• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.1334-1336
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• 2003

On the basis of comprehensive analysis and summarization of the image fusion algorithms provided by PCI Geomatica software, deficiencies in image fusion processing functions of this software are put forwarded in this paper. This limitation could be improved by further developing PCI Geomatica on the user’ side. Five effective algorithms could be added into PCI Geomatica. In this paper, the detailed description of how to customize and further develop PCI Geomatica by using Microsoft Visual C++ 6.0, PCI SDK Kit and GDB technique is also given. Through this way, the remote sensing imagery fusion functions of PCI Geomatica software can be extended.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.609-611
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• 2003

In the past, it has always been time -consuming and labor intensive to extract and update Digital Elevation Model (DEM). How to extract highly accurate DEM with efficiently and the most economical method has always been a cutting-edge topic in the remote sensing filed. This paper discusses using PCI Geomatica OrthoEngine software to extract DEM automatically from ASTER stereo satellite images (15 m resolution). For the study, DEMs were extracted for two sites in Taiwan, and the resulting DEMs were found to have RMS errors between 10 and 16 meters in both flat and mountainous areas.

• Korean Journal of Remote Sensing
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• v.25 no.4
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• pp.359-366
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• 2009

Research of accurate DEM generation using images of Kompsat-2 is not enough. This paper focused on generation of accurate Kompsat-2 DEM and comparison with DEM from common software like PCI Geomatica and ENVI. For Kompsat-2 DEM generation, we applied orbit-attitude sensor modeling technique and matching method based on epipolarity and image geometry. The comparison of performance with each commercial programs made a qualitative experiment through naked eyes and a quantitative experiment with USGS DTED. The accuracy was judged by the average absolute error and RMS error with DIED. The result of comparison experiment, we could confirm that the method used in the experiment showed much better performance than DEM made from other commercial programs in most of images.

• Proceedings of the KSRS Conference
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• v.2
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• pp.631-634
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• 2006

Three main important sources for establishing GIS are the orthomap in scale 1:5 000 with Ground Sampling Distance of 0,5m; DEM/DTM data with height error of ${\pm}$1,0m and topographic map in scale 1: 10 000. The new era with Very High Resolution Satellite (VHRS) images as IKONOS, QuickBird, EROS, OrbView and other ones having Ground Sampling Distance (GSD) even lower than 1m has been in potential for producing orthomap in large scale 1:5 000, to update existing maps, to compile general-purpose or thematic maps and for GIS. The accuracy of orthomap generated from VHRS image affects strongly on GIS reliability. Nevertheless, orthomap accuracy taken from VHRS image is at first dependent on chosen sensor geometrical models. This paper presents, at fist, theoretical basic of the Rational Polynomial Coefficient (RPC) model installed in the commercial ImageStation Systems, realized for orthorectifying VHRS images. The RPC model of VHRS image is a replacement camera mode that represents the indirect relation between terrain and its image acquired on the flight orbit. At the end of this paper the practical accuracies of IKONOS and QuickBird image orthorectified by RPC model on Canadian PCI Geomatica System have been presented. They are important indication for practical application of producing digital orthomaps.

• Korean Journal of Remote Sensing
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• v.34 no.3
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• pp.439-450
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• 2018

The lineament is a linear or curved terrain element to discriminate adjacent geological structures in each other. It has been widely used for analysis of geology, mineral exploration, natural disasters, and earthquake, etc. In the past, the lineament has been extracted using cartographic map or field survey. However, it is possible to extract more efficiently the lineament for a very wide area thanks to development of remote sensing technique. Remotely sensed observation by aircraft, satellite, or digital elevation model (DEM) has been used for visual recognition for manual lineament extraction. Automatic approaches using computer science have been proposed to extract lineament more objectively. In this study, we evaluate the characteristics of lineament which is automatically extracted with respect to difference of spatial resolution of DEM. We utilized two types of DEM: one is Shuttle Radar Topography Mission (SRTM) with spatial resolution of about 90 m (3 arc sec), and the other is the latest world DEM of TerraSAR-X add-on for Global DEM with 12 m spatial resolution. In addition, a global DEM was resampled to produce a DEM with a spatial resolution of 30 m (1 arc sec). The shaded relief map was constructed considering various sun elevation and solar azimuth angle. In order to extract lineament automatically, we used the LINE module in PCI Geomatica software. We found that predominant direction of the extracted lineament is about $N15-25^{\circ}E$ (NNE), regardless of spatial resolution of DEM. However, more fine and detailed lineament were extracted using higher spatial resolution of DEM. The result shows that the lineament density is proportional to the spatial resolution of DEM. Thus, the DEM with appropriate spatial resolution should be selected according to the purpose of the study.