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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 20, Issue 6 - Dec 2004
Volume 20, Issue 5 - Oct 2004
Volume 20, Issue 4 - Aug 2004
Volume 20, Issue 3 - Jun 2004
Volume 20, Issue 2 - Apr 2004
Volume 20, Issue 1 - Feb 2004
Selecting the target year
A Study on Change of Average SCS-CN Value by the Spatial Resolution
Chang Eun-Mi ; Jung In-Kyun ;
Korean Journal of Remote Sensing, volume 20, issue 6, 2004, Pages 361~368
Hydraulic models has a module to calculate SCS-CN values in order to estimate amount of water flow, which can be done with remotely sensed data and GIS data. The choice of the ancillary data tends to determine the range of SCS-CN values. We compare the results of SCS-CN value with satellite data of different spatial resolution and with soil maps of different scale. Mokhyun river basin was chosen,partly because of availbility of water quality and quantity data, partly because of rapid changes in land use and land cover since last ten years. The average CN values were calculated with spatial resolutions of 2.5 meter and 30 meter, We could not find any different result due to spatial resolution of CN resolution but due to both soil maps and to land cover maps. Further studies should be done for more than two kinds of satellite data.
Application of Linear Spectral Mixture Analysis to Geological Thematic Mapping using LANDSAT 7 ETM+ and ASTER Satellite Imageries
Kim Seung Tae ; Lee Kiwon ;
Korean Journal of Remote Sensing, volume 20, issue 6, 2004, Pages 369~382
The purpose of this study is the investigation of applicability of LSMA(Linear Spectral Mixture Analysis) on the geological uses with different radiometric and spatial types of sensor images such as Terra ASTER and LANDSAT 7 ETM+. As for the actual application case, geologic mapping for mineral exploration using ASTER and ETM+ at the Mongolian plateau region was carried out. After the pre-processing such as the geometric corrections and calibration of radiance, 7 endmembers, as spectral classes for geologic rock types, related to spectral signature deviation for the given application was determined by the pre-surveyed geological mapping information and the correlation matrix analysis, and total 20 images of ASTER and ETM+ were used to LSMA processing. As the results, fraction maps showing individual mineral types in the study area are presented. It concluded that this approach based on LSMA using ETM+ and ASTER is regarded as one of the effective schemes for geologic remote sensing.
Assessing Spatial Uncertainty Distributions in Classification of Remote Sensing Imagery using Spatial Statistics
Park No-Wook ; Chi Kwang-Hoon ; Kwon Byung-Doo ;
Korean Journal of Remote Sensing, volume 20, issue 6, 2004, Pages 383~396
The application of spatial statistics to obtain the spatial uncertainty distributions in classification of remote sensing images is investigated in this paper. Two quantitative methods are presented for describing two kinds of uncertainty; one related to class assignment and the other related to the connection of reference samples. Three quantitative indices are addressed for the first category of uncertainty. Geostatistical simulation is applied both to integrate the exhaustive classification results with the sparse reference samples and to obtain the spatial uncertainty or accuracy distributions connected to those reference samples. To illustrate the proposed methods and to discuss the operational issues, the experiment was done on a multi-sensor remote sensing data set for supervised land-cover classification. As an experimental result, the two quantitative methods presented in this paper could provide additional information for interpreting and evaluating the classification results and more experiments should be carried out for verifying the presented methods.
Analysis of Urban Surface Temperature Distribution Properties Using Spatial Information Technologies
Lee Kwang-Jae ; Jo Myung-Hee ;
Korean Journal of Remote Sensing, volume 20, issue 6, 2004, Pages 397~408
In this study, surface temperature which was extracted from Landsat TM band 6 was compared and analyzed with the AWS(Automatic Weather System) observation data for studying urban heat environment properties with possibility of remote sensing data application. In order to verification of the distribution properties of urban surface temperature, correlation analysis between surface temperature and NDVI, the distribution properties of urban surface temperature by land use/cover patterns were carried out by GIS spatial analysis techniques. The results presented that the spatial distribution of urban surface temperature was very different depending on various land use/cover patterns of surrounding areas. Also there was the reverse linear relationship between surface temperature and NDVI. These results will be worked as one of the major factors for environmentally sustainable urban planning considering the characteristics of weather environments in the near future.
A Study on Regular Grid Based Real-Time Terrain LOD Algorithm for Enhancing Memory Efficiency
Whangbo Taeg-keun ; Yang Young-Kyu ; Moon Min-Soo ;
Korean Journal of Remote Sensing, volume 20, issue 6, 2004, Pages 409~418
LOD is a widely used technique in 3D game and animation to represent large 3D data sets smoothly in real-time. Most LOD algorithms use a binary tree to keep the ancestor information. A new algorithm proposed in this paper, however, do not keep the ancestor information, thus use the less memory space and rather increase the rendering performance. To verify the efficiency of the proposed algorithm, performance comparison with ROAM is conducted in real-time 3D terrain navigation. Result shows that the proposed algorithm uses about 1/4 of the memory space of ROAM and about 4 times faster than ROAM.
Dempster-Shafer Fusion of Multisensor Imagery Using Gaussian Mass Function
Lee Sang-Hoon ;
Korean Journal of Remote Sensing, volume 20, issue 6, 2004, Pages 419~425
This study has proposed a data fusion method based on the Dempster-Shafer evidence theory The Dempster-Shafer fusion uses mass functions obtained under the assumption of class-independent Gaussian assumption. In the Dempster-Shafer approach, uncertainty is represented by 'belief interval' equal to the difference between the values of 'belief' function and 'plausibility' function which measure imprecision and uncertainty By utilizing the Dempster-Shafer scheme to fuse the data from multiple sensors, the results of classification can be improved. It can make the users consider the regions with mixed classes in a training process. In most practices, it is hard to find the regions with a pure class. In this study, the proposed method has applied to the KOMPSAT-EOC panchromatic image and LANDSAT ETM+ NDVI data acquired over Yongin/Nuengpyung. area of Kyunggi-do. The results show that it has potential of effective data fusion for multiple sensor imagery.