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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
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Volume & Issues
Volume 26, Issue 6 - Dec 2010
Volume 26, Issue 5 - Oct 2010
Volume 26, Issue 4 - Aug 2010
Volume 26, Issue 3 - Jun 2010
Volume 26, Issue 2 - Apr 2010
Volume 26, Issue 1 - Feb 2010
Selecting the target year
New Simple Decomposition Technique for Polarimetric SAR Images
Lee, Kyung-Yup ; Oh, Yi-Sok ;
Korean Journal of Remote Sensing, volume 26, issue 1, 2010, Pages 1~7
This paper proposes a new decomposition technique for polarimetric synthetic aperture radar (SAR) images. This new decomposition technique is based on the degree of polarization (DoP) and co-polarized phase-difference (CPD) of the measured polarimetric backscattering coefficients. This decomposition technique is compared with the existing three- and four-component decomposition techniques with the ALOS PALSAR full polarimetric L-band data acquired in 2009. It is shown that the new decomposition technique is better or comparable to the existing techniques for the study areas such as sea, bare soil, forest, and urban area.
Waveform Simulation of Full-Waveform LIDAR
Kim, Seong-Joon ; Lee, Im-Pyeong ;
Korean Journal of Remote Sensing, volume 26, issue 1, 2010, Pages 9~20
The LIDAR data can be efficiently utilized for automatic reconstruction of 3D models of objects on the terrain and the terrain itself. In this paper, we attempted to generate simulated waveforms of FW (Full-Waveform) LIDAR (LIght Detection And Ranging). We performed the geometric modeling of the sensor and objects, and the radiometric modeling of the waveform intensity. First, we compute the origins and directions of the sub-beams by considering the divergence effects of a laser beam. We then searched for the locations at which the sub-beams intersected with the objects, such as ground, buildings and trees. Finally, we generate the individual waveforms of the reflected sub-beams and the waveform of the entire beam by summing the individual ones. With the experimental results, we confirmed the waveforms were reasonably generated, showing the characteristics of the surfaces the beam interacted with.
Numerical Simulation of Radar Backscattering from Oil Spills on Sea Surface for L-band SAR
Park, Seong-Min ; Yang, Chan-Su ; Oh, Yi-Sok ;
Korean Journal of Remote Sensing, volume 26, issue 1, 2010, Pages 21~27
This paper presents a numerical simulation of the radar backscattering from oil spills on ocean surface. At first, a one-dimensionally rough sea surface is numerically generated for a given wind speed at HEBEI SPIRIT accident. Then, an oil-spilled sea surface is represented with a two-layered medium, which is generated by adding a thin low-dielectric oil layer on the randomly-rough highdielectric sea surface. The backscattering coefficients of various oil-spilled sea surfaces are obtained using the Method of Moments and Monte Carlo technique for various surface roughness, oil-layer thicknesses, frequencies, polarizations and incidence angles. The numerical method is verified with theoretical models for simple structures. The reduction of the backscattering coefficients due to the lowdielectric oil-layers on sea surfaces has been analyzed. These numerical results will help to detect any oil spills on sea surfaces, and consequently, to classify SAR images.
Downscaling of Thematic Maps Based on Remote Sensing Data using Multi-scale Geostatistics
Park, No-Wook ;
Korean Journal of Remote Sensing, volume 26, issue 1, 2010, Pages 29~38
It is necessary to develop an integration model which can account for various data acquired at different measurement scales in environmental thematic mapping with high-resolution ground survey data and relatively low-resolution remote sensing data. This paper presents and applies a multi-scale geostatistical methodology for downscaling of thematic maps generated from lowresolution remote sensing data. This methodology extends a traditional ordinary kriging system to a block kriging system which can account for both ground data and remote sensing data which can be regarded as point and block data, respectively. In addition, stochastic simulation based on block kriging is also applied to describe spatial uncertainty attached to the downscaling. Two downscaling experiments including SRTM DEM and MODIS Leaf Area Index (LAI) products were carried out to illustrate the applicability of the geostatistical methodology. Through the experiments, multi-scale geostatistics based on block kriging successfully generated relatively high-resolution thematic maps with reliable accuracy. Especially, it is expected that multiple realizations generated from simulation would be effectively used as input data for investigating the effects of uncertain input data on GIS model outputs.
Experiment for 3D Coregistration between Scanned Point Clouds of Building using Intensity and Distance Images
Jeon, Min-Cheol ; Eo, Yang-Dam ; Han, Dong-Yeob ; Kang, Nam-Gi ; Pyeon, Mu-Wook ;
Korean Journal of Remote Sensing, volume 26, issue 1, 2010, Pages 39~45
This study used the keypoint observed simultaneously on two images and on twodimensional intensity image data, which was obtained along with the two point clouds data that were approached for automatic focus among points on terrestrial LiDAR data, and selected matching point through SIFT algorithm. Also, for matching error diploid, RANSAC algorithm was applied to improve the accuracy of focus. As calculating the degree of three-dimensional rotating transformation, which is the transformation-type parameters between two points, and also the moving amounts of vertical/horizontal, the result was compared with the existing result by hand. As testing the building of College of Science at Konkuk University, the difference of the transformation parameters between the one through automatic matching and the one by hand showed 0.011m, 0.008m, and 0.052m in X, Y, Z directions, which concluded to be used as the data for automatic focus.
Landslide Detection and Landslide Susceptibility Mapping using Aerial Photos and Artificial Neural Networks
Oh, Hyun-Joo ;
Korean Journal of Remote Sensing, volume 26, issue 1, 2010, Pages 47~57
The aim of this study is to detect landslide using digital aerial photography and apply the landslide to landslide susceptibility mapping by artificial neural network (ANN) and geographic information system (GIS) at Jinbu area where many landslides have occurred in 2006 by typhoon Ewiniar, Bilis and Kaemi. Landslide locations were identified by visual interpretation of aerial photography taken before and after landslide occurrence, and checked in field. For landslide susceptibility mapping, maps of the topography, geology, soil, forest, lineament, and landuse were constructed from the spatial data sets. Using the factors and landslide location and artificial neural network, the relative weight for the each factors was determinated by back-propagation algorithm. As the result, the aspect and slope factor showed higher weight in 1.2-1.5 times than other factors. Then, landslide susceptibility map was drawn using the weights and finally, the map was validated by comparing with landslide locations that were not used directly in the analysis. As the validation result, the prediction accuracy showed 81.44%.
Review of SMOS Mission and Current Operation
Park, Hyuk ; Lee, Ho-Jin ;
Korean Journal of Remote Sensing, volume 26, issue 1, 2010, Pages 59~64
The second satellite in ESA's Earth Explorer series, the Soil Moisture and Ocean Salinity (SMOS) mission was launched into orbit at November 1, 2009. The SMOS will play a key role in the monitoring of climate change on a global scale using the payload of L-band synthetic aperture radiometer. It is the first ever satellite designed both to map sea surface salinity and to monitor soil moisture on a global scale, and will provide the important data to study the water cycle among oceans, the atmosphere and land. To introduce the operation of the SMOS, this paper shows brief summary of appearance and current operation.