1.1.6 Summary of Applications vs Products
1.1.6.1 Summary of Applications Introduction
The original focus of the ERS missions was
oceans and ice monitoring, and there has
been an impressive range of scientific
investigations in oceanography, polar
science, glaciology, and climate research
which will be supported by ASAR. These
include measurements of ocean surface
features (currents, fronts, eddies, internal
waves), directional ocean wave spectra, sea
floor topography, snow cover and ice
sheet dynamics. Operational systems have
been developed for mapping sea ice, oil
slick monitoring and ship detection.
The ASAR Instrument will provide continuity
and improvement upon the ocean, coastal one,
and land cover monitoring capabilities of
the previous ERS SAR instruments. ASAR
promises to be important for modelling
changes in vegetation, oceans, ice sheets,
snow and sea ice. Data is required in
order to initiate or validate models, and
for long-term monitoring over global to
regional scales, as well as smaller areas
of particular interest.
Three different groups of users of ASAR data are:
- Remote Sensing Science
- Earth Science Community
- Commercial Applications
1.1.6.1.1 Remote Sensing Science
A considerable amount of research has
been undertaken into the processing and
use of spaceborne SAR data from ERS-1
and ERS-2, as well as other SAR
instruments. The need for further
research will continue, both in data
processing and analysis techniques, and
in the development of geophysical
retrieval models. Research will be
undertaken by a range of users from
universities and research institutes, to
value-added companies and industries
seeking to improve the product or
service they are selling or using. The
availability of multi-polarised data
and data from the Global Monitoring
Mode will be of particular interest.
Preliminary processing of data at ground
stations and by value-added companies
includes calibration and validation of
data, feature detection, texture
analysis, reduction of speckle, image
registration, geocoding and radiometric
corrections. Techniques are continually
being developed; particularly when data
from a new sensor like ASAR becomes
available. Data from all modes will be
required for specific study sites
over land, ocean and ice.
The availability of data from multiple
incidence angles provides opportunities
to develop new data processing
techniques which may give new
information on soil moisture, forest
characteristics, geological structure,
etc. Data will be required at all modes
and polarisations for specific study
sites covering a range of incidence angles.
Algorithm Development
Considerable ocean-related research is
currently being undertaken by defence
departments to monitor fishing boats and
ships in busy traffic lanes. The
likelihood of detecting ships and ship
wakes will improve with the use of
multi-polarised data. In the coastal
zones, research is currently being
undertaken to develop methods of mapping
shorelines and the sea bottom in shallow
areas. Some of these applications
are now operational and will continue to
expand with ASAR.
Much of the basic research on
classification of ice types has been
carried out, and good algorithms are
available. The value of
multi-polarised data for ice type
discrimination, especially during the
ice formation and ice melting periods
has been demonstrated using airborne
systems. Data from both the Alternating
Polarisation and Wide Swath (HH and
VV) Modes available with ASAR will be
utilised throughout the year for test
areas in the Arctic Ocean.
To develop agricultural and vegetation
products, multi-temporal data across the
major crop and cover types, from which
backscatter models of crop type,
area, height and condition will be developed.
|
Figure 1.64 Backscatter of Sitka Spruce and Upland Pasture at Llyn Brianne, Wales. (Acknowledgement: Luckman and Baker, 1995.) Above: Polarisation and incidence angle effects on backscattering. Below: Relative contributions of surface, double-bounce and volume scattering. |
Forest mapping is of particular interest
in the humid tropics and other
persistently cloudy areas. Important
research topics include the
classification of forest types,
identification of burned forest,
assessment of forest stress and
monitoring of logging concessions. The
availability of multi-polarised and
variable incidence angle data from ASAR
should improve on the accuracy of ERS
results. For example, figure1.64 above shows how
backscatter varies with VV, HH and HV
polarisations across a range of
incidence angles, for Sitka Spruce and
Upland Pasture, and how these
measurements have been used in a
decomposition model to determine the
relative contribution of surface,
double-bounce and volume scattering mechanisms.
Many hydrological and agricultural
applications use soil moisture data.
Current research is investigating the
relationship between soil moisture
and backscatter across a range of soil
conditions (Le Toan et al, 1994). The
use of multi-polarised and
multi-incidence angle data should
increase the accuracy of models by
reducing the effect of surface roughness
and vegetation. There is a strong
interest in the use of Wide Swath
and Global Monitoring Modes, because of
the much improved temporal frequency of
coverage (Zmuda et al, 1997). Snow melt
and hydrology applications require
information on snow cover distribution
and snow water equivalent.
Table 1.4 provides a list
of the ASAR modes for applications being
addressed by remote sensing science. In
particular, it shows a very strong
demand for Alternating Polarisation (AP)
Mode. The other modes shown are:
Image (IM) Mode and Wide Swath (WS) Mode.
|
Table 1.4 ASAR Modes for Remote Sensing Science
|
|
Mode |
Polarisation |
Swath |
Remarks |
Agriculture |
AP |
VV/VH |
IS4-6 |
Multi-temporal |
Land cover |
AP |
VV/VH |
IS4-6 |
Multi-temporal |
Forestry |
AP |
VV/VH' |
IS4-6 |
Multi-temporal and interferometry |
Soil moisture |
AP |
VV/VH |
IS1-3 |
High revisit |
Snow melt |
IM |
HH or VV |
IS3-7 |
High revisit |
Hydrology |
AP |
VV/VH |
IS2-5 |
High revisit |
Geology |
IM |
HH |
IS4-7 |
|
Urban mapping |
AP |
HH/HV |
IS3-7 |
|
Inland water |
IM |
VV |
IS2-4 |
|
Oceanography |
AP |
VV/HH |
IS2-6 |
|
Coastal phenomena |
AP |
VV/HH |
IS2-6 |
|
Sea ice |
AP |
VV/HH |
IS2-6 |
|
Ship detection |
AP |
HH/HV |
IS2-7 |
|
Marine meteorology |
AP |
VV/HH |
IS2-6 |
|
Pollution monitoring |
WS |
VV |
|
|
1.1.6.1.2 Earth Science
The past decade has seen increasing
public concern about the Earth, its
environment and mankind's impact
upon it. Global threats such as
climate warming, stratospheric ozone
depletion, tropospheric pollution and,
more recently, regional events such as
the very intense El Niño, the
fires in S.E. Asia, and the floods in
mid Europe and China, have left us more
concerned than ever about the need to
monitor and understand what is going on
in the Earth's environment. There
are many aspects of the complex evolving
Earth System that we still do not understand.
These concerns have led to the
establishment of the concept of a Global
Climate Observing System (GCOS),
including both space- and
surface-based systems, to measure on a
routine basis all major elements of the
global climate system. Table 1.5 below provides a
summary of the principal observations
required in support of GCOS.
Ultimately, the way in which our
understanding of the Earth will improve,
is by the development of Earth System
models which integrate into data
from various sources. Earth observation
from space is a critical tool in this
task because of the unique synoptic view
and high repeat frequency that it
provides. Some of the earliest
initiatives, including METEOSAT and SPOT,
have already developed into long-term
applications programmes integrated into
regular operational use. The ERS
satellites have made major contributions
in areas as diverse as global and
regional ocean and atmospheric science,
sea ice, glaciology and snow cover
investigations, land surface studies and
the dynamics of the Earth's crust
(seismology and volcanology).
ENVISAT will provide new capabilities to
monitor atmospheric composition and
chemistry, with ASAR providing
continuity and improvement upon the
ocean, coastal zone and land cover
monitoring capabilities of the ERS SAR instruments.
ASAR promises to be particularly
important for modelling and monitoring
changes in vegetation, oceans, ice
sheets, snow and sea ice.
|
Table 1.5 Summary of GCOS principal observations
|
Planet
Earth |
PRINCIPAL SYSTEM
|
GCOS MISSIONS
|
PRINCIPAL OBSERVATIONS
|
|
|
Cloud Amount |
|
|
Cloud Drop Size Distribution |
|
|
Surface Fluxes
(heat, water) |
|
Global |
Solar Irradiance |
|
Radiative |
Surface
Radiation Fluxes |
|
Properties |
Earth Radiation Budget |
GLOBAL |
|
Multispectral Albedo |
|
|
Aerosols |
|
|
Ocean Colour |
|
|
Ocean Topography/Geoid |
|
Ocean |
Sea Ice Cover |
|
Characteristics |
Sea Surface Temperature |
|
|
Ocean Salinity |
|
|
Sea Surface Temperature |
|
Ocean |
Ocean Wind Vectors/Seed |
|
Atmosphere |
Sea Ice Cover
(as tracer) |
|
Boundary |
Ocean Wave
Height Spectra |
OCEANS |
|
Atmospheric
Surface Pressure |
|
|
Temperature Profile |
|
|
Cloud Clearing |
|
Atmospheric |
Wind Profile |
|
Thermodynamics |
Liquid Water/Ice |
|
|
Precipitation |
|
|
Humidity (profile/total) |
|
|
Constituents (total/profile) |
|
Atmospheric |
Atmospheric Dynamics |
|
Composition |
Ozone (total/profile) |
ATMOSPHERE |
& Chemistry |
Aerosols (total/role) |
|
|
Vegetation Characteristics |
|
Land |
Soil Moisture |
|
Atmosphere |
Snow & Ice Cover |
|
Interaction |
Land Surface Temperature |
|
|
Evaporation |
|
|
Vegetation Change |
|
Land |
Land Use Change |
LAND |
Biosphere
Climate Response |
|
The following applications are considered
to be the major areas of use for ASAR
data within Earth Sciences:
- Vegetation Monitoring
- Sea Ice Monitoring
- Glaciology and Snow Mapping
- Oceanography
- Coastal Zone Processes
These primary ASAR applications are
described in more detail in the
following sections.
Table 1.6 below gives a
summary of the ASAR modes mostly likely
to meet the various needs of the
Earth Sciences community.
|
Table 1.6 ASAR Modes for earth science
|
|
Mode |
Polarisation |
Swath |
Remarks |
Vegetation maps |
WS |
VV or HH |
|
Large area
cover, multi-temporal |
Soil moisture estimation |
WS |
VV |
|
|
Surface motion
and subsidence |
IM |
VV or HH |
IS2-5 |
Using interferometry |
Oceanography |
WS |
HH |
|
|
Coastal phenomena |
AP |
VV/HH |
IS2-6 |
|
Marine meteorology |
WS |
VV |
|
|
Wind/Wave Models |
WM |
VV |
|
|
Glacier/ice
sheet motion |
IM |
HH or VV |
IS3-6 |
|
Ice sheet extent
and melt areas |
WS |
HH or VV |
|
|
Snow climatology |
WS and GM |
HH or VV |
|
|
Wetlands |
WS |
VV |
|
|
Sea Ice |
WS and GM |
HH |
|
|
1.1.6.1.3 Commercial Applications
The growing availability of Earth
observation data is encouraging
increased involvement and investment by
value-added organisations and
end-users. These include government
departments with responsibility for
agriculture, the environment, pollution
control, meteorology, coastal
protection, transport (especially
coastal, marine and ice), fisheries and
hazard management.
The following applications are considered
to be the major areas for commercial
exploitation of ASAR data:
- Ship Routing through Sea Ice
- Sea Ice Monitoring
- Ocean Monitoring
- Monitoring Oil Slicks
- Nowcasting of ocean fronts, eddies
and current shears
- Agricultural Monitoring
- Forestry
- Hydrology and Water Management
- Flood Mapping
These commercial ASAR applications are
described in more detail in following sections.
|
Table 1.7 ASAR Modes for commercial applications
|
|
Mode |
Polarisation |
Swath |
Remarks |
Ship routing in sea ice |
|
|
|
|
Sea ice extent |
WS |
HH |
|
|
Ocean monitoring |
|
|
|
|
Surface features |
AP |
HH/HV |
IS2-6 |
|
Oil slicks |
WS |
VV |
|
|
Ship detection |
APorIM |
HH/HVHH |
IS2-7, IS5-7 |
|
Bathymetry |
IM |
HH |
IS2-5 |
|
Agricultural monitoring |
|
|
|
|
Crop area |
AP |
VV/VH or VV/HH |
IS4 |
|
Crop condition |
IM |
VV or HH |
IS2-7 |
|
Soil moisture |
WS |
VV |
|
High repeat |
Forestry |
|
|
|
|
Forest area/type/condition |
AP |
VV/VH |
IS4-6 |
|
Hydrology, and water management |
|
|
|
|
Runoff forecasts |
WS |
VV |
|
High repeat |
Flooding |
WS |
HH |
|
High repeat |
Oil and as industry |
|
|
|
|
Geological ma |
IM |
HH |
IS4-7 |
|
Natural hazards |
|
|
|
|
Earthquakes/volcanoes /land subsidence |
IM |
VV or HH |
IS1-7 |
|
1.1.6.2 Ocean Applications The oceans not only provide
valuable food and biophysical resources, they
also serve as transportation routes, are
crucially important in weather system
formation and CO2 storage, and are an important
link in the Earth's hydrological balance.
Understanding ocean dynamics is important
for fish stock assessment, ship routing,
predicting global circulation consequences of
phenomena such as El Niño, forecasting
and monitoring storms so as to reduce the impact
of disaster on marine navigation, offshore
exploration, and coastal settlements.
Studies of ocean dynamics include wind and wave
retrieval (direction, speed, height) , mesoscale
feature identification, bathymetry, water
temperature, and ocean productivity.
Ocean feature analysis includes
determining current strength and direction,
amplitude and direction of surface winds,
measuring sea surface temperatures, and
exploring the dynamic relationship and
influences between ocean and atmosphere.
Knowledge of currents, wind speed,
tides, storm surges and surface wave height
can facilitate ship routing. Sea floor
modelling supports waste disposal and
resource extraction planning activities.
Ocean circulation patterns can be determined
by the examination of mesoscale features
such as eddies, and surface gravity waves.
This knowledge is used in global climate
modelling, pollution monitoring, navigation
and forecasting for offshore operations.
Remote sensing offers a number of different
methods for acquiring information on the
open ocean and coastal region.
Scatterometres collect wind speed and
direction information, altimeters measure
wave height, and identify wind speed. SAR is
sensitive to spatially varying surface
roughness patterns caused
by the interaction of the upper ocean
with the atmosphere at the marine boundary
layer, and scanning radiometers and microwave sounders collect
sea surface temperature data. Buoy-collected
information can be combined with remote sensing data to
produce image maps displaying such
things as hurricane structure with annotated
wind direction and strength, and wave
height. This information can be useful
for offshore engineering activities,
operational fisheries surveillance and storm
forecast operations.
ASAR provides an option for acquiring
information on the open ocean and coastal
region. Several new SAR ocean applications
can be expected to reach pre-operational
or operational status during the lifetime of
ENVISAT, notably in the areas of pollution
monitoring, ship detection, and ocean
feature nowcasting. This information can be
useful for offshore engineering activities,
operational fisheries surveillance, and
storm forecast operations.
Some of the key areas of interest will
include the following:
-
Wave Characteristics
-
Ocean Fronts
-
Coastal Dynamics
-
Oil Slicks and ShipTraffic
Wide area coverage is useful for monitoring
and surveillance applications including ship
traffic, fisheries monitoring, oil spill
mapping, and ocean circulation mapping.
Intermediate area coverage is useful for
monitoring ship traffic, near-shore
fisheries activities, oil spill mapping,
and inter-tidal feature mapping. Small area
coverage is useful for harbour traffic
monitoring, aquaculture site location
and small spill mapping.
1.1.6.2.1 Wave Characteristics
For general sea-state information (waves,
currents, winds), the data is usually
time-sensitive; meaning that the
information is only valuable if it
is received while the conditions exist.
ASAR data is expected to play a key role
in the study of wave characteristics.
Certain wind speed
conditions are necessary in order for
the SAR to receive signal information
from the ocean surface. At very low
wind speeds (2 to 3m/s) the SAR is not
sensitive enough to detect the ocean
"clutter" and at very high
wind speeds (greater than 14 m/s)
the ocean clutter masks whatever
surface features may be present. The
principal scattering mechanism for ocean
surface imaging is Bragg scattering,
whereby the short waves on the ocean
surface create spatially varying
surface patterns. The backscatter intensity
is a function of the incidence angle
and radar wavelength, as
well as the sea state conditions at
the time of imaging. The surface waves
that lead to Bragg scattering are
roughly equivalent to the wavelength
used by ASAR and RADARSAT (5.3 cm).
These short waves are generally formed
in response to the wind stress at
the upper ocean layer. Modulation in the
short (surface) waves may be caused by
long gravity waves, variable wind speed,
and surface currents associated with
upper ocean processes such as eddies,
fronts and internal waves. These
variations result in spatially
variable surface roughness
patterns which are detectable on SAR
imagery, as shown in figure1.65 .
|
Figure 1.65 Atmospheric Waves (Copyright 1994, European Space Agency) |
The SAR data for this image was taken by
the European Space Agency's ERS-1
satellite on August 17, 1994. The scene
shows the southern coast of Melville
Island's Dundas Peninsula (in the
Parry Islands of northern Canada), with
north pointing about 30 degrees to
the right.
Internal waves form at the interfaces
between layers of different water
density, which are associated with
velocity shears (i.e., where the
water above and below the interface is
either moving in opposite directions or
in the same direction at different
speeds). Oscillations can occur if
the water is displaced vertically
resulting in internal waves. Internal
waves in general occur on a variety of
scales and are widespread phenomena
in the oceans. The most important are
those associated with tidal oscillations
along continental margins. The internal
waves are large enough to be detected by
satellite imagery. In the image shown
below, the internal waves, are
manifested on the ocean surface as a
repeating curvilinear pattern of dark
and light banding, a few kilometres east
of the Strait of Gibraltar, where the
Atlantic Ocean and Mediterranean Sea
meet. Significant amounts of water move
into the Mediterranean from the Atlantic
during high tide and/or storm
surges. (See figure1.66 )
|
Figure 1.66 ERS 1 scene of internal waves: Strait of Gibraltar ( ESA 1992) |
One ASAR study being proposed by Dr. Olga
Lavrova, a senior scientist at the Space
Research Institute Russian Academy of
Sciences in Russia, plans to
investigate circulation processes in the
ocean and atmosphere (transformation of
speed field, energy and momentum
transfer) for the case of a stratified
flow running against natural obstacles.
The study will employ theoretical and
experimental investigation of the
spatial and temporal structure and
dynamics of waves, vortexes, and vortex
streets that emerge behind small
islands, capes, rocks, and
underwater rapids in the presence of
currents in the ocean, and due to air
flows on the shore and islands in the
atmosphere. In addition to the study of
forms and parameters of these lee
structures, their relation to the speed
of the run-against flow, the
stratification of the media and the
morphometry of the obstacle will be
considered. This paves the way for the
estimation of flow speed and media
density stratification from space.
This project envisages development of
numerical models based on the classical
hydrodynamic theory of stratified fluid
running against an obstacle. Process
hydrodynamic characteristics retrieved
from ASAR images will serve as input
parameters for the models. The models
will be used to retrieve current
characteristics in ocean and wind fields
in atmosphere above ocean from remote
sensing data. Experimental tests
based on the models will allow to
observe in time and space the stages of
circulation processes around natural
obstacles to flows.
1.1.6.2.2 Ocean Fronts
There is increasing interest in the
maritime community in high-precision
nowcasting of ocean fronts, eddies and
current shears. Important
application areas could be: piloting of
large transport ships, fisheries and
fish farming, sea floor operations and
autonomous underwater vehicles,
acoustic sensors and acoustic
communication. Also, ASAR imagery,
together with data from other ENVISAT
instruments such as MERIS and AATSR, will
significantly enhance the nowcasting of
ocean features in coastal waters.
Open ocean applications include the study
of large-scale ocean features manifested
at the ocean surface by the interaction
of wind-driven currents with the
marine boundary layer. The principle
scattering mechanism for ocean surface
imaging is Bragg scattering, whereby
the short waves create spatially varying
surface patterns. The backscatter
intensity is a function of the incidence
angle and radar/wavelength, as well
as the wind and wave condition at the
time of imaging. For RADARSAT (5.3 cm
wavelength), the surface waves that
lead to Bragg scattering are roughly
equivalent to its wavelength. These
short waves are generally formed in
response to the wind stress at the
marine boundary layer. Modulation in the
short waves may be caused by long
gravity waves, variable wind speed, and
surface currents associated with
upper ocean processes such as eddies,
fronts, and internal waves. These
variations result in spatially variable
surface roughness pattern which is
imaged by the SAR.
1.1.6.2.3 Coastal Dynamics
|
Figure 1.67 RADARSAT image of coastal region (courtesy Radarsat International) |
Coastlines are environmentally sensitive
interfaces between the ocean and the
land, and respond to changes brought
about by economic development and
changing land-use patterns. Often
coastlines are biologically diverse
inter-tidal zones and can also be highly
urbanised. With over 60% of the
world's population living close to
the ocean, the coastal zone is a region
subject to increasing stress from human
activity. Government agencies concerned
with the impact of human activities in
this region need new data sources with
which to monitor such diverse
changes as coastal erosion, loss of
natural habitat, urbanisation, effluents
and offshore pollution. Many of the
dynamics of the open ocean and
changes in the coastal region can be
mapped and monitored using remote
sensing techniques.
Coastal zone monitoring implies
observation of the interaction of
oceanographic and atmospheric phenomena
with human activities in the
near-shore region. The key issues
include the delineation of the
coastline, defining areas of erosion and
sedimentation, mapping the
inter-tidal vegetation, and identifying
areas of human settlement and
accompanying activities. The coastal
zone is an environmentally sensitive
region subject to increasing stress from
economic development, and government
agencies concerned with the impact of
human activities in the near-shore
region are looking for new data sources
with which to monitor this region.
An excellent coastal zone application of
radar is aquaculture site monitoring.
These man-made structures provide higher
signal returns than the surrounding water.
The main areas of interest in the coastal
zone are changes in sea level and in
suspended sediment, carbon, and
nutrients. Activities are being
undertaken, at a range of scales, using
diverse data sets for ocean
measurements, land use, vegetation and
coastal morphology. There are
numerous local, national, regional, and
international programmes involved in the
coastal zone. Major programmes include
the International Oceanographic
Commission, the MAST programme organised
by the EC, and the IGBP Land-Ocean
Interactions in the Coastal Zone
(LOICZ) programme to determine how
changes in the Earth's system are
affecting coastal zones and altering
their role in global cycles.
ASAR data will certainly be used within
the range of activities in the coastal
zone. Examples of current use of SAR
data in the coastal zone include:
topographic maps of tidal flats, sea bed
topography, sediment distribution in The
Netherlands, an inter-tidal digital
terrain model of the Wash in the UK,
and coastal erosion in French Guiana.
The availability of multi-polarised data
and data at different incidence angles,
or at a specific incidence angle, should
improve the accuracy and quality of
products for many applications. The Wide
Swath (WS) and Global Monitoring (GM)
Modes will provide data that is not
currently available, for applications
requiring large area coverage.
For example, a new conceptual scheme in
coastal research being proposed by Dr.
Francis Gohin, a Physical Oceanographer
at IFREMER in France, is to deploy
optical instruments, combined with
airborne and spaceborne spectral and SAR
imagers like ASAR, to provide an
up-to-date means of observing the narrow
bands of red tides. By integrating
colour data obtained from aircraft and
satellites in classical data sets, a
3-D numerical model will provide
estimation of the chlorophyll content
and the suspended matter concentration
on the continental shelf of the Bay
of Biscay. Remote sensing methods can be
used in the validation of such models.
In return, these models help to
include passive remote sensing data,
poorly sampled in time because of
clouds, in a regular set of simulations.
In addition, a study being proposed by
researcher Samuray Elitas M.Sc. of the
TUBITAK Marmara Research centre in
Turkey, envisions ASAR data being
used to analyse coastal regions there.
As ASAR and multicolour MERIS images for
the project area arrive, the most recent
and/or simultaneous pollution
mapping of the Marmara Sea will be
evaluated by relating other geographical
information data like bathymetrical
information and land usage information.
Consequently, geographical information
systems for the Marmara marine
environment, supported by ASAR and
MERIS images will be established as a
whole database.
The effects of bathymetry are visible in
near-shore regions under light wind
conditions. Small incidence angles are
better suited to imaging inter-tidal
features such as mudflats, shoals and sandbars.
Large incidence angles provide a larger
radar backscatter contrast which
improves the discrimination of the
water/land boundary. The smooth
surface of a water body acts as a
specular reflector in contrast to the
diffuse scattering which occurs over
land. Open water surfaces will
appear dark in comparison to the
brighter returns from land. Shoreline
detection and the identification of
areas of erosion or sedimentation
can be improved by acquiring
multi-temporal data with different look
directions (e.g., ascending or descending).
1.1.6.2.4 Oil Slicks and ShipTraffic
|
Figure 1.68 RADARSAT image of coastal oil spill, Wales (Courtesy CCRS) |
Oil spills can destroy marine life as
well as damage habitat for land animals
and humans. The majority of marine oil
spills result from ships emptying
their billage tanks before or after
entering port. Large area oil spills
result from tanker ruptures or
collisions with reefs, rocky shoals,
or other ships. These spills are usually
spectacular in the extent of their
environmental damage and generate wide
spread media coverage. Routine
surveillance of shipping routes and
coastal areas is necessary to enforce
maritime pollution laws and identify offenders.
Remote sensing offers the advantage of
being able to observe events in remote
and often inaccessible areas. For
example, oil spills from ruptured
pipelines may go unchecked for a period
of time because of uncertainty of the
exact location of the spill, and limited
knowledge of the extent of the
spill. Remote sensing can be used to
both detect and monitor spills.
For ocean spills, remote sensing data can
provide information on the rate and
direction of oil movement through
multi-temporal imaging and input to
drift prediction modelling, and may
assist in targeting cleanup and control
efforts. Remote sensing devices used
include infrared video and
photography from airborne platforms,
thermal infrared imaging, airborne laser
fluourosensors, airborne and spaceborne
optical sensors, as well as airborne and
spaceborne SAR. SAR sensors have an
advantage over optical sensors in that
they can provide data under poor
weather conditions and during darkness.
Users of remotely sensed data for oil
spill applications include the Coast
Guard, national environmental
protection agencies and departments, oil
companies, shipping industry, insurance
industry, fishing industry, national
departments of fisheries and oceans, and
departments of defence.
Oil slicks and natural surfactants are
imaged through the localised suppression
of Bragg scale waves. Under calm
conditions, natural surfactants may
form over large areas of the ocean,
along current boundaries, and in areas
of upwelling. The accumulation of
natural surfactants at these
boundaries can delineate the general
circulation pattern and are visible on
the radar image as curvilinear features
with a darker tone than the surrounding
ocean. Oil spills also have a darker
tone with respect to the surrounding
ocean background. The detection of
an oil spill is strongly dependent upon
the wind speed. At wind speeds greater
than 10 m/s, the slick will be broken up
and dispersed, making it difficult
to detect. Another factor that can play
a role in the successful detection of an
oil spill is the difficulty in
distinguishing between a natural
surfactant and an oil spill.
Multi-temporal data and ancillary
information can help to discriminate
between the two phenomena. Wind shadows
near land, regions of low wind speed,
and grease ice can also be mistaken for
oil spills and ancillary data (or an
experienced user) is necessary to
distinguish between these features and a spill.
Oil companies are now actively using ERS
SAR imagery in their search for new oil
fields (oil seepage from the ocean floor
is an important indicator). The ASAR
Wide Swath Mode in VV polarisation will
be a unique instrument for detection of
oil slicks on the ocean surface,
offering a very good combination of wide
coverage and radiometric quality. The
fourfold increase in coverage capability
compared to ERS will make routine
services feasible also at lower latitudes.
Small incidence angles are
optimum for oil spill detection.
Detection will also depend on the spill
size, sea state conditions and image resolution.
At the Norwegian Computing
Centre, senior research scientist Anne
Solberg proposes to modify algorithms
for automatic detection of oil
spills originally developed for ERS SAR
images, for use with ASAR images.
Methods have been developed for
automatic detection of oil spills in
ERS images as part of the Norwegian oil
spill project and the European Union
project ENVISYS. ASAR Wide Swath
data will have a different pixel size
and a different radiometric resolution
than the ERS SAR images, and these will
be incorporated in the detection and
classification algorithms. The new
project will use ASAR data from four
test sites with a high probability of
observing oil slicks: the North Sea,
the English Channel, and two sites in
the Mediterranean.
The image shown in figure1.69 below, taken
over the "Flemish Cap," an
area in the Atlantic Ocean south east of
the coast of Newfoundland Canada, shows
two natural slicks (A) and five
ships. Two of the ships can be
identified to the east of the slicks and
three are clustered to the south. Wakes
are clearly visible behind the three
ships at the bottom of the image. This
information can be used to determine
their speed and direction of travel.
|
Figure 1.69 RADARSAT image of 'Flemish Cap,' east coast of Canada (courtesy of CCRS) |
With larger incidence
angles, the ocean background clutter
effects are reduced, improving the
detection of ships, coastline and
ice edges. For example, a ship is a
bright point target against the ocean
background clutter and can be detected
using image thresholding techniques.
However, as the ocean clutter increases
with increasing wind speeds, ship
detection becomes more difficult. At
wind speeds greater than 10 m/s it is
difficult to detect small fishing
vessels. This relationship with wind
speed is a critical factor for ship
detection as well as oil spill mapping
and feature detection. As the wind
speeds increase, the radar cross-section
of the ocean increases, reducing the
contract between the feature of interest
and the surrounding ocean.
Ship detection is a good example of the
operational role of radar. A wide range
of ship sizes may be detected under a
variety of sea-state conditions.
Radar can infer ship size, and if a wake
is present, its speed and direction of
travel. It should be noted that an HH
polarisation is less sensitive to wake
detection and, in studies to date, wakes
are infrequently detected. Potential
users of this information include
agencies who monitor ship traffic,
authorities responsible for sovereignty
and fisheries surveillance, as well as
customs and excise agencies charged with
stopping illegal smuggling activities.
(See figure1.70 )
|
Figure 1.70 Ship Wake. ESA image courtesy of the Alaska SAR Facility (copyright ESA) |
Large incidence angles are
optimum for ship target detection.
Detection depends on ship size and type,
heading with respect to look angles,
and sea state conditions at the time of imaging.
1.1.6.3 Land Applications
|
Figure 1.71 Multi-temporal, artificially coloured image ERS-1 SAR image, Germany-Darmstadt and Odenwald, Nov.11, 1991 (Copyright ESA 1991) |
Although the terms land cover and land
use are often used interchangeably, their actual
meanings are quite distinct. Land cover refers
to the surface cover on the ground, whether
vegetation, urban infrastructure, water, bare
soil or other. Identifying, delineating and
mapping land cover is important for global
monitoring studies, resource management, and
planning activities. Identification of land
cover establishes the baseline from which
monitoring activities (change detection) can be
performed, and provides the ground cover
information for baseline thematic maps.
Land use refers to the purpose the land
serves, for example, recreation, wildlife
habitat, or agriculture. Land use
applications involve both baseline
mapping and subsequent monitoring, since
timely information is required to know what
current quantity of land is in what type
of use and to identify the land use changes
from year to year. This knowledge will help
develop strategies to balance conservation,
conflicting uses, and developmental
pressures. Issues driving land use studies
include the removal or disturbance of
productive land, urban encroachment, and
depletion of forests.
It is important to distinguish this
difference between land cover and land use,
and the information that can be ascertained
from each. The properties measured with
remote sensing techniques relate to land
cover, from which land use can be inferred,
particularly with ancillary data or a
priori knowledge.
Resource managers involved in parks, oil,
timber, and mining companies, are concerned
with both land use and land cover, as are
local resource inventory or natural
resource agencies. Changes in land cover
will be examined by environmental monitoring
researchers, conservation authorities,
and departments of municipal affairs, with
interests varying from tax assessment to
reconnaissance vegetation mapping.
Governments are also concerned with the
general protection of national resources,
and become involved in publicly sensitive
activities involving land use conflicts.
C-band
Synthetic Aperture
Radar (SAR) satellites sensors, such
as ERS-1, ERS-2 and ASAR, allow the
agricultural industry to acquire imagery
anytime, using microwave energy 1.1.2.1. to
penetrate darkness, clouds, rain or haze (
See "Scientific
Background" 1.1.2. ). As such, they have
become an invaluable source of
information in mapping the aftermath of
natural disasters like hail storms, floods
and hurricanes.
As a result of observing the land surface
with the ERS
Synthetic Aperture Radar
(SAR) sensors a large number of land
applications has emerged, several based
on important developments which have been
made in the field of SAR
Interferometry 1.1.5.4. . SAR data are being used
for agricultural monitoring, forest mapping,
geological exploration and flood mapping,
while SAR Interferometry measurements of
topography and small
topographic changes are making major
contributions to environmental risk
assessment from earthquakes and land subsidence. The Advanced
Synthetic Aperture Radar (ASAR) sensor will
be used for numerous land-based applications
which include:
-
Global Vegetation Monitoring
-
Forestry
-
Geology and Topography
-
Agriculture
-
Natural Hazards
-
Flooding, Hydrology and
Water Management
-
Urban Studies
1.1.6.3.1 Global Vegetation Monitoring
Land cover is defined as the observed
physical cover, including vegetation and
human constructions, of the Earth's surface.
For many ecological studies, there is a
need for current information on the
distribution and amount of vegetation.
This need has not been fully
addressed by a quarter century of
spaceborne remote sensing systems
operating in the visible and
near-infrared region of the electromagnetic
spectrum 1.1.2.1. . Collection of
visible/near-infrared imagery over
ecologically important regions on a
continuous basis is often limited by
cloud cover, particularly in tropical
and boreal biomes. However, radar
data can be acquired at any time since
imagery acquisition is not hindered by
atmospheric conditions or darkness ( See
"Scientific Background" 1.1.2. ).
Radar data can be used in applications
supporting land cover delineation, base
mapping and updating, and environmental
monitoring. In these applications,
radar data is used as a tool for
distinguishing differences in surface roughness, moisture
content, and geometric shape associated
with different land uses and covers,
which in turn allows the delineation
and identification of land cover types
and related land use and cultural
features. By using the backscatter models 1.1.2.4.1.
of crop types, area, height and
condition changes, through the
application of multitemporal
imagery, changes in land use and
land cover over time can be assessed.
The image shown in figure1.72 below provides
an example of 25 km resolution
global backscatter data from the ERS Scatterometer,
which contains information on
vegetation type, standing biomass and
active vegetation. In comparison, the
Advanced Synthetic Aperture Radar (ASAR)
Global Monitoring Mode
(GM) will provide the much improved
spatial resolution 1.1.2.2.1.
of 1 km, similar to that of AVHRR.
|
Figure 1.72 Global backscatter data collected by the ERS Scatterometer in August 1993, showing major vegetation types and morphological units (i.e. tropical rain forest, savannah, deserts, mountain ranges, tundra). Acknowledgement: E. Mougin, P. Frison, CESR, Toulouse; Y. Kerr, LERTS/CESBIO, Toulouse, France. |
One of the the main aims of global
vegetation mapping is to characterise
the function of biomes within the
climate change models, and to
quantify the extent to which changes in
global vegetation distribution may
affect the climate. Climate data are the
main inputs for these models. When
radar data are acquired for the
quantitative study of land use and land
cover, it is important that data are
calibrated, since this allows image
brightness values to
be more directly related to target backscatter. When
radar data are acquired over a number of
time periods, for the purposes of
monitoring change for land use and land
cover applications, it is again
important that data are calibrated.
Image calibration for change
detection ensures that any change in the
image are a result of a change in the
target and not from a change in the
sensor. ASAR products will be
used, along with other remote sensing
data, for initialising,
parameterising, and calibrating models,
on a global and regional scale, and for
the monitoring of changes in vegetation
type and status. ASAR data and
products developed from the Global Monitoring
(GM) and Wide Swath Modes
(WS) are of particular interest.
1.1.6.3.2 Forestry
Accurate and consistent mapping is
essential for the successful management
of forests. Global forests provide
invaluable benefits and resources,
both of an ecological and economic
nature, to the world's population.
Not only to the forests provide a supply
of fuel and building material, but
they also retain soil, regulate run-off,
minimise the siltation of water, and
provide fruits, nuts, tree extracts
and medicinal plants. As the large
proportion of the Earth's surface
is occupied by forests, which are
continually changing, a management
tool is required that is capable both of
covering large areas of the Earth's
surface, as well as revisiting those
areas with some frequency.
The ability of spaceborne radar sensors
to image the globe in a short period of
time, unimpaired by such atmospheric
effects as light rain and cloud, is
well known.( See section entitled "Scientific
Background" 1.1.2. ). As with other
applications, this ability is
well-suited to forestry applications, as
a large proportion of the world's
forests are found in tropical areas
where there is cloud cover for much of
the year or at high latitudes where
there are long periods of darkness
during the winter months. By using multi-temporal
analysis and interferometric
techniques, ERS data are beginning
to be used in operational mapping programmes.
The image shown in figure1.73 below gives an
indication of the deforestation that
is occurring in the Brazil.
|
Figure 1.73 Brazil Deforestation. This artificially coloured ERS-1 SAR image, covering an area 75 km x 75 km, shows the Teles Pires river in Brazil (Mato Grosso State). A regular pattern of deforestation is clearly seen in the rectangular patches of destroyed forest extending over areas as large as 20 kilometres ( copyright ESA 1992 ) |
Radar is particularly effective for the
delineation of burned areas because of
its sensitivity to differences in
structure and moisture content. (
See "Scientific
Background" 1.1.2. ). Several months
after a forest fire, burnt forest
areas dry out and leaves and small twigs
drop from the trees which results in a
contrast in structure and moisture
content between burnt and unaffected
areas. On radar imagery, this produces a
contrast in backscatter, where the burnt
areas appear darker than the
unaffected forested areas.
The ability of C-band radar to
discriminate between some forest types
has been shown in a range of forest
environments. In areas of mixed
deciduous and coniferous forests,
separation of general forest type is
accomplished through the use of multitemporal data;
the leaf-on and leaf-off conditions
of deciduous species results in a
seasonal change in backscatter which
contrasts with that of the coniferous
species which do not experience
leaf-off. It is important to note
that in order to acquire useful
information on general forest type,
using radar satellites, stands will have
to be large and of uniform
composition. Species differentiation is
more difficult in general at microwave
frequencies 1.1.2.1. then with optical data
because of overlap in signatures between species.
The higher incidence angles 1.1.5.2.
and dual polarisation 1.1.5.1.
data from ASAR will improve the
potential for forestry applications. Use
of low incidence angles enhances the
sensitivity to biomass, whereas the
use of high incidence angles improves
mapping of deforestation. Dual
polarisation will improve discrimination
of forest types.
The graphs in figure1.74 below show how
backscatter 1.1.2.1.2. varies
with VV, HH and HV
polarisations across a range of incidence angles,
for Sitka Spruce and Upland Pasture, and
how these measurements have been used in
a decomposition model to determine the
relative contribution of surface,
double-bounce and volume scattering
mechanisms.( See "Scattering
Mechanisms"1.7 in the section
entitled "Scientific
Background" 1.1.2. ).
In the two upper graphs shown below
polarisation and incidence angle effects
on backscattering are shown, and in the
bottom two graphs relative
contributions of surface, double-bounce
and volume scattering are shown.
|
Figure 1.74 Backscatter of Sitka Spruce and Upland Pasture at Llyn Brianne, Wales. (Acknowledgement: Luckman and Baker, 1995). |
The multipolarisation, multi-swath modes
of ASAR ( see section
entitled "Principles of
Measurement" 1.1.3. ) offer a greatly
enhanced capability for forest
assessment over any previous spaceborne
SAR mission. New research being proposed
brings together expertise in SAR data,
software, ecology, and forestry, as
well as a long history of ground data.
The application of ASAR to the
quantitative assessment of forest
characteristics such as yield,
species, and phenology will be
demonstrated for tropical, boreal and
temperate forests.
1.1.6.3.3 Geology and Topography
Traditionally geological information for
mapping at local and regional scales has
been acquired through field work by
qualified geoscientists. Optical
remote sensing from air- and spaceborne
platforms provide a synopic view of the
terrain which allows geological
information to be collected over a
larger region. Geological information
from optical sensors are however,
hindered by cloud cover,
identification of features restricted by
illumination conditions, and the
delineation of geological structure
dependent on the angle and elevation
of the sun. Radar remote sensing has
proven to be an effective tool for the
extraction of geological information,
unhindered by external illumination
and weather conditions. ( See "Scientific Background" 1.1.2. ).
The side-looking
configuration of spaceborne Synthetic Aperture
Radar (SARs) 1.1.2.3. highlights relief,
which assists in topographic mapping
for terrain analysis.
When relief information provided by
radar is combined with optical data, an
image is created that provides valuable
terrain information. The use of
shallow incidence angles
produces a shading effect or shadowing which can
emphasise even subtle slopes in the
landscape. These are often
attributable to underlying geological
units and structures.
The image in figure1.75 below, shows
excellent imaging of faults and
contrasts, using enhanced ERS-1 (SAR)
imagery.
|
Figure 1.75 ERS-1 SAR enhanced and enlarged image of Penzhinskaya Guba, North Kamchatka, Russia. ( Image created by Dr. William Harbert of the Geophysics Department, University of Pittsburgh ) |
Geological mapping with SAR data has
become well established and a number of
organisations offer a commercial service
for mapping structure, but the
effect of layover in hilly
terrain prevents widespread use of the
data. ASAR Image Mode (IM)
products, with high incidence angles
will be of particular interest to reduce
terrain distortions. The Alternating
Polarisation Mode (AP) products
may be of value for texture analysis in
arid areas. Wide Swath Mode
(WS) products will be useful for
looking at regional and continental
geological structures.
Other remotely sensed data can be
integrated with SAR data to provide
additional information for an imaged
area, thus creating an enhanced
image map for interpretation. Another
valuable combination is with the varied
data sets generated by modern
geophysical surveying, which is
widespread in mineral exploration.
Combined with radar imagery, it provides
a means of correlating, or at least
locating, inferred subsurface
mineral horizons, structural features,
or lithologies with respect to surface relief.
In the creation of the image shown in figure1.76 below,
topographic phase recovery from
stacked ERS SAR interferometry 1.1.5.4.
and a low resolution Digital Elevation
Model (DEM) were used.
|
Figure 1.76 Interferogram created by using 25 ERS SAR images from an area of Southern California containing 2700 m of relief; compared with the topography measured by the Shuttle Radar Topography Mission. Fringes from two major earthquakes and a seismic slip on the San Andreas Fault are clearly isolated. ( Image created by David T. Sandwell and Lydie Sichoix at the Institute of Geophysics and Planetary Physics, Scripps Institution of Oceanography, La Jolla, CA |
Radar has also proven to be a promising
tool for mineral and hydrocarbon
exploration. Certain types of
mineralization and hydrocarbon
resources are often associated with
specific geological structures thus, the
mapping of these
structures when topographically
expressed can assist in the
identification of areas of high mineral
and hydrocarbon potential. Often
radar data are merged with geophysical
data. The radar data allows the delineation of
topographically expressed structures,
while the geophysical data aids in
the identification of strong magnetic
signature. Resulting composites show the
correlation between geological structure
and magnetic anomalies which aid in
the planning of detailed ground surveys.
1.1.6.3.4 Agriculture
The use of Earth-observation satellite
data can provide agriculture and its
related industries, such as food and
insurance, with cost-effective
methods for wide-scale and localised
monitoring of crop output and condition
factors. Optical and radar satellite
imagery can be used as a tool for
recording important information that is
needed before and during the growing
season. The information derived from
this imagery can be of particular
importance to individuals and
organisations in the agriculture
industry including farmers, agricultural
co-operatives, agribusiness and food companies.
Earth-observation data can provide:
- Soil moisture detection and monitoring
- Crop studies and acreage determination
- Hail, flood, and hurricane damage mapping
The ERS programme has demonstrated the
ability of satellite radars,
independently of weather conditions, to
identify crops, detect soil moisture
and monitor seasonal land cover changes.
Multi-temporal
techniques are used, which involve the
collection and analysis of SAR data on a
series of different dates over the
period of interest. Interferometric
coherence has also been used to
improve land cover discrimination.
Soil Moisture and Detection:
Soil moisture variability is an important
factor in many agricultural business
processes. It is a valuable input into
crop yield prediction models and
helps in the determination of plant
stress zones for the management of
agricultural inputs. Radar imagery can
be used to create moisture maps and
for irrigation management, as well as to
monitor the effectiveness of central
pivot irrigation systems. A further
use in this area involves developing
moisture level base maps for monitoring
regions of high flood probability.
The ASAR
Wide Swath (WS) and Global Monitoring (GM)
Modes will be of most interest to soil
moisture and large area vegetation
mapping.
Crop studies and acreage determination
Satellite imagery is a valuable tool in
determining varying levels of crop
vigour within fields or agricultural
management zones. Plant stress can
be monitored and growth inputs applied
in a more timely and efficient manner
when the different areas of stress are
available in a single image to the
farm manager. Satellite imagery can
therefore increase the efficiency of
crop scouting practices by more
precisely targeting areas that need
to be examined or tested. Imagery can be
used to produce vigour maps that can be
linked to geospatial information and
allow the farmer to determine the
relative health of all planted areas at
one time.
An increasing aspect of precision farming
is the management of agricultural zones
within fields. Soil type, crop vigour,
and irrigation levels, as revealed
by Earth-observation data, can be
delivered to the customer and input into
field management GIS to aid in the
efficient application of fertiliser and
other agricultural input chemicals.
ERS data are now being
used operationally within major European
programmes concerned with
agricultural statistics (MARS STAT) and
the control of agricultural subsidies
(MARS PAC). Within MARS STAT the use of
ERS data has improved the estimates
of crop area early in the crop growing
season. ERS data are used as a
substitute for optical data in the
MARS PAC control activity when cloudy
conditions are encountered at key times
during the crop growing season.
Figure1.77 below shows the
use of multi-temporal ERS
data for mapping the areas using
different rice cropping systems in
the Mekong Delta of Vietnam.
|
Figure 1.77 Map of different rice cropping systems in the Mekong Delta, derived from classification of seven ERS SAR images acquired over the period May to December 1996. (Acknowledgement: Balababa et al. 1997). |
ASAR Image Mode (IM)
offers continuity for agricultural
applications, enhanced by the
ability of variable incidence angles.
The Alternating
Polarisation Mode (AP) will
greatly improve crop classification.
1.1.6.3.5 Natural Hazards
A number of areas of study relating to
natural hazards will utilise ASAR data. These include:
Volcanic Activity:
The Afar triangle, located in the
Republic of Djibouti of East Africa and
shown in the image below, is the only
place on Earth where the mid-ocean
ridge is visible as a rift in an arid
desert. It is thus a uniquely privileged
site for long-term study by radar interferometry.
|
Figure 1.78 ERS-2 Image of the Afar Triangle in East Africa |
The area shown above has experienced
damage in this century by volcanic
eruptions and large earthquakes. To
evaluate the risk of such events in
the future, it is essential to
understand the geophysical signatures
recorded in the topographic relief and
the deformation field. The ASAR instrument can
measure both of these signals with SAR
interferometry 1.1.5.4. . The imaging geometry,
surface conditions, and climate are
optimal for SAR interferometry.
Earthquakes:
To study seismically active fault
systems, it is important to measure both
the long-term rate of deformation
averaged over several seismic cycles
and the short-term deformation
associated with the seismic activity
along individual faults. The first type
of measurement requires accurate
topographic maps to quantify the
cumulative displacement of Quaternary
surfaces and geomorphic structures, such
as alluvial fans or glacial
moraines. The second type of
measurements requires the capacity of
estimating subtle displacements of the
ground at the millimetre level of
precision over short time intervals.
With the advent of spaceborne radar
systems, such as ERS-1, ERS-2, and
now ASAR, the
technique of SAR interferometry 1.1.5.4.
is becoming a new tool for active
tectonics by providing both
mm-precision surface change maps
spanning periods of days to years and
m-precision, high resolution topographic
maps for measuring crustal strain
accumulated over longer periods of time.
A strong earthquake shook northwestern
Turkey, levelling buildings, and cutting
power and phone lines. The quake had a
magnitude of 7.8, making it nearly
as powerful as the 7.9-magnitude San
Francisco quake, which killed 700 people
in 1906. The digital elevation
model (DEM) of this area, shown
below, was produced by interferometric
analysis of synthetic aperture
radar (SAR) data from the ESA ERS-1 and ERS-2
satellites . Pairs of SAR images from
tandem acquisitions, with temporal
separation of one day, were processed
separately to produce a height map
in ground range coordinates. Then the
height maps were projected into UTM coordinates.
Final elevations in the DEM are the
average of the overlapping SAR
interferometric height maps.
|
Figure 1.79 Izmit Earthquake digital Elevatio Model from ERS SAR Interferometry ERS data ESA (1995,1996,1999),DEM Eric Fielding, Oxford (1999) Shaded relief image of interferometric DEM from three descending and one ascending ERS SAR Tandem pairs, with GTOPO30 filling in gaps. |
In the ERS-1 SAR
interferometric map below, created at
the Jet Propulsion Laboratories
(JPL), the post seismic surface
movements following the Landers 1992
earthquake are clearly evident
Ref. [1.29 ]
.
|
Figure 1.80 ERS-1 Interferometric map, Landers 1992 earthquake. Images used were from Sep. 27, 1992 to Jan 23, 1996. Map created by JPL. |
The Interferometric
SAR data revealed several
centimetres of post-seismic rebound
in step-overs of the 1992 break with a
characteristic decay time of 0.7 years.
Such a rebound can be explained by
shallow crustal fluid flow associated
with the dissipation of pore pressure
gradients caused by co-seismic stress changes.
In figure1.81 below, SAR
images spanning three different time
intervals in the three years following
the earthquake were combined. In the
left panel the interferogram covers 41
days after the event, starting on 7
August 1992. The most striking features
are the localised strain along three
sections of the 1992 surface rupture
where the rupture changed direction or
jumped to another fault branch and
formed two pull-apart structures and a
compressive jog (boxes in left panel).
The observed displacement in the fault
step-overs is consistent with
surface uplift in the pull-apart
structures and subsidence in the
compressive jog, i.e., opposed to the
direction of the co-seismic
movements, which is shown in the panel
on the right.
|
Figure 1.81 ERS-1 3 pass interferogram of Landers earthquake (JPL 1996) |
Land Subsidence:
Subsidence is the sinking of the
Earth's surface in response to
geological or man-induced causes. This
surface displacement is shown by the
image below, created from ERS-1 SAR data by the
Jet Propulsion Laboratory (JPL). In
this image, which shows the location of
existing and future Global Positioning
System (GPS) stations of the Southern
California Integrated GPS Network
(SCIGN), the colours of the radar image
represent the change in range due to
surface displacement toward the
satellite antenna, which is illuminating
the area from the east with an incidence
angle of 23 deg.off the vertical.
The black lines are mapped as active
faults. One full colour cycle represents
5.6 cm of range change between the
dates of acquisition of the radar data
(20 October, 1993 - 22 December, 1995).
Grey areas within the radar swath are zones where
the radar correlation is lost due to
steep slopes and seasonal change of
the vegetation.
|
Figure 1.82 ERS-1 SAR 3-pass interferogram showing subsidence in Panoma California. Image created by JPL |
Although surface displacement in this
region is primarily due to the tectonic
activity, as shown in the above image by
the concentric rings visible along
the western edge of the SAR swath, other
features visible on the image are
related to human activity such as water
and oil withdrawal. Regions of
ground subsidence include the Pomona (P)
area (water), the Beverly Hills (BH) oil
field (oil) and localised spots in
the San Pedro and Long Beach airport
(LBA) area (probably oil industry
activity). Noticeable surface uplift is
observed in the Santa Fe Springs oil
field (SFS) and east of Santa Ana (SA).
Surface uplift in these areas may result
from the recharge of aquifers or oil
fields with water, or from the
poro-elastic response of the ground
subsequent to water or oil withdrawal.
The relationship between the sinking of
the earth's surface and how this is
displayed by the SAR interferogram 1.1.5.4.
is depicted in figure1.83 below.
|
Figure 1.83 Relationship between ERS-1 SAR Interferogram and Panoma Subsidence. Image generated by JPL |
In the interferogram, the colours depict
the displacement of the ground along the
radar line of sight (23 degree off
vertical) having occurred between
October 20, 1993 and December 22, 1995.
The shaded view in the centre is the
radar phase field displayed with 20,000
vertical exaggeration. The top view
gives a street map wrapped on the phase field.
1.1.6.3.6 Flooding, Hydrology and Water Management
Floods are among the most frequent of all
natural hazards. They are extreme events
that are usually sudden and short-lived,
and can cause considerable
economic loss due to damage to
buildings, destruction of infrastructure
as well as the loss of human
lives. One of the biggest problems
during such an emergency is to obtain an
overall view of the phenomenon, with a
clear idea of the extent of
the flooded area, and to predict the
likely developments.
|
Figure 1.84 Extensive flooding near Oxford, UK. (Courtesy Institute of Hydrology, UK) |
ERS SAR products, such as
those created by ERS-1 and ERS-2,
as well as ASAR, can be used in
the event of flooding to permit
immediate assessments of the areas at
risk and aid decision-making on relief
and cleanup operations. Products derived
from archived SAR data may provide
accurate spatial information on the
extent of previous flood events. This is
being used for management planning
for preventative measures in areas where
flooding occurs regularly. ERS SAR data
can serve as up-to-date information in
the absence of conventional optical
satellite or other data. This is often
the case in bad weather conditions which
accompany flooding events.
The low resolution ERS SAR images shown
below, which were obtained from the
Rapid Information Dissemination System
(RAIDS) of the UK, gives an
indication of how SAR imagery can be
used to monitor a floods progression.
|
Figure 1.85 Reduces Resolution images ( 100 km x 100 km. pixel size 400m ) of the River Maas in the Netherlands shown before (left) and during (right) flooding (Imagery 1994-95 ESA) |
The image below gives an example of the
hybrid change detection procedure used
to detect human induced land cover
changes in Southwest Florida
Ref. [1.35 ]
. The work carried out at
the Environmental Research Institute of
Michigan, Duke University, was to
advance techniques for monitoring and
predicting changes in the hydrologic
condition of regional scale wetland
ecosystems in the south Florida region.
The objectives were to integrate
satellite remote sensing data with
hydrologic models and field data to
improve capabilities for monitoring and
understanding processes controlling
surface water flow in Florida wetlands.
It was found that the herbaceous
wetlands in their study area exhibited a
wide range of conditions, from dry to
saturated soils to flooded, which
are readily detected by the C-Band ERS-2 SAR sensor.
|
Figure 1.86 Vegetation and hydropattern dynamics of Big Cypress National Preserve PCA - Unsupervised classification of 1997 - 1998 ERS-2 SAR imagery. ( Image courtesy of Environmental Research Institute of Michigan, Duke University) |
ASAR will add a new wealth of data for
such research around the world.
1.1.6.3.7 Urban Studies
The interrelated issues of urban sprawl,
traffic congestion, noise, and air
pollution are major socio-economic
problems faced by most major cities.
Though it is desirable to know about the
storage of heat in a particular city and
how that amount of heat changes from day
to night and from one day to the
next, the information is difficult to
obtain because of the complex
three-dimensional structure of the urban
surface and the variety of materials
involved. Structures, pavements,
vegetation and the ground itself must
all be taken into account. Large
bodies of water nearby are a further complication.
|
Figure 1.87 Mean image computed from five ERS SAR images, of the city of Nantes. The island is the island of Beaulieu. The Loire river appears in grey, crossed by several bridges in bright. In dark are the major roads, and the airport in the lower left corner. (copyright ESA 1994) |
In the above image the
importance of the relative direction of
the target with respect to the radial
direction of the radar wave clearly
impacts the results. If the relative
direction is perpendicular to the radial
direction, then this object is clearly
visible, even if it is flat such as
a road or a railway track within a flat
area. If the object is orientated in the
same direction than the radar wave,
then it is not visible. This is the case
for the central station of Nantes and of
the large railway complex in the western
part of the Beaulieu island. However
if the same object is surrounded by e.
g. buildings reflecting the radar
signal, it will be perceived because
of the created contrast.
The direct analysis of the
ASAR measurements,
with many different polarisations and
viewing angles, allows the recognition
of different urban environments. The
interferometric analysis of the same
data, acquired in more than one passage,
can be used for the 3D characterisation
of a zone.
1.1.6.3.8 References
Peltzer, Gilles, "Crustal
Deformation Studies Using SAR
Interferometry", Jet Propulsion
Labratories at the California Institute
of Technology and the Earth and Space
Science Division of the University of
California Los Angeles.
ASAR Science Advisory Group, Editor
R.A.Harris, European Space Agency 1998,
"ASAR Science and
Applications", ESA SP-1225
Sandwell, David T., and Sichoix, L.,
"Topographic Phase Recovery From
Stacked ERS Interferometry and a Low
Resolution Digital Elevation
Model", Institute of Geophysics and
Planetary Physics, Scripps Institution
of Oceanography, La Jolla, CA.
Submitted to Journal of Geophysical
Research, March 1, 2000
Harbert, Dr. W., "Geological
Interpretation of North Kamchatka,
Russia: Constrains from Synthetic
Aperture Radar, Digital Elevation Models
and Digital Residual Magnetics",
Geophysics Department, University of
Pittsburgh. Abstract published in
Earth Observation Magazine, September
1992, pp. 45-47.
Paillou, P.,"Arid Sub-Surface
Imaging using Radar Techniques",
Observatoire Astronomique de
Bordeaux, BP 89, 33270 Floirac, France,
web: http://www.observ.u-bordeaux.fr/~paillou/paillou.html
Wright, T., Fielding, E., Parsons, B.,
"The 17 August 1999, Izmit
Earthquake Displacements and
Topography from SAR Interferometry"
, www.earth.ox.ac.uk/~geodesy/izmit.html.
Kasischke,E.S., et. al, "Monitoring
Regional-Scale Hydrologic Processes in
the South Florida Ecosystem",
Environmental Research Institute of
Michigan, Duke University, US., January
31, 2000.
1.1.6.4 Sea Ice Applications
There is a wide range of sea ice data
applications in the marine community and
across a number of industrial sectors.
Industries and agencies operating in
ice-infested waters include commercial
shippers, offshore oil exploration
companies, fisheries, military, regulatory
agencies, and research institutions. Other
industrial sectors use ice information when
designing ship hulls and offshore drilling
platforms, to perform risk assessment, and
to establish insurance premiums.
The sea ice markets include agencies in the
USA, Canada, Japan, Russia, Norway, and the
Baltic countries. SAR data are combined with
other sources of data to optimise sea ice
forecasts, and are also transmitted directly
to ice breakers and ships operating near the
ice edge.
Ice information is required at continental or
global scales. As described by Manore et al.
(1991), the requirement for these scales
comes largely from the global ice studies
community, which has interests in:
- monitoring global sea ice extent as an
indicator of climatic change
- providing better parameterizations of
sea ice in ocean-ice-atmosphere global
circulation models
- better understanding of the processes of
heat and mass exchange between the
ocean, ice, and the atmosphere
Radar data can aid in areas of study such as
ice concentration determination, ice type
classification, ice feature identification,
ice motion monitoring, and iceberg
tracking. Information on total ice
concentration, location of the ice edge, ice
type and thickness, ice topography, the
presence and location of leads, ice
pressure, state of ice decay, and iceberg
and ice island location can be derived
directly from radar imagery.
Note that HH polarisation
differentiates between open water and ice
better than VV polarisation. Also note
that the appearance of a given ice feature
may differ significantly in wet versus dry
conditions. When surface meltwater is on
the ice or ocean spray is on the surface at
the ice edge, feature brightness may differ from
that encounter in dry conditions. When wet
surface conditions prevail, it is useful to
have a reference image acquired before the
onset of melt conditions.
|
Figure 1.88 RADARSAT SAR Image With Sea Ice Deformation (SAR image is Copyright CSA 1998. Grid produced by the Radarsat Geophysical Processor System) |
The above is a RADARSAT ScanSAR Wide B
geocoded image of sea ice in the Beaufort
Sea on January 11, 1998, that has been
block-averaged (10 x 10) to 1000 metre
pixel size.
|
Figure 1.89 RGPS Lagrangian Ice Motion Visualization( Using data produced by the Radarsat Geophysical Processor System ) |
The above image is an early
attempt to visualize the RGPS Ice Motion
product. RGPS is the Radarsat Geophysical
Processor System under development by
the Polar Remote Sensing Group at JPL. The
visualization is an ASF Science Division
project directed by Dr. Mitchell Roth,
UAF Professor of Computer Science, with
Richard Guse, CS graduate student. The data
is derived from arctic snapshot data of
an area in the Beaufort Sea acquired by ASF
in November of 1996. This datatake is cycle
15 based on 143 ScanSAR B images. Ice motion
is visualized using a colourwheel (shown
below.) The direction is given by colour
(1-1 correspondence with the colourwheel)
& the magnitude of its movement is
given as the saturation (white being slow
and full colour being fast, not necessarily 1-1).
|
Figure 1.90 Colour Wheel |
This visualization is a
'composite' of vectors in 3-space,
the z-coordinate (out of the screen)
represents the time the vector is
computed with more recent vectors on top.
Sea Ice Motion Derived from
Satellite Imagery
Sea ice motion data are utilized both in
fundamental scientific research and for
practical every-day purposes. Ice motion
data help scientists in many research
endeavors such as: analyzing the polar
regions' latent heat advection;
determining the local oceanic surface
stresses; passively tracing currents;
tracking new areas of open water (formed by
ice divergence and shear); and understanding
the effects of icebreaker vessels. In
addition to furthering this fundamental
research, the data are also used to help
forecast weather and ice conditions,
evaluate possible hazards, and contribute to
the overall understanding of environmental
impacts in the Arctic region.
Traditionally there have been many obstacles
in acquiring sea ice motion data. Sea ice is
by nature located in remote, inaccessible
regions, and the ice extends over a large
area. Though ice motion can be determined by
placing sensors directly onto ice floes, the
cost of installing and maintaining many
field instruments is prohibitively high. It
is similarly prohibitive for scientists to
stay in the field and monitor the sea
ice motion themselves! One can readily see
the benefits of studying sea ice remotely,
from satellites.
There are also complications with monitoring
sea ice from space, however. Cloudy skies
hide the sea ice from some sensors, and long
winter nights thwart the ability to image
polar regions with visible light. The
research community therefore turned to the
Synthetic Aperture Radar (SAR) as a
viable sea ice imager. Since a SAR emits its
own signals (similar to a camera's
flash), it works during the day or
night. The radar signals also penetrate
through cloud cover, a characteristic which
is especially valuable to oceanographers.
Scientists determined that a satellite-borne
SAR could routinely and reliably image large
regions of sea ice.
The SAR-carrying ERS-1 satellite, launched in
July 1991, provided many scientists the
chance to study sea ice with SAR. The
Geophysical Processor System (GPS), an
effort led by Ron Kwok of JPL, was designed
to facilitate this research. The GPS
generated sea ice motion, sea ice
classifications, and ocean wave spectra data
from ASF's collection of ERS-1 SAR
imagery. Scientists could then use the
derived geophysical information for
their various research projects.
|
Figure 1.91 Melville Island Canada Copyright 1992, European Space Agency |
This image above was derived from SAR
data obtained by the European Space
Agency's ERS-1 satellite on October 11,
1992. This scene shows a portion of Melville
Island, way up in northern Canada (108 W, 75 N),
and should be of particular interest to you
geologists. The image covers about 65 km by
55 km. North points approximately 33 degrees
counter-clockwise from the top of this scene,
and the spacecraft was descending
"down" the right side of the image, so
the scene's radar illumination is from the
right.
1.1.6.4.1 Sea Ice Applications - Ice Sheet Dynamics
Radar is sensitive to the
physical properties of sea ice
(salinity, microstructure, and surface
roughness) that vary with ice
concentration, type, age and thickness.
Elements that are employed to visually
discriminate ice types in SAR imagery
include the structural
characteristics of floes, such as the
shape and presence of ridges, fractures,
and melt ponds. The ability to
discriminate ice types is highly
dependent on the geographic region and
the season of imaging because different
ice types exist in different regions and
at different times of the year. The
most promising season is winter when the
snowpack is dry and cold. During the
drier months of winter the surface
texture is the primary key for
discrimination. In the warmer months,
when free water is present, the
differences between old and
first-year ice become more difficult to
discriminate, in particular when the
overlying snow pack is saturated and the
differences in backscatter are
significantly reduced. Classification
ambiguity can be reduced by
consulting the past history of ice
features in a particular region, ice
climatology, and current meteorological
conditions (Ramsay et al, 1993).
The identification of specific structural
features within the sea ice is also
important for navigation because they
pose hazards to vessels. The
identification of leads and floes is
used to optimise route selection, and
RADARSAT's sensitivity to surface
roughness and its fine spatial
resolution permit the detection of ice
ridges and their orientation.
The image shown in figure1.92 , available
through the Alaska SAR
Facility
Ref. [1.37 ]
, shows an example of grease ice.
|
Figure 1.92 Grease Ice(Copyright 1991, European Space Agency) |
The SAR data for this image was taken by
the European Space Agency's ERS-1
satellite on October 2, 1991. The centre
location of the complete image is
73.58 N, 166.60 E, north of Siberia in
the East Siberian Sea. North points
approximately 30 degrees counter
clockwise from the top of this scene.
In addition to the detection of ice
structures, knowledge of the state of
decay or growth of sea ice is important
to infer its strength. During
periods of decay when temperatures are
above freezing, the ice is relatively
weak and can be more easily traversed by
an ice-strengthened vessel. However,
during an extended period of ice growth
when temperatures fall below freezing,
the same ice could be impassable.
Ongoing monitoring of sea ice to
identify the onset of melt and freeze-up
may aid in route selection (Ramsay et
al, 1993).
Another factor that can impede the
progress of ice-strengthened vessels is
the continual movement of the sea ice in
response to wind and ocean currents,
and the pressure that is created within
the ice floes. Because these movements
are continual, monitoring must be an
ongoing activity, requiring frequent
and sequenced imaging.
Icebergs of all sizes, including those
less than 5 m in size (referred to as
bergy bits), are of interest to shipping
and offshore operators because of
the hazard they pose to ships and
structures such as oil platforms. Steep
incidence angles and the low-resolution
of reconnaissance-scale imagery,
pose problems in detecting icebergs in
pack ice and in open water. In open
water, the sea conditions and
orientation of larger icebergs with
respect to the SAR will determine
whether they can be detected. In pack
ice, the signature of an iceberg is
often lost in the backscatter from the
surrounding sea ice.
Areas of glaciology to which ASAR
contributes include: monitoring the ice
extent and the boundaries of ice sheets,
and mapping the motion of ice sheets
and glaciers. figure1.93 provides a
simple example of the use of ERS
data for mapping changes in the extent
of the Larsen Ice Shelf, Antarctica.
There are many similar examples. SAR
data is still being used on an
irregular basis when something
interesting happens, rather than as a
monitoring tool. Interferometry and
correlation measurements which show
movement of the ice sheets are very
important to this work. ASAR will
provide valuable continuity in the
supply of data started with ERS.
Mass balance and ice dynamics are the key
scientific questions, with the
parameters to be derived from ASAR including:
- Ice boundaries (every 2 weeks)
- Ice export due to calving (every 2 weeks)
- Extent of melt zones (2 weeks during
summer; Greenland and Antarctic Peninsula)
- Snow and ice faces (once a year)
- Ice motion by means of feature
tracking (once a year
- Surface morphology (flow lines,
rifts, crevasse zones etc.) (once a year).
Depending on the topography and the
requirements for spatial detail, the
ice sheets may be separated into the
boundary zone (including the
ice shelves) and the interior part.
Baseline operation for the boundary
zones is considered to be the Wide
Swath Mode for the measurement
of parameters (1), (2) and (3)
above. Baseline operation mode for
the interior could be the Global
Monitoring Mode, for the
measurement of parameters (3) and
(4). The preferred operation modes
for selected zones (ice streams) are
Image Modes at higher incidence
angles (IS3 to IS7), for measurement
of (5) and (6) above with
approximately annual repetition of observations.
|
Figure 1.93 Radar interferogram of a portion of the Rutford ice stream in Antarctica, based on two ERS-1 images taken six days apart. The fringe pattern (colour cycle) is essentially a map of ice flow velocity, with one fringe representing 28 mm of range change along the radar line of site.(From Goldstein et al, 1993) |
There are a number of key studies in
this field being proposed that will
utilise ASAR data to a great extent.
Some of these are briefly
discussed below.
One study, to be conducted by Dr.
Massimo Frezzotti at the ENEA
Environmental Department in Italy,
will focus on using ENVISAT ASAR
data to study the XXI century
iceberg calving of East Antarctic.
The objective is to study the
iceberg calving process, to perform
monitoring of ice front change, and
to evaluate a century behaviour of
iceberg calving. Comparisons are to
be made using new ASAR images
and previous data (aerial
photographs, satellite images),
taken several years apart (1947 -
65; 1972 - 73; 1988 - 93; 1996) to
estimate the XXI century of
ice front fluctuation and of iceberg
discharge. The study of the dynamics
of seaward extension of floating
glaciers will allow the
investigators to hypothesise the ice
ocean interaction.
Another area of research, to be
carried out by Dr. Eric Rignot at
the Jet Propulsion Laboratory in the
United States, will study two
related ice sheet dynamics and
evolution problems that are
addressable with ENVISAT data:
- The stability of the onset areas
of fast-moving glaciers in
Greenland and Antarctica using
SAR interferometry.
- The time evolution of surface
rifting, crevasse development
and meltwater production on
Antarctica's floating ice
shelves using dual
polarisation SAR data.
The two research topics are related
because fast moving glaciers are
strongly influenced by the presence
or absence of buttressing ice
shelves (Antarctica) or floating ice
tongues (north Greenland).
The first topic will attempt at
detecting mechanical instabilities
(surge) of large ice streams
draining polar ice sheets in
response to climate change
(e.g., enhanced melting at the
coast). The second topic will
provide new insights into the
physical mechanisms (rift
propagation, meltwater accumulation)
controlling tabular iceberg
production in the Antarctic.
At the British Antarctic Survey, Dr.
Christopher Doake and associates
propose to use ENVISAT data to
investigate two important
components of the Antarctic Ice Sheet:
- the ice streams draining the
West Antarctic Ice Sheet (WAIS)
- the climatically sensitive ice shelves
The ice streams that drain the WAIS
are the key controls on its size and
configuration. Dr. Doake will use
ASAR brightness data and
interferometry to investigate the
current dynamics of these ice
streams and use velocity fields to
calculate ice flux, searching for
changes that could indicate a state
of imbalance. The WAIS ice streams
will then be contrasted with an ice
station in East Antarctica,
that drains a similar area of ice
sheet but has a different dynamical
character. Dr. Doake's team has
recently shown that the ice
shelves along the Antarctic
Peninsula are sensitive indicators
and integrators of a regional
climate change. The ENVISAT data
will be used to monitor the
predicted changes and to determine
the flow regime of the ice shelves.
Yet another study being proposed
comes from director Kenneth Jezek at
the Byrd Polar Research centre in
the United States. This
project will concentrate on
compiling an ENVISAT SAR mosaic of
Antarctica. The acquisitions will be
coordinated with planned
acquisitions by the Canadian
RADARSAT. The intent is to answer
important questions about seasonal
processes such as calving, melting,
coastal polynya formation and
the consequences on glacier flow.
The possibility of complete,
simultaneous interferometric
coverage of Antarctica offers
the greatest scientific payoff and
could revolutionise our
understanding of how Antarctica
responds to changing global climate.
And Dr. Johnathan Bamber at the
Centre for Remote Sensing,
University of Bristol in the UK,
will use Interferometric ASAR data
to provide information on the
dynamics and temporal stability of
the flow of the ice sheets and
Arctic ice masses.
These are but a few of the areas of
ice dynamics research in which ASAR
data will be of major benefit.
Incidence angle is not a
critical factor in sea ice
monitoring. However, shallow
incidence angles are more effective
in highlighting surface topography,
separating the ice/water boundary,
and detecting icebergs.
References:
Report of a Workshop
Held in Boulder, Colorado: February
3 - 4, 1994, Timothy H. Dixon,
Editor , University of Miami,
Rosenstiel School of Marine and
Atmospheric Science. available at http://southport.jpl.nasa.gov/scienceapps/dixon/index.html
Alaska SAR Facility,
web site www.asf.alaska.edu
1.1.6.4.2 Sea Ice Applications - Snow Cover In many areas of the world,
the majority of freshwater available for
consumption and irrigation results from
snowpack runoff. Snow wetness,
snow-water equivalent and the aerial extent
of the snow cover are the most important
parameters in predicting total runoff.
Mapping the extent of wet snow is
possible using SAR data (Rott et al, 1988)
as wet snow produces a low radar return in
contrast to dry snow which is
essentially transparent at C-band.
The ice sheets of Antarctica and
Greenland are the principal stores of
fresh water in the Earth's
hydrological system and changes in
their mass balance affect the mean sea
level. Changes in the height of ice
sheets can indicate changes in the mass
balance. Snow cover, snow
accumulation, and ice type information
are also required for monitoring,
detection of change and process studies
at high latitudes and high altitudes.
The presence of snow on the ground has a
significant influence on the radiative
balance of the Earth's surface and
on the heat exchange between the
surface and atmosphere. ERS has
demonstrated the value of SAR data for
mapping snow cover, and the Global
Monitoring Mode is of special
interest for monitoring the areal extent
of snow and the temporal dynamics during
the melt period, on a weekly basis for
climate research purposes.
Snow mapping is also important for
hydrology and water management. Snow
cover extent data are required every 2
weeks during the melting season, and
the baseline operation in mountainous
areas should be Image Mode at high
incidence angles (IS4 to IS7).
Scientists Craig Lingle,
Carl Benson, and Kristina Ahlnaes, of
the Geophysical Institute, use Synthetic
Aperture Radar (SAR) imagery to
monitor glaciers. At the fall 1996
meeting of the American Geophysical
Union (AGU), these researchers presented
a poster which detailed how glacier
facies (zones) can be examined through
satellite SAR imagery. They focused
their attention on the Nabesna
Glacier, which flows down the slopes of
Mt. Wrangell in south-central Alaska.
|
Figure 1.94 Glacier facies on Mt. Wrangell, Alaska, examined with SAR imagery. image size was greatly reduced for display here) ( Copyright ERS) |
The image above is a
multi-temporal image of Mt. Wrangell and
Nabesna Glacier derived from midsummer,
late-summer, and winter ERS-1 SAR data.
Mt. Wrangell is located at left-centre, with
Nabesna Glacier flowing to the east (right)
before turning north (up). The
glacier's wet snow facies (zone) is
outlined by the blue region. The pink areas
mark the upper extent of summer snow melt.
The SAR imagery (shown in figure1.94 ) is
particularly effective at
distinguishing between a glacier's
characteristic zones. Near its terminus
the glacier is covered by rocks which
scatter the transmitted radar
signals back to the SAR sensor.
Consequently, the glacier's
terminus appears rather bright in the
SAR imagery. Above the terminus lies
the ablation area. The relatively smooth
ice in this region is specular; it
"forward scatters" a
significant portion of the radar
signals away from the spacecraft. The
ablation area is therefore assigned a
medium to dark grey image intensity. The
light streaks seen in the ablation area
correspond to medial moraines: lines of
rock debris on the glacier's
surface which strongly backscatter radar.
The radar response from the next zone,
termed the "wet snow facies,"
changes dramatically with the seasons.
In summer this snow is wet and
dense. Small pools of water may form on
the glacier's surface. These
surface characteristics imply that
nearly all of the radar signals are
forward scattered away from the
spacecraft. As a result, this zone looks
very dark in the summer SAR imagery (See
figure1.95 .)
|
Figure 1.95 ERS-1 SAR image for June 23, 1993 The wet snow facies (zone) is dramatically outlined as the dark region between the lower ablation area and the bright percolation facies. |
In early autumn, however,
it's a different story. The wet
snow freezes into coarse crystals which
cause strong backscatter. To the SAR
sensor, the wet snow zone then appears
much brighter. Higher still, the
"dry snow facies" lies on and
near Mt. Wrangell's summit, where
the weather is cold and dry. The radar
signals pass right through the
summit's homogenous, dry snow
and are almost entirely absorbed. Since
few signals are backscattered from this
region, Mt. Wrangell's crater
appears dark, as seen in the
December SAR image. Due to the stable
snow characteristics atop Mt. Wrangell,
this area has a consistent radar
signature year-round. (See figure1.96 .)
|
Figure 1.96 ERS-1 SAR image for September 29, 1993 |
In the above image, water in the
wet snow facies is re-freezing, resulting in
similar radar responses from that zone and
the neighbouring ablation area. The
upper boundary of melted snow (the dark
region below Mt. Wrangell's base)
stands out in this early autumn image.
The dramatic differences between
the dark wet snow facies and the bright
percolation facies during summer, and
between the bright wet snow facies and
the relatively dark ablation area in winter,
allow researchers to map the extent of a
glacier's facies. This information is
very important because it is closely related
to mass balance: the amount of new snow
accumulated versus the amount of meltwater
lost. Shifts in facies' boundaries
are also indications of climate change;
glaciers react significantly to small
variations in climate.
|
Figure 1.97 ERS-1 SAR image for December 30, 1992 |
Mt. Wrangell's crater
(left-centre) contains the dry snow
facies, where radar signals are
primarily absorbed. The arrow
marks the late-summer snow line;
above this boundary, snow remains on
the glacier's surface
throughout the year.
A project was undertaken at
the Alaska SAR Facility, by visiting
scientist Kim Partington, to try and
determine if both the ablation/wet
snow and wet snow/percolation boundaries
could be seen in a single image, if that
image was the result of combining
imagery from various seasons into
one year.
A blue colour scheme was
applied to the December image, red to
the June image, and green to the
September image. The three colour
images were then merged. If the red,
green, and blue values were all of
similar strength, the result was simply
a shade of grey. This would imply no
change in radar response between the
seasons. The percolation facies on
Wrangell's upper volcanic cone is
white; this zone backscatters
brightly year-round. The darker radar
signature from the dry snow facies
within the crater is similarly stable
throughout the year. Blue patches
indicate that the corresponding regions
backscattered the radar most brightly in
winter. The wet snow zone, which has
low radar response in the summer but
backscatters strongly in the winter, is
therefore coloured blue. The pink
regions were least bright in late
summer and hence mark the upper extent
of snow melt. The green area surrounding
Mt. Wrangell's summit, implying
brightest radar backscatter in
September, is believed to be caused by
the development of hoar frost at that
time of year.
|
Figure 1.98 Multi-temporal image which combines the June, September, and December SAR images into one product. Nabesna Glacier's wet snow facies is represented by the blue region. The upper boundary of the pink region marks the highest extent of summer snow melt. |
ASAR data will provide scientists with a
valuable new tool in their
investigations into snow cover studies.
One such study being proposed by Dr.
Jan-Gunnar Winther, head of the
Antarctic Section of the Norwegian Polar
Institute, is to use ASAR and MERIS data
for studies of snow distribution,
and glacier characteristics, and to
evaluate how these sensors can improve
our present use of satellite data
for studies of how the cryosphere
responds to climate change, as well as
for applications within hydropower
production management. In
particular, the goal is to determine:
- how snow distribution on Svalbard
affects regional climate
- snow distribution in mountainous
areas of Norway, for updating
hydrological models used for
management of hydropower production
as well as to monitor glaciers on
Svalbard for studies of mass balance,
surge mechanisms, calving and
sensitivity to climate change.
References:
Alaska SAR Facility web
site: www.asf.alaska.edu/user_serv/features
1.1.6.4.3 Sea Ice Applications - Sea Ice Mapping Radar data can be used in
applications supporting regional sea ice
mapping and monitoring, iceberg monitoring,
as well as marine transport and
fisheries support. In the remote and
extensive areas affected by sea ice, radar
remote sensing has been able to provide
comprehensive, timely, and accurate
information. Active microwave remote
sensing instruments are particularly
effective for sea ice mapping because of
their all-weather, day-and-night and
high-resolution imaging capability. As
well, to be an effective information
tool, the imagery must be captured on a
regular basis if imaging in Arctic regions.
Sea ice research is currently
concentrating on increasing our
understanding of the processes operating
in local areas and on continuous
monitoring to identify seasonal changes.
Sea ice models, used to estimate surface
flux and understand process behaviour,
require information on ice extent,
concentration, and leads at varying
resolutions appropriate to the use of
Image (IM) and Wide Swath (WS) Mode
data. Monthly, seasonal, and annual
products are required. Areas of special
interest are monitored continuously,
while other areas require data only
during times of fieldwork. Some
large-scale monitoring is undertaken for
which a large swath width is required.
The most important features of interest
to potential users are ice concentration
and delineation of ice edges.
Information regarding the location
of the ice edge is vital, since most
ships are not ice-strengthened and any
contact with ice is potentially
dangerous. The discrimination
between new ice and water is also required.
|
Figure 1.99 ERS-1 SAR image showing sea ice signatures, fall freeze-up, Beaufort Sea (image courtesy of Alaska SAR Facility) |
ASAR offers data similar to both ERS SAR
and RADARSAT, both of which are being
used extensively for sea ice research.
Both Wide Swath and Image Modes will
provide valuable data.
Some ambiguity in the interpretation of
newly formed ice and smooth water may
occur under calm conditions because the
water surface is very similar to
that of new ice. In general, the new sea
ice, although a relatively flat surface,
is "rougher" than a calm water
surface (because of the presence of
ridges and rafting) and is therefore
distinguishable on radar imagery.
Generally, the images are
interpreted with the use of ancillary
data such as meteorological records,
recent and historical ice records,
bathymetry, and data on ocean and
coastal currents and winds.
The identification and mapping of ice
types is another feature of interest to
navigators. Ice-type definitions are
based on the age of the sea ice,
which is directly correlated to its
thickness and strength. Of greatest
importance to navigators is the
differentiation between new, first
year and multi-year ice. Because of
their strength and hardness, multi-year
sea ice and icebergs are significant
hazards to ships and offshore
structures (Ramsay et al, 1993).
There are several cooperative projects
collecting and analysing sea ice
information. For example, the Arctic
Climate System Study (ACSYS), a
regional project within the World
Climate Research Programme (WCRP), is a
ten-year programme that began in 1994.
Its objectives are to improve
understanding of the processes within
the Arctic Ocean, including assembling a
basin-wide climatological database of
sea ice extent and concentration
(from satellite observations) and of ice
thickness and motion (using underwater
sonars) and drifting ice buoys.
Another investigation, being led by Dr.
Son V. Nghiem, at the Jet Propulsion
Laboratory in the United States, will
develop new algorithms using ENVISAT
ASAR and MERIS for sea ice mapping,
iceberg tracking, and studying sea ice
surface thermal effects.
ENVISAT-RADARSAT synergy will be used to
enhance sea ice operational
applications. The approach is to use
ASAR data at different polarisations
to classify open ocean and ice for ice
mapping, lead detection, and iceberg tracking.
To study sea ice surface thermal effects
under clouds, ASAR is used to detect
surface temperature change and map melt
pond areas under both clear sky and
cloudy conditions with MERIS for cloud
detection. ASAR Wide Swath imagery is
combined with the RADARSAT ScanSAR
product to provide a near daily
revisit at high latitude with added
polarisation diversity to improve ice
mapping ambiguities.
1.1.6.4.4 Sea Ice Application - Ship
Routing through Sea Ice
Satellite SAR data is particularly useful
for mapping the extent and type of sea
ice for ship routing due to the
availability of data in all-weather
conditions and during darkness. There
can be significant benefits in improving
the efficiency of offshore operations.
Since the launch of ERS-1, systems
have been developed which send
information and images directly to ice
breakers and ice-strengthened ships, and
images are also sent to Ice Centres that
produce forecasts of ice conditions.
|
Figure 1.100 RADARSAT image of the Gulf of St Lawrence, Eastern Canada (image courtesy of CCRS) |
Figure1.100 above shows a
number of different ice types present in
the Gulf of St Lawrence in Canada.
The Synthetic Aperture Radar (SAR) is
sensitive to variations in the salinity,
surface roughness and surface
wetness of ice.
This type of imagery is very useful to
agencies for locating, monitoring and
evaluating the movement of sea ice. The
ability to determine ice type and
monitor ice motion are extremely
important to ship navigation. Based on
this kind of information, navigators can
determine the path of least resistance
and plan the ships' routes through
the ice. The area indicated by (A)
depicts first year ice floes. Rough
"brash ice", indicated as (B)
and pressure ridges (C) are also clearly visible.
One-to-three day coverage is required for
ice forecasting and ship routing. The
temporal repeat time is of greater
importance than a high spatial
resolution and current use of ERS SAR
and RADARSAT data has shown that 100 m
data will meet the product
specification. RADARSAT or ASAR Wide
Swath Mode is the obvious choice in
order to have the wide area coverage.
Ship navigation requires information at a
scale which is useful when supporting
ship routing decisions over regions of 1
to 50 km. High-resolution data is
required to identify individual ice
features, so that in case of an
emergency, immediate ship routing
decisions can be made. Specific
features of interest on acquired imagery
include the size and thickness (or type)
of ice floes, ice ridges, leads, and
icebergs. For navigation, coverage is
also required for areas of 100 to 2000
km in extent, at spatial resolutions of
1 to 50 km. At this scale, broad ice
conditions can be assessed and ship
operators can identify the overall least
costly or least hazardous route. The
information requirements for these
applications include ice edge location,
ice concentration and type
determination, and lead detection
(open areas or cracks in the ice).
Small-scale (large area) imagery provides
regional mapping capability for sea ice
concentration, ice edge location, ice
motion tracking, and ice type
classification. This information can be
useful for tactical navigation depending
on the actual ice environment.
Intermediate-scale imagery provides
detail for medium-scale mapping and
tactical navigation support.
|