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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 28, Issue 6 - Dec 2012
Volume 28, Issue 5 - Oct 2012
Volume 28, Issue 4 - Aug 2012
Volume 28, Issue 3 - Jun 2012
Volume 28, Issue 2 - Apr 2012
Volume 28, Issue 1 - Feb 2012
Selecting the target year
A Study on Fast Extraction of Endmembers from Hyperspectral Image Data
Kim, Kwang-Eun ;
Korean Journal of Remote Sensing, volume 28, issue 4, 2012, Pages 347~355
DOI : 10.7780/kjrs.2012.28.4.1
A fast algorithm for endmember extraction is proposed in this study which extracts min. and max. pixels from each band after MNF transform as candidate pixels for endmember. This method finds endmembers not from the entire image pixels but only from the previously extracted candidate pixels. The experimental results by N-FINDR using a simulated hyperspectral image data and AVIRIS Cuprite image data showed that the proposed fast algorithm extracts the same endmembers with the conventional methods. More studies on the effect of noise and more adaptive criteria in extracting candidate pixels are expected to increase the usability of this method for more fast and efficient analysis of hyperspectral image data.
Anomaly Detection from Hyperspectral Imagery using Transform-based Feature Selection and Local Spatial Auto-correlation Index
Park, No-Wook ; Yoo, Hee-Young ; Shin, Jung-Il ; Lee, Kyu-Sung ;
Korean Journal of Remote Sensing, volume 28, issue 4, 2012, Pages 357~367
DOI : 10.7780/kjrs.2012.28.4.2
This paper presents a two-stage methodology for anomaly detection from hyperspectral imagery that consists of transform-based feature extraction and selection, and computation of a local spatial auto-correlation statistic. First, principal component transform and 3D wavelet transform are applied to reduce redundant spectral information from hyperspectral imagery. Then feature selection based on global skewness and the portion of highly skewed sub-areas is followed to find optimal features for anomaly detection. Finally, a local indicator of spatial association (LISA) statistic is computed to account for both spectral and spatial information unlike traditional anomaly detection methodology based only on spectral information. An experiment using airborne CASI imagery is carried out to illustrate the applicability of the proposed anomaly detection methodology. From the experiments, anomaly detection based on the LISA statistic linked with the selection of optimal features outperformed both the traditional RX detector which uses only spectral information, and the case using major principal components with large eigen-values. The combination of low- and high-frequency components by 3D wavelet transform showed the best detection capability, compared with the case using optimal features selected from principal components.
Comparative Analysis of Target Detection Algorithms in Hyperspectral Image
Shin, Jung-Il ; Lee, Kyu-Sung ;
Korean Journal of Remote Sensing, volume 28, issue 4, 2012, Pages 369~392
DOI : 10.7780/kjrs.2012.28.4.3
Recently, many target detection algorithms were developed for hyperspectral image. However, almost of these studies focused only accuracy from 1 or 2 data sets to validate and compare the algorithms although they give limited information to users. This study aimed to compare usability of target detection algorithms with various parameters. Five parameters were proposed to compare sensitivity in aspect of detection accuracy which are related with radiometric and spectral characteristics of target, background and image. Six target detection algorithms were compared in aspect of accuracy and efficiency (processing time) by variation of the parameters and image size, respectively. The results shown different usability of each algorithm by each parameter in aspect of accuracy. Second order statistics based algorithms needed relatively long processing time. Integrated usabilities of accuracy and efficiency were various by characteristics of target, background and image. Consequently, users would consider appropriate target detection algorithms by characteristics of data and purpose of detection.
Assessment of Topographic Normalization in Jeju Island with Landsat 7 ETM+ and ASTER GDEM Data
Hyun, Chang-Uk ; Park, Hyeong-Dong ;
Korean Journal of Remote Sensing, volume 28, issue 4, 2012, Pages 393~407
DOI : 10.7780/kjrs.2012.28.4.4
This study focuses on the correction of topographic effects caused by a combination of solar elevation and azimuth, and topographic relief in single optical remote sensing imagery, and by a combination of changes in position of the sun and topographic relief in comparative analysis of multi-temporal imageries. For the Jeju Island, Republic of Korea, where Mt. Halla and various cinder cones are located, a Landsat 7 ETM+ imagery and ASTER GDEM data were used to normalize the topographic effects on the imagery, using two topographic normalization methods: cosine correction assuming a Lambertian condition and assuming a non-Lambertian c-correction, with kernel sizes of
pixels. The effects of each correction method and kernel size were then evaluated. The c-correction with a kernel size of
produced the best result in the case of a land area with various land-cover types. For a land-cover type of forest extracted from an unsupervised classification result using the ISODATA method, the c-correction with a kernel size of
produced the best result, and this topographic normalization for a single land cover type yielded better compensation for topographic effects than in the case of an area with various land-cover types. In applying the relative radiometric normalization to topographically normalized three multi-temporal imageries, more invariant spectral reflectance was obtained for infrared bands and the spectral reflectance patterns were preserved in visible bands, compared with un-normalized imageries. The results show that c-correction considering the remaining reflectance energy from adjacent topography or imperfect atmospheric correction yielded superior normalization results than cosine correction. The normalization results were also improved by increasing the kernel size to compensate for vertical and horizontal errors, and for displacement between satellite imagery and ASTER GDEM.
Analysis on the Snow Cover Variations at Mt. Kilimanjaro Using Landsat Satellite Images
Park, Sung-Hwan ; Lee, Moung-Jin ; Jung, Hyung-Sup ;
Korean Journal of Remote Sensing, volume 28, issue 4, 2012, Pages 409~420
DOI : 10.7780/kjrs.2012.28.4.5
Since the Industrial Revolution, CO2 levels have been increasing with climate change. In this study, Analyze time-series changes in snow cover quantitatively and predict the vanishing point of snow cover statistically using remote sensing. The study area is Mt. Kilimanjaro, Tanzania. 23 image data of Landsat-5 TM and Landsat-7 ETM+, spanning the 27 years from June 1984 to July 2011, were acquired. For this study, first, atmospheric correction was performed on each image using the COST atmospheric correction model. Second, the snow cover area was extracted using the NDSI (Normalized Difference Snow Index) algorithm. Third, the minimum height of snow cover was determined using SRTM DEM. Finally, the vanishing point of snow cover was predicted using the trend line of a linear function. Analysis was divided using a total of 23 images and 17 images during the dry season. Results show that snow cover area decreased by approximately
, equivalent to a 73% reduction. The minimum height of snow cover increased by approximately 290 m, from 4,603 m to 4,893 m. Using the trend line result shows that the snow cover area decreased by approximately
in the dry season and
overall each year. In contrast, the annual increase in the minimum height of snow cover was approximately 9.848 m in the dry season and 11.251 m overall. Based on this analysis of vanishing point, there will be no snow cover 2020 at 95% confidence interval. This study can be used to monitor global climate change by providing the change in snow cover area and reference data when studying this area or similar areas in future research.
Verification of CDOM Algorithms Based on Ocean Color Remote Sensing Data in the East Sea
Kim, Yun-Jung ; Kim, Hyun-Cheol ; Son, Young-Baek ; Park, Mi-Ok ; Shin, Woo-Chur ; Kang, Sung-Won ; Rho, Tae-Keun ;
Korean Journal of Remote Sensing, volume 28, issue 4, 2012, Pages 421~434
DOI : 10.7780/kjrs.2012.28.4.6
Colored Dissolved Organic Matter (CDOM) is one of the important components of optical properties of seawater to determine ecosystem dynamics in a given marine area. The optical characteristics of CDOM may depend on the various ecosystem and environmental variables in the sea and those variables may vary region to region. Therefore, the retrieval algorithm for determining light absorption coefficient of CDOM (
) using satellite remote sensing reflectance (
) developed from other region may not be directly applicable to the other region, and it must be validated using an in-situ ground-truth observation. We have tested 6 known CDOM algorithms (three Semi-analytical and three Empirical CDOM algorithms) developed from other regions of the world ocean with laboratory determined in-situ values for the East Sea using field data collected during seven oceanographic cruises in the period of 2009~2011. Our field measurements extended from the coastal waters to the open oceanic type CASE-1 Waters. Our study showed that Quasi-Analytical Algorithm (QAA_v5) derived
(412) appears to match in-situ
(412) values statistically. Semi-analytical algorithms appeared to underestimate and empirical ones overestimated
in the East Sea.
(412) value was found to be relatively high in the relatively high satellite derived-chlorophyll-a area.
(412) value appears to be influenced by the amount of chlorophyll-a in seawater. The outcome of this work may be referenced to develop
algorithm for the new Korean Geostationary Ocean Color Imager (GOCI).
Estimation of Satellite-based Spatial Evapotranspiration and Validation of Fluxtower Measurements by Eddy Covariance Method
Sur, Chan-Yang ; Han, Seung-Jae ; Lee, Jung-Hoon ; Choi, Min-Ha ;
Korean Journal of Remote Sensing, volume 28, issue 4, 2012, Pages 435~448
DOI : 10.7780/kjrs.2012.28.4.7
Evapotranspiration (ET) including evaporation from a land surface and transpiration from photosynthesis of vegetation is a sensitive hydrological factor with outer circumstances. Though both direct measurements with an evaporation pan and a lysimeter, and empirical methods using eddy covariance technique and the Bowen ratio have been widely used to observe ET accurately, they have a limitation that the observation can stand for the exact site, not for an area. In this study, remote sensing technique is adopted to compensate the limitation of ground observation using the Moderate Resolution Imaging Spectroradiometer (MODIS) multispectral sensor mounted on Terra satellite. We improved to evapotranspiration model based on remote sensing (Mu et al., 2007) and estimated Penman-Monteith evapotranspiration considering regional characteristics of Korea that was using only MODIS product. We validated evapotranspiration of Sulma (SMK)/Cheongmi (CFK) flux tower observation and calculation. The results showed high correlation coefficient as 0.69 and 0.74.
Relationship between PM2.5 Mass Concentrations and MODIS Aerosol Optical Thickness at Dukjuk and Jeju Island
Lee, Kwon-Ho ; Park, Seung-Shik ;
Korean Journal of Remote Sensing, volume 28, issue 4, 2012, Pages 449~458
DOI : 10.7780/kjrs.2012.28.4.8
Using the MODerate resolution Imaging Spectro-radiometer (MODIS) retrieved aerosol optical thickness (AOT) along with ground measurements of PM2.5 mass concentration, we assessed local air quality over Dukjuk and Jeju island and estimated possibility of satellite derived PM2.5 during nine intensive observation periods in 15 October 2005 - 24 October 2007. Averaged PM2.5 mass concentrations showed relatively variable as
at Dukjuk and
at Jeju. The maximum values of
(Jeju) were recorded during Asian dust storm day. Similarly, the maximum values of MODIS AOT were found as 3.73 (Gosan) and 1.14 (Jeju). Averaged MODIS AOTs at Dukjuk (
) were larger than that at Jeju (
). An empirical relationship between MODIS AOT and PM2.5 mass was obtained and results show that there was a good correlation between satellite and ground based values with a linear correlation coefficient of 0.85 at Dukjuk. The result clearly demonstrates that satellite derived AOT is a good surrogate for monitoring PM air quality over study area. However, meteorological and other ancillary datasets are necessary to further apply satellite data for air quality research.
Development of Image Collection Planning Optimization Using Heuristic Method
Bae, Hee-Jin ; Jun, Jung-Nam ; Chae, Tae-Byeong ;
Korean Journal of Remote Sensing, volume 28, issue 4, 2012, Pages 459~466
DOI : 10.7780/kjrs.2012.28.4.9
Satellite operation is divided as user's request, image collection planning, product generation, distribution. Image collection planning is to make image collection plan of satellite to reflect user's request in proper time based on NTO (New Task Order) and AO (Archive Order) using limited satellite resources. Image collection planning has high computational cost because of considering several variables simultaneously, is to be performed identical process repeatedly. In this paper, optimization research of image collection planning is performed for efficient planning. First, formulation of image collection planning is made to require satellite image as much as possible and then Heuristic algorithm is suggested for solution of formulation.
Preliminary Performance Testing of Geo-spatial Image Parallel Processing in the Mobile Cloud Computing Service
Kang, Sang-Goo ; Lee, Ki-Won ; Kim, Yong-Seung ;
Korean Journal of Remote Sensing, volume 28, issue 4, 2012, Pages 467~475
DOI : 10.7780/kjrs.2012.28.4.10
Cloud computing services are known that they have many advantages from the point of view in economic saving, scalability, security, sharing and accessibility. So their applications are extending from simple office systems to the expert system for scientific computing. However, research or computing technology development in the geo-spatial fields including remote sensing applications are the beginning stage. In this work, the previously implemented smartphone app for image processing was first migrated to mobile cloud computing linked to Amazon web services. As well, parallel programming was applied for improving operation performance. Industrial needs and technology development cases in terms of mobile cloud computing services are being increased. Thus, a performance testing on a satellite image processing module was carried out as the main purpose of this study. Types of implementation or services for mobile cloud varies. As the result of this testing study in a given condition, the performance of cloud computing server was higher than that of the single server without cloud service. This work is a preliminary case study for the further linkage approach for mobile cloud and satellite image processing.