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REFERENCE LINKING PLATFORM OF KOREA S&T JOURNALS
> Journal Vol & Issue
Korean Journal of Remote Sensing
Journal Basic Information
Journal DOI :
The Korean Society of Remote Sensing
Editor in Chief :
Volume & Issues
Volume 19, Issue 6 - Dec 2003
Volume 19, Issue 5 - Oct 2003
Volume 19, Issue 4 - Aug 2003
Volume 19, Issue 3 - Jun 2003
Volume 19, Issue 2 - Apr 2003
Volume 19, Issue 1 - Feb 2003
Selecting the target year
Analysis of Forest Cover Information Extracted by Spectral Mixture Analysis
Korean Journal of Remote Sensing, volume 19, issue 6, 2003, Pages 411~419
An area corresponding to the spatial resolution of optical remote sensor imagery often includes more than one pure surface material. In such case, a pixel value represents a mixture of spectral reflectance of several materials within it. This study attempts to apply the spectral mixture analysis on forest and to evaluate the information content of endmember fractions resulted from the spectral unmixing. Landsat-7 ETM+ image obtained over the study area in the Kwangneung Experimental Forest was initially geo-referenced and radiometrically corrected to reduce the atmospheric and topographic attenuations. Linear mixture model was applied to separate each pixel by the fraction of six endmember: deciduous, coniferous, soil, built-up, shadow, and rice/grass. The fractional values of six endmember could be used to separate forest cover in more detailed spatial scale. In addition, the soil fraction can be further used to extract the information related to the canopy closure. We also found that the shadow effect is more distinctive at coniferous stands.
Radarsat-1 Doppler Information Extraction Technique Using Both Received Echo Data and Orbital and Attitude Information of Satellite
Korean Journal of Remote Sensing, volume 19, issue 6, 2003, Pages 421~430
The extraction technique for Doppler information(Doppler centroid frequency(f
) and it's rate(f
) is very important to make an image from the radar echo signal data. Clutterlock and auto-focusing techniques have been widely used to extract accurate Doppler information. But both techniques are not easy to implement in SAR processor and need quite lots of time to calculate accurate f
because they are generally based on echo signal data only. In this paper we suggest hybrid method for Doppler extraction using both of echo signal data and orbital and attitude information of satellite. In this method CDE(Correlation Doppler Estimation) technique is only used to estimate exact modular f
using received echo signal data and rest of other algorithms are based on simple mathematical model of geometry between satellite and ground targets as well as the Doppler frequency ambiguity resolving problem. The experimental results using Radarsat-1 signal data shows that the proposed method can be effectively used for the extraction of Doppler information.
Analysis on 3D Positioning Precision Using Mobile Mapping System Images in Photograrmmetric Perspective
Korean Journal of Remote Sensing, volume 19, issue 6, 2003, Pages 431~445
In this paper, we experimentally investigated the precision of 3D positioning using 4S-Van images in photograrmmetric perspective. The 3D calibration target was built over building facade outside and was captured separately by two CCD cameras installed in 4S-Van. After then, we determined the interior orientation parameter for each CCD camera through self-calibration technique. With the interior orientation parameter computed, the bundle adjustment was performed to obtain the exterior orientation parameters simultaneously for two CCD cameras using calibration target image and object coordinates. The reverse lens distortion coefficients were computed and acquired by least squares method so as to introduce lens distortion into epipolar line. It was shown that the reverse lens distortion coefficients could transform image coordinates into lens distorted image coordinates within about 0.5 pixel. The proposed semi-automatic matching scheme incorporated with lens distorted epipolar line was implemented with scene images captured by 4S-Van in moving. The experimental results showed that the precision of 3D positioning from 4S-Van images in photograrmmetric perspective is within 2cm in the range of 20m from the camera.
A Study on the Analysis of Geo-Accuracy with KOMPSAT-1 EOC Pass Imagery
Korean Journal of Remote Sensing, volume 19, issue 6, 2003, Pages 447~456
This study investigated the method for obtaining 3-dimensional terrain information on inaccessable areas by evaluating geometric accuracy of the EOC pass image and scene image acquired from the KOMPSAT-1 satellite. For this purpose, the following four experiments were conducted to evaluate the accuracy of the KOMPSAT-1 EOC satellite data. 1) Calculation of ground coordinates by using ancillary data and image coordinates on Level 1R that were processed by the pre-processing system of KOMPSAT-1. 2) Calculation of 3-dimensional ground coordinates from the ground coordinates of stereo images calculated by using ancillary data, based on space intersections. 3) Execution of bundle adjustment by using GCP (Ground Control Point) extracted in a part of the stereo pass image (KOMPSAT-1 EOC, 1 scene size); and then, evaluation of the ground coordinates from the calculated exterior orientation. 4) Evaluation of accuracy by applying the exterior orientation calculated from 3) To the whole pass image.
Fast Triangulation of Terrain Data through Unique Point Extraction
Korean Journal of Remote Sensing, volume 19, issue 6, 2003, Pages 457~464
Triangulated irregular network is one of the most frequently used terrain modeling methods. It represents terrain precisely using only a small amount of data, and enables fast rendering of terrain. In this paper, ridges and valleys are extracted from the terrain, and used as a set of vertices for the construction of triangulated irregular network. An experiment shows the new method reduces the time for construction of the triangulated irregular network significantly with almost equal amount of induced error.
Automatic Estimation of Threshold Values for Change Detection of Multi-temporal Remote Sensing Images
Korean Journal of Remote Sensing, volume 19, issue 6, 2003, Pages 465~478
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.
Image Classification Using Modified Anisotropic Diffusion Restoration
Korean Journal of Remote Sensing, volume 19, issue 6, 2003, Pages 479~490
This study proposed a modified anisotropic diffusion restoration for image classification. The anisotropic diffusion restoration uses a probabilistic model based on Markov random field, which represents geographical connectedness existing in many remotely sensed images, and restores them through an iterative diffusion processing. In every iteration, the bonding-strength coefficient associated with the spatial connectedness is adaptively estimated as a function of brightness gradient. The gradient function involves a constant called "temperature", which determines the amount of discontinuity and is continuously decreased in the iterations. In this study, the proposed method has been extensively evaluated using simulated images that were generated from various patterns. These patterns represent the types of natural and artificial land-use. The simulated images were restored by the modified anisotropic diffusion technique, and then classified by a multistage hierarchical clustering classification. The classification results were compared to them of the non-restored simulation images. The restoration with an appropriate temperature considerably reduces error in classification, especially for noisy images. This study made experiments on the satellite images remotely sensed on the Korean peninsula. The experimental results show that the proposed approach is also very effective on image classification in remote sensing.