Chapter 8
Microwave sensing
Introduction to Remote Sensing
Instructor: Dr. Cheng-Chien Liu
Department of Earth Sciences
National Cheng-Kung University
Last updated: 4 June 2003
8.1 Introduction
 Microwave
• 1mm~1m  not micro at all
 Features:
• Penetration  any weather condition
• Irrelevant to visible light
 Active and passive, airborne and
spaceborne
8.2 Radar development
 Radio detection and ranging (RADAR)
• pulse of microwave energy  objects  echoes
 detect and ranging
• Nonimaging radar:
e.g. Doppler radar  Doppler frequency shift  velocity
• Plan position indicator (PPI)
circular display screen
rotating antenna
weather forecasting, air traffic control, navigation
Poor spatial resolution  not appropriate for R.S.
8.2 Radar development(Cont.)
 Side-looking airborne radar (SLAR)
• Side-looking radar (SLR)
• Antenna  fixed below the aircraft  point to the
side
• Fig 8.1: SLAR image
• Continuous strips  depicting large ground areas
• 1950s  military reconnaissance
All-weather operating capability
Active, day-or-night imaging system
Declassification  time lag  non-military targets
• An active state of advancement
8.2 Radar development(Cont.)
 Applications of SLAR
• A complete survey of the Darien province of Panama
Fig 8.2
1967
Persistent cloud cover
• Mapping Venezuela
Fig 8.3
1971
Improve the accuracy of the country boundary
Water resourcessource of several rivers
• Project Radam (Radar of the Amazon)
1971~1976
Geologic analysis, timber inventory, transportation route location,
mineral exploration
8.2 Radar development (cont.)
 Applications of SLAR (cont.)
• Applications in ocean
Determine wind, wave and ice conditions, internal waves
Study ocean bottom contours
 Spaceborne radar remote sensing
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1978  Seasat
Shuttle Imaging Radar
1980s: Soviet Cosmos experiments
1991: Almaz-1, ERS-1, JERS-1
1991: Radarsat
8.3 SLAR system operation
 Fig 8.4: Operating principle of SLAR
• Solid lines: radar pulse sent
• Dashed lines: return signals
• Signal from tree: later and smaller than signal
from house
• The slant range SR=ct/2
SR: direct distance between transmitter and object
8.3 SLAR system operation (cont.)
 Fig 8.5: How to create a SLAR image
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fly speed Va
synchronizer switch  transmitter  receiver
transmitted pulse
receive and process
record
8.4 Spatial resolution of SLAR
systems
 Ground resolution cell size 
• Pulse length  range direction
• Antenna bandwidth  azimuth direction
 Range resolution
• Fig 8.6: Dependence of range resolution on
pulse length
Pulse length PL
Slant-range distance ABsr=ABcosq
If ABsr >1/2PL separate signal  differentiable
If ABsr <1/2PL overlapped signal  one large object
8.4 Spatial resolution of SLAR
systems (cont.)
 Fig 8.7: slant-range resolution 
ground range resolution
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•
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•
Depression angle qd
Look angle ql
ABsr=Abcosqd AB=Rr=ABsr/cosqd =ct/2cosqd
Example 8.1
8.4 Spatial resolution of SLAR
systems (cont.)
 Azimuth resolution
• Fig 8.8: Dependence of Ra, b, GR
Ra=GRb
Example 8.2
Antenna beamwidth: b=l/AL
• ALbRa
Physical length of antenna
 Brute force, real aperture, noncoherent radar
 e.g. l=5cm, b=10mrad  AL=5m
if b =2mrad  AL=25m
 Simple for design and data processing
 Short l, short range, low altitude
8.4 Spatial resolution of SLAR
systems (cont.)
 Azimuth resolution (cont.)
• ALbRa (cont.)
Synthesizing and effective length of antenna
 Synthetic Aperture Radar (SAR)
 Complex
 Single physically short antenna+motion along the flight line
 successive elements of a single, long synthetic antenna
 Near range  fewer elements
 Ra=constant  fn(Range)
Another view of explaining how SAR operate (Fig 8.10)
 Ahead of the aircraft  upshifted f
 Behind the aircraft  downshifted f
8.5 Geometric characteristics of
SLAR imagery
 Different from photo and scanner imagery
 Slant-range scale distortion
• Fig 8.11: Slant-range vs ground-range image format
A=B=C but A1<B1<C1
GR=(SR2-H΄2)1/2
• Range scale = fn(H΄)
• Azimuth scale = fn(Vair, VCRT)
• Inertial navigator and control system
 strict control of flight parameters
 reconcile and equalize these independent scales
8.5 Geometric characteristics of
SLAR imagery (cont.)
 Relief displacement
• Fig 8.12: RD on SLAR versus photos
Layover effect: a vertical feature lay over the closer features and
appears to lean toward the nadir
• Fig 8.13: Effects of terrain relief on SLAR images
Terrain slope steeper than lines perpendicular to the direction of the
radar pulse  layover effect.
D: no layover but foreshortening effect
C: image of the front slope  foreshortened  0
B: layover effect, right side is facing away from the radar antenna  no
return signal  dark
A: layover effect, right side is also illuminated  weak return
8.5 Geometric characteristics of
SLAR imagery (cont.)
 Parallax
• Fig 8.14: Flight orientation to produce parallax
a: opposite side
b: same side but different altitude  altitude parallax
• Fig 8.15: Stereo SLAR image, flying same
flight line at different altitude
8.6 Transmission characteristics of
Radar signals
 Table 8.1: Radar band designation
• Letter codes  arbitrarily selected for military
security
 Wavelength
• l  atmospheric attenuation/dispersion
• Precipitation echoes  D6/l4
D: drop diameter
• Applications: PPI  range of heavy rain
e.g. l= 1cm  echo, l=3cm  no echo
8.6 Transmission characteristics of
Radar signals (cont.)
 Polarization
• The signal can be filtered in such a way that its
electrical wave vibrations are restricted to a
single plane perpendicular to the direction of
wave propagation
• Send: H,V
Receive: H,V
Like-polarized: HH, VV
Cross-polarized: HV, VH
Circular polarization
• Mode of polarization  details see §8.8
8.7 Earth surface feature characters
influencing radar returns
 Geometric characteristics:
• Fig 8.16: Effect of sensor/terrain geometry
Local incident angle (Fig 8.17): qi
 Flat terrain: qi =ql
 Consider earth curvature: qi >ql
Radar shadow  complete dark and sharp
• Factors that dominate radar image
0 < qi < 300: topographic slope
300 < qi < 700: surface roughness
700 < qi : radar shadows
8.7 Earth surface feature characters
influencing radar returns (cont.)
 Geometric characteristics (cont.)
• Fig 8.18: Radar reflection from various surfaces
SVH rms 
 (surface variance height )
Rayleigh criterion:
 SVHrms > l/8cosqi  Rough surfacediffuse reflectorsignificant return
 SVHrms  l/8cosqi  Smooth surfacespecular reflectorlow return
Modified Rayleigh criterion:
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SVHrms> l/(4.4cosqi)  rough
SVHrms< l/(25cosqi)  smooth
Others: intermediate
Table 8.2: various bands, various qi
Corner reflector: double reflection  bright, sparkles
(see Fig 8.22 and 8.23)
2
8.7 Earth surface feature characters
influencing radar returns (cont.)
 Electrical characteristics
• Complex dielectric constant (DC) 
reflectivity & conductivity
Dry natural material: DC  3~8
Water: DC  80
Moisture  DC
Plant: moisture  good reflectors
Metal  DC (e.g. metal bridges in Fig 8.22a)
8.7 Earth surface feature characters
influencing radar returns (cont.)
 Soil Response
• Soil moisture  DC  limit radar penetration
• Extremely dry soil condition  penetration of L-band
(Fig 8.30)
 Vegetation response
• Size
Vegetation canopy: leaves, stems, stalks, limbs,….
Underlying soil
• Wavelength
Short (2~6cm)  sensing crop canopies and tree leaves
Longer (10~30cm)  sensing tree trunks and limbs
8.7 Earth surface feature characters
influencing radar returns (cont.)
 Vegetation response (cont.)
• Other factors:
Moisture
Like-polarized (HH or VV) penetrates more than crosspolarized
Align in the azimuth direction
qi
8.7 Earth surface feature characters
influencing radar returns (cont.)
 Water and ice response:
• Smooth water surface  specular reflector  no
returns
• Rough water surface  varying strengths of
returns
• Wave moving toward or away from the radar
system  easier to detect
• Sea ice  dielectric properties
Ice age, surface roughness, internal geometry, temperature,
snow cover…
8.8 Interpretation of SLAR imagery
 Applications of SLAR image
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Mapping major rock units and surficial materials
Mapping geologic structure (folds, faults and joints)
Mapping vegetation types
Determining sea ice types
Mapping surface drainage features
 l v.s. roughness
• Table 8.3
• Fig 8.19
8.8 Interpretation of SLAR imagery
(cont.)
 Intensity of return signal
• High  slopes facing aircraft, rough objects,
high moisture, metal, urban building (corner
reflection.)
• Low  smooth water, pavements, playas
• No  radar shadow
 Speckle:
• Grainy or salt-and-pepper pattern
• Random constructive and destructive interface 
random bright and dark areas
8.8 Interpretation of SLAR imagery
(cont.)
 Multiple-look processing
• Reduce speckle
• Average several independent images for the
same area
• Amount of speckles  (number of looks)-1/2
• The size of the resolution cell & number of
looks
8.8 Interpretation of SLAR imagery
(cont.)
 Fig 8.20: SLAR image
• Large synclinal mountain  upper left and center
• Flight on the top  lighter tone on the slopes
facing up
• Return signals  vegetation surfaces
• Banding around mountain  alternation of
bedrock types
• River and lake  dark tone
• HV shows less contrast than HH
It’s not always possible to predict HH or HV is better
8.8 Interpretation of SLAR imagery
(cont.)
 Fig 8.21
• Basaltic lava flow
C: The “Sunshine Basalt” flow  Sunshine Crater
 Darker tone on the HV image.
D: The “Pisgah Basalt” flow  Pisgah Crater
A: lighter tone on the HV image  greater density of
vegetation
B: boundary
Playa (dry lakebed)  dark tone
 Gravel road
8.8 Interpretation of SLAR imagery
(cont.)
 Fig 8.22a: small urban area
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Large building  corner reflection  high return
Metallic bridge  high return
River water  dark
Rectangle field
Bed sedimentary rock
 Fig 8.22b: horizontally bedded sedimentary rocks
with loess cover
• Potential soil erosion  strip farming  contour lines
8.8 Interpretation of SLAR imagery
(cont.)
 Fig 8.23:
• IRIS:
high resolution mode 3m  6m resolution
Wide swath mode: 18m  10m resolution
• Malldark
• Potomac Riverblack
• Airport
 Fig 8.24: Multiwavelength SLAR image
• Wooded area: diffuse reflectors in both X and L band
• Cultivated fields: diffuse reflectors in X band but acts
as near-specular reflectors in the L band
8.9 Experimental Radar remote
sensing from space
 Seasat-1
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1978-1978, (99 days)
800km, near-polar orbit
SAR, L-band (23.5cm), HH polarization
Swath: 100 km
• Resolution: 25m25m (range  azimuth)
• Original goals:
 Global sea surface wave field
 Polar sea ice conditions.
• Also revealed applications to
 Ocean: internal waves, current boundaries, eddies, fronts, bathymetric features,
storms, rainfalls, windrows.
 Land: geology water resources, land cover mapping, agricultural assessment.
8.9 Experimental Radar remote
sensing from space (cont.)
 Seasat-1 images
• Fig 8.25: Seasat SAR image of the English Channel
near the straits of Dover.
Tidal variations  7m, 1.5m/s
Sand bars  hazardous
• Fig 8.26: Pack ice
Banks Island (lower right-hand portion)
Brighter ice areas  rough surface  older ice
Darker areas  open water or recently frozen ice
3 days  15km
Fletcher’s Ice Island: 7km  12 km, 157km in 2 month
• Fig 8.27: Appalachian mountains. L-band, 1:575,000
Sidelighting  auticlines and synclines
8.9 Experimental Radar remote
sensing from space (cont.)
 Shuttle Imaging Radar
• SIR-A: 1981
260km
SAR. L-band (23.5cm), HH polarization
9.4m antenna, 470~530 look angle
Resolution: 40m 40m (range  azimuth)
Swath: 50km
Fig 8.28: Saudi Arabia & Iraq. (MSS vs SAR)
 Dry river channels  smooth, dry layer of wind- deposited silt  lots radar return  dark
 Outcropping carbonate rocks  rough angular surface  strong radar return.
Fig 8.29: Eastern China
 White spots  villages
 Levee
Fig 8.30: Sahara Desert
 Penetration of L-band wave in extremely dry material  underlying bedrock structure
8.9 Experimental Radar remote
sensing from space (cont.)
 Shuttle Imaging Radar (cont.)
• SIR-B: 1984
Tiltable antenna (150 ~ 600)
 Assessing the effect of various incident angles
 Stereo images
Resolution
 Azimuth: 25m
 Range: 14m at 600~ 46m at 150
Fig 8.31: Montreal
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Developed area  bright area
River  dark area
Bridge
Long, striplike patterns of agricultural fields (lower right)
Fig 8.32: Mt. Shasta.
 a: 600, b:qi=300
 Young lava flow  unvegetated angular chunks of basalt
Older lava flows  darker, more vegetated
8.9 Experimental Radar remote
sensing from space (cont.)
 Shuttle Imaging Radar (cont.)
• Fig 8.33: perspective views of Mt. Shasta
Generated from Fig 8.32
Successive views taken counterclockwise around the mountain
• Fig 8.34: Stereopair (450 and 540)
Small stereo convergence angle (90) but excellent image
Snow cover  dark
• Fig 8.35: northern Florida
Flat, 45m mean elevation, sandy soil overlay weathering, limestone,
sinkhole lakes
Water bodies (W), clear-cut areas(C), powerline right-of-way (P), roads
( R), Pine forest (F), Cypress-tupelo swamps (S)
 Cypress-tupelo swamps: dark (580)  light (450)  lighter (280)
 Specular reflection from the standing water + tree trunks  complex corner reflector
effect
8.9 Experimental Radar remote
sensing from space (cont.)
 Shuttle Imaging Radar (cont.)
• SIR-C/X-SAR
1994
X-band(3cm), C-band(6cm), L-band (23cm)
Antenna + shuttle  pointable
Swath: 15-90km
Resolution: 10~200m
Plate
• Cosmos-1870
Experiment
1987
8.10 ALMAZ-1
 ALMAZ-1
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3-31-1991~10-17-1992
USSR
Commercial basis
Altitude: 300km  360km
S-band (10cm)
L= 300 ~ 600
Resolution:10m ~ 30m
2 antennas
Swath: 350km  2
Radiometric scanner (RMS)
 Fig 8.36: Almaz radar image
8.11 ERS Satellite Program
 Agency: ESA (European Space Agency)
 Orbit: 777km, Sun synchronous
 Design life: 3 years
 ERS-1: 1991
 ERS-2: 1995
8.12 Sensors onboard ERS-1
 C-band AMI (active microwave instrument)
 Ku-band radar altimeter
 An along-track scanning radiometer
 3 modes of AMI
• IMAGE
• WAVE
• WIND
8.13 ERS-1 AMI image
interpretation
 AMI vs SIR-A, -B and Almaz-1
• Shorter : C-band
• Steeper qi: qi =230
• VV
 Fig 8.37: ERS-1 radar image
• Canada/USA border
• Milk River
 Fig 8.38:
• Center pivot irrigation area  moisture  lighter
• Marsh  roughness, moisture  corner reflection 
lighter
8.13 ERS-1 AMI image
interpretation (cont.)
 Fig 8.39: mountainous region.
• Effect of layover  steep ql
• The Pacific Ocean
 Fig 8.40: area of regenerating forest
clearcut.
• Clear cut  pasture  smooth grass surface
 visible
• Reprocess  clearcut  light-colored
• River
8.13 ERS-1 AMI image
interpretation (cont.)
 Fig 8.42: internal waves from the Atlantic
Ocean to the Mediterranean Sea.
• 2km
• Different salinities  different layer
• Tide  current
 Fig 8.43: St. Lawrance River
• Wind  roughened surface  lighter tone
• Influence of an atmospheric front on water surface
roughness  pattern (upper-left  lower-right)
• Small river mixed with St. Lawrence River 
temperature difference  arc shape
8.13 ERS-1 AMI image
interpretation (cont.)
 Fig 8.44: oil slick
• Oil films  dampening wave  darker
8.14 JERS-1
 JERS-1
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1992
568km, sun-synchronous orbits
SAR, L-band (23cm), HH polarization
Swath: 75km
Resolution: 18m
Expected lifetime: 2 years
 Fig 8.45: Mt. Fuji
• Snow-covered  dark
• Lake  dark
• Forest  lighter-toned
8.15 Radarsat:
 Radsat
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1995
798km, sun-synchronous orbit
SAR, C-band (5.6cm). HH polarization
Swath and resolution:
Table 8.4: Radarsat beam selection modes
Fig 8.46: Radarsat imaging mode
• Stereo coverage
• Data storage and transmit
• Applications
8.16 Spaceborne radar system
summary
 Table 8.5
8.17 Radar remote sensing of Venus
 Magellan spacecraft
• 1989
• Elliptical polar orbit: 2100km above the poles to 175km above
the equator
• SAR, s-band
• Swath 16,000km long, 25km wide
• Resolution: 75m
• Fig 8.47: Mead impact crater (d=280km)
• Fig 8.48: radar stereopair of the crater Geopert-Meyer
 Same side at =150, 280
 The edge of a ridge belt
 Planetary scientists
 Fig 8.49: Sapas Mons
8.18 Elements of passive microwave
sensing
 Passive microwave sensing vs thermal sensing
• Similar principles  blackbody radiation theory (Fig 8.50)
• Use antenna
 Fig 8.51: Components of a passive microwave
signal
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•
•
•
Emitted from the surface = fn(T, material)
Emitted from the atmosphere
Reflected from the surface
Transmitted from the surface
 Passive microwave sensing
• fn(surface electrical, chemical and textural characteristics, bulk
configuration and shape, viewing angle)
8.19 Passive microwave sensors
 Microwave radiometers
• Basic configuration (Fig 8.52)
Switch  rapid, alternate sampling between the antenna signal and a
calibration temperature reference signal
Amplify weak signal
Readout and recording
• Trade-off between antenna beamwidth and system
sensitivity
• Apparent antenna temperature
The system is calibrated in terms of the temperature that a blackbody
located at the antenna must reach to radiate the same energy as
collected from the ground
8.19 Passive microwave sensors (cont.)
 Scanners
• Scan transverse to the direction of flight
• Mechanically, electronically, multiple antenna
array
• Fig 8.53: Passive microwave image
Looks like thermal image, but bright  cold
Agricultural fields
Striping  irrigation
Density  moisture
8.20 Applications of passive
microwave sensing
 Advantages
 Disadvantages
 Meteorology
 Oceanography
 Geology
8.21 LIDAR
 Fig 8.54: Principle of lidar bathymetry
 Fig 8.55: Lidar returns measured over
a forest canopy
 Laser-induced fluorescence (LIF)
• Single-channel laser source + multi-channel
receivers
• Distinguish several plant groups