■■■i 
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences. Vol. XXXVII. Part B4. Beijing 2008 
976 
model was adopted. Mapping to the east of the Joliot-Curie 
quadrangle revealed that the quality of the Cycle 3 images 
declined dramatically toward the end of the cycle in terms of 
both signal-to-noise ratio and data dropouts, increasing the need 
for interactive editing by a factor of several. 
A particular concern of the geologists interested in using 
Magellan stereo DTMs was whether artifacts could occur at 
high-contrast boundaries, either directly by effects on the SAR 
images or as a result of the errors that such boundaries were 
known to induce in the altimetry used for vertical control. We 
addressed these issues by test mapping of a 10°x3° region in the 
rugged highlands of Ovda Regio containing sharp boundaries 
between high and low radar backscatter. These boundaries are 
caused by a temperature-dependent change in the equilibrium 
mineral phases on the surface, so they are expected to form at 
nearly constant elevation. The images clearly show the surface 
to be smoothly sloping near the boundaries, but the altimetry 
contains artifactual “pits” as deep as 3 km. We found, as 
expected, that our smooth (linear with time) adjustment to the 
spacecraft ephemerides did not allow the stereo DTM surface to 
deform to follow altimetry artifacts. Vertical control points 
placed in the “pits” were readily identified as outliers, and the 
stereo DTM indicated highly consistent elevations along the 
contrast boundary, with variations of -200 m locally, compared 
to -500 m variation previously estimated by mapping with 
uncontrolled images in MST (Arvidson et al., 1994). The 
constancy of the transition elevation provides as good a test of 
the precision of our stereo mapping as is likely to be obtained 
until a future mission supplies higher resolution data. 
2.4 Lessons Learned 
Overall, our Magellan experience showed that digital stereo- 
grammetric processing techniques, including automatic image 
matching, could be applied successfully to planetary SAR data, 
and that a custom sensor model could be used to bundle adjust 
and work with images that had already been map projected and 
even mosaicked. Our tests showed the utility of a “seed” DTM 
for automatic matching and the value of opposite-side radar 
stereopairs for mapping areas of subtle relief, and suggested 
what may be a general rule, that accurate mapping requires both 
the best available reconstructed ephemerides and further bundle 
adjustment based on image tiepoints. Finally, we learned not to 
underestimate the additional complications and difficulties that 
arise in the mapping of each new area of Venus. 
3. TITAN 
3.1 Cassini Mission and Data 
The Cassini-Huygens mission consists of the NASA Cassini 
spacecraft, which went into orbit around Saturn in 2004, and the 
ESA Huygens probe carried by Cassini, which landed on the 
giant satellite Titan in 2005. Investigation of Titan, which is 
larger than the planet Mercury and wrapped in a smoggy 
nitrogen atmosphere four times denser than Earth’s, is a major 
objective of the Cassini instruments as well as the sole goal of 
Huygens. Prior investigations of the organic chemistry of 
Titan’s atmosphere raised the strong possibility of reservoirs of 
liquid methane and ethane on the body’s surface, where they 
might be expected to form lakes and even participate in an 
exotic equivalent of Earth’s hydrologic cycle. The RADAR 
instrument (Elachi et al., 2004) uses Ku band (2.17 cm X) 
microwaves to penetrate the atmospheric clouds and haze, and 
has provided the highest resolution images of Titan's surface 
apart from very localized coverage from the cameras on 
Huygens. On selected flybys of Cassini past Titan, the RADAR 
obtains a SAR image strip 200-500 km wide and as much as 
6000 km (130° of arc) in length. So far, approximately 25% of 
Titan's surface has been imaged, at resolutions from about 0.3 
to 1.5 km; a grid spacing of 175 m (1/256°) is used to ensure 
oversampling of the data. Beginning in late 2006, most new 
SAR image strips partly overlapped one or more earlier images, 
and by the end of 2007, more than 20 image overlaps covering 
more than 1% of Titan in stereo were available (Figure 2). 
Operating in other modes, the RADAR also provides lower 
resolution altimetry, scatterometry, and radiometry data. 
As in the Magellan mission, the image strips are known as 
BIDRs (Stiles, 2008b) and are made available in map projected 
form. The pattern of Cassini flybys (Fig. 2) is much less regular 
than the north-south arrangement of orbit strips on Venus, 
however, so each BIDR uses an Oblique Cylindrical projection 
oriented along its individual flyby ground track. Mosaics of 
multiple BIDRs transformed to a common global map 
projection are being made, but these are not useful for 
stereoanalysis because there is no equivalent to the Cycle-1 and 
Cycle-3 data sets of Magellan. Instead, we use the individual 
BIDRs and map the overlap areas of pairs of them. 
Figure 2. Mosaic of Cassini RADAR image coverage of Titan. 
Polar Stereographic projections of the northern (left) and 
southern (right) hemispheres with 10° parallels. Longitude 0° is 
at the bottom on left, at top on right. Stereo overlaps with same- 
side illumination and viewing are shown in green, opposite-side 
in red, and high-angle overlaps in yellow. Total coverage to 
date is -25%, total stereo -1%. 
3.2 Methodology 
Our approach to radargrammetry with Cassini data closely 
follows that outlined above for Magellan, in broad outline using 
ISIS to ingest and prepare the data and SOCET SET with a 
custom sensor model written by us to perform bundle 
adjustment, automated matching, and DTM editing. The inputs 
for mapping are BIDRs in Oblique Cylindrical projection rather 
than BIDRs, MIDRs, and FMAPs in Sinusoidal projection, but 
the sensor model follows the same steps of identifying the 
relevant radar burst for a given ground point, calculating the 
range-Doppler coordinates of the point for that burst, and then 
duplicating the transformation of range-Doppler into BIDR 
pixel coordinates. The Cassini BIDRs must be treated as 
mosaics, however, because they contain five parallel swaths of 
data obtained by the five separate beams of the instrument. It is 
thus necessary to identify first the beam and then the burst 
whose parameters should be used in sensor model calculations 
for any given pixel. The small number of BIDRs (tens versus