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16 TerraSAR-X, TanDEM-X, and PAZ

16 TerraSAR-X, TanDEM-X, and PAZ

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456



CHAPTER 6 MICROWAVE AND LIDAR SENSING



from the Shuttle Radar Topography Mission, discussed in Section 6.19. The

initial data collection for this new global DEM took just over one year. The results

began to be made available in 2014, following a second year of data collection to

improve the accuracy in areas of rough terrain.

A third satellite based on the TerraSAR-X design, and flying in the same orbit,

is planned for launch in 2015. This system, known as PAZ (“peace” in Spanish)

will further extend the opportunities for data collection by this constellation of

X-band SARs, leading to very frequent revisit opportunities and more interferometric image pairs for mapping the dynamic topography of the earth’s surface.

Figure 6.48 shows an example of TerraSAR-X imagery acquired in its High

Resolution Spotlight mode over a copper mine in Chuquicamata, Chile. The

mine, located in the Atacama Desert of northern Chile, is the largest copper mine

in the world by volume. The imagery consists of a mosaic of data from two separate orbit tracks, with ground range resolutions ranging from 1.04 m to 1.17 m.

The large whorled pattern at upper left, with relatively dark texture, is the open

pit mine, with an access road spiraling into it. The bright dots within this pattern

are vehicles working in the mine. Other features in this image include buildings,

roads, and tailing piles associated with the mine operations.

Another High Resolution Spotlight mode image from TerraSAR-X is shown in

Figure 6.49. This image covers a portion of Charles de Gaulle Airport, the largest

airport in France, located outside Paris. The architectural design of Terminal 1,

located left of the center of the image, has been compared to the shape of an octopus. As in this example, radar images of airports tend to have high contrast, due

to the close proximity of large flat surfaces (which appear dark, due to specular



Figure 6.48 High Resolution Spotlight imagery from TerraSAR-X, over a copper mine in

Chuquicamata, Chile (scale 1:44,000). Full resolution of this image ranges from 1.04 m to

1.17 m. (Copyright: DLR e.V. 2009, Distribution Airbus DS/Infoterra GmbH.)



6.17 THE COSMO-SKYMED CONSTELLATION



457



Figure 6.49 Charles de Gaulle Airport, France, shown in a TerraSAR-X High Resolution Spotlight

image (scale 1:67,000). Full resolution of this image is 2.4 m. (Copyright: DLR e.V. 2009, Distribution

Airbus DS/Infoterra GmbH.)



reflection) and angular, metallic structures dominated by high-intensity corner

reflections (which are very bright in tone).



6.17



THE COSMO-SKYMED CONSTELLATION

While 2007 saw the launch of the first satellite in the TerraSAR-X family, it also

featured the launch of the first two satellites in the Italian Space Agency’s

COSMO-SkyMed constellation, on June 8 and December 9 of that year. Two additional COSMO-SkyMed satellites were launched on October 25, 2008, and

November 5, 2010. Like the German TerraSAR-X satellites, COSMO-SkyMed

operates in the X-band. The satellites in this constellation share a common orbit

plane, with an altitude of 620 km. The individual satellites have a 16-day repeat

cycle but are spaced several days apart, providing multi-satellite revisit periods

ranging from one day to several days; however, due to the cross-track pointability

of the SAR antennas, most locations can be imaged every 12 hours.

Like the other recent SAR systems discussed here, COSMO-SkyMed offers

a variety of imaging modes, ranging from the 1-m resolution Spotlight mode

(covering a 10-km by 10-km area) to several ScanSAR modes covering a 100-km

to 200-km swath at single-look resolutions of 16 m to 30 m. The system’s emphasis is on rapid tasking and frequent image acquisitions for applications ranging

from disaster response to defense and security. It can also be used for repeat-pass

interferometry with temporal baselines as short as one day.

A second generation of COSMO-SkyMed satellites is currently being planned

for launch beginning in 2017. If carried out as planned, this should ensure the

continued availability of these data as the first generation of satellites in the constellation reaches the end of their design life.



458



CHAPTER 6 MICROWAVE AND LIDAR SENSING



6.18 OTHER HIGH-RESOLUTION SPACEBORNE RADAR SYSTEMS

As described in Chapter 5, the Indian Space Research Organization (ISRO) has

devoted significant resources to developing and launching electro-optical satellites operating in the visible and infrared regions of the spectrum. At the same

time, ISRO has not neglected the field of radar remote sensing. The first civilian

SAR satellite built by ISRO was launched on April 26, 2012. Named RISAT-1, it

features a C-band SAR with single, dual, and quad polarization options, and resolution modes ranging from 1 m to 50 m. It is primarily intended for agricultural

and natural-resource monitoring applications.

Another agency with a long record of successful optical satellite launches that

is now moving into the field of radar remote sensing is the UK’s Surrey Satellite

Technology Ltd. (SSTL), whose typically lightweight and nimble satellites have

contributed to the Disaster Monitoring Constellation (DMC) discussed in Chapters 5 and 8. SSTL is currently preparing its first NOVASAR-S satellite, an S-band

radar system that the company hopes will be the first of a series of radar satellites.

While radar systems are typically massive in size and in power requirements,

NOVASAR-S would be less than a quarter of the size of India’s RISAT-1. This,

in turn, would lead to greatly reduced launch costs, making a multi-satellite constellation more affordable.

If launched as planned, NOVASAR-S would be the first S-band radar satellite

since Almaz-1 ceased operations more than two decades ago. Compared to the

extensive body of research on the scattering behavior of shorter and longer wavelength C- and L-band radar systems, there have been relatively few studies at this

intermediate wavelength. The NOVASAR-S would be able to collect up to three of

the four linear polarization combinations (HH, HV, VH, and VV) during any given

image acquisition, an improvement over the dual-polarization mode but not

offering the theoretically complete measurement of polarimetric scattering that

would be provided by a fully quad-pol system.

Given that many weather-related natural disasters (including tropical storms,

floods, and tornadoes) are often accompanied by heavy cloud cover, the addition of

one or more radar satellites to the DMC would certainly strengthen that constellation’s

role in disaster monitoring and response. The availability of an S-band radar system to

complement the other X-, C-, and L-band radar satellites currently operational or

planned for launch would also likely be beneficial for agricultural and natural resources management applications, although more research is needed in this area.

At the opposite extreme from the numerous short-wavelength, high-resolution

SAR systems described in the preceding sections, NASA’s planned Soil Moisture

Active Passive (SMAP) mission will include a long-wavelength L-band radar with a

very coarse spatial resolution and a wide field of view (swath width 1000 km).

While the single-look resolution for SMAP’s radar will vary widely across this

wide swath, its data will be distributed with multilook processing resampled to a

uniform 1-km grid.



6.19 SHUTTLE RADAR TOPOGRAPHY MISSION



459



In combination with a passive microwave radiometer that shares the same

platform, SMAP’s radar will help measure soil moisture and moisture state (frozen or liquid). These data are intended to contribute to systematic global monitoring of the water cycle, climate, and water exchanges among the soil column,

ecosystems, and the atmosphere. It will also support forecasting of weather,

floods/droughts, agricultural productivity, and other processes that involve soil

moisture and soil state.



6.19



SHUTTLE RADAR TOPOGRAPHY MISSION

The Shuttle Radar Topography Mission (SRTM) was a joint project of the National

Imagery and Mapping Agency (NIMA) and NASA to map the world in three dimensions. During a single Space Shuttle mission on February 11 to 22, 2000, SRTM

collected single-pass radar interferometry data covering 119.51 million km2 of the

earth’s surface, including over 99.9% of the land area between 60° N and 56° S latitude. This represents approximately 80% of the total land surface worldwide and is

home to nearly 95% of the world’s population.

The C-band and X-band antennas from the 1994 SIR-C/X-SAR shuttle missions (Section 6.11) were used for data collection. To provide an interferometric

baseline suitable for data acquisition from space, a 60-m-long rigid mast was

extended when the shuttle was in orbit, with a second pair of C-band and X-band

antennas located at the end of the mast. The primary antennas in the shuttle’s

payload bay were used to send and receive data, while the outboard antennas on

the mast operated only in receiving mode. The extendible mast can be seen during testing prior to launch in Figure 6.50. In Figure 6.50a most of the mast is

stowed within the canister visible in the background. In Figure 6.50b the mast is

extended to its full length. The two outboard antennas were not installed on the

mast at the time of these tests; during the mission they were mounted on the triangular plate visible at the end of the mast in Figure 6.50. An artist’s rendition of

the shuttle in orbit during SRTM is provided in Figure 6.51. This illustration

shows the position and orientation of the various SRTM components, including

the main antenna inside the shuttle’s payload bay; the canister for storage of the

mast, the mast itself, and the outboard antennas at the end of the mast.

The system collected 12 terabytes of raw data during the 11-day mission, a

volume of data that would fill over 15,000 CD-ROMs. Processing this volume of

data took two years to complete. The elevation data are being distributed by the

U.S. Geological Survey. The SRTM processor produces digital elevation models

with a pixel spacing of 1 arcsecond of latitude and longitude (about 30 ma). The

absolute horizontal and vertical accuracy of the data are better than 20 and 16 m,

a



Prior to 2014, the data for areas outside the U.S. were aggregated to 3 arcseconds (about 90 m).



460



(a)



CHAPTER 6 MICROWAVE AND LIDAR SENSING



(b)



Figure 6.50 The SRTM extendable mast during prelaunch testing: (a) view of the mast

emerging from the canister in which it is stowed during launch and landing; (b) the mast fully

extended. (Courtesy NASA/JPL/Caltech.)



Figure 6.51 Artist’s rendition of the shuttle in orbit during SRTM, showing the

positions of the main antenna inside the payload bay, the canister, the mast, and the

outboard antennas. (Courtesy NASA/JPL/Caltech.)



respectively. In addition to the elevation data, the SRTM processor produces

orthorectified radar image products and maps showing the expected level of error

in the elevation model.

Figure 6.52 shows a perspective view of a DEM for the Los Angeles metropolitan area. The DEM was derived from interferometric analysis of SRTM imagery,



6.19 SHUTTLE RADAR TOPOGRAPHY MISSION



461



Figure 6.52 Perspective view of a DEM of the Los Angeles area, derived from SRTM

interferometric radar data. A Landsat-7 ETMỵ image has been draped over the DEM to show

land cover patterns. (Courtesy NASA/JPL/Caltech.)



and a Landsat-7 ETMỵ image was draped over the DEM. This view is dominated

by the San Gabriel Mountains, with Santa Monica and the Pacific Ocean in the

lower right and the San Fernando Valley to the left.

Technical problems during the shuttle mission caused 50,000 km2 of the targeted land area to be omitted by SRTM. These omitted areas represent less than

0.01% of the land area intended for coverage. All the omitted areas were located

within the United States, where topographic data are already available from other

sources.

As the first large-scale effort to utilize single-pass radar interferometry for

topographic mapping from space, the project has proved to be highly successful.

The resulting topographic data and radar imagery represent a unique and highly

valuable resource for geospatial applications. However, with the anticipated near

future availability of globally consistent, higher-resolution spaceborne radar topographic data such as the database now being compiled from TerraSAR-X and

TanDEM-X interferometry (Section 6.16), the groundbreaking SRTM data set will

likely come to be seen as an important early stepping stone on the path to a world

where continually updated topographic data are available at increasingly high

resolution across the whole earth. Figure 6.53 compares the resolution of the

12.5-m resolution globally consistent digital elevation data set from TerraSAR-X/

TanDEM-X to the pre-2014 3-arcsecond (90-m) resolution SRTM elevation data,

for a site near Las Vegas, NV. Just as a decade ago the SRTM project represented

a dramatic improvement in the consistency and availability of digital elevation

data worldwide, the high-resolution DEMs currently being produced from



462



CHAPTER 6 MICROWAVE AND LIDAR SENSING



(a)



(b)



Figure 6.53 Comparison of digital elevation data from (a) the 3-arcsecond (90-m) resolution

SRTM data set to (b) the 12.5-m resolution elevation data currently being collected worldwide by

TerraSAR-X and TanDEM-X. (Courtesy German Aerospace Center – DLR.)



spaceborne radar satellites will represent a similar quantum jump in resolution

and detail over the 3-arcsecond SRTM data set.



6.20 SPACEBORNE RADAR SYSTEM SUMMARY

The proliferation of new radar satellites and multi-satellite constellations, and the

diversity of operating modes offered by all of these systems, render the task of



TABLE 6.7



Characteristics of Major Past Operational Spaceborne SAR Systems



Years in

operation



Satellite



Country



Radar

band



Pol.

mode



Look

angle



Resolution,

m



1991–1992

1991–2000

1992–1998

1995–2011

1995–2013

2002–2012

2006–2011



Almaz-1

ERS-1

JERS-1

ERS-2

Radarsat-1

Envisat

ALOS



Soviet Union

ESA

Japan

ESA

Canada

ESA

Japan



S

C

L

C

C

C

L



HH

VV

HH

VV

HH

Dual

Quad



20–70°

23°

35°

23°

10–60°

14–45°

10–51°



10–30

30

18

30

8–100

30–1000

10–100



6.20 SPACEBORNE RADAR SYSTEM SUMMARY



TABLE 6.8



463



Characteristics of Major Current Operational Spaceborne SAR Systems



Year of

launch



Satellite



Country



Radar

band



Pol.

mode



Look

angle



Resolution,

m



2007

2007

2007

2007

2008

2010

2010

2012

2014

2014



TerraSAR-X

COSMO-SkyMed 1

COSMO-SkyMed 2

Radarsat-2

COSMO-SkyMed 3

TanDEM-X

COSMO-SkyMed 4

RISAT-1

ALOS-2

Sentinel 1A



Germany

Italy

Italy

Canada

Italy

Germany

Italy

India

Japan

ESA



X

X

X

C

X

X

X

C

L

C



Dual

Quad

Quad

Quad

Quad

Dual

Quad

Quad

Quad

Dual



15–60°

20–60°

20–60°

10–60°

20–60°

15–60°

20–60°

12–50°

10–60°

20–47°



1–18

1–100

1–100

1–100

1–100

1–18

1–100

1–50

1–100

5–40



TABLE 6.9

Expected

launch

2015

2015

2015

2016

2017

2017

2018



Characteristics of Major Planned Future Spaceborne SAR Systems

Satellite



Country



Radar

band



Pol.

mode



Look

angle



Resolution,

m



SEOSAR/Paz

NOVASAR-S

SMAP

Sentinel 1B

COSMO-SkyMed

2nd Generation-1

COSMO-SkyMed

2nd Generation-2

Radarsat Constellation

1, 2, 3



Spain

UK

US

ESA

Italy



X

S

L

C

X



Dual

Tria

Trib

Dual

Quad



1560

1570

3550

2047

2060



118

630

1000ỵ

540

1100



Italy



X



Quad



2060



1100



Canada



C



Quad



1060



3100



a



While NOVASAR-S could collect data in any of the four polarization combinations HH, HV, VH, and VV, it could

record at most three of these polarizations during any given image acquisition.

b

The SMAP radar will have fixed HH, HV, and VV polarizations.



summarizing the diversity of spaceborne radar sensors increasingly difficult.

Tables 6.7, 6.8, and 6.9 are presented to assist in this process by compiling the

essential characteristics of past, current, and planned future spaceborne radars.

Note that there has been a general trend toward increasing design sophistication,

including multiple polarizations, multiple look angles, and multiple combinations



464



CHAPTER 6 MICROWAVE AND LIDAR SENSING



of resolution and swath width. However, none of these systems operates at more

than one wavelength band—a fact that testifies to the technical challenges

involved in designing spaceborne multi-wavelength radar systems.



6.21 RADAR ALTIMETRY

The radar systems described in the preceding sections of this chapter all are sidelooking instruments, designed to collect image data on a pixel-by-pixel basis

across a wide spatial area. Another class of radar remote sensing systems, however, is designed to look directly downward and measure the precise distance

from the radar antenna to the earth’s surface. These sensors are referred to as

radar altimeters, and while they do not normally produce image data per se, the

spatial data they collect on the earth’s oceans, lakes, ice sheets, land surface, and

seafloor are widely used in the geosciences and in practical applications ranging

from water resources management to monitoring and forecasting the behavior of

the El Nino/Southern Oscillation.

The basic principle behind radar altimetry is quite simple: The radar antenna

transmits a microwave pulse downward to the surface and measures the elapsed

time for the returning pulse. This in turn can be used to calculate the distance

from the antenna to the surface. If the position of the antenna is known accurately, the elevation of the surface can be determined with a similar degree of

accuracy. While this appears straightforward, in practice there are several challenges to the design and operation of radar altimeters.

Many applications of radar altimetry require centimeter-scale resolution in

the vertical dimension. To ensure this, the transmitted pulse duration must be

very brief, on the order of nanoseconds. This in turn would require an unfeasibly

large power for the transmitted signal. Radar altimeters (and many imaging

radars as well) circumvent this problem by using sophisticated signal processing

methods, such as a pulse compression approach that involves modulating the signal (referred to as “chirp”).

During the signal’s transit from the antenna to the surface, it fans outward,

such that for spaceborne radar altimeters the normal diameter of the pulse’s footprint on the surface may be 5 to 10 km or more. The shape of the returning signal

recorded by the antenna (referred to as the waveform) is a composite of thousands of individual echoes from scattering nodes within this broad footprint. The

roughness of the surface will affect the waveform, such that as the surface roughness increases, it becomes more challenging to identify a specific elevation for the

altimeter’s footprint. Figure 6.54 illustrates the interaction between a transmitted

pulse from a radar altimeter and an ideal, flat surface. At time t ¼ 1, the pulse has

not yet intersected the surface. At t ¼ 2, only the very center of the wavefront is

being scattered back, producing a weak but rapidly increasing signal. At t ¼ 3, a

larger area is being illuminated, and because this area of illumination is still

directly beneath the sensor, it sends back a strong echo. At t ¼ 4 and t ¼ 5, the



6.21 RADAR ALTIMETRY



Elapsed

time



t=1



t=2



t=3



t=4



465



t=5



Transmitted

pulse



Ground



Returning

signal



intensity



Footprint

(plan view)



time



Figure 6.54 Schematic diagram of the signal transmitted and received by a radar altimeter.



Intensity



wavefront is expanding outward away from the center of the altimeter’s footprint,

and the returned signal consequently becomes weaker. This produces the characteristic waveform of a radar altimeter, with a steeply rising leading edge followed by a gradually tapering trailing edge. Over a more complex surface with a

rougher texture, the front of the waveform will be less steep, the peak will be less

obvious, and the trailing edge will be noisier (Figure 6.55).

Since the early 1990s spaceborne radar altimeters have been operated

from a variety of platforms, including the ERS-1, ERS-2, and Envisat satellites

(Section 6.13); the Topex/Poseidon mission (1992–2005) and its successors Jason-1

(2001–present) and OSTM/Jason-2 (2008–present), all three of which are joint

efforts of the United States and France); and others. Of particular note, the ESA’s



a

b



Time

Figure 6.55 Returning pulses from radar altimeter measurements

over a flatter surface (solid line a) and a rougher surface (dashed

line b).



466



CHAPTER 6 MICROWAVE AND LIDAR SENSING



radar altimetry satellite Cryosat-2 was successfully launched on April 8, 2010. The

Cryosat-2 mission is primarily focused on monitoring the seasonal and long-term

dynamics of the earth’s land ice and sea ice, including the large polar ice sheets

of Greenland and Antarctica, smaller ice caps and glaciers elsewhere, and the seasonally expanding and contracting Arctic and Antarctic sea ice.

Plate 29 shows a global data set of ocean bathymetry, derived from analysis of

spatial variations in the long-term average height of the oceans as measured by

radar altimeters, primarily Topex/Poseidon. While one might assume that because

water flows downhill, the ocean surface must be flat, in reality there are irregularities in “sea level” at both short and long time scales. Sea level temporarily rises

and falls in individual regions due to changes in local atmospheric pressure, wind

strength and direction, and the dynamics of ocean currents. Over long periods,

sea level tends to be higher in some areas than others, because the ocean surface

reflects the presence of ridges, valleys, and abyssal plains on the ocean floor.

(Conceptually, this is similar to the finer-scale representation of local bathymetry

in the English channel as seen in the Seasat-1 SAR imagery in Figure 6.35.)

Again, the radar altimeters do not see through the ocean directly; instead, they

map the surficial expression of broad-scale submarine features deep below the

surface.



6.22 PASSIVE MICROWAVE SENSING

Operating in the same spectral domain as radar, passive microwave systems yield

yet another “look” at the environment—one quite different from that of radar.

Being passive, these systems do not supply their own illumination but rather

sense the naturally available microwave energy within their field of view. They

operate in much the same manner as thermal radiometers and scanners. In fact,

passive microwave sensing principles and sensing instrumentation parallel those

of thermal sensing in many respects. As with thermal sensing, blackbody radiation theory is central to the conceptual understanding of passive microwave sensing. Again as in thermal sensing, passive microwave sensors exist in the form of

both radiometers and scanners. However, passive microwave sensors incorporate

antennas rather than photon detection elements.

Most passive microwave systems operate in the same spectral region as the

shorter wavelength radar (out to 30 cm). As shown in Figure 6.56, passive microwave sensors operate in the low energy tail of the 300 K blackbody radiation

curve typifying terrestrial features. In this spectral region, all objects in the natural environment emit microwave radiation, albeit faintly. This includes terrain

elements and the atmosphere. In fact, passive microwave signals are generally

composed of a number of source components—some emitted, some reflected, and

some transmitted. Over any given object, a passive microwave signal might

include (1) an emitted component related to the surface temperature and material

attributes of the object, (2) an emitted component coming from the atmosphere,



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