• Proceedings of the KSRS Conference
• /
• 1998.09a
• /
• pp.325-330
• /
• 1998

The first Korean remote sensing satellite, Korea Multi-Purpose Satellite (KOMPSAT-1), is going to be launched in 1999. This will carry a 7m resolution Electro-Optical Camera (EOC) for earth observation. The primary mission of the KOMPSAT-1 is to acquire stereo imagery over the Korean peninsular for the generation of 1:25,000 cartographic maps. For this mission, research is being carried out to assess the possibilities of automated or semi-automated mapping of EOC data and to develop, if necessary, such enabling tools. This paper discusses the issue of automated DEM generation from EOC data and identifies some important aspects in developing a for DEM generation system from EOC data. This paper also presents the current status of the development work for such a system. The development work has focused on sensor modelling, stereo matching and DEM interpolation techniques. The performance of the system is shown with a SPOT stereo pair. A DEM generated from a commercial software is also presented for comparison. The paper concludes that the proposed system creates preferable results to the commercial software and suggests future developments for successful generation of DEM for EOC data.

• Korean Journal of Remote Sensing
• /
• v.18 no.1
• /
• pp.61-69
• /
• 2002

The purpose of Electro-Optical Camera (EOC), the primary payload of KOMPSAT-1, is to collect high resolution visible imagery of the Earth including Korean Peninsula. EOC images will be distributed to the public or many user groups including government, public corporations, academic or research institutes. KARI will offer the online service to the users through internet. Some application, e.g., generation of Digital Elevation Model (DEM), needs a secondary data such as satellite ephemeris data, attitude data to process the EOC imagery. EOC imagery with these ancillary information will be distributed in a file of Hierarchical Data Format (HDF) file formal. HDF is a physical file format that allows storage of many different types of scientific data including images, multidimensional data arrays, record oriented data, and point data. By the lack of public domain softwares supporting HDF file format, many public users may not access EOC data without difficulty. The purpose of this research is to develop a browsing system of EOC data for the general users not only for scientists who are the main users of HDF. The system is PC-based and huts user-friendly interface.

• Proceedings of the KSRS Conference
• /
• 2002.10a
• /
• pp.780-785
• /
• 2002

As the KOMPSAT-1 satellite can roll tilt up to $\pm$45$^{\circ}$, we have analyzed some EOC images taken at different tilt angles fur this study. The required ground coordinates for bundle adjustment and geometric accuracy, are read from the digital map produced by the National Geography Institution, at a scale of 1:5, 000. These are the steps taken for the tilting angle of KOMPSAT-1 satellite to be present in the evaluation of the accuracy of the geometric of each different stereo image data: Firstly, as the tilting angle is different in each image, the satellite dynamic characteristic must be determined by the sensor modeling. Then the best sensor modeling equation is determined. The result of this research, the difference between the RMSE values of individual stereo images is due more the quality of image and ground coordinates than to the tilt angle. The bundle adjustment using three KOMPSAT-1 stereo pairs, first degree of polynomials for modeling the satellite position were sufficient.

• Proceedings of the KSRS Conference
• /
• 2004.10a
• /
• pp.518-521
• /
• 2004

Change detection is one of the common research topics in remote sensing. In general, global change detection methods using image difference method, etc, are used in low resolution images and local change detection methods using floating windows, etc, are used in high resolution images. But, these methods have disadvantages in practical use. If changed area images are automatically produced, these images will be used in public area such as regional planning, regional development managements. In this research, we developed new change detection method applicable KOMPSAT EOC images. This method automatically produces subset images in changed area.

• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
• /
• 2003.04a
• /
• pp.265-269
• /
• 2003

최근 인공위성 영상자료는 주기적인 획득 시기를 가지고 있고 수치 지형도에 비해 쉽게 인지할 수 있기 때문에 지형변화 모니터링 분야에서 활발하게 이용되고 있다 그러나 인공위성 영상자료들은 촬영조건 및 센서의 특성에 따라 다른 기하학적인 왜곡을 포함하고 있을 뿐만 아니라 공간, 방사 및 분광 해상도가 상이하기 때문에 정밀한 분석 결과 산출에 어려움이 있다. 즉, 두 개 이상의 영상을 비교 분석하기 위해 기본적인 센서 정보의 차이에서 발생하는 정오차를 소거하고 지형기복에 의해 발생하는 부정오차를 제거하기 위한 정밀 기하보정은 반드시 선행되어야 한다. 따라서, 본 연구에서는 공간해상도가 다르기 때문에 발생하는 정오차 및 부정오차를 제거하기 위해 정밀정합을 실시하였다. 정밀 정합된 kompsat EOC 및 Landsat TM 영상으로 토지피복 변화를 탐지함으로써 위치정확도가 높은 탐지결과를 얻을 수 있었다. 정확한 위치정보를 가지는 탐지 결과는 지형지물의 갱신이나 다양한 GIS 응용의 기본자료로서 사용할 수 있을 것으로 기대된다.

• Journal of Astronomy and Space Sciences
• /
• v.17 no.1
• /
• pp.117-122
• /
• 2000

The KOMPSAT(Korea Multi-Purpose SATellite) has two optical imaging instruments called EOC(Electro-Optical Camera) and OSMI (Ocean Scanning Multispectral Imager). The image data of these instruments are transmitted to ground station and restored correctly after post-processing with the telemetry data transfeered from KOMPSAT spacecraft. The major timing information of the KOMPSAT is OBT (On-Board Time) which is formatted by the on-board computer of the spacecraft, based on 1Hz sync. pulse coming from the GPS receiver involved. The OBT is transmitted to ground station with the house-keeping telemetry data of the spacecraft while it is distributed to the instruments via 1553B data bus for synchronization during imaging and formatting. The timing information contained in the spacecraft telemetry data would have direct relation to the image data of the instruments, which should be well explained to get a more accurate image. This paper addresses the timing analysis of the KOMPSAT spacecraft and instruments, including the gyro data timing analysis for the correct restoration of the EOC and OSMI image data at ground station.

• Proceedings of the Korean Association of Geographic Inforamtion Studies Conference
• /
• 2003.04a
• /
• pp.581-587
• /
• 2003

독립 요소 분석 (Independent Component Analysis: ICA)는 텍스처를 의미 있는 특징으로 변환하는 강인한 영상 필터를 생성하기 위한 확률적 방법이다. ICA는 고차통계적 특성을 사용하여 ICA 필터와 독립 요소를 동시에 학습한다. 제안한 분류 방법은 fast ICA 알고리즘을 사용하여 KOMPSAT 영상으로부터 ICA 필터를 생성한 다음, 필터에 의해 투영된 텍스처들의 특징들을 독립 평면상에서 무감독 방법으로 분류한다. KOMPSAT 영상은 텍스처 성분이 뚜렷하지 않는 영역이 존재하기 때문에 본 논문에서는 투영된 특징 값들과 윈도우 내의 정규화된 평균 화소값으로 특징 벡터를 재구성하였다. 분류 방법으로는 K-means 클러스터링을 적용하였다. 6.6m 해상도를 가진 KOMPSAT 흑백 영상에 대해 제안한 방법은 우수한 분류 성능을 보인다.

• Proceedings of the Korean Association of Geographic Inforamtion Studies Conference
• /
• 2003.04a
• /
• pp.575-580
• /
• 2003

KOMPSAT-1 위성의 EOC영상은 위성에서 지구를 촬영하는 동안 발생하는 영상 왜곡을 포함하고 있다. 본 연구는 EOC영상의 영상왜곡을 보정하기 위하여 수치지도를 이용하는 정밀기하보정에 대하여 연구한다. 정밀기하보정 과정은 수치지도와 EOC영상의 좌표계를 통합하는 과정을 거쳐 오버레이를 만들어 수치지도의 삼각점을 기준으로 위성영상에서 GCP를 선택하고, 이 GCP를 이용하여 위성 영상을 딜로니 삼각형들의 Mesh형태로 변환하여 모든 딜로니 삼각형을 리샘플링하는 과정을 거쳐 보정된 EOC영상을 얻는다.

• Proceedings of the Korean Association of Geographic Inforamtion Studies Conference
• /
• 2003.04a
• /
• pp.22-25
• /
• 2003

EOC(Electro Optical Camera)는 한반도 및 전 세계 육지 영역 관측용으로 설계되었다. EOC는 1999년 12월 21일 발사된 다목적 실용위성 1호에 탑재되어 가시광 대역(510 ～730nm)으로 입사하는 복사 정보를 수집해 왔다. 획득된 EOC 영상 자료는 다목적 실용위성 1호의 탑재체 자료전송 시스템(Payload Data Transmission System, PDTS)을 통해 지상으로 전송되며, 수신된 자료에 대한 방사 보정 및 기하 보정 등의 일련의 전처리(Pre-processing) 과정을 거쳐 EOC 표준 영상이 생성된다. EOC 영상에 대한 MTF 보상은 방사 보정 후 수행될 수 있으며, 다목적 실용위성 지상국에서는 사용자의 요구에 따라 EOC 영상에 대한 MTF 보상을 수행하고 그 결과를 제공한다. MTF 보상은 EOC의 점 확산 함수(Point Spread Function)를 이용하여 수행되며, 현재 Wiener 필터를 이용하여 수행되고 있다. 본문에서는 현재 다목적 실용위성 1호 영상처리시스템의 EOC 영상에 대한 MTF 보상을 소개하고, EOC의 점 확산 함수에 기초하여 역 필터(Inverse Filter) 및 의사 역 필터(Pseudo Inverse Filter)를 제작, EOC 영상에 대한 MTF 보상 수행 후 그 결과를 Wiener 필터를 이용한 결과와 비교, 분석한다.

• Korean Journal of Remote Sensing
• /
• v.23 no.6
• /
• pp.507-520
• /
• 2007

Satellite passive microwave(PM) sensors have been observing polar sea ice concentration(SIC), ice temperature, and snow depth since 1970s. Among them SIC is playing an important role in the various studies as it is considered the first factor for the monitoring of global climate and environment changes. Verification and correction of PM SIC is essential for this purpose. In this study, we calculated SIC from KOMPSAT-1 EOC images obtained from Arctic sea ice edges from July to August 2005 and compared with SSM/I SIC calculated from NASA Team(NT) algorithm. When we have no consideration of sea ice types, EOC and SSM/I NT SIC showed low correlation coefficient of 0.574. This is because there are differences in spatial resolution and observing time between two sensors, and the temporal and spatial variation of sea ice was high in summer Arctic ice edge. For the verification of SSM/I NT SIC according to sea ice types, we divided sea ice into land-fast ice, pack ice, and drift ice from EOC images, and compared them with SSM/I NT SIC corresponding to each ice type. The concentration of land-fast ice between EOC and SSM/I SIC were calculated very similarly to each other with the mean difference of 0.38%. This is because the temporal and spatial variation of land-fast ice is small, and the snow condition on the ice surface is relatively dry. In case of pack ice, there were lots of ice ridge and new ice that are known to be underestimated by NT algorithm. SSM/I NT SIC were lower than EOC SIC by 19.63% in average. In drift ice, SSM/I NT SIC showed 20.17% higher than EOC SIC in average. The sea ice with high concentration could be included inside the wide IFOV of SSM/I because the drift ice was located near the edge of pack ice. It is also suggested that SSM/I NT SIC overestimated the drift ice covered by wet snow.