Figures
8.8 Three thematic maps of the U.S. obtained from the LDAS web site
(http://ldas.gsfc.nasa.gov/). These maps are a (A) vegetation classi-
ﬁcation map, (B) classiﬁcation map of the soil texture type, and (C)
elevation map. The description of the soil and vegetation classes can
be found in Table 8.2. . . . . . . . . . . . . . . . . . . . . . . . . . . . 81
8.9 Diﬀerence (in days) between the night-time (Figure 8.7 F) and day-
time (Figure 8.7 E) phase-shift of the soil temperature at 5 cm depth. 82
8.10 The time series of the soil surface temperature for the 5 selected pixels
(as marked in Figure 8.7). The circles in combination with the dashed
line represent the satellite derived monthly average Ts values at 5 cm
depth, and the solid line is the time series analysis model. . . . . . . . 83
– viii –
List of Tables
3.1 Characteristics of the SMMR instrument. . . . . . . . . . . . . . . . . 16
3.2 Characteristics of the extracted Oklahoma Mesonet ﬁeld stations. . . . 19
5.1 Polynomial parameters that describe the relation between the absolute
value of the dielectric constant of the soil (k) and the ﬁtting parameters
C1,C2, C3 and C4 (See Equation 5.3). . . . . . . . . . . . . . . . . . . 40
6.1 Contribution of the input parameters in the total standard deviations
of the soil moisture and vegetation optical depth. Note, the soil mois-
ture values (θ) are in m3 m−3. . . . . . . . . . . . . . . . . . . . . . . 57
8.1 Median vegetation optical depth (τ), NDVI, and LAI values for dif-
ferent land covers derived from the Mean, Maximum and Minimum
monthly images of 1983 . . . . . . . . . . . . . . . . . . . . . . . . . . 73
8.2 Description of the soil and vegetation classes, as given in Figure 8.8. . 81
– ix –



Retrieval of Land Surface Parameters using Passive Microwave Remote Sensing

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