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Title
Remote sensing for resources development and environmental management
Author
Damen, M. C. J.

Satellite imagery is not the only form of
digital imagery available. Airborne digital
scanners are available and can produce
imagery with higher resolution than that
available from satellites. Such imagery
could be used to map for cultural features
in urban areas which require more detailed
interpretation. This would still allow the
source data to be in a more useful digital,
multispectral form.
PROBLEMS
To date digital satellite imagery has only
seen limited use in a mapping context.
Problems such as the availability of high
resolution imagery, accurate correction
techniques, and a general lack of
understanding of digital image processing
have hindered the entry of digital satellite
imagery into the map production environment.
Until the recent launch of SPOT, the highest
resolution digital satellite imagery
generally available has been the LANDSAT-TM
imagery, which has a pixel resolution of 30
metres square. Evaluation of TM imagery
(Welch, Jordan, and Ehlers, 1985) has shown
that imagery can be geometrically corrected
to an RMSxy error of less than 20 metres.
The SPOT satellite is the first commercial
satellite capable of producing high
resolution imagery which can be used to
derive planimetry and topography at scales
of 1:50,000 and smaller (Welch, 1985). SPOT
will use two sensors, a panchromatic sensor
(PLA) with 10 metre pixel resolution, and
three-band multispectral sensor (MLA) with
20 metre pixel resolution.
SPOT will also provide the unique capability
of producing stereo image pairs through the
use of pointable imaging sensors. These
stereo image pairs will make it possible to
extract elevation information directly from
the satellite imagery. Prototype systems
have already been developed to automatically
extract digital elevation models (DEM) from
stereo image pairs. Using simulated SPOT
data, RMS errors of less than 10 metres have
been achieved for automatically generated
digital terrain models (Cooper, Friedmann,
and Wood, 1985 ) .
The use of precision corrected, geocoded
imagery in the map making process will
dramatically improve the quality and variety
of 'cartographic products that can be
produced. Simply put, geocoded imagery is
imagery which has been transformed to a
desired map projection with the rows and
columns of pixels aligned with the
projection axis. In fact, geocoded imagery
provides more than just transformed rows and
columns. Geocoded imagery has also been
corrected for all source dependent errors,
resampled to a standard square pixel size
(e.g. MSS pixels are resampled to 50
metres, TM to 25 metres, SPOT MLA to 12.5
metres, and PLA to 6.25 metres), and each
geocoded image is sized to an integral
number of standard mapsheets.
There are numerous benefits to be had from
using geocoded imagery. The two most
obvious include satellite sensor
independence of the data and easy
integration with other image and non-image
data. Because geocoding removes source
dependent errors and transforms the imagery
to a standard map format, the problems
associated with multi-source images are
eliminated. Imagery from both LANDSAT TM
and MSS sensors and SPOT can be easily
combined and manipulated together.
Similarly, geocoded imagery can be used in
combination with any other data that shares
the same map projection.
General acceptance of mapping from satellite
imagery will only come about once its
feasibility can be proven. This paper will
attempt to show that mapping can be done
from such imagery through the use of new
digital techniques and that it is feasible
to map from satellite imagery in an
operational environment.
THE MAP PRODUCTION PROCESS
The production of the sample topographic
base map from digitally-processed satellite
imagery followed the flow shown in Figure 1.
FIGURE 1 - The Map Production Process
The key step is the precision image
correction and geocoding procedure. This
procedure allowed the raw satellite imagery
to be corrected to the cartographic accuracy
standards required by the map maker. The
combination of geocoding and correction in
this process made it possible to place the
digital imagery into a common map coordinate
system without additional accuracy-degrading
transformation steps.
This technique involved modeling the motion
of the spacecraft and sensor during the data
collection orbit. Through the use of a
sophisticated spacecraft model, ground
control points were used only to "fine tune"
the model for more precise geometric image
correction. This allowed the use of many
fewer ground control points to achieve
subpixel accuracy than would be required for
standard warping methods. In general, only
7 to 15 control points are required to
precision geocode a 34,000 sq. kilometre
image to subpixel accuracy.
The extraction of elevation information
required a stereo pair of corrected images
as input. The elevation extraction process
is fully automated. The computer matched
corresponding features in the left and right
images and determined the relative elevation