• Korean Journal of Remote Sensing
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• v.21 no.2
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• pp.163-171
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• 2005

I have developed a processor for synthetic aperture radar (SAR) raw data compression using range-doppler algorithm for educational purpose. The program realized a generic SAR focusing algorithm so that it can deal with any SAR system if the specification is known. It can run efficiently on a low-cost computer by selecting minimum size out of a whole dataset, and can produce intermediate images during the process. Especially, the program is designed for educational purpose in such a way that Doppler centroid and azimuth ambiguity can be determined graphically by the user. By distributing the source code and the algorithm to public, I intend to maximize the educational effect on understanding and utilizing SAR data. This paper introduces the principle of SAR focusing algorithm embedded on the eSAR processor and shows an example of data processing using ERS-1 raw data.

• Korean Journal of Remote Sensing
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• v.15 no.1
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• pp.61-71
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• 1999

Several physical phenomena on the sea surface are analyzed from SAR images of South Sea areas, Korea. Strong wave patterns propagating in southerly direction are seen in ERS-1 SAR image on October 11, 1994, and a wave directional spectrum is calculated from this image using the SAR modulation transfer function. RADARSAT SAR image of August 15, 1996 reveals internal waves in northern coastal waters of Cheju Island. Analysis indicates that the internal waves may have been generated by the tidal currents traveling over the shallow bottom of the stratified water in the summer during the tidal changeovers fro ebb to flood and shows patterns of trains of solitons. RADARSAT SAR image taken 3 days after the oil spill accident near Goeje Isalnd on April 3, 1997 detects distinct oil slicks from the accident area but also shows slicks near the coast caused by wind sheltering of coastal mountains and chemical-biological activities.

• Korean Journal of Remote Sensing
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• v.30 no.2
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• pp.293-302
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• 2014

Radar systems are used in remote sensing mainly as space-borne, airborne and ground-based Synthetic Aperture Radar (SAR), scatterometer and Doppler radar. Those systems are composed of expensive equipments and require expertise and professional skills for operation. Because of the limitation in getting experiences of the radar and SAR systems and its operations in ordinary universities and institutions, it is difficult to learn and exercise essential principles of radar hardware which are essential to understand and develop new application fields. To overcome those difficulties, in this paper, we present the construction and experiment of a low-cost educational radar system based on the blueprints of the MIT Cantenna system. The radar system was operated in three modes. Firstly, the velocity of moving cars was measured in Doppler radar mode. Secondly, the range of two moving targets were measured in radar mode with range resolution. Lastly, 2D images were constructed in GB-SAR mode to enhance the azimuth resolution. Additionally, we simulated the SAR raw data to compare Deramp-FFT and ${\omega}-k$ algorithms and to analyze the effect of antenna positional error for SAR focusing. We expect the system can be further developed into a light-weight SAR system onboard a unmanned aerial vehicle by improving the system with higher sampling frequency, I/Q acquisition, and more stable circuit design.

• Journal of Korean Society of Forest Science
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• v.111 no.3
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• pp.435-449
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• 2022

Forest canopy height is an indispensable vertical structure parameter that can be used for understanding forest biomass and carbon storage as well as for managing a sustainable forest ecosystem. Plot-based field surveys, such as the national forest inventory, have been conducted to provide estimates of the forest canopy height. However, the comprehensive nationwide field monitoring of forest canopy height has been limited by its cost, lack of spatial coverage, and the inaccessibility of some forested areas. These issues can be addressed by remote sensing technology, which has gained popularity as a means to obtain detailed 2- and 3-dimensional measurements of the structure of the canopy at multiple scales. Here, we reviewed both international and domestic studies that have used remote sensing technology approaches to estimate the forest canopy height. We categorized and examined previous approaches as: 1) LiDAR approach, 2) Stereo or SAR image-based point clouds approach, and 3) combination approach of remote sensing data. We also reviewed upscaling approaches of utilizing remote sensing data to generate a continuous map of canopy height across large areas. Finally, we provided suggestions for further advancement of the Korean forest canopy height estimation system through the use of various remote sensing technologies.

• Korean Journal of Remote Sensing
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• v.31 no.3
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• pp.255-265
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• 2015

Very high resolution (VHR) satellite imagery provide valuable information on urban change monitoring due to multi-temporal observation over large areas. Recently, there has been increased interest in the urban change detection technique using VHR Synthetic Aperture Radar (SAR) imaging system, because it can take images regardless of solar illumination and weather condition. In this paper, we proposed a texture-based urban change detection method using the VHR SAR texture features generated from Gray-Level Co-Occurrence Matrix (GLCM). In order to evaluate the efficiency of the proposed method, the result was compared, visually and quantitatively, with the result of Non-Coherent Change Detection (NCCD) which is widely used for the change detection of VHR SAR image. The experimental results showed the greater detection accuracy and the visually satisfactory result compared with the NCCD method. In conclusion, the proposed method has shown a great potential for the extraction of urban change information from VHR SAR imagery.

• Korean Journal of Remote Sensing
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• v.13 no.1
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• pp.57-73
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• 1997

This paper is related to the correction of radiometric distortions induced by topographic relief. RADARSAT SAR image data were obtained over the mountainous area near southern part of Seoul. Initially, the SAR data was geometrically corrected and registered to plane rectangular coordinates so that each pixel of the SAR image has known topographic parameters. The topographic parameters (slope and aspect) at each pixel position were calculated from the digital elevation model (DEM) data having a comparable spatial resolution with the SAR data. Local incidence angle between the incoming microwave and the surface normal to terrain slope was selected as a primary geometric factor to analyze and to correct the radiometric distortions. Using digital maps of forest stands, several fields of rather homogeneous forest stands were delineated over the SAR image. Once the effects of local incidence angle on the radar backscatter were defined, the radiometric correction was performed by an empirical fuction that was derived from the relationship between the geometric parameters and mean radar backscatter. The correction effects were examined by ground truth data.

• Korean Journal of Remote Sensing
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• v.34 no.6_1
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• pp.969-979
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• 2018

This paper presents reflection symmetry of polarimetric SAR over the Amazon rainforest in terms of correlation coefficients between the pairs of HH- and HV-pol and VV- and VH-pol data by ALOS PALSAR. The reflection symmetry is defined as a non-zero correlation between HH- and HV-pol and VV- and VH-pol over natural distributed targets, and is a fundamental assumption for cross-talk calibration coefficient computation and for three-component decomposition for polarimetric SAR data. The Amazon rainforest is especially one of the common global reference sites for the reflection symmetry. The correlation coefficients for the pairs of reflection symmetry obtained in this study range from 0.018 to 0.097. The results imply that there exists a non-negligible dependency between co-pol and cross-pol in the distributed natural targets, and consequently the non-zero correlation must be considered as a potential contribution to errors of spaceborne SAR polarimetry to some extent.

• Korean Journal of Remote Sensing
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• v.37 no.6_2
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• pp.1901-1922
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• 2021

Since most large earthquakes occur by reactivation of preexisting active faults, it is important to understand the locations and characteristics of active faults in terms of earthquake hazard research and earthquake disaster prevention. Recently, several remote sensing techniques are broadly used for lineament analysis performed prior to field surveys in active fault surveys. The aim of this paper is introducing simple principles and application examples of each remote sensing technique (satellite remote sensing, airborne remote sensing, InSAR, LiDAR) widely used for active fault investigation. This paper also explains the analytical methods for the slope break generated by fault activity based on GIS and the horizontal displacement of the strike-slip fault. In discussion, we would like to discuss the problems and solutions on making DEM based on aerial photography, and a new developed technique (RRIM) to overcome the problems of DEM based on aerial LiDAR. Understanding remote sensing techniques used for active fault investigation and utilizing appropriate methods depending on the situation and limitations of each remote sensing technique are important for effective active fault investigation.

• Korean Journal of Remote Sensing
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• v.29 no.1
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• pp.1-9
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• 2013

To classify the landfast ice in the north of the Greenland, observation data, multifrequency Synthetic Aperture Radar (SAR) images and texture images were used. The total four types of sea ice are first year ice, highly deformed ice, ridge and moderately deformed ice. The texture images that were processed by K-means algorithm showed higher accuracy than the ones that were processed by SAR images; however, overall accuracy of maximum likelihood algorithm using texture images did not show the highest accuracy all the time. It turned out that when using K-means algorithm, the accuracy of the multi SAR images were higher than the single SAR image. When using the maximum likelihood algorithm, the results of single and multi SAR images are differ from each other, therefore, maximum likelihood algorithm method should be used properly.

• Korean Journal of Remote Sensing
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• v.34 no.5
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• pp.739-747
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• 2018

Integration analysis of multi-sensor satellite images is becoming increasingly important. The first step in integration analysis is image registration between multi-sensor. SIFT (Scale Invariant Feature Transform) is a representative image registration method. However, optical image and SAR (Synthetic Aperture Radar) images are different from sensor attitude and radiation characteristics during acquisition, making it difficult to apply the conventional method, such as SIFT, because the radiometric characteristics between images are nonlinear. To overcome this limitation, we proposed a modified method that combines the SAR-SIFT method and shape descriptor vector DLSS(Dense Local Self-Similarity). We conducted an experiment using two pairs of Cosmo-SkyMed and KOMPSAT-2 images collected over Daejeon, Korea, an area with a high density of buildings. The proposed method extracted the correct matching points when compared to conventional methods, such as SIFT and SAR-SIFT. The method also gave quantitatively reasonable results for RMSE of 1.66m and 2.45m over the two pairs of images.