SPOT 5 HRS STUDY - AUTOMATIC DTM EXTRACTION
REGIONS 1 (MONTMIRAIL - FRANCE) AND 7 (RASHT - IRAN)
Shaheen Ghayourmanesh, Yun Zhang
Geodesy and Geomatics Engineering, University of New Brunswick, PO Box 4400, Fredericton, NB, CANADA
Postal code: E3B SA3 — Email: v1m37@unb.ca , yunzhang@unb.ca
Commission I
KEY WORDS: Automation, Software, DTM, Extraction, Orthoimage, Stereoscopic, SPOT
ABSTRACT:
With improved spatial resolution of available satellite images and the ability to collect the stereo images within a short time period,
the importance of satellite images f
or generating elevation information has grown. Most of the users try to use satellite images
because of the reasonable time and cost for ordering. The speed of information generation by satellite sensors from planning to
execution is much higher than the conventional ways such as aerial photography process. Therefore, high-speed and high-accuracy
software tools are required for information extraction from satellite images. Automatic DTM extraction from the satellite images is
yet the challenging task. Different algorithms and software tools have been developed. In this study, the performance of two
commercial remote sensing software tools, OrthoEngine of PCI Geomatica V8.2.3 and the OrthobasePro of ERDAS Imagine V8.6
and V8.7, have been evaluated for automatic DTM extraction from the SPOT 5 stereo pan imagery. The capability of SPOT 5 stereo
pan images for DTM generation is analyzed, and the performances of the software tools for the orbit modelling and automatic image
matching are discussed.
1. INTRODUCTION
Automatic DTM extraction process from satellite images can be
enerally divided into two components:
- Orbit modeling
- Automatic image matching
o
I
2
These two components are important in the success of
automatic DTM extraction process. The first one is correct orbit
modeling. The second one is the successful image matching
process. In the high resolution images, the orbit modeling of the
sensor is one of the most important parts because all equations
for orthorectification and DTM extraction are based on that, but
the problem in the orbit modeling is the lack of knowledge of
the sensor attitude in the time t. Any error in the orbit modeling
causes error in the other parts of DTM generation process and
the accuracy of the generated DTM. For example, image
matching process usually is done on epipolar images.
Therefore, any error in epipolar resampling process, which uses
orbit modeling, causes difficulties and errors in the matching
process. Also, for two matched points, the accuracy of the
ground coordinate is directly dependent on the accuracy of the
orbit modeling.
In this report, two commercial softwares, PCI Geomatica v8.2.3
and ERDAS Imagine v8.6 and v8.7, are used to evaluate the
automatic DTM extraction for SPOT 5 imagery. The goal is to
find the accuracy of the DTM which is derived automatically
by them. This accuracy shows two things:
I- The usefulness of the SPOT 5 stereo images for DTM
generation
2- The art of the software in orbit modeling and automatic
image matching.
The data used in this research are:
I- Two stereo HRS SPOT 5 along track (Rasht, IRAN), DTM
of that region, the digital maps used for generating the DTM.
2- Two stereo HRS SPOT 5 along track (Montmirail,
FRANCE), DTM of that region.
Because of some problems in the second data, just the first one
is used in this report.
In section 2, the results of PCI Geomatica v8.2.3 will be shown
and then, in section 3, the results of ERDAS Imagine v8.6 and
v8.7 will be shown.
2. PCI GEOMATICA
The PCI Geomatica is commercial software which enables user
to process images for mapping purposes. This software consists
of different modules. The module which handles the
orthorectification and DTM extraction is OrthoEngine. It is
capable for different kinds of sensors like aerial imagery,
optical satellite imagery and radar imagery. This research is for
evaluating the capability of the software in handling SPOT 5
stereo imagery for automatic DTM generation.
In use of the OrthoEngine, there are some stages that should be
followed. In the following, the steps will be described.
2.1 Project definition
The first step is to define the kind of project for OrthoEngine.
The Toutin’s model for SPOT 5 in Satellite Orbit Modeling has
been selected, which is shown in Figure 1.
About this model, in the PCI website has been written: “The
model, a cooperative development between PCI Geomatics and
the Canada Centre for Remote Sensing (CCRS, Natural
Resources Canada), was developed by Dr. Thierry Toutin at
CCRS and is a rigorous 3D parametric model based on
principles related to orbitography, photogrammetry, geodesy
and cartography. It further reflects the physical reality of the
complete viewing geometry and corrects all geometric
distortions due to the platform, sensor, Earth, and cartographic
projection that occur during the imaging process.”
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