Quantifying Surface Roughness to Detect Geothermal Manifestations from Polarimetric Synthetic Aperture Radar (PolSAR) Data

Fourtieth Workshop on Geothermal Reservoir Engineering Stanford University

1. QUANTIFYING SURFACE ROUGHNESS
TO DETECT GEOTHERMAL
MANIFESTATIONS FROM POLARIMETRIC
SYNTHETIC APERTURE RADAR (POLSAR)
DATA
AsepSaepuloh
1
, KatsuakiKoike
2
, Mohamad NurHeriawan
1
, and TaikiKubo
2
1
Bandung Institute of Technology (ITB), Indonesia.
2
Kyoto University, Japan.
Corresponding: [email protected]

2. PRESENTATION CONTENT
1.INTRODUCTION
2.DATA ACQUISITION AND MEASUREMENTS
3.SURFACE ROUGHNESS QUANTIFICATION AND GEOTHERMAL
ASSESSMENT
4.BACKSCATTERING POLARIMETRIC SAR RESPONSE TO THE
SURFACE ROUGHNESS
5.CONCLUSIONS

3. 1. INTRODUCTION
➢Characterizing physical properties of ground surface using
Synthetic Aperture Radar (SAR) are crucial for geological
target detection under Torrid Zone condition.
➢The backscattering intensity of SAR chiefly is a function of two
physical quantities of surface material, surface roughness and
dielectric parameter.
➢The two parameters were proved effective to discriminate
ground surface materials at volcanic field such as pyroclastic
flows, lava, and lahars.
➢Focused on the surface roughness parameter at geothermal
field.

4. OBJECTIVE AND STUDY AREA
Objectives:
➢How to quantify and identify
the surface roughness at
geothermal manifestation
zones, altered surfaces, mud
pools, and hot springs at a
geothermal field.
➢How to generate surface
roughness model based on field
measurement and SAR remote
sensing technique.
Jakarta
Bandung
KalimantanWindu
Wayang
Malabar
500 km
Study area:
➢Mt. Wayang Windu geothermal field in the
southern part from Bandung City, West Java,
Indonesia was selected as study area.

5. SURFACE ROUGHNESS
➢The surface roughness means the variance of Earth surface
elevations above the horizontal line.
➢Planetary surface roughness extraction and modelling using
remotely sensed techniques is one of challenging topics for the last
decades. The surface roughness is one parameter that geological
features could be predicted such as topographic feature
associated with lava flows.
➢For geothermal field, the interaction between hydrothermal fluid
and host rocks is aimed to be analyzed by the surface roughness
parameter.
➢The resistance of the rocks presented by their roughness to the
geological processes such as alteration due to geothermal process
depends on rock type and/or thermal intensity.

6. QUANTIFICATION PROBLEM
➢Typical quantifying techniques: template devices, stereo-
photography, simple surveying, laser altimetry, and radar
interferometric.
➢Data collected in fields problem: how to quantify the surface
roughness for comparison with radar observation and
prediction of backscatter behavior in various polarization
modes.
➢We measured surface roughness at a field along three
directions: azimuth, range, and dominant topographic
undulation.

7. 2. DATA ACQUISITION AND
MEASUREMENTS
Satellite data used
➢ALOS PALSAR
➢Multi-looking images
➢Backscattering coefficient used
➢The co- (HH,VV) and cross-
polarization (HV,VH) to model
field roughness
??????
�??????
0
=4??????
4
ℎ
0
2
cos
4
�
????????????
�??????
2
??????
Layer penetration possibility of the L-,
X-, and C-bands. The Horizontal (H)
and Vertical (V) polarized was used.

8. 2. DATA ACQUISITION AND
MEASUREMENTS
Field Measurements
➢A set of pin meters.
➢Measured roughness at
geothermal manifestations.
➢Nine zones targeted
including hot springs,
fumaroles, mud pools, and
alteration zones.
➢The gridded measurements
about 30 m lag were
performed.Ramiru
Malabar
Puncak Besar
Gambung
Bedil
Wayang
WinduNini 3.5 kmNWW240
WW241
WW242WW243
WW244
WW245
WW246WW247WW248WW249WW250
WW251
WW252WW253WW254WW255
WW256
WW257
WW258WW259WW260WW261
WW262
WW263WW264
WW265
WW267
WW268
WW269
30 m
Crater
Hot Spring
Measured Point+
Zone-3
Zone-2
Zone-1

9. MEASUREMENT TECHNIQUE
➢Investigated profile lengths common used from centimeters to
hundred meters scale.
➢The longer profile length produced generalization effect when
root-mean-square (RMS) roughness base quantification is
used.
➢According L-band frequency of ALOS PALSAR, a physical
measures using fixed 30 cm pin meter assuming the surface is
stationary.
➢we measured surface roughness at field along flight direction
of the SAR sensor (azimuth), look direction (range), and
dominant topographic undulations.

10. MEASUREMENT TECHNIQUE
The field roughness measurements permit to establish three
qualitative classes of geothermal surface manifestation: alteration
zones, mud pools, and hot springs.N-S
E-W N 115º S
Zone -1 (Altered Surfaces)
N-S E-W N 110º S
Zone -2 (Mud Pool)
N-S E-W N 115º S
Zone -3 (Hot Spring)

11. 3. SURFACE ROUGHNESS QUANTIFICATION
AND GEOTHERMAL ASSESSMENT
➢The root-mean-squared (RMS) height H
0 of profile to quantify surface roughness
from the pin reading.
➢Detrending and interleaving processes to produce zero mean of the profile,
emphasize the small scale variation of terrain, reduce topographic effect, and
obtain correlation each pin height dependency to the profile length (Shepard
et al., 2001).
�
0�=
1
??????
෍
??????=1
??????
????????????
??????−ҧ??????
2
�-15,0
-10,0
-5,0
0,0
5,0
0 5 10 15 20 25 30
Height (cm)
Pin Length (cm)
WW-20 (N115E)
Raw Detrend
-5,0
0,0
5,0
10,0
0 5 10 15 20 25 30
Height (cm)
Pin Length (cm)
WW-20 (E-W)
Raw Detrend
-5,0
0,0
5,0
10,0
15,0
0 5 10 15 20 25 30
Height (cm)
Pin Length (cm)
WW-20 (N-S)
Raw Detrend

12. 3. SURFACE ROUGHNESS QUANTIFICATION
AND GEOTHERMAL ASSESSMENT
➢Correlating the H
0 to the acidity parameter at and around
surface manifestations.
➢The acidity parameter presented by pH lower than 7 is one
parameter to identify geothermal surface manifestation.
➢There were three zones identified based on geothermal
manifestation types:
Zone-1 => altered surfaces
Zone-2 => mud pools
Zone-3 => hot springs

13. 3. SURFACE ROUGHNESS QUANTIFICATION
AND GEOTHERMAL ASSESSMENT
➢Zone-1 altered lava and pyroclastics; the geothermal fluids affected to the rock
matrices higher than rock fragments, remains gravel - boulder.
➢Zone-2 tuffs and lahars; the alteration and weathering processes change fine
rocks to soil and produces flat surfaces at mud pools zone.
➢Zone-3 fine to coarse old volcanic products; the hot springs might affect the
host rocks weakly, surface roughness is independently to the pH.y = -0,27x + 5,7
R² = 0.5
2
3
4
5
6
7
8
0 10 20 30
pH
H
0(cm)
Zone -1 (Altered Surfaces)
N-S
E-W
N . . . E
Mean
Linear (Mean)
y = 0,92x + 4,34
R² = 0.6
4,00
4,50
5,00
5,50
6,00
6,50
7,00
7,50
8,00
0,002,004,006,00
pH
H
0(cm)
Zone -2 (Mud Pool)
N-S
E-W
N . . . E
Mean
Linear (Mean)
y = 0,17x + 6,85
R² = 0.03
4,50
5,00
5,50
6,00
6,50
7,00
7,50
8,00
0,00 2,00 4,00 6,00
pH
H
0 (cm)
Zone -3 (Hot Spring)
N-S
E-W
N . . . E
Mean
Linear (Mean)

14. Saepulohet al. (2015) IEEE-Geoscience
andRemoteSensingLetters.
www.indahnesia.com & Bronto, 2006
Smooth
Rough
??????
0
=4??????
4
ℎ
0
2
cos
4
�
????????????
2
??????
Incidence
angle
Surface
undulation
??????
??????=??????
????????????
0
??????
�
2
??????
2
4??????
3
??????
4
Rough Smooth
Electrical
properties
Roughness funct.
4. BACKSCATTERING POLARIMETRIC SAR RESPONSE
TO THE SURFACE ROUGHNESS

15. 4. BACKSCATTERING POLARIMETRIC SAR RESPONSE
TO THE SURFACE ROUGHNESS
➢Measurement direction of surface roughness, radar
geometry, and polarization mode are the main discussion.
➢How the surface roughness at field responses to the radar
backscattering in range and azimuth direction.
➢The initial surface roughness model was used as basis
sensitivity identification to the surface roughness at the
field (Saepuloh et al., 2015).
ℎ
0�??????=λ−
1
60
ln1−
10
0.1×??????
????????????
0
0.04cos�
??????

16. SAR MODEL TO SURFACE ROUGHNESS
➢The linear fitting for R
2
between surface
roughness at field H
0 and model h
0.
➢The highest R
2
were obtained by surface
roughness model from cross-polarization
modes except in the E-W measurement
direction.
➢The N-E measurement with HV and VH
polarization is the highest R
2
about 0.5.
➢Improving the h
0, we used the HV and VH
polarized mode to the initial model.
0
0,1
0,2
0,3
0,4
0,5
0,6
H0(N-S) H0(E-W) H0(N to E) Mean
Correlation
Determination
(
R
2
)
Pin Direction
h0(HH)h0(HV)h0(VH)h0(VV)

17. SAR MODEL TO SURFACE ROUGHNESS
➢The linear fitting method with R
2
was
used as the optimum criterion to the
h
0.
➢The improved h
0 with HV and VH
polarization as follows:
ℎ
0�??????,??????�=ℎ
0
2
�??????+ℎ
0
2
??????�×??????
�
??????
3
×10
cos�
??????
7
y = 20.7x - 1.4
R² = 0.6
0
2
4
6
8
10
12
0 0,1 0,2 0,3 0,4 0,5
H
0
(
N
-
S
)
h
0(HV,VH)

18. SAR MODEL TO SURFACE ROUGHNESS
➢For Zone-1, the spatial distribution of
low pH agreed to the rough surface
roughness.
➢The high resistance of the rock
fragments than rock matrices to the
hydrothermal fluid caused the
ground surface is composed chiefly
by material in gravel and boulder
size.
➢The volcanic products from lava
and pyroclastics were responsible
the roughness of altered surfaces. RMS height model (cm)
10.7
4.9
2.7
1.6
-0.1
pH
6.8
5.91
5.57
4.46
2.77
WW_01_24 Legend
Point
h
0 (cm)RMS height model (cm)
10.7
4.9
2.7
1.6
-0.1
pH
6.8
5.91
5.57
4.46
2.77
WW_01_24 Legend
Point
pH
100 m
100 m
Zone -1 (Altered Surfaces)

19. SAR MODEL TO SURFACE ROUGHNESS
➢For Zone-2, the smooth surfaces are
located at northeast part and
agreed with low and medium pH as
presented by point from WW25 to
WW29.
➢The hydrothermal interaction with
tuff and laharic breccia caused the
surface of mud pool zones is flat.
➢The very smooth surfaces distributed
sparsely at NW and SE are predicted
from strong weathering process.
75 m
75 m
Zone -2 (Mud Pools)WW_25_51 BY PH
7.47
7.01
6.83
6.67
4.05
mod1_zone2 by _COL3
4.68
2.25
1.61
1.03
-0.38 WW_25_51 BY PH
7.47
7.01
6.83
6.67
4.05
mod1_zone2 by _COL3
4.68
2.25
1.61
1.03
-0.38
h
0 (cm)
pH

20. SAR MODEL TO SURFACE ROUGHNESS
➢For Zone-3, the smooth surfaces are
located at southeast and west,
respectively.
➢The hot springs are located at very
smooth surface as presented by low
pH at WW60, WW61, and WW71.
➢The interaction between
hydrothermal fluids and fine to
coarse old volcanic products at
Zone-3 is responsible to the flattering
of the surfaces.
Zone -3 (Hot Springs)
60 m
60 mmod1_zone4 by _COL3
3.84
1.63
1.2
0.76
-0.39
WW_60_94 BY PH
7.55
7.22
7.01
6.78
4.89 mod1_zone4 by _COL3
3.84
1.63
1.2
0.76
-0.39
WW_60_94 BY PH
7.55
7.22
7.01
6.78
4.89
h
0 (cm)
pH

21. CONCLUSIONS
➢The rock types and thermal activities were significant to the
surface roughness condition.
➢The surface roughness model could be estimated based on
Polarimetric Synthetic Aperture Radar (PolSAR) data from the
Phased Array Synthetic Aperture Radar (PALSAR) onboard
Advanced Land Observing Satellite (ALOS).
➢The N-S field roughness measurements at altered surfaces
provided the best correlation with the backscattering of
cross-polarization, HV and VH modes.
➢According to the field data and model, the low pH
coincided to the rough surfaces at altered surfaces and the
smooth surfaces at mud pools.

22. ACKNOWLEDGMENT
The authors wish to thank “Beneficial and Advanced
Geothermal Use System (BAGUS)” project in the Science and
Technology Research Partnership for Sustainable Development
(SATREPS) for supporting this cooperative research. This research
is also supported fully by LPPM-ITB.

23. THANK YOU