Go to the main menu
Skip to content
Go to bottom
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
Feature Selection for Image Classification of Hyperion Data
Kim, Yong Il ; Lee, Yong Ung ;
Korean Journal of Remote Sensing, volume 19, issue 2, 2003, Pages 18~171
Observation and Analysis of Shoreline Changes Using the Remote Unmanned Automatic Camera Monitoring System
Korean Journal of Remote Sensing, volume 19, issue 2, 2003, Pages 99~106
The shoreline changes were observed and analysed using the video image by a remote unmanned automatic camera monitoring system installed at Haeundae beach of Busan City. In order to analyse quantitatively the shoreline changes caused by waves and tides, the image averaging technique and the rectification technique for obliquely acquired image were applied to the video image during the typhoon Bart in September, 1999. The results showed that the camera monitoring system can be used as a very cost effective and efficient tool for monitoring shorelines which change continuously due to waves and tides.
A Study of Drought Susceptibility on Cropland Using Landsat ETM+ Imagery
Korean Journal of Remote Sensing, volume 19, issue 2, 2003, Pages 107~115
This research investigated the 2001 spring drought on croplands in South Korea using satellite imagery. South Korea has suffered from spring droughts almost every year. Meteorological indices have been used for monitoring droughts, however they don't tell the local severity of drought. Therefore, this research aimed at detecting the local, spatial pattern of drought severity at a cropland level. This research analyzed the agricultural drought using the wetness of remotely sensed pixels that affects the growth of early crops significantly in the spring. This research, specifically, analyzed the spatial distribution and severity of drought using the tasseled cap transformation and topographical factors. The wetness index from the tasseled cap transformation of Landsat 7 ETM/sub ＋/ imagery was very useful for detecting the 2001 spring drought susceptibility in agricultural croplands. Especially, the wetness values smaller than -0.2 were identified as the croplands that were suffering from serious water deficit. Using the water deficit pixels, drought severity was modeled finally.
Characteristics of Landsat ETM+ Image for Gomso Bay Tidal Flat Sediments
Korean Journal of Remote Sensing, volume 19, issue 2, 2003, Pages 117~133
A field survey and Landsat ETM+ image acquisition carried out simultaneously. Using these data, we attempted to establish relationships between tidal flat environmental factors and reflectance observed by ETM+, and to set up a new critical grain size useful for optical remote sensing. Although the grain size of 4
has been conventionally used as a critical size by sedimentologists, the correlation with optical reflectance was very low. Instead, the grain size of 2
showed a relatively high correlation coefficient, 0.699, with ETM+ band 4, except near tidal channels in upper tidal flat. We concluded that the grain size of 2
would be better to use for a critical grain size in Gomso Bay. The grain size also correlated well with moisture content having a correlation coefficient of -0.811 when the 2
criterion was used. The results of factor analysis showed moisture content was more important parameter than topographic relief, and they were different from German tidal flats in which topographic relief was the prior factor This can be explained by finer grain composition of the Gomso bay tidal flat. In short, moisture content and topography as well as grain size should be considered in tidal flat remote sensing.
Analysis of Land-cover Types Using Multistage Hierarchical flustering Image Classification
Korean Journal of Remote Sensing, volume 19, issue 2, 2003, Pages 135~147
This study used the multistage hierarchical clustering image classification to analyze the satellite images for the land-cover types of an area in the Korean peninsula. The multistage algorithm consists of two stages. The first stage performs region-growing segmentation by employing a hierarchical clustering procedure with the restriction that pixels in a cluster must be spatially contiguous, and finally the whole image space is segmented into sub-regions where adjacent regions have different physical properties. Without spatial constraints for merging, the second stage clusters the segments resulting from the previous stage. The image classification of hierarchical clustering, which merges step-by step two small groups into one large one based on the hierarchical structure of digital imagery, generates a hierarchical tree of the relation between the classified regions. The experimental results show that the hierarchical tree has the detailed information on the hierarchical structure of land-use and more detailed spectral information is required for the correct analysis of land-cover types.
Evaluation of The Image Segmentation Method for DEM Generation of Satellite Imagery
Korean Journal of Remote Sensing, volume 19, issue 2, 2003, Pages 149~157
In this study, for efficient replacement of sensor modelling of high-resolution satellite imagery, image segmentation method is applied to the test area of the SPOT-3 satellite imagery. After that, a third-order polynomial model in the sectioned area is compared with the RFM which Is to the entire in the test area. As results, plane error of the third-order polynomial model is lower(approximately 0.8m) than that of RFM. On the other hand, height error of RFM is lower(approximately 1.0m).
Building Roof Reconstruction in Remote Sensing Image using Line Segment Extraction and Grouping
Korean Journal of Remote Sensing, volume 19, issue 2, 2003, Pages 159~169
This paper presents a method for automatic 3-d building reconstruction using high resolution aerial imagery. First, by using edge preserving filtering, noise is eliminated and then images are segmented by watershed algorithm, which preserves location of edge pixels. To extract line segments between control points from boundary of each region, we calculate curvature of each pixel on the boundary and then find the control points. Line segment linking is performed according to direction and length of line segments and the location of line segments is adjusted using gradient magnitudes of all pixels of the line segment. Coplanar grouping and pplygonal patch formation are performed per region by selecting 3-d line segments that are matched using epipolar geometry and flight information. The algorithm has been applied to high resolution aerial images and the results show accurate 3D building reconstruction.
Feature Selection for Image Classification of Hyperion Data
Korean Journal of Remote Sensing, volume 19, issue 2, 2003, Pages 170~179
In order to classify Land Use/Land Cover using multispectral images, we have to give consequence to defining proper classes and selecting training sample with higher class separability. The process of satellite hyperspectral image which has a lot of bands is difficult and time-consuming. Furthermore, classification result of hyperspectral image with noise is often worse than that of a multispectral image. When selecting training fields according to the signatures in the study area, it is difficult to calculate covariance matrix in some clusters with pixels less than the number of bands. Therefore in this paper we presented an overview of feature extraction methods for classification of Hyperion data and examined effectiveness of feature extraction through the accuracy assesment of classified image. Also we evaluated the classification accuracy of optimal meaningful features by class separation distance, which is also a method for band reduction. As a result, the classification accuracies of feature-extracted image and original image are similar regardless of classifiers. But the number of bands used and computing time were reduced. The classifiers such as MLC, SAM and ECHO were used.