• Korean Journal of Remote Sensing
• /
• v.19 no.6
• /
• pp.465-478
• /
• 2003

This paper presents two methods for automatic estimation of threshold values in unsupervised change detection of multi-temporal remote sensing images. The proposed methods consist of two analytical steps. The first step is to compute the parameters of a 3-component Gaussian mixture model from difference or ratio images. The second step is to determine a threshold value using Bayesian rule for minimum error. The first method which is an extended version of Bruzzone and Prieto' method (2000) is to apply an Expectation-Maximization algorithm for estimation of the parameters of the Gaussian mixture model. The second method is based on an iterative thresholding algorithm that successively employs thresholding and estimation of the model parameters. The effectiveness and applicability of the methods proposed here were illustrated by two experiments and one case study including the synthetic data sets and KOMPSAT-1 EOC images. The experiments demonstrate that the proposed methods can effectively estimate the model parameters and the threshold value determined shows the minimum overall error.

• Proceedings of the Korean Association of Geographic Inforamtion Studies Conference
• /
• 2003.04a
• /
• pp.588-595
• /
• 2003

High resolution panchromatic satellite images collected by sensors such as IRS-1C/D and KOMPSAT-1 have a spatial resolution of approximately 6 ${\times}$ 6 ㎡, making them very attractive for urban applications. However, the spectral information present in these images is very limited. In order to overcome this limitation, an object-oriented classification approach is used to identify basic land cover types in urban areas. Before an image can be classified it is segmented at different aggregation levels using a multiresolution segmentation approach. In the course of this segmentation various statistical as well as topological information is collected for each segment. Based on this information it is possible to classify image objects and to arrive at much better results than by looking only at single pixels. Using an image recorded by KOMPSAT-1 over the City of Vienna a land cover classification was carried out for two areas. One was used to set up the rules for the different land cover types. The second subset was classified based on these rules, only adjusting some of the functions governing the classification process.

• Aerospace Engineering and Technology
• /
• v.3 no.2
• /
• pp.141-148
• /
• 2004

The importance of satellite data for numerous applications is stressed by the fact that many countries have given the development of space technologies very high priority. Among these, Korea has established a medium-term space development strategy to promote space development both on a scientific as well as commercial level. As part of this strategy, the first operational earth-observation, multi-purpose satellite(KOMPSAT-1) was launched successfully in December, 1999. The Electro-Optical Camera (EOC) on board of KOMPSAT-1 supplies panchromatic images with a spatial resolution of 6.6m Until April, 2004, it collected over 150.000 images of the Korean Peninsula and the rest of the world. This paper examines the use of remote sensing data to analyze urban growth in the city of Daejeon from 1960 to 2003. By using visual interpretation, land use maps are created.

• Proceedings of the KSRS Conference
• /
• 2005.10a
• /
• pp.257-259
• /
• 2005

A crop management system was developed using Visual Basic and ArcGIS VBA. The system is operated on ArcGlS 8.3 with Microsoft Access MOB. Landsat +ETM, KOMPSAT-l EOC, ASTER VNIR and IKONOS panchromatic (pan) and multi-spectral (MIS) images were included in the system to understand what kind of agriculture-related information can be extracted for each images. Agriculture related data inventories using crop cover information such as texture and average pixel value of the crop based on cultivation calendar were designed ,and implemented. Three IKONOS images (May 25,2001, December 25,2001, October 23,2003) were loaded in the system to show crop cover characteristics such as rice, pear, grape, red pepper, garlic, and surface water cover of reservoir with field surveys. GIS layers such as DEM (Digital Elevation Model), stream, road, soil, land use and administration boundary were also supplied and can be overlaid with images to enhance the understanding the general agricultural characteristics and identifying the location easily.

• Journal of The Korean Society of Agricultural Engineers
• /
• v.46 no.7
• /
• pp.15-21
• /
• 2004

This study is to present a standardized agricultural land use classification scheme at various spatial resolution (from 1 m to 30 m) of satellite images including Landsat TM, KOMPSAT-1 EOC, ASTER VNIR and IKONOS panchromatic (PAN) and multi-spectral (MS) images. The satellite images were interpreted especially for identifying agricultural land use, crop types, agricultural facilities and structures of 18 items. It was found that there is a threshold spatial resolution between 4 m and 6.6 m to identify the full items. Thus it is suggested that IKONOS fusion image (MS enhanced by PAN) is required to produce land use map for agricultural purpose.

• Korean Journal of Remote Sensing
• /
• v.21 no.1
• /
• pp.83-89
• /
• 2005

This study utilized a spatial region growing segmentation and a classification using fuzzy membership vectors to detect the changes in the images observed at different dates. Consider two co-registered images of the same scene, and one image is supposed to have the class map of the scene at the observation time. The method performs the unsupervised segmentation and the fuzzy classification for the other image, and then detects the changes in the scene by examining the changes in the fuzzy membership vectors of the segmented regions in the classification procedure. The algorithm was evaluated with simulated images and then applied to a real scene of the Korean Peninsula using the KOMPSAT-l EOC images. In the expertments, the proposed method showed a great performance for detecting changes in land-cover.

• Journal of Korean Society for Geospatial Information Science
• /
• v.10 no.5 s.23
• /
• pp.67-74
• /
• 2002

The geometriccorrection of a satellite imagery is performed by making a systematic correction with satellite ephemerides and attitude angles followed by employing the Ground Control Points (GCSs) or Digital Elevation Models (DEMs). In a remote area or an inaccessible area, however, GCPs are unavailable to be surveyed and thus they can be obtained only by reading maps, which are not accurate in reality. In this study, we performed the systematic correction process to the inaccessible area and the precise geometric correction process to the adjacent accessible area by using GCPs. Then we analyzed the correlation between the two geo-referenced Korea Multiurpose Satellite (KOMPSAT-1 EOC) images. A new geometrical correction for the inaccessible area imagery is achieved by applying the correlation to the inaccessibleimagery. By employing this new method, the accuracy of the inaccessible area imagery is significantly improved absolutely and relatively.

• Korean Journal of Remote Sensing
• /
• v.12 no.1
• /
• pp.81-88
• /
• 1996

The effects of atmospheric refraction of rays on the geometry of high-resolution images such as the KOMPSAT-EOC images are described. An atmospheric refraction mechanism is modelled and the geometric errors caused by the refraction are calculated from the model simulation. This paper shows that a maximum geometric error of 1 pixel (7m) occurs from the standard atmospheric condition. Severer geometric distortions in images cause from an atmopheric abnormality.

• Proceedings of the KSRS Conference
• /
• 2004.10a
• /
• pp.144-147
• /
• 2004

Two different sensors (here, KOMPSAT and RADARSAT) are considered for ship detection, and are used to delineate the detection performance for their data. The experiments are set for coastal regions of Mokpo Port and Ulsan Port and field experiments on board pilot boat are conducted to collect in situ ship validation information such as ship type and length. This paper introduce mainly the experiment result of ship detection by both RADARSAT SAR imagery and landbased RADAR data, operated by the local Authority of South Korea, so called vessel traffic system (VTS) radar. Fine imagery of Ulsan Port was acquired on June 19, 2004 and in-situ data such as wind speed and direction, taking pictures of ships and natural features were obtained aboard a pilot ship. North winds, with a maximum speed of 3.1 m/s were recorded. Ship's position, size and shape and natural features of breakwaters, oil pipeline and alongside ship were compared using SAR and VTS. It is shown that KOMPSAT/EOC has a good performance in the detection of a moving ship at a speed of 7 kts or more an hour that ship and its wake can be imaged. The detection capability of RADARSAT doesn't matter how fast ship is running and depends on a ship itself, e.g. its material, length and type. Our results indicate that SAR can be applicable to automated ship detection for a VTS and SAR combination service.

• Korean Journal of Remote Sensing
• /
• v.21 no.3
• /
• pp.243-252
• /
• 2005

Wavelet transform and its inverse processing provide the effective framework for data fusion. The purpose of this study is to investigate applicability of wavelet transform using texture images for the urban remote sensing application. We tried several experiments regarding image fusion by wavelet transform and texture imaging using high resolution images such as IKONOS and KOMPSAT EOC. As for texture images, we used homogeneity and ASM (Angular Second Moment) images according that these two types of texture images reveal detailed information of complex features of urban environment well. To find out the useful combination scheme for further applications, we performed DWT(Discrete Wavelet Transform) and IDWT(Inverse Discrete Wavelet Transform) using texture images and original images, with adding edge information on the fused images to display texture-wavelet information within edge boundaries. The edge images were obtained by the LoG (Laplacian of Gaussian) processing of original image. As the qualitative result by the visual interpretation of these experiments, the resultant image by each fusion scheme will be utilized to extract unique details of surface characterization on urban features around edge boundaries.