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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 24, Issue 6 - Dec 2008
Volume 24, Issue 5 - Oct 2008
Volume 24, Issue 4 - Aug 2008
Volume 24, Issue 3 - Jun 2008
Volume 24, Issue 2 - Apr 2008
Volume 24, Issue 1 - Feb 2008
Selecting the target year
A Remote Sensed Data Combined Method for Sea Fog Detection
Heo, Ki-Young ; Kim, Jae-Hwan ; Shim, Jae-Seol ; Ha, Kyung-Ja ; Suh, Ae-Sook ; Oh, Hyun-Mi ; Min, Se-Yun ;
Korean Journal of Remote Sensing, volume 24, issue 1, 2008, Pages 1~16
Steam and advection fogs are frequently observed in the Yellow Sea from March to July except for May. This study uses remote sensing (RS) data for the monitoring of sea fog. Meteorological data obtained from the Ieodo Ocean Research Station provided a valuable information for the occurrence of steam and advection fogs as a ground truth. The RS data used in this study were GOES-9, MTSAT-1R images and QuikSCAT wind data. A dual channel difference (DCD) approach using IR and shortwave IR channel of GOES-9 and MTSAT-1R satellites was applied to detect sea fog. The results showed that DCD, texture-related measurement and the weak wind condition are required to separate the sea fog from the low cloud. The QuikSCAT wind data was used to provide the wind speed criteria for a fog event. The laplacian computation was designed for a measurement of the homogeneity. A new combined method, which includes DCD, QuikSCAT wind speed and laplacian computation, was applied to the twelve cases with GOES-9 and MTSAT-1R. The threshold values for DCD, QuikSCAT wind speed and laplacian are -2.0 K,
and 0.1, respectively. The validation results showed that the new combined method slightly improves the detection of sea fog compared to DCD method: improvements of the new combined method are
increases in the Heidke skill score, 10% decreases in the probability of false detection, and
increases in the odd ratio.
Method for Analysis on Optimization of Averaging Interval of Rainfall Rate Measured by Tipping-Bucket Rain Gauges
Nam, Kyung-Yeub ; Chang, Ki-Ho ; Kim, Kyung-Eak ; Oh, Sung-Nam ; Choi, Young-Jean ; Kim, Kyung-Sik ; Lee, Dong-In ; Kim, Kum-Lan ;
Korean Journal of Remote Sensing, volume 24, issue 1, 2008, Pages 17~24
Rainfall data from three different types of rain gauge system have been collected for the summertime rain event at Mokpo in the Korean peninsula. The rain gauge system considered in this paper is composed of three tipping-bucket rain gauges with 0.1, 0.2, and 0.5 mm measuring resolutions, the Optical Rain Gauge (ORG), and the PARSIVEL (PARticle SIze and VELocity). The PARSIVEL rainfall rate has been considered as the reference for comparison since it gave good resolution and performance on this event. Comparison with the PARSIVEL rainfall rate gives the results that the error and temporal variation of rainfall rate are simultaneously reduced with increasing the averaging interval of rainfall rate or decreasing the size of tipping bucket. This suggests that the estimated rainfall rate must be optimized, differently for the type of tipping-bucket rain gages, by minimizing the averaging interval of rainfall rate under the condition satisfying the given performance of rainfall rate.
Assessment of Future Climate Change Impact on DAM Inflow using SLURP Hydrologic Model and CA-Markov Technique
Kim, Seong-Joon ; Lim, Hyuk-Jin ; Park, Geun-Ae ; Park, Min-Ji ; Kwon, Hyung-Joong ;
Korean Journal of Remote Sensing, volume 24, issue 1, 2008, Pages 25~33
To investigate the hydrologic impacts of climate changes on dam inflow for Soyanggangdam watershed
of northeastern South Korea, SLURP (Semi-distributed Land Use-based Runoff Process) model and the climate change results of CCCma CGCM2 based on SRES A2 and B2 were adopted. By the CA-Markov technique, future land use changes were estimated using the three land cover maps (1985, 1990, 2000) classified by Landsat TM satellite images. NDVI values for 2050 and 2100 land uses were estimated from the relationship of NDVI-Temperature linear regression derived from the observed data (1998-2002). Before the assessment, the SLURP model was calibrated and verified using 4 years (1998-2001) dam inflow data with the Nash-Sutcliffe efficiencies of 0.61 to 0.77. In case of A2 scenario, the dam inflows of 2050 and 2100 decreased 49.7 % and 25.0 % comparing with the dam inflow of 2000, and in case of B2 scenario, the dam inflows of 2050 and 2100 decreased 45.3 % and 53.0 %, respectively. The results showed that the impact of land use change covered 2.3 % to 4.9 % for the dam inflow change.
Analysis of Land Use Change Impact on Storm Runoff in Anseongcheon Watershed
Park, Geun-Ae ; Jung, In-Kyun ; Lee, Mi-Seon ; Shin, Hyung-Jin ; Park, Jong-Yoon ; Kim, Seong-Joon ;
Korean Journal of Remote Sensing, volume 24, issue 1, 2008, Pages 35~43
The purpose of this study is to evaluate the hydrological impact due to temporal land cover change by gradual urbanization of upstream watershed of Pyeongtaek gauging station of Anseong-cheon. WMS HEC-1 was adopted, and OEM with 200 m resolution and hydrologic soil group from 1:50,000 scale soil map were prepared. Land covers of 1986, 1990, 1994 and 1999 Landsat TM images were classified by maximum likelihood method. The watershed showed a trend that forest & paddy areas decreased and urban/residential area gradually increased during the four selected years. The model was calibrated at 2 locations (Pyeonglaek and Gongdo) by comparing observed with simulated discharge results for 5 summer storm events from 1998 to 2001. The watershed average CN values varied from 61.7 to 62.3 for the 4 selected years. To identify the impact of streamflow by temporal area change of a target land use, a simple evaluation method that the CN values of areas except the target land use are unified as one representative CN value was suggested. By applying the method, watershed average CN value was affected in the order of paddy, forest and urban/residential, respectively.
Evaluation of Future Climate Change Impact on Streamflow of Gyeongancheon Watershed Using SLURP Hydrological Model
Ahn, So-Ra ; Ha, Rim ; Lee, Yong-Jun ; Park, Geun-Ae ; Kim, Seong-Joon ;
Korean Journal of Remote Sensing, volume 24, issue 1, 2008, Pages 45~55
The impact on streamflow and groundwater recharge considering future potential climate and land use change was assessed using SLURP (Semi-distributed Land-Use Runoff Process) continuous hydrologic model. The model was calibrated and verified using 4 years (1999-2002) daily observed streamflow data for a
which has been continuously urbanized during the past couple of decades. The model was calibrated and validated with the coefficient of determination and Nash-Sutcliffe efficiency ranging from 0.8 to 0.7 and 0.7 to 0.5, respectively. The CCCma CGCM2 data by two SRES (Special Report on Emissions Scenarios) climate change scenarios (A2 and B2) of the IPCC (Intergovemmental Panel on Climate Change) were adopted and the future weather data was downscaled by Delta Change Method using 30 years (1977 - 2006, baseline period) weather data. The future land uses were predicted by CA (Cellular Automata)-Markov technique using the time series land use data of Landsat images. The future land uses showed that the forest and paddy area decreased 10.8 % and 6.2 % respectively while the urban area increased 14.2 %. For the future vegetation cover information, a linear regression between monthly NDVI (Normalized Difference Vegetation Index) from NOAA/AVHRR images and monthly mean temperature using five years (1998 - 2002) data was derived for each land use class. The future highest NDVI value was 0.61 while the current highest NDVI value was 0.52. The model results showed that the future predicted runoff ratio ranged from 46 % to 48 % while the present runoff ratio was 59 %. On the other hand, the impact on runoff ratio by land use change showed about 3 % increase comparing with the present land use condition. The streamflow and groundwater recharge was big decrease in the future.
A Comparative Study of 3D DWT Based Space-borne Image Classification for Differnet Types of Basis Function
Yoo, Hee-Young ; Lee, Ki-Won ; Kwon, Byung-Doo ;
Korean Journal of Remote Sensing, volume 24, issue 1, 2008, Pages 57~64
In the previous study, the Haar wavelet was used as the sole basis function for the 3D discrete wavelet transform because the number of bands is too small to decompose a remotely sensed image in band direction with other basis functions. However, it is possible to use other basis functions for wavelet decomposition in horizontal and vertical directions because wavelet decomposition is independently performed in each direction. This study aims to classify a high spatial resolution image with the six types of basis function including the Haar function and to compare those results. The other wavelets are more helpful to classify high resolution imagery than the Haar wavelet. In overall accuracy, the Coif4 wavelet has the best result. The improvement of classification accuracy is different depending on the type of class and the type of wavelet. Using the basis functions with long length could be effective for improving accuracy in classification, especially for the classes of small area. This study is expected to be used as fundamental information for selecting optimal basis function according to the data properties in the 3D DWT based image classification.
A Comparative Study of Algorithms for Estimating Land Surface Temperature from MODIS Data
Suh, Myoung-Seok ; Kim, So-Hee ; Kang, Jeon-Ho ;
Korean Journal of Remote Sensing, volume 24, issue 1, 2008, Pages 65~78
This study compares the relative accuracy and consistency of four split-window land surface temperature (LST) algorithms (Becker and Li, Kerr et ai., Price, Ulivieri et al.) using 24 sets of Terra (Aqua)/Moderate Resolution Imaging Spectroradiometer (MODIS) data, observed ground grass temperature and air temperature over South Korea. The effective spectral emissivities of two thermal infrared bands have been retrieved by vegetation coverage method using the normalized difference vegetation index. The intercomparison results among the four LST algorithms show that the three algorithms (Becker-Li, Price, and Ulivieri et al.) show very similar performances. The LST estimated by the Becker and Li's algorithm is the highest, whereas that by the Kerr et al.'s algorithm is the lowest without regard to the geographic locations and seasons. The performance of four LST algorithms is significantly better during cold season (night) than warm season (day). And the LST derived from Terra/MODIS is closer to the observed LST than that of Aqua/MODIS. In general, the performances of Becker-Li and Ulivieri et al algorithms are systematically better than the others without regard to the day/night, seasons, and satellites. And the root mean square error and bias of Ulivieri et al. algorithm are consistently less than that of Becker-Li for the four seasons.
Adaptive Reconstruction of Harmonic Time Series Using Point-Jacobian Iteration MAP Estimation and Dynamic Compositing: Simulation Study
Lee, Sang-Hoon ;
Korean Journal of Remote Sensing, volume 24, issue 1, 2008, Pages 79~89
Irregular temporal sampling is a common feature of geophysical and biological time series in remote sensing. This study proposes an on-line system for reconstructing observation image series contaminated by noises resulted from mechanical problems or sensing environmental condition. There is also a high likelihood that during the data acquisition periods the target site corresponding to any given pixel may be covered by fog or cloud, thereby resulting in bad or missing observation. The surface parameters associated with the land are usually dependent on the climate, and many physical processes that are displayed in the image sensed from the land then exhibit temporal variation with seasonal periodicity. A feedback system proposed in this study reconstructs a sequence of images remotely sensed from the land surface having the physical processes with seasonal periodicity. The harmonic model is used to track seasonal variation through time, and a Gibbs random field (GRF) is used to represent the spatial dependency of digital image processes. The experimental results of this simulation study show the potentiality of the proposed system to reconstruct the image series observed by imperfect sensing technology from the environment which are frequently influenced by bad weather. This study provides fundamental information on the elements of the proposed system for right usage in application.