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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
L-band SAR-derived Sea Surface Wind Retrieval off the East Coast of Korea and Error Characteristics
Kim, Tae-Sung ; Park, Kyung-Ae ; Choi, Won-Moon ; Hong, Sungwook ; Choi, Byoung-Cheol ; Shin, Inchul ; Kim, Kyung-Ryul ;
Korean Journal of Remote Sensing, volume 28, issue 5, 2012, Pages 477~487
DOI : 10.7780/kjrs.2012.28.5.1
Sea surface winds in the sea off the east coast of Korea were derived from L-band ALOS (Advanced Land Observing Satellite) PALSAR (Phased Array type L-band Synthetic Aperture Radar) data and their characteristics of errors were analyzed. We could retrieve high-resolution wind vectors off the east coast of Korea including the coastal region, which has been substantially unavailable from satellite scatterometers. Retrieved SAR-wind speeds showed a good agreement with in-situ buoy measurement by showing relatively small an root-mean-square (RMS) error of 0.67 m/s. Comparisons of the wind vectors from SAR and scatterometer presented RMS errors of 2.16 m/s and
, 3.62 m/s and
for L-band GMF (Geophysical Model Function) algorithm 2009 and 2007, respectively, which tended to be somewhat higher than the expected limit of satellite scatterometer winds errors. L-band SAR-derived wind field exhibited the characteristic dependence on wind direction and incidence angle. The previous version (L-band GMF 2007) revealed large errors at small incidence angles of less than
. By contrast, the L-band GMF 2009, which improved the effect of incidence angle on the model function by considering a quadratic function instead of a linear relationship, greatly enhanced the quality of wind speed from 6.80 m/s to 1.14 m/s at small incident angles. This study addressed that the causes of wind retrieval errors should be intensively studied for diverse applications of L-band SAR-derived winds, especially in terms of the effects of wind direction and incidence angle, and other potential error sources.
Classification of Remote Sensing Data using Random Selection of Training Data and Multiple Classifiers
Park, No-Wook ; Yoo, Hee Young ; Kim, Yihyun ; Hong, Suk-Young ;
Korean Journal of Remote Sensing, volume 28, issue 5, 2012, Pages 489~499
DOI : 10.7780/kjrs.2012.28.5.2
In this paper, a classifier ensemble framework for remote sensing data classification is presented that combines classification results generated from both different training sets and different classifiers. A core part of the presented framework is to increase a diversity between classification results by using both different training sets and classifiers to improve classification accuracy. First, different training sets that have different sampling densities are generated and used as inputs for supervised classification using different classifiers that show different discrimination capabilities. Then several preliminary classification results are combined via a majority voting scheme to generate a final classification result. A case study of land-cover classification using multi-temporal ENVISAT ASAR data sets is carried out to illustrate the potential of the presented classification framework. In the case study, nine classification results were combined that were generated by using three different training sets and three different classifiers including maximum likelihood classifier, multi-layer perceptron classifier, and support vector machine. The case study results showed that complementary information on the discrimination of land-cover classes of interest would be extracted within the proposed framework and the best classification accuracy was obtained. When comparing different combinations, to combine any classification results where the diversity of the classifiers is not great didn't show an improvement of classification accuracy. Thus, it is recommended to ensure the greater diversity between classifiers in the design of multiple classifier systems.
The Tendency Analysis of Albedo by Land Cover Over Northeast Asia Using MODIS 16-Day Composited Albedo data
Park, Eun-Bin ; Han, Kyung-Soo ; Lee, Chang-Suk ; Pi, Kyung-Jin ;
Korean Journal of Remote Sensing, volume 28, issue 5, 2012, Pages 501~508
DOI : 10.7780/kjrs.2012.28.5.3
Albedo is known as a factor that directly impacts on the surface energy balance one of the elements of earth radiation balance. The change of albedo includes the change of soil moisture, vegetation, solar zenith angle, snow, and so on. In addition, it operates as a crucial path to understanding feedback mechanisms between radiation balance and its influence on climate and vegetation dynamics and therefore, observing the variation of albedo is a one of the essential procedures for anticipating climate change. In this study, we used MODIS 16-Day composited Albedo data from 2001 to 2011 years with the purpose of observing the change of albedo over Northeast Asia. According to the tendency of albedo for 11 years, albedo in the area of an active vegetation has increased in near-infrared (NIR) domain and decreased in visible (VIS) domain. On the basis of local changes in vegetation in 2002, the both area of the Gobi Desert and the Manchuria was enormously changed and chosen the research area and furthermore, the vegetation of both regions had deteriorated due to the change of the minimum value since 2010.
Estimating Rice Yield Using MODIS NDVI and Meteorological Data in Korea
Hong, Suk Young ; Hur, Jina ; Ahn, Joong-Bae ; Lee, Jee-Min ; Min, Byoung-Keol ; Lee, Chung-Kuen ; Kim, Yihyun ; Lee, Kyung Do ; Kim, Sun-Hwa ; Kim, Gun Yeob ; Shim, Kyo Moon ;
Korean Journal of Remote Sensing, volume 28, issue 5, 2012, Pages 509~520
DOI : 10.7780/kjrs.2012.28.5.4
The objective of this study was to estimate rice yield in Korea using satellite and meteorological data such as sunshine hours or solar radiation, and rainfall. Terra and Aqua MODIS (The MOderate Resolution Imaging Spectroradiometer) products; MOD13 and MYD13 for NDVI and EVI, MOD15 and MYD15 for LAI, respectively from a NASA web site were used. Relations of NDVI, EVI, and LAI obtained in July and August from 2000 to 2011 with rice yield were investigated to find informative days for rice yield estimation. Weather data of rainfall and sunshine hours (climate data 1) or solar radiation (climate data 2) were selected to correlate rice yield. Aqua NDVI at DOY 233 was chosen to represent maximum vegetative growth of rice canopy. Sunshine hours and solar radiation during rice ripening stage were selected to represent climate condition. Multiple regression based on MODIS NDVI and sunshine hours or solar radiation were conducted to estimate rice yields in Korea. The results showed rice yield of
in 2011, respectively and the difference from statistics were
, respectively. Rice yield distributions from 2002 to 2011 were presented to show spatial variability in the country.
Spatial Estimation of Priestley-Taylor Based Potential Evapotranspiration Using MODIS Imageries: the Nak-dong river basin
Sur, Chanyang ; Lee, Jongjin ; Park, Jaeyoung ; Choi, Minha ;
Korean Journal of Remote Sensing, volume 28, issue 5, 2012, Pages 521~529
DOI : 10.7780/kjrs.2012.28.5.5
The evapotranspiration (ET) is one of the most important factor in the hydrological cycle. In this study, remote sensing based ET algorithm using Moderate Resolution Imaging Spectroradiometer (MODIS) was considered. Then, Priestley-Taylor algorithm was used for estimation of potential evapotranspiration in South Korea, and its spatial distribution was analyzed. Overall applicability between estimated potential evapotranspiration and weather station pan evaporation in Nakdong river basin was represented. The results using small pan showed that correlation coefficient in Pohang and Moonkyung Station was 0.70 and 0.55, respectively. However, the results using large pan showed correlation coefficient in Pohang and Moonkyung Station was 0.62 and 0.52, respectively.
Monitoring Red Tide in South Sea of Korea (SSK) Using the Geostationary Ocean Color Imager (GOCI)
Son, Young Baek ; Kang, Yoon Hyang ; Ryu, Joo Hyung ;
Korean Journal of Remote Sensing, volume 28, issue 5, 2012, Pages 531~548
DOI : 10.7780/kjrs.2012.28.5.6
To identify Cochlodinium polykrikoides red tide from non-red tide water (satellite high chlorophyll waters) in the South Sea of Korea (SSK), we improved a spectral classification method proposed by Son et al.(2011) for the world first Geostationary Ocean Color Imager (GOCI). C. polykrikoides blooms and non-red tide waters were classified based on four different criteria. The first step revealed that the radiance peaks of potential red tide water occurred at 555 and 680 nm (fluorescence peak). The second step separated optically different waters that were influenced by relatively low and high contributions of colored dissolved organic matter (CDOM) (including detritus) to chlorophyll. The third and fourth steps discriminated red tide water from non-red tide water based on the blue-to-green ratio, respectively. After applying the red tide classification, the spectral response of C. polykrikoides red tide water, which is influenced by pigment concentration as well as CDOM (detritus), showed different slopes for the blue and green bands (lower slope at blue bands and higher slope at green bands). The opposite result was found for non-red tide water. This modified spectral classification method for GOCI led to increase user accuracy for C. polykrikoides and non-red tide blooms and provided a more reliable and robust identification of red tides over a wide range of oceanic environments than was possible using chlorophyll a concentration, or proposed red tide detection algorithms. Maps of C. polykrikoides red tide in SSK outlined patches of red tide covering the area near Naro-do and Tongyeong during the end of July and early of August, 2012 and extending into from Wan-do and Geoje-do during the middle of August, 2012.
A Comparative Study on the Applicability of A Priori Estimates of Adjustment Models for Assessment of Surface Parameter Estimates
Seo, Suyoung ;
Korean Journal of Remote Sensing, volume 28, issue 5, 2012, Pages 549~559
DOI : 10.7780/kjrs.2012.28.5.7
This paper presents a comparative analysis on the applicability of a priori statistic information about adjustment models when the surface shape parameters are estimated at an arbitrary point in an elevation data. Although the reliability of the estimates are known to be affected by surface condition and the adjustment models, there has been little research in a systematic and detail way. When the raw data have been taken from a real measurement, its true value cannot be known, however, thus this study used simulation data in order to analyze clearly the applicability of adjustment models. The generation of simulated data was performed by superimposing horizontal, slope, and curve surfaces and adding a certain amount of noise. Comparative analysis was performed by associating the a posteriori estimates with a priori statistics of each adjustment models. The experimental results show the estimation characteristics of adjustment models against varying surface conditions.
A MTF Compensation for Satellite Image Using L-curve-based Modified Wiener Filter
Jeon, Byung-Il ; Kim, Hongrae ; Chang, Young Keun ;
Korean Journal of Remote Sensing, volume 28, issue 5, 2012, Pages 561~571
DOI : 10.7780/kjrs.2012.28.5.8
The MTF(Modulation Transfer Function) is one of quality assesment factors to evaluate the performance of satellite images. Image restoration is needed for MTF compensation, but it is an ill-posed problem and doesn't have a certain solution. Lots of filters were suggested to solve this problem, such as Inverse Filter(IF), Pseudo Inverse Filter(PIF) and Wiener Filter(WF). The most commonly used filter is a WF, but it has a limitation on distinguishing signal and noise. The L-curve-based Modified Wiener Filter(MWF) is a solution technique using a Tikhonov regularization method. The L-curve is used for estimating an optimal regularization parameter. The image restoration was performed with Dubaisat-1 images for PIF, WF, and MWF. It is found that the image restored with MWF results in more improved MTF by 20.93% and 10.85% than PIF and WF, respectively.
Outlier Detection from High Sensitive Geiger Mode Imaging LIDAR Data retaining a High Outlier Ratio
Kim, Seongjoon ; Lee, Impyeong ; Lee, Youngcheol ; Jo, Minsik ;
Korean Journal of Remote Sensing, volume 28, issue 5, 2012, Pages 573~586
DOI : 10.7780/kjrs.2012.28.5.9
Point clouds acquired by a LIDAR(Light Detection And Ranging, also LADAR) system often contain erroneous points called outliers seeming not to be on physical surfaces, which should be carefully detected and eliminated before further processing for applications. Particularly in case of LIDAR systems employing with a Gieger-mode array detector (GmFPA) of high sensitivity, the outlier ratio is significantly high, which makes existing algorithms often fail to detect the outliers from such a data set. In this paper, we propose a method to discriminate outliers from a point cloud with high outlier ratio acquired by a GmFPA LIDAR system. The underlying assumption of this method is that a meaningful targe surface occupy at least two adjacent pixels and the ranges from these pixels are similar. We applied the proposed method to simulated LIDAR data of different point density and outlier ratio and analyzed the performance according to different thresholds and data properties. Consequently, we found that the outlier detection probabilities are about 99% in most cases. We also confirmed that the proposed method is robust to data properties and less sensitive to the thresholds. The method will be effectively utilized for on-line realtime processing and post-processing of GmFPA LIDAR data.
Study on Site Selection of A/R CDM Using LiDAR Data
Guishan, Cui ; Park, Taejin ; Lee, Woo-Kyun ; Lee, Jongyeol ; Kwak, Doo-Ahn ; Kwak, Hanbin ;
Korean Journal of Remote Sensing, volume 28, issue 5, 2012, Pages 587~596
DOI : 10.7780/kjrs.2012.28.5.10
Verifying about eligibility of targeted site is necessary for execute Afforestation and Reforestation Clean Development Mechanism (A/R CDM) project which is followed by system of Kyoto protocol. The site have to be identified by which could not be in conformity with definition of forest. This study tried to propose a technology of classify for site selection of A/R CDM. We chose several parts of Yangpyeng as study area and applied LiDAR data and remotely sensed imagery for considering about tree height, degree of crown closure, and land area which 3 factors for identify forest. LiDAR data was used for offset the shortage of remotely sensed imagery that cannot perfectly determine the forest definition due to absence of 3-dimentional information, but can be obtained from LiDAR. Considering tree height, degree of crown closure, and land area simultaneously by moving window, classified fields to forest and non forest based on pixel size. As a result, 124.06 ha for suitable to doing plantation and approximately 357.02 ha are in negative. Technology that applied for analyzing will provide fundamental methodology not only site selection for A/R CDM, but will be utilized in other Kyoto protocol.