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R A D A R S A T G E O L O G Y H A N D B O O K
Reproduction of the contents of this Handbook is permissible and encouraged.
Cover: photograph courtesy of Dr. Fons Dekker of Dekker Remote Sensing; RADARSAT subscene ofVenezuela © Canadian Space Agency/Agence spatiale canadienne 1996. Data received by the Canada Centre forRemote Sensing. Processed and distributed by RADARSAT International.
T A B L E O F C O N T E N T S
page
Preface
Objectives VIHandbook Organization VIAcknowledgments VI
Chapter 1 Comparison of Satellite Imaging Systems
Comparison: Optical and Radar Data 1 - 1The RADARSAT Satellite 1 - 3
Chapter 2 The RADARSAT Satellite
Understanding Radar Imagery 2 - 1RADARSAT’s State-of-the-Art Features 2 - 4Unique Characteristics of SAR Data 2 - 8
Chapter 3 Visual Interpretation of RADARSAT Imagery
Structural Interpretations 3 - 1Lithologic Interpretations 3 - 8Geological Applications Guidelines 3 - 13
Chapter 4 Image Enhancement of RADARSAT Data
Hardcopy Products 4 - 1Digital Products 4 - 1
Chapter 5 Value-Added RADARSAT Products
Radar Imagery Manipulation 5 - 1Data Integration 5 - 6
Chapter 6 Summary
Summary 6 - 1
Reference Materials
Glossary G - 1References R - 1
List of Figures
FIGURE 1.1 Optical vs. Radar Data: Tropical Environment - Guyana 1 - 2FIGURE 2.1 Electromagnetic Spectrum 2 - 1FIGURE 2.2 Energy Interaction in a SAR System 2 - 2FIGURE 2.3 Surface Roughness from Varying Terrains 2 - 3FIGURE 2.4 SAR Operating Beam Modes 2 - 4FIGURE 2.5 RADARSAT Beam Positions 2 - 5FIGURE 2.6 RADARSAT Resolution Comparison: Island of Borneo 2 - 6FIGURE 2.7 Incidence Angle Comparison: Timmins, ON, Canada 2 - 8FIGURE 2.8 Effects of Terrain Relief on Viewing Geometry 2 - 10FIGURE 2.9 Terrain Relief Effects on SAR Imagery: Calgary, AB, Canada 2 - 11FIGURE 2.10 Radiometric Effects: Quito, Ecuador 2 - 12FIGURE 3.1 Lineament Extraction Using RADARSAT: Rio Arauca, Venezuela 3 - 2FIGURE 3.2 Lineament Detection in an Arid Environment: Death Valley, NV, USA 3 - 3FIGURE 3.3 Detection of Lineaments Using Varying Viewing Angles 3 - 4FIGURE 3.4 Scarp Slope Detection: Taipei, Taiwan 3 - 6FIGURE 3.5 Local Drainage Anomaly: Rio Arauca, Venezuela 3 - 7FIGURE 3.6 Local Drainage Anomaly: Venezuela 3 - 8FIGURE 3.7 Quaternary Lithology: Bathurst Island, NWT, Canada 3 - 9FIGURE 3.8 Volcanic Lithology: Kamchatka Peninsula, Russian Federation 3 - 10FIGURE 3.9 Treetop Geology in Tropical Regions: Kalimantan, Indonesia 3 - 12FIGURE 4.1 Unfiltered vs. Filtered RADARSAT Image 4 - 3FIGURE 4.2 Block Averaged and Decimated Images: Vancouver, BC, Canada 4 - 5FIGURE 5.1 Stereo Viewing with RADARSAT: Sarawak, Malaysia 5 - 3FIGURE 5.2 RADARSAT Anaglyph: Southern Highlands, Papua New Guinea 5 - 4FIGURE 5.3 RADARSAT Image Mosaic: Island of Borneo 5 - 5
FIGURE 5.4 DEM Created with RADARSAT Data: Papua New Guinea 5 - 7FIGURE 5.5 Integration of RADARSAT/Optical Data: Cape Breton Island, NS, Canada 5 - 8FIGURE 5.6 LANDSAT TM/RADARSAT Merge: Vancouver, BC, Canada 5 - 9FIGURE 5.7 IHS Transformation: Sudbury Basin, ON, Canada 5 - 10
List of Tables
TABLE 3.1 Geological Activities and RADARSAT Recommendations 3 - 13
A C K N O W L E D G E M E N T S
V I R A D A R S A T G E O L O G Y H A N D B O O K
O B J E C T I V E S
The RADARSAT Geology Handbook is intended to be used as a training and
reference guide for those geologists making the transition from the optical to the
radar environment, and for those geologists who are already using RADARSAT
data. It will also be a useful desktop reference for performing initial geological
interpretations with RADARSAT imagery. The examples presented in this
handbook clearly demonstrate RADARSAT’s powerful utility in the world of
hydrocarbon and mineral exploration.
H A N D B O O K O R G A N I Z A T I O N
The RADARSAT Geology Handbook is divided into six chapters. The first chapter
is designed to provide the geologist with a comparison of optical and radar data
products, and to introduce the RADARSAT satellite. The satellite is explained in
more detail in Chapter Two. The third chapter discusses the techniques used to
visually interpret geologic structures and lithologies on RADARSAT imagery. The
chapter provides examples from arctic, volcanic, arid and tropical environments and
shows a range of structural features. The geologic mapping capabilities offered by
radar technology are also presented. The fourth chapter discusses RADARSAT film
and digital data products, and the digital image processing techniques used to
enhance structural features and SAR image appearance. The fifth chapter explains
the RADARSAT value-added products and various data fusion techniques. This
section covers anaglyphs, DEMs and stereo pairs. A brief summary of the handbook
is provided in Chapter Six, and is followed by a glossary of terms and an extensive
reference list.
A C K N O W L E D G M E N T S
The completion of this handbook was made possible from input provided by the
staff at RADARSAT International (RSI), geologists at the Canada Centre for
Remote Sensing (CCRS), and Dr. Fons Dekker of Dekker Remote Sensing in
Calgary, Alberta, Canada. This handbook marks the end of a two-year joint
Canadian International Development Agency (CIDA) project between Venezuela
and Canada.
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3
4
5
6
COMPARISON OF SATELLITE IMAGING SYSTEMS
THE RADARSAT SATELLITE
VISUAL INTERPRETATION OF RADARSAT IMAGERY
IMAGE ENHANCEMENT OF RADARSAT DATA
VALUE-ADDED RADARSAT PRODUCTS
SUMMARY
REFERENCE MATERIALS
1
C O M P A R I S O N O F S A T E L L I T E I M A G I N G S Y S T E M S 1 - 1
With the rapid advancement of the technology age and the increased competition
to locate new natural resources deposits to meet the demands of the growing
global economy, geologists are considering new and effective exploration
techniques. There has been a steady movement from traditional analog
techniques to the use of more advanced digital imagery.
Satellite imagery has numerous advantages over its predecessor aerial photography
(Berger, 1994), providing cost-effective increased spatial coverage. Digital satellite
data can easily be manipulated and enhanced to highlight features of interest.
Data fusion with existing geologic data can be easily performed using the
appropriate software. The main trade-offs in using digital satellite data over
airborne data are limited resolution and limited choice of flight directions. This
challenge will be overcome with the launch of high resolution Smallsat satellites
in 1997 and 1998, with resolutions ranging from 1 to 5 metres.
C O M P A R I S O N : O P T I C A L A N D R A D A R D A T A
RADARSAT differs from optical sensors in the kind of data it acquires and how
the data is collected. Optical multispectral systems which include LANDSAT
TM and SPOT are referred to as passive systems, in that they rely on sunlight
reflected off the Earth to image the planet’s surface. Since data is collected at
frequencies roughly equivalent to the human eye, sensors are unable to collect
data in darkness or wherever conditions such as cloud cover, fog, dust, hail or
smoke prevail. RADARSAT by comparison, uses Synthetic Aperture Radar
(SAR), which sends its own microwave signals down to the Earth and processes
the signals that it receives back. As an active sensor, RADARSAT’s longer
wavelength is better suited for atmospheric penetration and can collect data
regardless of the Earth’s atmospheric conditions. This ability provides the user
with significant advantages when it comes to viewing under conditions that
preclude observations made by aircraft or optical satellites.
In the past few years, radar remote sensing has proven to be an effective tool for
the extraction of geological information, unrestricted by external illumination
conditions. SAR imagery is particularly suited for geological mapping primarily
in tropical regions, because of the geological structure, surficial bedrock and
lineaments information it provides. The radar backscatter qualities are directly
related to ground topography, dielectric properties, and surface roughness of
the terrain being imaged. In addition, radar can acquire multiple images which
can be used to provide stereoscopic viewing.
Figure 1.1 provides a comparison of optical and radar data collected for a
region over coastal Guyana. The LANDSAT TM image shows very little surface
expression and its clarity is hindered by the moderate cloud cover. The
RADARSAT image penetrates through the cloud cover and uses “treetop
geology” to express the underlying geologic features and structures.
FIGURE 1.1: Optical vs. radar data: tropical environment - Guyana
The two images compare acquisitions over an area in Guyana made by LANDSAT TM and
RADARSAT. Note the prominent geologic structure that is visible in the lower left corner of the
RADARSAT image, but remains undetected on the cloud-covered LANDSAT imagery. RADARSAT:
Wide beam position 1, acquired August 19, 1996. LANDSAT-5: acquired December 30, 1986 TM,
Bands 3, 4, 5. RADARSAT data © Canadian Space Agency/Agence spatiale canadienne 1996.
Received by the Canada Centre for Remote Sensing. Processed and distributed by RADARSAT
International. LANDSAT data © EOSAT.
1 - 2 R A D A R S A T G E O L O G Y H A N D B O O K
C O M P A R I S O N O F S A T E L L I T E I M A G I N G S Y S T E M S 1 - 3
T H E R A D A R S A T S A T E L L I T E
RADARSAT, launched November 4, 1995 was the result of a joint venture
between the Canadian Government, private industry and NASA. As Canada’s
first Earth observation satellite, and the world’s first operationally-oriented
radar sensor, RADARSAT is providing valuable information for use in monitoring
the world’s environmental and natural resources.
Addressing Canada’s first major need for a radar sensor, RADARSAT provides
effective surveillance of the Canadian Arctic, which is characterized by long
periods of darkness in the winter. Major shipping routes cross this vast region
which recently gained importance due to its significant mineral and petroleum
reserves. Another need met by RADARSAT is to monitor Canada’s coastline,
which is one of the longest in the world, and is perennially cloud-covered
and foggy.
RADARSAT was launched in a sun-synchronous, dawn-dusk orbit with a
24-day repeat cycle. It provides regular imaging opportunities as frequently as
daily above the Arctic, and every five days over equatorial latitudes.
For geologists who have been trained to work with optical images, a transition
must be made to understand the unique features of radar imagery and to
successfully utilize the radar data. An introductory discussion of the
RADARSAT satellite is provided in Chapter Two, followed by an overview of
radar image interpretation in Chapter Three.
2
3
4
5
6
COMPARISON OF SATELLITE IMAGING SYSTEMS
THE RADARSAT SATELLITE
VISUAL INTERPRETATION OF RADARSAT IMAGERY
IMAGE ENHANCEMENT OF RADARSAT DATA
VALUE-ADDED RADARSAT PRODUCTS
SUMMARY
REFERENCE MATERIALS
1
T H E R A D A R S A T S A T E L L I T E 2 - 1
RADARSAT differs from research-oriented radar sensors such as ERS and
JERS-1, given that RADARSAT is the first radar sensor totally dedicated to
operational applications and it offers a variety of beam modes to meet
requirements of the particular application at hand. Using a single frequency
C-Band (5.3 Ghz frequency or 5.6 cm wavelength), the RADARSAT SAR has
the ability to shape and steer its radar beam over a 500 kilometre range.
RADARSAT provides complete global coverage with the satellite’s orbit repeated
every 24 days. The Arctic is imaged daily, while equatorial areas achieve complete
coverage approximately every 5 days. The following sections discuss
RADARSAT’s unique features and the benefits these pose for geologists.
U N D E R S T A N D I N G R A D A R I M A G E R Y
What is a radar image?
Radar images are single frequency representations of the Earth, which highlight
changes in the terrain’s roughness, relief, and moisture levels. They are similar
to other types of Earth observation imagery in that they represent the reflectivity
portion of the electromagnetic spectrum (Figure 2.1). However, radar imagery
is derived from a portion of the light spectrum that human vision is unable to
detect. This special wavelength is capable of penetrating rain, cloud and haze, to
provide a continually clear view of the Earth.
FIGURE 2.1: Electromagnetic spectrum
OPTICAL RADAR
Gamma Rays X-Rays U.V. Rays Visible
Near and MidInfrared
Thermal Infrared Microwave TV/Radio
(cm) 10-10
10-9
10-8
10-7
10-6
10-5
10-4
10-3
10-2
10-1
1.0 10 100
FIGURE 2.2: Energy interaction in a SAR system
Why are radar images black and white?
Radar images are black and white not because they are fundamentally different
from other data sources (i.e LANDSAT or SPOT optical sensors), but because
they do not have a multispectral component necessary for false-colour formation.
LANDSAT TM is sensitive to the Earth’s reflectivity at seven different
wavelengths, hence the seven bands. Colour is achieved by combining any three
of the optical bands. RADARSAT contains only one spectral band, and thus
offers a unique dataset for the exploration geologist.
What do radar images consist of?
A radar image is the ratio of microwave energy transmitted to the Earth to the
energy which is reflected directly back to the sensor. The energy returning to
the sensor is called backscatter (see Figure 2.2). The backscatter of an imaged
area is dependent upon local topography, centimetre-scale roughness, and
dielectric properties, which are directly affected by moisture levels. Low
2 - 2 R A D A R S A T G E O L O G Y H A N D B O O K
T H E R A D A R S A T S A T E L L I T E 2 - 3
backscatter values are portrayed as dark image tones or grey levels which
approximate black, while high backscatter values are shown as light image tones
or grey levels approximating white.
FIGURE 2.3: Surface roughness from varying terrains
What sort of information is provided by radar images?
Radar imagery provides valuable information to a broad user community.
Geology, agriculture and landcover mapping are just a few of the applications
which benefit from the way in which a radar image portrays landcover types.
Although no two land units are the same, there are general rules which apply to
certain landcover classes. Water is usually dark- a product of specular reflection
and resulting weak return, while urban areas are always very bright due to the
presence of corner reflectors (see Figure 2.3). Everything else falling between
these two extremes is represented in various shades of grey. By interpreting the
various tones, textures and patterns on the image, the user can unlock information
pertaining to geologic structure and lithology.
R A D A R S A T ’ S S T A T E - O F - T H E - A R T F E A T U R E S
Range of Beam Modes
RADARSAT is equipped with seven beam modes, which offer image resolutions
ranging from 8 to 100 metres. RADARSAT is designed in such a way that its
beam can be steered at incidence angles ranging from 10-60 degrees. It offers
spatial coverage ranging from 50-500 kilometre swaths, and can be used for
mapping at scales of 1:1,000,000 to 1:50,000. These features are described in
Figures 2.4 and 2.5.
FIGURE 2.4: SAR operating beam modes
2 - 4 R A D A R S A T G E O L O G Y H A N D B O O K
T H E R A D A R S A T S A T E L L I T E 2 - 5
FIGURE 2.5: RADARSAT beam positions
BEAM MODE BEAM POSITION INCIDENCE APPROXIMATE NOMINALANGLE RANGE (º) RESOLUTION (m) AREA (km)
Fine F1 near 36.4 - 39.6 8 * 50 x 50F1 36.8 - 39.9F1 far 37.2 - 40.3F2 near 38.8 - 41.8F2 39.2 - 42.1F2 far 39.6 - 42.5F3 near 41.1 - 43.7F3 41.5 - 44.0F3 far 41.8 - 44.3F4 near 43.1 - 45.5F4 43.5 - 45.8F4 far 43.8 - 46.1F5 near 45.0 - 47.2F5 45.3 - 47.5F5 far 45.6 - 47.8
* tape recorded data may cover smaller area
Standard S1 20 - 27 25 100 x 100S2 24 - 31S3 30 - 37S4 34 - 40S5 36 - 42S6 41 - 46S7 45 - 49
Wide W1 20 - 31 30 165 x 165W2 31 - 39 150 x 150W3 39 - 45 150 x 150W3 (for tape recorded) 138 x 150
ScanSAR Narrow SN1 20 - 40 50 300 x 300SN2 31 - 46
ScanSAR Wide SW1 20 - 49 100 500 x 500
Extended High H1 49 - 52 25 75 x 75H2 50 - 53H3 52 - 55H4 54 - 57H5 56 - 58H6 57 - 59
Extended Low L1 10 - 23 35 170 x 170
In Figure 2.6, three RADARSAT beam modes are used to view the Island of
Borneo, supplying the user with both a regional and a site-specific view of the
newly discovered Busang gold deposit.
FIGURE 2.6: RADARSAT resolution comparison: Island of Borneo
ScanSAR Narrow: acquired August 5, 1996, area: 125 x 125 km, subscene. Standard beam position 6:
acquired September 29, 1996, area: 79 x 73.5 km, subscene. Fine beam position 5: acquired May 12,
1996, area: 10 x 16 km, subscene. RADARSAT data © Canadian Space Agency/Agence spatiale
canadienne 1996. Received by the Canada Centre for Remote Sensing. Processed and distributed by
RADARSAT International.
2 - 6 R A D A R S A T G E O L O G Y H A N D B O O K
RADARSAT’s ScanSAR Narrow beam mode offers 50 m resolution and a 300
by 300 km coverage, which supports the identification of structural trends and
features. The Standard beam mode (25 metre resolution) helps optimize
mapping, geophysical and drilling programs. The Fine beam mode, (8 metre
resolution) is suitable for mapping at scales of 1:50,000.
Range of Viewing Geometries
RADARSAT’s side-looking geometry greatly enhances subtle topographic
features that aid in the interpretation of lineaments. RADARSAT offers 35
beam positions with a viewing angle range of 10 to 60 degrees. The effects of
using different viewing angles is seen in Figure 2.7 of Timmins, Ontario. The
RADARSAT Wide beam position 1 image, which uses a smaller (steeper) angle,
has less tonal variation and makes geologic features more difficult to discern.
The Wide beam position 2 image, with its larger (shallower) viewing angle,
clearly emphasizes the subtle geological structures and increases the
land/water contrast.
T H E R A D A R S A T S A T E L L I T E 2 - 7
2 - 8 R A D A R S A T G E O L O G Y H A N D B O O K
FIGURE 2.7: Incidence angle comparison: Timmins, ON, Canada
The shallower angle of the Wide beam position 2 image creates a larger artificial shadow, thus
highlighting subtle geological features more clearly than the steeper Wide beam position 1 image.
Wide beam position 1: acquired September 15, 1996, subscene. Wide beam position 2: acquired
August 12, 1996, subscene. Descending pass. RADARSAT data © Canadian Space Agency/Agence
spatiale canadienne 1996. Received by the Canada Centre for Remote Sensing (CCRS). Processed
and distributed by RADARSAT International. Enhancement and interpretation by CCRS.
U N I Q U E C H A R A C T E R I S T I C S O F S A R D A T A
Image Geometry
It is virtually impossible to represent an area on the Earth’s surface without
geometrical distortion. Within radar imagery, tall objects appear to lean towards
T H E R A D A R S A T S A T E L L I T E 2 - 9
the radar sensor. The radar sensor measures the time-delay between transmission
and reception for each radar pulse. Since the radar pulse generally reflects off
the mountain top first, the mountain top is interpreted as being closer than the
mountain base. This phenomenon is called foreshortening (see Figure 2.8a).
When foreshortening becomes so extreme that an object “falls over”, resulting
in the loss of one side of the mountain, it is known as layover (see Figure 2.8b).
Shadows are also an inherent characteristic of most radar images, and occur
primarily on the leeward sides of mountains. Shadowing enhances lineaments,
joints, and faults, by highlighting changes in feature orientation. This concept is
explained in Figure 2.8c. The effects of terrain relief on SAR imagery is clearly seen
in Figure 2.9.
Image Radiometry
SAR images are monochromatic (black and white) and the relative
brightness of a pixel is directly related to the radar reflectivity of the ground
target it portrays. The radiometric values range between the two extremes:
completely dark and completely bright. Figure 2.10 illustrates how the radar
technology can affect the digital values used to represent two very similar areas.
Therefore, if an object reflects much of its incident radar energy back to the
sensor, it will have a relatively high digital value and be represented as a white
pixel. If an object does not reflect much energy back to the sensor, it will attain
a low digital value and be represented as a black pixel.
2 - 1 0 R A D A R S A T G E O L O G Y H A N D B O O K
FIGURE 2.8: Effects of terrain relief on viewing geometry
radarshadowArtist concepts: drawings not to scale.
C) ShadowShadow area not imaged
2
1
2
1
A) Foreshortening1- SAR perceived distance2- Actual distance
B) Layover1- Top of mountain viewed before the bottom2- Actual ground distance
FIGURE 2.9: Terrain Relief Effects on SAR Imagery: Calgary, AB, Canada
The effects of layover, foreshortening and shadows are clearly illustrated in this mountainous
terrain. Standard beam position 1: acquired February 12, 1996, area: 20 x 20 km, subscene.
RADARSAT data © Canadian Space Agency/Agence spatiale canadienne 1996. Received by the
Canada Centre for Remote Sensing. Processed and distributed by RADARSAT International. Data
acquired during the commissioning phase and may not conform to system specifications.
T H E R A D A R S A T S A T E L L I T E 2 - 1 1
LookDirection
2 - 1 2 R A D A R S A T G E O L O G Y H A N D B O O K
FIGURE 2.10: Radiometric Effects: Quito, Ecuador
The sensor-facing slope is extremely bright and the leeward slope is dark, despite the valley having
symmetrical slopes of similar land cover. Fine beam position 5: acquired February 4, 1996, descending
pass, subscene. RADARSAT data © Canadian Space Agency/Agence spatiale canadienne 1996.
Received by the Canada Centre for Remote Sensing. Processed and distributed by RADARSAT
International.
Proper interpretation of radar images demands a basic understanding of
elevation-related effects (such as layover and shadows) on the image’s geometry
and radiometric values.
2
3
4
5
6
COMPARISON OF SATELLITE IMAGING SYSTEMS
THE RADARSAT SATELLITE
VISUAL INTERPRETATION OF RADARSAT IMAGERY
IMAGE ENHANCEMENT OF RADARSAT DATA
VALUE-ADDED RADARSAT PRODUCTS
SUMMARY
REFERENCE MATERIALS
1
V I S U A L I N T E R P R E T A T I O N O F R A D A R S A T I M A G E R Y 3 - 1
Radar technology has an inherent sensitivity to the detection of lineaments,
joints, faults and shear zones due to its side-looking configuration, and can
therefore provide precise information on the subtle changes in relief.
RADARSAT brightens the sensor-facing slopes of ridges while accentuating the
lee slopes with shadow leaving the interpreter with a clear view of the surface. It
is up to the interpreter to determine the origin of the surface undulations
whether it be geomorphologic or structural. It is the knowledge of the study
area, and the other vital datasets such as seismic, aeromagnetics, and gravity,
which enable the geologist to draw accurate conclusions. Radar-derived
geologic information is used in Quaternary mapping, mineral and hydrocarbon
exploration, and geologic hazard identification.
This chapter covers the interpretation of structural and lithological
information from a RADARSAT image by making specific reference to
lineaments, bedding plane attitude and drainage network analysis.
S T R U C T U R A L I N T E R P R E T A T I O N S
RADARSAT provides geologists with a unique and complementary data source
with respect to contact, structure, lineaments and landforms. The following
section provides examples of various structures that can be detected using
RADARSAT imagery.
Interpreting Exposed Structures
Lineaments
RADARSAT has an ability to highlight linear elements of an image which are
not near-parallel to the look direction. Not only does RADARSAT provide an
image which clearly shows lineaments, but it offers additional information to
allow the interpreter to determine its heritage. Lineaments may be
human-induced, geomorphological or structural in origin. RADARSAT provides
information to assist with the discrimination of various lineament features.
3 - 2 R A D A R S A T G E O L O G Y H A N D B O O K
Pipelines, hydro corridors, railroads and roads are examples of human-induced
lineaments. Eskers, aligned sinkholes, and longitudinal dunes are geomorpho-
logic lineaments. Bedrock faulting produces a unique set of surface characteristics,
which in many cases provides information on fault type and relative age. Spatial
offsets of lithologic units and sharp breaks in topography may indicate the presence
of faults. RADARSAT imagery reveals lineaments previously undetected using
optical data. Lineaments detected from RADARSAT imagery are shown in
Figures 3.1 and 3.2.
FIGURE 3.1: Lineament extraction using RADARSAT: Rio Arauca, Venezuela
This example shows a series of parallel lineaments related to faulting in a tropical environment.
RADARSAT data © Canadian Space Agency/Agence spatiale canadienne 1996. Received by the
Canada Centre for Remote Sensing. Processed and distributed by RADARSAT International. Data
acquired during the commissioning phase and may not conform to system specifications.
Normal Fault
Transfer Fault
Arauca Arch Direction
Thrust Fault
V I S U A L I N T E R P R E T A T I O N O F R A D A R S A T I M A G E R Y 3 - 3
FIGURE 3.2: Lineament detection in an arid environment: Death Valley, NV, USA
One of the many lineaments in this arid enviroment is highlighted above. ScanSAR Narrow beam
position 2: acquired March 23, 1996, ascending pass, subscene. RADARSAT data © Canadian
Space Agency/Agence spatiale canadienne 1996. Received by the Canada Centre for Remote
Sensing. Processed and distributed by RADARSAT International. Data acquired during the
commissioning phase and may not conform to system specifications.
Look Direction Effects on Lineaments
Many natural features have a strong, preferred orientation, which is commonly
expressed as parallel linear features (Sabins, 1987). The success of detecting
certain directions of lineaments is related to the look direction. Linear geologic
features that are oriented at a normal or oblique angle to the radar look direction,
are enhanced by highlights and shadows (Sabins, 1987). As the lineaments
become aligned with the look direction, the subsequent reduction of backscatter
decreases the probability of lineament detection. The amount of weathering
along the lineament will also affect feature detection (see Figure 3.3).
FIGURE 3.3: Detection of lineaments using varying viewing angles
This diagram delineates the areas of lineament suppression, while outlining the optimal angles for
increased feature detection.
3 - 4 R A D A R S A T G E O L O G Y H A N D B O O K
V I S U A L I N T E R P R E T A T I O N O F R A D A R S A T I M A G E R Y 3 - 5
Note: If your lineaments trend within the zone of suppression, choose an image
from the opposite orbital direction (descending in this case) to ensure a “clear”
view of the lineaments in a given concession. Acquiring both ascending and
descending passes of a region of interest ensures complete detection of
lineaments.
Strike and Dip
Folds, domes and basins reveal tell-tale signs of their attitudes when they
deform under the forces of erosion. Drainage networks and unique erosion
patterns provide insight into the classification of scarp and dip slopes, and an
approximation of their orientation (i.e strike and dip). The general criteria for
determining the dip direction of inclined rock units is discussed in the following
section.
Scarp Slopes
Scarp slopes perpendicular to bedding are characterized by two easily identifiable
thematic characteristics on radar imagery. Firstly parallel topographic benches
reflect the presence of rock units with alternating resistivities. These appear as
light and dark bands on one side of a positive structure. Secondly stream
networks appear more dendritic on the scarp slope than those on the dip slopes.
Dip Slopes
Dip slopes parallel to bedding are characterized by triangular-shaped ridges
(flatirons), which generally point away from the dip direction (see Figure 3.4).
The drainage network has long branches and is less dendritic than in areas
associated with scarp slopes.
FIGURE 3.4: Scarp slope detection: Taipei, Taiwan
In this example, the striped scarp slope and the flatirons are clearly visible, differentiating them
from a Quaternary formation and providing concise structural information. Standard beam
position 4: acquired January 2, 1996, descending pass, subscene. RADARSAT data © Canadian
Space Agency/Agence spatiale canadienne 1996. Received by the Canada Centre for Remote
Sensing. Processed and distributed by RADARSAT International. Data acquired during the
commissioning phase and may not conform to system specifications.
Highly deformed slopes benefit from stereoscopic coverage. With a three-
dimensional perspective, all of the available geologic information can be viewed
using the stereo pair.
Drainage Network Analysis
Radar is sensitive to drainage networks due to the dielectric differences between
3 - 6 R A D A R S A T G E O L O G Y H A N D B O O K
water, moist soil and riparian vegetation, and erosion-induced topographic
variations. Structural information can be derived using interpretation techniques
based on tonal variations. Abrupt changes in drainage density can denote
lithologic and structural differences.
Local Drainage Anomalies
Flowing water develops unique drainage patterns as it accommodates changes
in surface conditions. Obscured and buried structures can cause streams and
rivers to develop unique drainage patterns referred to as “drainage anomalies”.
Anomalous drainage patterns may indicate the presence of faults or fractures,
but require ancillary data to reach a final conclusion. A few examples of these
anomalies are shown in Figures 3.5 and 3.6.
FIGURE 3.5: Local drainage anomaly: Rio Arauca, Venezuela
This example shows a river flowing through a fault cluster (refer to Figure 3.1) and the resulting
right angle turns in the river’s course. This feature indicates that there is resistant underlying
bedrock impeding the water’s flow path. Inset: Right-angle bends (Berger, 1994). Standard beam
position 5: acquired March 3, 1996, subscene. RADARSAT data © Canadian Space Agency/Agence
spatiale canadienne 1996. Received by the Canada Centre for Remote Sensing. Processed and
distributed by RADARSAT International. Data acquired during the commissioning phase and may
not conform to system specifications.
V I S U A L I N T E R P R E T A T I O N O F R A D A R S A T I M A G E R Y 3 - 7
FIGURE 3.6: Local drainage anomaly: Venezuela
The braided drainage system can be representative of elevation changes, impeding dome
structures or changes in surface material density. Existing geologic datasets should be consulted
to confirm the basin’s evolution. The RADARSAT image clearly shows it as being anomalous. Inset:
Abnormal Divergence (Berger, 1994). Standard beam position 5: acquired March 3, 1996, subscene.
RADARSAT data © Canadian Space Agency/Agence spatiale canadienne 1996. Received by the
Canada Centre for Remote Sensing. Processed and distributed by RADARSAT International. Data
acquired during the commissioning phase and may not conform to system specifications.
L I T H O L O G I C I N T E R P R E T A T I O N S
RADARSAT imagery provides information on the exposed bedrock, layers of
vegetation, and the overburden found in the area. The dominant parameter
determining how a given rock unit will appear in a radar image is its surface
texture. Rock units break down differentially, resulting in unique surface
roughness distinguishable on radar imagery due to contrasting backscatter. In
the next section, surficial materials are identified using RADARSAT imagery in
varying environments and terrains.
Quaternary Environments
Quaternary mapping in glaciated terrain involving the delineation of landforms
3 - 8 R A D A R S A T G E O L O G Y H A N D B O O K
?
with the assessment of surficial material, has been successfully demonstrated
using radar alone or in combination with other data sources. Radar data provides
information on landform topography, from which many other Quaternary features
can be identified by their characteristic morphology. Figure 3.7 is a striking
representation of the surficial and structural geology in the arctic, characterized
by a remarkable pattern of folds. The sharp contact between rock types is
distinguished using tonal and textural differences.
FIGURE 3.7: Quaternary lithology: Bathurst Island, NWT, Canada
Figure 3.7 shows an image of an arid and arctic environment. The finer siltstone particles produce a
darker return, while the coarser limestone particles produce a brighter backscatter return attributed
to the increased surface roughness. These textures result from freeze/thaw processes acting upon
units of different resistivities, creating surface debris with differing particle sizes. Standard beam
position 7: acquired March 21, 1996, descending pass, subscene. RADARSAT data © Canadian
Space Agency/Agence spatiale canadienne 1996. Received by the Canada Centre for Remote
Sensing (CCRS). Processed and distributed by RADARSAT International. Data acquired during the
commissioning phase and may not conform to system specifications. Enhancement and
interpretation by CCRS.
V I S U A L I N T E R P R E T A T I O N O F R A D A R S A T I M A G E R Y 3 - 9
Volcanic Environments
The ability to image rock units is a result of the side-looking configuration of
radar, which highlights topographic relief. Figure 3.8 shows an image collected
in a volcanic environment in which the surface texture controls the appearance
of the rock strata. Terrain units are identified by the unique textures, shapes,
and tones in the radar imagery, which in this case are affected by the age and
texture of the various lava flows, soil moisture, and the absence/presence
of snow.
FIGURE 3.8: Volcanic lithology: Kamchatka Peninsula, Russian Federation
The large volcano seen in the centre of the image is Mount Kluchevskaya Sopka, which has an
elevation of approximately 4,500 metres. Standard beam position 4: acquired April 1, 1996,
descending pass, subscene. RADARSAT data © Canadian Space Agency/Agence spatiale
canadienne 1996. Received by the Canada Centre for Remote Sensing. Processed and distributed
by RADARSAT International.
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Forested, Tropical Environments
Unfortunately overburden is found in most of the world’s terrains (as is evident
in the examples above), and in those environments there is little surface or
canopy penetration by a radar signal. The collected lithologic information is
based on erosional patterns and structural inferences, in combination with
supporting datasets. In tropical regions, RADARSAT indirectly creates a
representation of the surface by imaging variations in the heights of treetops,
because regional and local geomorphology is mimicked in the tree canopy
(Figure 3.9). To the skilled interpreter, radar imagery creates an image as
though the forest cover is removed. Exploration geologists can then use this
information to detect small-scale geologic structures, erosional patterns, and
subtle topographic features.
V I S U A L I N T E R P R E T A T I O N O F R A D A R S A T I M A G E R Y 3 - 1 1
3 - 1 2 R A D A R S A T G E O L O G Y H A N D B O O K
FIGURE 3.9: Treetop geology in tropical regions: Kalimantan, Indonesia
The “Treetop Geology” concept is illustrated in this RADARSAT image of a dense tropical forest in
Indonesia. An eroded, sedimentary dome structure is clearly evident. RADARSAT was also able to
detect this feature, despite the heavy forest cover and perennial cloud cover. Fine beam
position 4: acquired March 21, 1996, area: 21 x 21 km, subscene. RADARSAT data © Canadian
Space Agency/Agence spatiale canadienne 1996. Received by the Canada Centre for Remote
Sensing. Processed and distributed by RADARSAT International. Data acquired during the
commissioning phase and may not conform to system specifications.
V I S U A L I N T E R P R E T A T I O N O F R A D A R S A T I M A G E R Y 3 - 1 3
G E O L O G I C A L A P P L I C A T I O N S G U I D E L I N E S
TABLE 3.1: Geological Activities and RADARSAT Recommendations
GEOLOGICAL ACTIVITY RESPONSE AND RECOMMENDATIONS
Geological RADAR RESPONSE Structure Mapping Geological structures often have characteristic forms, which, if located
near the Earth’s surface, may be manifested topographically as the side-looking configuration of radar highlights relief.
RECOMMENDATIONSRADARSAT Beam Mode: All beam modes are suitable for geological structure mapping. The final beam mode selection is dependent on the areal coverage and the level of detail required. Generally, Fine and Standard beam modes are best suited for detailed geological structure mapping, while Wide and ScanSAR are better for basin-wide geological structure mapping.
RADARSAT Incidence Angle: Shallow incidence angles are ideal for enhancing subtle terrain features through shadowing. In areas of high relief, too much shadowing may occur with shallow incidence angles and therefore, intermediate incidence angles may be more suitable.
Look Direction: Orientation of geological structures relative to look direction should be considered.
When to Acquire RADARSAT Data: Acquire data when geological structure information is required, regardless of seasons. Avoid periods of heavy snowcover.
Lineament RADAR RESPONSEIdentification Lineaments, such as folds and faults may be manifested as topographic
relief. The ability to image lineaments is a result of the side-looking configuration of radar which highlights relief.
RECOMMENDATIONSRADARSAT Beam Mode: The beam mode chosen is dependent on the width of the lineaments, and on areal coverage and the level of detail required. Generally, Fine and Standard beam modes are best suited for detailed lineament identification, while Wide and ScanSAR are better for regional identification.
3 - 1 4 R A D A R S A T G E O L O G Y H A N D B O O K
GEOLOGICAL ACTIVITY RESPONSE AND RECOMMENDATIONS
RADARSAT Incidence Angle: Shallow incidence angles are ideal for enhancing the subtle topographic relief of lineaments.
Look Direction: A look direction perpendicular to the direction oflineaments enhances their detectability. The acquisition of both ascending and descending passes maximizes the number of lineaments that can be identified.
When to Acquire RADARSAT Data: Acquire data when lineament information is required.
Seismic Zones RADAR RESPONSEIdentification Seismic zones are often characterized by the presence of faults which
may be manifested topographically. The ability to image seismic zones is a result of the side-looking configuration of radar, which highlights this topography.
RECOMMENDATIONSRADARSAT Beam Mode: The beam mode chosen is dependent on the width of the lineaments associated with seismic zones, and on areal coverage and the level of detail required. Generally, Fine and Standard beam modes are best suited for detailed seismic zones identification, while Wide and ScanSAR are better for regional seismic zone identification.
RADARSAT Incidence Angle: Shallow incidence angles are ideal forenhancing the subtle topographic relief of lineaments.
Look Direction: A look direction perpendicular to the direction of lineaments will enhance their detectability. The acquisition of both ascending and descending passes maximizes the number of lineaments that can be identified.
When to Acquire RADARSAT Data: Acquire data when lineamentinformation associated with seismic zones is required.
Landform Delineation RADAR RESPONSELandforms often have characteristic shapes which may be manifested as topographic relief. The ability to image landforms is a result of the side-looking configuration of radar, which highlights relief.
RECOMMENDATIONSRADARSAT Beam Mode: All beam modes are suitable for landform
V I S U A L I N T E R P R E T A T I O N O F R A D A R S A T I M A G E R Y 3 - 1 5
GEOLOGICAL ACTIVITY RESPONSE AND RECOMMENDATIONS
delineation. The final beam mode selection is dependent on the areal coverage and the level of detail required. Generally, Fine and Standard beam modes are best suited for detailed landform delineation, while Wide and ScanSAR are better for regional landform delineation.
RADARSAT Incidence Angle: Shallow incidence angles are ideal for enhancing subtle terrain features through shadowing.
Look Direction: Orientation of land forms relative to look direction should be considered.
When to Acquire RADARSAT Data: Acquire data when landform information is required, regardless of season. Avoid periods of heavy snowcover.
Surficial Bedrock RADAR RESPONSEGeological Mapping Depending on the type of physical weathering, surficial bedrock may
characteristically fracture to produce fragment sizes, which are a function of elements such as rock fabric, texture and mineral composition. Individual rock units may break down differentially, resulting in unique backscatter.
RECOMMENDATIONSRADARSAT Beam Mode: All beam modes are suitable for surficialbedrock mapping. The final beam mode selection is dependent on the areal coverage and the level of detail required. Generally, Fine and Standard beam modes are best suited for detailed surficial bedrock mapping, while Wide and ScanSAR are better for regional surficial bedrock geological mapping.
RADARSAT Incidence Angle: The main parameter that may differentiate rock fragment size associated with surficial bedrock units is surface roughness. Shallow incidence angles maximize the contrast in backscatter resulting from variances in roughness.
Look Direction: Orientation of geological structures relative to look direction should be considered.
When to Acquire RADARSAT Data: Acquire data when moisture levels are low in order that the backscatter be more closely correlated to surface roughness than to moisture content.
GEOLOGICAL ACTIVITY RESPONSE AND RECOMMENDATIONS
Surficial Material RADAR RESPONSEAssessment Non-vegetated, unconsolidated surficial material contains different
fragment sizes which may produce a characteristic soil roughness and soil moisture holding capability. Radar is sensitive to changes in roughness and moisture, and the result is contrasting backscatter between different surficial units.
RECOMMENDATIONSRADARSAT Beam Mode: All beam modes are suitable for the assessmentof surficial materials. The final beam mode selection is dependent on the areal coverage and the level of detail required. Generally, Fine and Standard beam modes are best suited for detailed surficial assessment, while Wide and ScanSAR are better for regional surficial material assessment.
RADARSAT Incidence Angle: If surficial material is assessed based on soil moisture, steep incidence angles are preferred to minimize thebackscatter associated with soil roughness. If surficial materials are assessed based on soil surface roughness, shallow incidence angles are better suited.
Look Direction: Orientation of geological structures relative to look direction should be considered.
When to Acquire RADARSAT Data: If surficial material assessment is based on soil surface roughness, then acquire data when the moisture levels are low to ensure that the backscatter is more closely correlated to surface roughness than it is to moisture content.
Sedimentology RADAR RESPONSEMapping Unconsolidated sediments, such as those deposited by glaciers, are often
manifested as topographic relief. The ability to image sedimentological units is a result of the side-looking configuration of radar which highlights topographic relief. Sediments also have characteristic grain sizes with different moisture holding capacities, and they may produce a characteristic surface roughness. Radar is sensitive to changes in moisture and roughness, which results in contrasting backscatter between different sediments. Each consolidated type shows unique erosional patterns, including karsting in carbonates and bedding in clasticenvironments.
3 - 1 6 R A D A R S A T G E O L O G Y H A N D B O O K
V I S U A L I N T E R P R E T A T I O N O F R A D A R S A T I M A G E R Y 3 - 1 7
GEOLOGICAL ACTIVITY RESPONSE AND RECOMMENDATIONS
RECOMMENDATIONSRADARSAT Beam Mode: All beam modes are suitable for sedimentology mapping. The final beam mode selection is dependent on the areal coverage and the level of detail required. Generally, Fine and Standard beam modes are best suited for detailed sedimentology mapping, while Wide and ScanSAR are better for basin-wide sedimentology mapping.
RADARSAT Incidence Angle: If sedimentology mapping is carried out based on the delineation of topographic relief, shallow incidence angles are ideal for enhancing subtle terrain features. If sedimentology mapping is carried out based on soil moisture differences, steep incidence angles are preferred to minimize the backscatter associated with soil roughness. If sedimentology mapping is carried out based on the determination of surface roughness, shallow incidence angles are better as they maximize the contrast in surface roughness.
Look Direction: In areas of moderate to high relief, acquisition of both ascending and descending passes allows the true form of topographic features to be represented.
When to Acquire RADARSAT Data: If sedimentology mapping is carried out based on soil moisture or surface roughness, then the data should be acquired when the vegetation is at a minimum to avoid having the vegetation response to RADARSAT’s energy dominate the backscatter.
Landslide Hazard RADAR RESPONSEAssessment RADARSAT Beam Mode: Landslide hazard areas are defined when the
locations of past landslides are identified. Landslides change the landscape through the transportation of vegetation and soil, thus affected areas have different canopy and soil roughness than surrounding unaffected areas. Radar is sensitive to these variances in roughness, and produces contrasting backscatter between affected and unaffected areas.
RECOMMENDATIONSRADARSAT Beam Mode: Both Standard and Fine beam mode can be usedto obtain detailed information on individual landslides.
RADARSAT Incidence Angle: Shallow incidence angles will minimize geometric distortions associated with areas of moderate to high relief.
GEOLOGICAL ACTIVITY RESPONSE AND RECOMMENDATIONS
Look Direction: For moderate to high relief terrain, acquisitions of both ascending and descending passes maximizes the amount of landslide information.
When to Acquire RADARSAT Data: Acquire data when landslide information is required.
Coastal Erosion RADAR RESPONSEAssessment A smooth water surface is a specular reflector, which results in low
backscatter. The rougher surface of the land however, is a diffuse scatterer and produces relatively high amounts of backscatter. Evaluationof the change in backscatter over time allows the assessment of coastal erosion.
RECOMMENDATIONSRADARSAT Beam Mode: Depending on the level of detail required, all of RADARSAT’s beam modes are suitable for coastal erosion assessment.
RADARSAT Incidence Angle: Shallow incidence angles create the greatest contrast between water and land. At these angles there is specular reflection from the water surface while the roughness of the land surface is enhanced.
Look Direction: N/A
When to Acquire RADARSAT Data: Coastal erosion assessment deals with the delineation of the land/water boundary over time. Acquire data when the coastline needs to be monitored.
3 - 1 8 R A D A R S A T G E O L O G Y H A N D B O O K
2
3
4
5
6
COMPARISON OF SATELLITE IMAGING SYSTEMS
THE RADARSAT SATELLITE
VISUAL INTERPRETATION OF RADARSAT IMAGERY
IMAGE ENHANCEMENT OF RADARSAT DATA
VALUE-ADDED RADARSAT PRODUCTS
SUMMARY
REFERENCE MATERIALS
1
I M A G E E N H A N C E M E N T O F R A D A R S A T D A T A 4 - 1
RADARSAT’s multiple beam modes and positions combined with the available
levels of processing provide geologists with an extensive selection of digital
products. To efficiently access the information contained within these products,
one must understand the digital characteristics and the implications of the
selected image processing procedures. Before the imagery is interpreted, the
RADARSAT image is calibrated to compensate for errors related to satellite
movement, the SAR antenna and ground reception. Calibration provides a
means of ensuring the consistency of data quality both within the image
(relative calibration) and from one image to another (absolute calibration).
Various digital image processing techniques used to analyze radar images are
discussed in the following sections.
H A R D C O P Y P R O D U C T S
Hardcopy products are often the most convenient to use. They are portable and
easy to handle in remote locations. These print and film products can also be
utilized as field maps and interpreted directly to extract application information.
Hardcopy RADARSAT products contain the actual image plus auxiliary
information.
D I G I T A L P R O D U C T S
Digital RADARSAT products can provide the geologist with greater flexibility
in how the data is manipulated and utilized. Digital interpretations are less
labour-intensive and less costly than visual interpretations. Digital 8-bit images
contain 256 grey levels, while the human eye can only distinguish approximately
16 to 32 distinct grey tones. Therefore, a visual interpretation alone may not be
sufficient to notice all the subtle radiometric differences in a radar image.
Speckle
SAR imagery is characterized by the presence of speckle, which is a “salt and
pepper” effect occurring throughout the radar image. The SAR sensor transmits
thousands of pulses for a given area on the ground defined as the resolution
cell. The pulses are reflected from many scattering points within the resolution
cell, but the motion of the satellite causes each received pulse to be phase-shifted.
When all the pulses are added vectorially, resolution cells within a homogeneous
ground region will have a different backscatter value. A seemingly
homogeneous surface area will have an irregular distribution of light and dark
pixels, producing a granular effect. The brightness variation is called speckle.
Speckle is a phenomenon of the technology used in the creation of the image
and is not related to the imaged target. There will always be high pixel
variability even if the landcover is uniform.
Speckle can be controlled at the initial image processing stage by data sampling.
Any attempts to rid the image of speckle will result in a loss of potentially
important information; therefore, one must carefully analyze the methodology
used, such that the information loss is minimized and the overall smoothing
effect increases image interpretability.
Speckle Removal
The most common form of speckle removal is filtering, which employs various
techniques of pixel averaging to smooth out the speckle. The extent of the
smoothing varies with the filtering technique and how it is implemented.
Filtering techniques are included in the radar modules of commercially available
image analysis software packages. Mean and median filters are examples of
non-adaptive filters which can be used to despeckle, and the Frost and Kuan are
examples of adaptive filters. Figure 4.1 is an example of a RADARSAT subscene
which has been filtered to remove the speckle. The sedimentary geological
feature in this remote area of Indonesia is more clearly emphasized when the
Kuan and/or Gamma filters are applied to remove speckle. These adaptive
filters smooth speckled areas while preserving point target detail. Additional
information regarding the digital manipulation of RADARSAT imagery can be
obtained from the RADARSAT Data Processing and Integration Handbook.
4 - 2 R A D A R S A T G E O L O G Y H A N D B O O K
I M A G E E N H A N C E M E N T O F R A D A R S A T D A T A 4 - 3
FIGURE 4.1: Unfiltered vs. filtered RADARSAT images
Fine beam position 4: acquired March 21, 1996, area: 3.5 x 5 km, subscene. RADARSAT data
© Canadian Space Agency/Agence spatiale canadienne 1996. Received by the Canada Centre for
Remote Sensing. Processed and distributed by RADARSAT International. Data acquired during the
commissioning phase and may not conform to system specifications.
Spatial Filtering Techniques
Decimation and Block Averaging
A radar pixel is rarely interpreted individually, but rather in combination with
surrounding pixel values creating shapes and patterns which provide the basis
for interpreting structural features. In some cases, it is desirable to have a
relatively simple procedure which is able to reduce the original image to a more
manageable file size. Decimation takes every nth pixel value to produce an
image with coarser resolution. The trade-off is a decreased file size. Decimation
results in a loss of information and discontinuous lines because neighbouring
values are not considered.
To retain more image information, the block average procedure is used. This
degrades the image both spatially and radiometrically, resulting in a much
smoother-looking image. The pixel values in the original image are modified on
the basis of the grey levels of the neighbouring pixels (Lillesand and Kiefer,
1994) to produce one mean value for the moving window. Moving
neighbourhoods or windows of 3 x 3 or 5 x 5 pixels are typically used in such
procedures. Although smoothing can produce a less granular texture, it creates
larger pixels and may give the appearance of softened edges in the image. A
RADARSAT image using the block averaging and decimation methods is shown
in Figure 4.2.
4 - 4 R A D A R S A T G E O L O G Y H A N D B O O K
I M A G E E N H A N C E M E N T O F R A D A R S A T D A T A 4 - 5
FIGURE 4.2: Block averaged and decimated Images: Vancouver, BC, Canada
The Block Averaged image shows more contrast between landcover classes and the land/water
boundaries than the decimated image. Block averaging provides increased delineation of linear
features given that neighbouring values are taken into consideration. Fine beam position 3:
acquired March 12, 1996, area: 16.5 x 16.5 km, subscene. RADARSAT data © Canadian Space
Agency/Agence spatiale canadienne 1996. Received by the Canada Centre for Remote Sensing.
Processed and distributed by RADARSAT International. Data acquired during the commissioning
phase and may not conform to system specifications.
2
3
4
5
6
COMPARISON OF SATELLITE IMAGING SYSTEMS
THE RADARSAT SATELLITE
VISUAL INTERPRETATION OF RADARSAT IMAGERY
IMAGE ENHANCEMENT OF RADARSAT DATA
VALUE-ADDED RADARSAT PRODUCTS
SUMMARY
REFERENCE MATERIALS
1
For some applications, a single RADARSAT image may be the only data you
require. For other applications, it may be useful to have several RADARSAT
images covering a large area or acquired at different times, or from different
look directions. Furthermore, you may want to integrate (or fuse) RADARSAT
data with other image products, geologic map data, or database information
associated with features on the image. This chapter discusses the various
techniques used to digitally integrate radar data.
R A D A R I M A G E R Y M A N I P U L A T I O N
Stereo Viewing
Stereo pairs are a helpful tool for mapping structures that are either highly
deformed or consisting of extremely low-angle dipping strata (Mahmood, et al.,
1996). RADARSAT images acquired using different beam positions contain
parallax in exactly the same manner as aerial photos. The common area between
the two images can be represented in three dimensions. Radar stereo pairs can
then be viewed using traditional photogrammetric techniques including use of a
stereoscope or glasses designed to show three dimensions. Stereo pairs can be
used to enhance the interpretability of geologic structures (see Figure 5.1), for
assessing the dip and strike of inclined strata, or for mapping highly-deformed
landforms.
Anaglyphs
Stereo pairs can be represented in anaglyph format, whereby the two images are
overlaid digitally: one in shades of red, and the other in shades of blue. When
viewed through proper glasses, the two images appear to create a three-dimen-
sional viewing environment. This effect is clearly demonstrated in the anaglyph
created of Papua New Guinea (see Figure 5.2).
Mosaics
Extensive coverage of a particular area can be obtained by overlapping parallel
strips into a mosaic. Mosaics are an inexpensive (in some cases less than
$0.02/km2 USD) and easy-to-use source of information for mapping large
V A L U E - A D D E D R A D A R S A T P R O D U C T S 5 - 1
areas. Figure 5.3 showing the Island of Borneo, is an example of a mosaic
created using 12 RADARSAT ScanSAR beam mode images. Many image
analysis packages offer the functionality to join RADARSAT images and adjust
the radiometric properties to produce such a seamless mosaic. An accurate
mosaic requires that the radar look direction be held constant; if not, the
shadows and highlights will be reversed in different parts of the mosaic.
5 - 2 R A D A R S A T G E O L O G Y H A N D B O O K
FIGURE 5.1: Stereo viewing with RADARSAT: Sarawak, Malaysia
An example of a RADARSAT stereo pair created for an area of folded sediments. Standard beam
position 5 (left): acquired May 28, 1996. Standard beam position 6 (right): acquired June 3, 1996,
area: 22 x 72 km. RADARSAT data © Canadian Space Agency/Agence spatiale canadienne 1996.
Received by the Canada Centre for Remote Sensing. Processed and distributed by RADARSAT
International.
V A L U E - A D D E D R A D A R S A T P R O D U C T S 5 - 3
FIGURE 5.2: RADARSAT anaglyph: Southern Highlands, Papua New Guinea
Standard beam position 2: acquired September 6, 1996. Standard beam position 7: acquired
September 9, 1996. RADARSAT data © Canadian Space Agency/Agence spatiale canadienne 1996.
Received by the Canada Centre for Remote Sensing. Processed and distributed by RADARSAT
International.
5 - 4 R A D A R S A T G E O L O G Y H A N D B O O K
FIGURE 5.3: RADARSAT image mosaic: Island of Borneo
Image mosaic comprised of 12 ScanSAR Narrow images. RADARSAT data © Canadian Space
Agency/Agence spatiale canadienne. Received by the Canada Centre for Remote Sensing.
Processed and distributed by RADARSAT International. Image mosaic by Resource GIS and
Imaging Ltd. (RGI).
V A L U E - A D D E D R A D A R S A T P R O D U C T S 5 - 5
DEM Creation Using RADARSAT Stereo Pairs
Stereo pairs can be used to derive digital elevation models (DEMs) for almost
any location in the world. DEMs are a representation of the surface elevation,
and provide the means of correcting the geometric distortion inherent in SAR
imagery. With these DEMs and the appropriate software, it is possible to create
three-dimensional perspectives which best suit the user’s viewing needs. The
accuracy of the derived DEM will depend on the use of an appropriate combination
of beam positions for a specific terrain relief. In mountainous regions, same side
stereo pairs can be collected in both ascending and descending orbits. This
allows areas excluded by shadows or layover to be filled in from an opposite
viewing direction. DEMs can be used to correct geometric distortions such as
foreshortening and layover.
RADARSAT-derived DEMs can now be created at levels of detail approximate
to 1:100,000 scale mapping standards. Figure 5.4 shows a DEM derived from a
RADARSAT stereo image pair created using Standard beam positions 2 and 7.
The resulting image can be imported into a GIS system as a base map, especially
in those areas where only limited or outdated maps are available.
D A T A I N T E G R A T I O N
Radar data is easily integrated with other datasets, thus creating an enhanced
interpretive mapping tool. The decision to integrate is made when the general
characteristics of a dataset are summarized. For example, although radar data
provides thematic value, its strongest value is related to structure.
Aeromagnetics and gravity are two perfect examples. These two datasets benefit
synergistically from the radar data, resulting in datasets which have more
thematic value than the sum of their original parts.
Figures 5.5 and 5.6 represent SAR images which have been digitally fused with a
multi-channel optical image to obtain increased geologic information. The
combined maps are very useful for the geologic mapping of structures and
lithology. The merged image retains most of the multispectral LANDSAT TM
information, while the RADARSAT image accentuates the terrain features.
5 - 6 R A D A R S A T G E O L O G Y H A N D B O O K
RADARSAT data provides information on surface expression, while
aeromagnetic data shows sediment thickness. Radar data is commonly merged
with LANDSAT TM (see Figure 5.6), adding thematic information to help infer
information about the underlying soil, sediment and bedrock conditions.
FIGURE 5.4: DEM created with RADARSAT data: Papua New Guinea
The image was colourized according to elevation, and draped over a perspective view of the DEM.
Standard beam position 2: acquired August 29, 1996. Standard beam position 7: acquired August 26,
1996. RADARSAT data © Canadian Space Agency/Agence spatiale canadienne 1996. Received by
the Canada Centre for Remote Sensing. Processed and distributed by RADARSAT International.
DEM by Intermap Technologies Ltd.
V A L U E - A D D E D R A D A R S A T P R O D U C T S 5 - 7
FIGURE 5.5: Integration of RADARSAT/optical data: Cape Breton Island, NS, Canada
This merged image emphasizes key features enhanced by integrating radar and optical data. The
RADARSAT portion outlines subtle geological features and lineaments, including the Aspy Fault,
while the LANDSAT data clearly identifies vegetated and cleared areas. RADARSAT Standard beam
position 1: acquired November 28, 1995, subscene. LANDSAT: acquired September 14, 1990, TM,
bands 4, 5, 7. RADARSAT data © Canadian Space Agency/Agence spatiale canadienne 1995.
Received by the Canada Centre for Remote Sensing (CCRS). Processed and distributed by
RADARSAT International. Data acquired during the commissioning phase and may not conform to
system specifications. LANDSAT data received by CCRS and reproduced courtesy of EOSAT.
Enhancement and interpretation by CCRS.
5 - 8 R A D A R S A T G E O L O G Y H A N D B O O K
FIGURE 5.6: LANDSAT TM/RADARSAT merge: Vancouver, BC, Canada
The RADARSAT Fine beam mode image provides textural information on the surrounding landcover,
while the LANDSAT TM image separates vegetated areas from urban areas. The final merged product
is better at identifying point targets such as oil storage tanks (centre of image). RADARSAT Fine
beam position 3: acquired March 3, 1996. LANDSAT: acquired September 1994, bands 1, 2, 3.
RADARSAT data © Canadian Space Agency/Agence spatiale canadienne 1996. Received by the
Canada Centre for Remote Sensing (CCRS). Processed and distributed by RADARSAT International
(RSI). Data acquired during the commissioning phase and may not conform to system specifications.
LANDSAT data received by CCRS and processed by RSI. Reproduced courtesy of EOSAT.
IHS (Intensity-Hue-Saturation) Transformation
Images can be fused using multi-channel image combination techniques. One
V A L U E - A D D E D R A D A R S A T P R O D U C T S 5 - 9
technique is known as an IHS (Intensity-Hue-Saturation) Transformation,
which is a common method used to fuse optical and radar images, and is
adequate for highlighting topographic features. Three channels of optical or
other data are represented as Red-Green-Blue (RGB) channels in a digital
image. Using an image analysis program, the RGB image is converted to an IHS
image. The intensity channel (I) is then replaced with the radar image, while the
optical data remains in the hue (H) and saturation (S) channels. The final image
retains most of the multispectral information, as well as accentuated terrain
features from the radar image (see Figure 5.7).
FIGURE 5.7: IHS transformation: Sudbury Basin, ON, Canada
The aeromagnetic data shows geologic units expressed from their respective magnetic signatures,
while RADARSAT offers structural and topographic information. RADARSAT Standard beam position
1: acquired June 4, 1996. RADARSAT data © Canadian Space Agency/Agence spatiale canadienne
1996. Received by the Canada Centre for Remote Sensing (CCRS). Processed and distributed by
RADARSAT International. Enhancement and interpretation by CCRS.
5 - 1 0 R A D A R S A T G E O L O G Y H A N D B O O K
2
3
4
5
6
COMPARISON OF SATELLITE IMAGING SYSTEMS
THE RADARSAT SATELLITE
VISUAL INTERPRETATION OF RADARSAT IMAGERY
IMAGE ENHANCEMENT OF RADARSAT DATA
VALUE-ADDED RADARSAT PRODUCTS
SUMMARY
REFERENCE MATERIALS
1
S U M M A R Y 6 - 1
The imagery examples presented throughout this handbook have demonstrated
that RADARSAT imagery can support geological mapping based on image
tones, textures and patterns caused by topographic contrasts and surface
roughness (Mahmood, et al., 1996). RADARSAT has proven itself to be of
significant use for geological applications.
RADARSAT can help with the logistical planning of projects due to its ability to
collect data under inclement weather and in areas with dense tropical
vegetation. Radar can greatly improve the success of mineral prospecting and
petroleum extraction, by providing information on:
• regional seismic line coverage
• drill site access
• production facilities
• pipeline routing and access
• hydrocarbon reserves
In closing, RADARSAT imagery is only one source of data available to
geologists. By integrating RADARSAT data with other surface and subsurface
data, published geologic maps, and field checks, exploration geologists can
achieve optimal results in interpreting geologic structures.
2
3
4
5
6
COMPARISON OF SATELLITE IMAGING SYSTEMS
THE RADARSAT SATELLITE
VISUAL INTERPRETATION OF RADARSAT IMAGERY
IMAGE ENHANCEMENT OF RADARSAT DATA
VALUE-ADDED RADARSAT PRODUCTS
SUMMARY
REFERENCE MATERIALS
1
G L O S S A R Y G - 1
G L O S S A R Y
A
Active System: A remote sensing system that emits its own energy source to
illuminate the Earth’s terrain. RADARSAT is one example.
Anaglyph: A method of obtaining a three-dimensional image of topography
by viewing two adjoining images that have been assigned red and blue colours.
They can be viewed in three dimensions by means of special lenses: one being
red and the other blue.
Antenna: A device that transmits and receives microwave and radio energy in
radar systems.
B
Backscatter: The portion of the microwave energy scattered by the terrain
surface directly back towards the antenna.
Block Averaging: A spatial filtering technique which reduces the image size by
using a moving window to average neighbouring pixels to produce a final
brightness value.
C
Contact Print: A reproduction from a photographic negative in direct contact
with photosensitive paper.
Corner Reflector: A cavity formed by two or three smooth planar surfaces
intersecting at right angles. Energy entering a corner reflector is directed back
towards the source.
D
Decimation: A spatial filtering technique that samples every nth pixel value,
without considering the neighbouring pixel values to produce an image with a
decreased file size.
Dielectric Constant: A measure of the electrical properties of surface
materials, which influence the radar return.
Digital Elevation Models (DEMs): A stereo analysis technique whereby a
computer ingests information from a digitized stereo pair and produces a
geometrically corrected digital map with correlated elevation measurements.
Digital Image Processing: Computer manipulation of the digital number
(DN) values of an image.
Drainage Anomaly: Unique pattern of stream channels and valleys that
appears anomalous with respect to the surrounding drainage features. Usually
reflects local topographic and structural controls.
F
Far Range: The portion of the radar image furthest from the sensor flight
path.
Flatiron: A typical surface expression of a dissected cuesta. Expressed as a
triangularly shaped ridge with an apex that points away from the dip direction.
Foreshortening: A distortion on radar images that occurs when the emitted
wavefront strikes the top of a vertical feature and makes it appear to lean toward
the sensor.
G
Geometric Correction: Image processing procedure that corrects spatial
distortions in an image.
G - 2 R A D A R S A T G E O L O G Y H A N D B O O K
G L O S S A R Y G - 3
Grey Scale: A sequence of grey tones ranging from black to white.
Ground Control Point: A geographic feature of known location that is
recognizable on images and can be used to determine geometric corrections.
Ground Range: On radar images, the distance from the ground track to the
object.
H
Hue: Indicates the dominant wavelength of a colour. Hue is usually
represented as a value between 0 and 255.
I
Image: A pictorial representation acquired in any wavelength of the
electromagnetic spectrum.
Intensity-hue-saturation (IHS) Transformation: Any image enhancement
technique that separates intensity, hue, and saturation components from an
image and modifies them.
Incidence Angle: The angle formed between an imaginary line normal to the
surface and another connecting the antenna and the target.
Interpretation: The process in which a person or image processing software
extracts information from an image.
L
Layover Effect: An extreme case of foreshortening when the topographic
slope is equal to or larger than the incidence angle. The slope facing the radar
image disappears underneath the back slope.
Lineaments: Linear topographic or tonal feature on the terrain and on images
that may represent zones of structural weaknesses.
Look Direction: The direction chosen for a radar survey to take advantage of
radar shadows, which improve the appearance of features of interest.
M
Microwave: Electromagnetic wavelength of 1mm-1m (.3GHz to 300GHz).
Mosaic: Composite image made by piecing together individual images
covering adjacent areas.
N
Near Range: Refers to the portion of the radar image closest to the satellite
flight path.
O
Obscured Structure: A geological structure whose rock units are partially
covered by vegetation or soil, and must be analyzing its effect on surface
features.
Overlap: The extent to which adjacent images cover the same terrain,
expressed as a percentage.
P
Parallax: Displacement of a target position in an image caused by the shift in
the observation position.
Passive System: A remote sensing system that relies on naturally occurring
radiation or reflected light from the Earth’s surface to create an image.
LANDSAT TM and SPOT are examples.
G - 4 R A D A R S A T G E O L O G Y H A N D B O O K
G L O S S A R Y G - 5
Pixel: The smallest discrete area on an image (from PICTure ELement).
R
Radar: An acronym for RAdio Detection And Ranging. Radar is an active
form of remote sensing that operates in the microwave and radio wavelength
regions.
Radar Shadow: Dark signatures on a radar image representing no signal
return. A shadow extends in the far range direction from an object that intercepts
the radar beam.
Range Resolution: The spatial resolution in the range direction, which is
determined by the pulse length of the transmitted microwave energy.
Resolution: Ability to separate closely spaced objects on an image. Resolution
is commonly expressed as the most closely spaced line pairs per unit distance
that can be distinguished.
S
Scarp Slope: The short and steep slope of a cuesta. The scarp slope indicates
the anti-dip direction.
Shadow: See Radar Shadow.
Signature: A set of characteristics by which a material or an object may be
identified on an image or photograph.
Slant Range: An imaginary line running between the antenna and the target.
Speckle: Uncertainty associated with each pixel in the image of the scene,
producing a salt-and-pepper effect.
Stereo: Imaging technique of using parallax properties from two images of the
same area to extract elevation information.
Surface Roughness: The average vertical relief of small-scale irregularities of
the terrain surface.
Synthetic Aperture Radar (SAR): SAR systems use the motion of the satellite
and doppler frequency shift to electronically synthesize the large antenna necessary
for acquisition of high-resolution radar images.
T
Tone: Each distinguishable shade of grey from white to black on an image.
Topographic Inversion: The illusion that may occur on images with extensive
shadows. Ridges appear to be valleys, and valleys appear to ridges. The illusion
is corrected by orienting the image so that the shadows trend from the top
margin of the image to the bottom.
Treetop Geology: The ability to map surface topography indirectly by
examining variations in the heights of treetops. This is one of the major
advantages of radar over passive systems.
G - 6 R A D A R S A T G E O L O G Y H A N D B O O K
R E F E R E N C E M A T E R I A L S R - 1
R E F E R E N C E S
Journals/Books
Berger, Z., 1994. Satellite Hydrocarbon Exploration: Interpretation andIntegration Techniques. Springer-Verlag Publishers, 319 pp.
Brown, R.J., B. Brisco, et al., 1996. RADARSAT Applications: Review of
GlobeSAR Program. Canadian Journal of Remote Sensing, Vol 22, No. 4,
pp. 404-419.
CASI, 1993. Special Issue: RADARSAT. Canadian Journal of Remote Sensing,
Vol 19, No. 4, entire issue.
CASI, 1994. Special Issue on Radar Geology. Canadian Journal of RemoteSensing, Vol 20, No. 3, entire issue.
Chigne, N., F. Dekker, et al., 1996. Spaceborne Radar (ERS-1 and
RADARSAT-1) Tests for Hydrocarbon Exploration in Venezuela.
II AAPG/SVG International Congress and Exhibition, Caracas, Venezuela,
8-11 September, pp. A9-A10.
Dekker, F., and D. Nazarenko, 1994. Radar Offers Many Unique Benefits as an
Exploration Tool in Tropical Environments. Earth Observation Magazine, Vol 3, No. 5, May, pp. 26-29.
Dekker, F., 1994. A Comparison of Various Remote Sensing Tools, IncludingAirborne and Satellite SAR, for Hydrocarbon Exploration in Tropical RainForests: Projected Usefulness of RADARSAT For Geological Applications. Report
prepared for RADARSAT International, #93-110, 54 pp.
Evans, D.L., T.G Farr, et al., 1986. Multipolarization Radar Images for
Geologic Mapping and Vegetation Discrimination. IEEE Transactions onGeoscience and Remote Sensing, Vol GE-24, No. 2, pp. 246-257.
Harris, J.R., R. Murray, and T. Hirose, 1990. IHS Transform for the
Integration of Radar Imagery with Other Remotely Sensed Data.
Photogrammetric Engineering and Remote Sensing, Vol 56, No. 12, December,
pp. 1631-1641.
Lillesand, T.M, and R.W. Kiefer, 1994. Remote Sensing and ImageInterpretation. John Wiley and Sons, Inc., Toronto, ON, Canada, 750 pp.
Mahmood, A.S., Carboni et al., 1996. Potential Use of RADARSAT in
Geologic Remote Sensing. Eleventh Thematic Conference and Workshop onApplied Geologic Remote Sensing, Las Vegas, NV, 27-29 February, 1995,
pp. I475-I484.
Thompson, M.D., and B.J. Mercer, 1996. Digital Terrain Models. EarthObservation Magazine, March, pp. 22-26.
RADARSAT International, 1995. RADARSAT Illuminated: Your Guide toProducts and Services. Unpublished manual, 60 pp. (available from RADARSAT
International).
RADARSAT International, 1996. RADARSAT Data Processing andIntegration Handbook. Unpublished manual, 30 pp. (available from
RADARSAT International).
RADARSAT International, 1997. Hydrocarbon Exploration UsingRADARSAT: Looking for Oil and Gas in Venezuela. Unpublished
brochure (available from RADARSAT International).
Rossignol, S., and K.P. Corbley, 1996. Reconnaissance by Radar. CanadianMining Journal, Vol 117, No. 6, December, pp. 13-16.
Sabins, F.F. Jr., 1987. Remote Sensing: Principles and Interpretation.W.H. Freeman and Company, 3rd Ed., New York, 404 pp.
Singhroy, V.H., 1992. Radar Geology: Techniques and Results. Episodes, Vol 15
pp. 15-20.
R - 2 R A D A R S A T G E O L O G Y H A N D B O O K
R E F E R E N C E M A T E R I A L S R - 3
Websites
RADARSAT International (education) www.RADARSATinACTION.com
RADARSAT International (corporate) www.rsi.ca
Canada Centre for Remote Sensing www.ccrs.nrcan.gc.ca
Canadian Space Agency www.radarsat.space.gc.ca