• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.21 no.2
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• pp.165-172
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• 2003

IKONOS satellite images are particularly well suited for stereo feature extraction. But, because IKONOS doesn't offer information about the satellite ephemeris and attitude, we have to use IKONOS RPC(Rational Polynomial Coefficients) data for 3-D feature extraction. In this study, it was intended to increase the accuracy and the efficiency in application of high resolution satellite images. Therefore, this study develop the program to extract 3-D feature information and have analyzed the geometric accuracy of the IKONOS satellite images by means of the change with the number, distribution and height of GCPs. This study will provide basic information for luther studies of the accuracy correction in IKONOS and high resolution satellite images.

• 한국공간정보시스템학회:학술대회논문집
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• 2005.05a
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• pp.369-374
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• 2005

정사영상 생성, 도시 공간의 모형화 등 도면화의 다양한 응용분야에 적용을 위해서는 위성 영상으로부터 수치고도모형을 생성하는 것은 중요하며, SPOT-5, IKONOS, QUICKBIRD, ORBVIEW 등의 고해상도 위성영상은 효율적이고 경제적으로 수치고도모형을 생성할 수 있는 정보를 제공하고 있다. 그러나, 이들 고해상도 위성영상으로부터 수치고도모형을 생성하기 위해서는 센서모형화, 에피폴라 영상 생성 그리고 영상정합에 대한 사전지식이 필요하다. 이들 중 에피폴라 영상생성은 중요한 인자이며 이에 대한 연구는 아직 미흡한 실정이다. 뿐만 아니라, IKONOS 위성영상으로부터 수치고도모형을 생성하는 연구는 다항식비례모형에 기반한 연구가 주로 이루어졌다. 이에 본 연구에서는 센서 독립적이면서 적은 수의 기준점만으로 센서모형화와 에피폴라 영상생성이 가능한 평행투영모형을 이용하여 수치고도모형을 생성하는 일련의 처리과정을 새롭게 제안하였다. 제안된 방법론은 IKONOS 위성영상을 이용하여 적용하고 평가하였다.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.28 no.3D
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• pp.437-444
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• 2008

In the paper, a methodology is verified to integrate IKONOS-2 satellite imagery and ALS dataset by compensating biases of RPC models. To achieve this, conjugate features from both data should be extracted in advance. For this purpose, linear features are chosen as conjugate features because they can be accurately extracted from man-made structures in urban area and more easily extracted than point features from ALS data. Then, observation equations are established from similarity measurements of the extracted features. During the process, several kinds of transformation functions were selected and used to register them. In addition, it was also analyzed how the number of linear features used as control features affects the accuracy of registration results. Finally, the results were evaluated by using check-points obtained from DGPS surveying techniques and it was clearly demonstrated that the proposed algorithms are appropriate to integrate these data.

• Journal of Korean Society for Geospatial Information Science
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• v.13 no.1 s.31
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• pp.55-61
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• 2005

Digital Elevation Model (DEM) generation from remotely sensed imagery is crucial for a variety of mapping applications such as ortho-photo generation, city modeling. High resolution imaging satellites such as SPOT-5, IKONOS, QUICK-BIRD, ORBVIEW constitute an excellent source for efficient and economic generation of DEM data. However, prerequisite knowledge in the areas of sensor modeling, epipolar resampling, and image matching is required to generate DEM from these high resolution satellite imagery. From the above requirements, epipolar resampling emerges as the most important factors. Research attempts in this area are still in high demand and short supply. Another cause that adds to the complication of the problem is that most studies of DEM generation from IKONOS scenes have been based on rational function model. In this paper, we proposed a new methodology for DEM generation from satellite scenes using parallel projection model which is sensor independent, makes it possible for sensor modeling and epipolar resampling by only few control points. The performance and feasibility of the developed methodology is evaluated through real dataset captured by IKONOS.

• Korean Journal of Remote Sensing
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• v.18 no.4
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• pp.221-231
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• 2002

In this study we applied a DEM generation algorithm developed in-house to satellite images at various resolution and discussed the results. We tested SPOT images at l0m resolution, EOC images at 6.6m and IKONOS images at 1m resolution. These images include the same urban area in Daejeon city. For camera model, we used Gupta & Hartley's(1997) DLT model for all three image sets. We carried out accuracy assessment using USGS DTED for SPOT and EOC and 23 check points for IKONOS. The assessment showed that SPOT DEM had about 38m RMS error, EOC DEM 12m RMS error and IKONOS DEM 6.5m RMS error. In terms of image resolution, SPOT and EOC DEM error corresponds to 2∼4 pixels where as IKONOS DEM error 6∼7pixels. IKONOS DEM contains more errors in pixels. However, in IKONOS DEM, individual buildings, apartments and major roads are identifiable. All three DEMs contained errors due to height discontinuity, occlusion and shadow. These experiments show that our algorithm can generate urban DEM from 1m resolution and that, however, we need to improve the algorithm to minimize effects of occlusion and building shadows on DEMs.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.21 no.1
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• pp.19-26
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• 2003

As recently, high-resolution satellite images of 1m spatial resolution are opened to the public and able to be used commercially, the studies that make ortho-images using them and apply to digital mapping and database of geo-spatial information system are having been progressed actively. Therefore, the purposes of this study are to establish the auto-extraction methods and to develope algorithms for automatically extracting buildings out of man-made structures, after making the IKONOS ortho-image. As the result of this study, we can extract buildings automatically at 72% out of the whole buildings. And we have analyzed the error trend by means of the comparison with ortho-image, digital map and drawing result, then we could know that obtain the good result for extraction of the building through the methods and algorithms of this study.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.25 no.3
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• pp.183-190
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• 2007

To make use of surveying data obtained from different sensors and different techniques, it is a pre-requite step that register them in a common coordinate system. For this purpose, we developed methodologies to register IKONOS-2 Satellite Imagery using LiDAR(Light Detection And Ranging) data. To achieve this, conjugate features from these data should be extracted in advance. In this study, linear features are chosen as conjugate features. Then, to register them, observation equations are established from similarity measurements of the extracted features and the results was evaluated statistically. The results clearly demonstrate that the proposed algorithms are appropriate to register these data.

• Journal of Korean Society of Forest Science
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• v.101 no.3
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• pp.356-364
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• 2012

This study was to estimate the biomass of Mt. Changbai mountain area using the IKONOS imagery and field survey data. Then, we prepared the regression function using the vegetation index derived from the IKONOS and biomass estimated from field measured data of previous studies, respectively. The five vegetation index which used in the regression model was SAVI, NDVI, SR, ARVI, and EVI. As a result, the rank of the R-square from coefficient of correlation was as follow, SAVI(0.84), NDVI(0.73), SR(0.59), ARVI(0.0036), EVI(0.0026). Finally, we estimated the biomass of non-measured area using the Soil Adjusted Vegetation Index (SAVI). This study can be used as reference methodology for the estimation of carbon sinks of primary forest.

• Journal of Korean Society for Geospatial Information Science
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• v.11 no.2 s.25
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• pp.61-66
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• 2003

The change detection using the satellite imagery and airphotos has been carried out in the application of terrain mapping, environment, forestry, facility detection, etc. The low-spatial resolution data such as Landsat, NOAA satellite images is generally used for automatic change detection, while on the other hand the high-spatial resolution data is used for change detection by image interpretation. The research to integrate automatic method with manual change detection through the high-spatial resolution satellite image is performed. but the problem such as shadow, building 'lean' due to perspective geometry and precision geocorrection was found. In this paper we performed change detection using the IKONOS satellite images, and present the concerning problem.

• Journal of Korean Society for Geospatial Information Science
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• v.15 no.4
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• pp.103-109
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• 2007

Ortho images and Digital Elevation Model (DEM) have been applied in various fields. It is necessary to acquire Ground Control Points (GCPs) for processing high resolution satellite images. However surveying GCPs require many time and expense. This study was performed to investigate whether GCPs automatically extracted from ortho images and DTED Level 2 can be applied to sensor modeling for high resolution satellite images. We analyzed the performance of the sensor model established by GCPs extracted automatically. We acquired GCPs by matching satellite image against ortho images. We included the height acquired from DTED Level 2 data in these GCPs. The spatial resolution of the DTED Level 2 data is about 30m. Absolution accuracy of this data is below 18m above MSL. The spatial resolution of ortho image is 1m. We established sensor model from IKONOS images using GCPs extracted automatically and generated DEMs from the images. The accuracy of sensor modeling is about $4{\sim}5$ pixel. We also established sensor models using GCPs acquired based on GPS surveying and generated DEMs. Two DEMs were similar. The RMSE of height from the DEM by automatic GCPs and DTED Level 2 is about 9 m. So we think that GCPs by DTED Level 2 and ortho image can use for IKONOS sensor modeling.