• Korean Journal of Remote Sensing
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• v.38 no.2
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• pp.139-151
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• 2022

SAGD (Steam-Assisted Gravity Drainage) method is widely used for oil recovery in oil sands regions. The SAGD operation causes surface displacement, which can affect the stability of oil recovery plants and trigger various geological disasters. Therefore, it isimportant to monitor the surface displacement due to SAGD in the oil sands region. In this study, the surface displacement due to SAGD operations of the Athabasca oil sands region in Alberta, Canada, was observed by applying Permanent Scatterer Interferometric Synthetic Aperture Radar (PSInSAR) technique to the Sentinel-1 time series SAR data acquired from 2016 to 2021. We also investigated the construction and expansion of SAGD facilitiesfrom Landsat-7/8 time seriesimages, from which the characteristics of the surface displacement according to the oil production activity of SAGD were analyzed. Uplift rates of 0.3-2.5 cm/yr in the direction of line of sight were observed over the SAGDs and their vicinity, whereas subsidence rates of -0.3--0.6 cm/yr were observed in areas more than several kilometers away from the SAGDs and not affected by oil recovery activities. Through the analysis of Landsat-7/8 images, we could confirm that the SAGDs operating after 2012 and showing high oil production activity caused uplift rates greater than 1.6 cm/yr due to the subsurface steam injection. Meanwhile, very small uplift rates of several mm per year occurred over SAGDs which have been operated for a longer period of time and show relatively low oil production activity. This was probably due to the compression of reservoir sandstone due to continuous oil recovery. The subsidence observed in areas except for the SAGDs and their vicinity estimated to be a gradual land subsidence caused by melting of the permafrost. Considering the subsidence, it was expected that the uplift due to SAGD operation would be greater than that observed by the PSInSAR. The results of this study confirm that the PSInSAR can be used as an effective means for evaluating productivity and stability of SAGD in the extreme cold regions.

• Korean Journal of Remote Sensing
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• v.38 no.6_2
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• pp.1589-1605
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• 2022

Phase unwrapping is an essential procedure for interferometric synthetic aperture radar techniques. Accordingly, a lot of phase unwrapping methods have been developed. Deep-learning-based unwrapping methods have recently been proposed. In this paper, we reviewed state-of-the-art deep-learning-based unwrapping approaches in terms of 1) the approaches to predicting unwrapped phases, 2) deep learning model structures for phase unwrapping, and 3) training data generation. The research trend of the approaches to predicting unwrapped phases was introduced by categorizing wrap count segmentation, phase jump classification, phase regression, and deep-learning-assisted method. We introduced the case studies of deep learning model structure for phase unwrapping, and model structure optimization to relate the overall phase information. In addition, we summarized the research trend of the training data generation approaches in the views of phase gradient and noise in the main. And the future direction in deep-learning-based phase unwrapping was presented. It is expected that this paper is used as guideline for exploring future direction of deep-learning-based phase unwrapping research in Korea.

• Journal of Korean Society of societal Security
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• v.2 no.2
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• pp.85-90
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• 2009

In recent days, climatic change cause abnormal weather all over the world and we have a great loss of life and property every year. In Korea, we suffer from landslide problem because large regions of Korea Peninsula are composed of mountain. In order to detect rapidly and to take follow-up measures of disaster, the remote sensing is being used actively as conventional field survey has many restrictions in accessibility because of more time and man power requirement. In additions interferometric SAR is one of the techniques that have our attention because it can provide many kinds of accurate surface information without restriction of atmospheric and ground conditions by using L-band. In this study, we aimed to monitor the displacement of mountain area in Kangwondo and this results will be used for detecting landslide. Also we build the web system for detecting and analyzing the landslide.

• Korean Journal of Remote Sensing
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• v.37 no.6_1
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• pp.1625-1630
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• 2021

In Bangkok, Thailand, there is an increasing concern for ground subsidence with the rapid urbanization. Given the presence of flood vulnerability due to the flat low-lying topography and proximity to the river delta, it is particularly significant to monitor deformation that can potentially augment flood hazards. In this paper, we have applied persistent scatterer interferometric synthetic aperture radar (PSInSAR) technique to investigate subsidence in Bangkok with the use of Sentinel-1 acquisitions spanning from June 2018 to October 2021. The vertical displacement velocity obtained from both ascending and descending orbits revealed regional-scale subsidence at rates up to 30 mm/yr. In addition, ongoing subsidence was observed in the suburb areas with the localized vertical subsidence exceeding 80 mm. The areas are primarily industrial and agricultural sectors, thus, the ground subsidence detected is probably caused by groundwater withdrawal. However, further work is needed to diagnose the trends of aquifer resources.

• Korean Journal of Remote Sensing
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• v.38 no.5_1
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• pp.447-460
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• 2022

It is well known that satellite synthetic aperture radar interferometry (InSAR) has been widely used for the observation of surface displacement owing to earthquakes, volcanoes, and subsidence very precisely. In wetlands where vegetation exists on the surface of the water, it is possible to create a water level change map with high spatial resolution over a wide area using the InSAR technique. Currently, a number of imaging radar satellites are in operation, and most of them support a ScanSAR mode observation to gather information over a large area at once. The Cienaga Grande de Santa Marta (CGSM) wetland, located in northern Colombia, is a vast wetland developed along the Caribbean coast. The CGSM wetlands face serious environmental threats from human activities such as reclamation for agricultural uses and residential purposes as well as natural causes such as sea level rise owing to climate change. Various restoration and protection plans have been conducted to conserve these invaluable environments in recognition of the ecological importance of the CGSM wetlands. Monitoring of water level changes in wetland is very important resources to understand the hydrologic characteristics and the in-situ water level gauge stations are usually utilized to measure the water level. Although it can provide very good temporal resolution of water level information, it is limited to fully understand flow pattern owing to its very coarse spatial resolution. In this study, we evaluate the L-band ALOS-2 PALSAR-2 ScanSAR mode to observe the water level change over the wide wetland area using the radar interferometric technique. In order to assess the quality of the interferometric product in the aspect of spatial resolution and coherence, we also utilized ALOS-2 PALSAR-2 stripmap high-resolution mode observations.

• Proceedings of the KSRS Conference
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• v.1
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• pp.368-371
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• 2006

A coastline is the boundary between land and ocean masses. Knowledge of coastline is essential for autonomous navigation, geographical exploration, coastal erosion monitoring and modelling, water line change, etc. Many methods have been researched to extract coastlines from the synthetic aperture radar (SAR) and optic images. Most methods were based on the intensity contrast between land and sea regions. However, in these methods, a coastline detection task was very difficult because of insufficient intensity contrast and the ambiguity in distinguishing coastline from other object line. In this paper, we propose an efficient method for the delineation of coastline using interferometric coherence values estimated from ERS tandem pair. The proposed method uses the facts that a tandem pair of ERS is acquired from a time interval of an accurate day and that the coherent and incoherent values in coherence map are land and water, respectively. The coherence map was generated from ERS tandem pair, filtered by MAP filter, and divided into land and water by the determination of threshold value that is based on the bimodality of the histogram. Finally, a coastline was detected by delineating the boundary pixels. There was a good visual match between the detected coastline and the manually contoured line. The interferometric coherence map will be helpful to identify land and water regions easily, and can be used to many applications that are related with a coastline.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.26 no.1
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• pp.81-87
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• 2015

We present an implementation result of a computer GUI-based simulator using MATLAB to verify the performance of interferometric radar altimeter(IRA) which is possible to measure the slant range altitude and the cross-track angle to the nearest point for terrain aided navigation(TAN). After a brief description of the principle of TAN and IRA, we present that the grids are divided for the modeling of the reflected signal in digital elevation map(DEM) and so the radar cross section(RCS) of each grid is calculated and the signal-noise ratio(SNR) of the reflected signal in the radar beam width. And the signal processing procedures of the IRA and the structure of the IRA simulator are shown.

• Journal of Korea Water Resources Association
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• v.55 no.12
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• pp.1125-1135
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• 2022

Damages by heavy snow does not occur very often, but when it does, it causes damage to a wide area. To mitigate snow damage, it is necessary to know, in advance, the depth of snow that causes damage in each region. However, snow depths are measured at observatory locations, and it is difficult to understand the spatial distribution of snow depth that causes damage in a region. To understand the spatial distribution of snow depth, the point measurements are interpolated. However, estimating spatial distribution of snow depth is not easy when the number of measured snow depth is small and topographical characteristics such as altitude are not similar. To overcome this limit, satellite images such as Synthetic Aperture Radar (SAR) can be analyzed using Differential Interferometric SAR (DInSAR) method. DInSAR uses two different SAR images measured at two different times, and is generally used to track minor changes in topography. In this study, the spatial distribution of snow depth was estimated by DInSAR analysis using dual polarimetric IW mode C-band SAR data of Sentinel-1B satellite operated by the European Space Agency (ESA). In addition, snow depth was estimated using geostationary satellite Chollian-2 (GK-2A) to compare with the snow depth from DInSAR method. As a result, the accuracy of snow cover estimation in terms with grids was about 0.92% for DInSAR and about 0.71% for GK-2A, indicating high applicability of DInSAR method. Although there were cases of overestimation of the snow depth, sufficient information was provided for estimating the spatial distribution of the snow depth. And this will be helpful in understanding regional damage-causing snow depth.

• Korean Journal of Remote Sensing
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• v.27 no.2
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• pp.171-180
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• 2011

MAI (multiple aperture SAR interferometry) method has been recently developed to improve the measurement accuracy of along-track surface deformation. By means of split-beam SAR processing, this novel technique produces forward- and backward-looking interferograms, which are combined to generate an MAI interferogram. The along-track surface deformation can then be derived from the MAI interferogram. The achieved accuracy of the along-track surface deformation is approximately 8 cm for interferograms with a coherence of 0.6. It is commonly recognized that the topographic phase on an MAI interferogram can be ignored. However, in this paper, we have generated an MAI interferogram from an ALOS P ALSAR interferometric pair spanning the 2010 Haiti earthquake, and shown that the topographic phase distortion on the MAI interferogram can reach to about $3.45{\times}10^{-4}$ rad./m. This distortion corresponds to an along-track surface deformation of about 98 cm. We have proposed an efficient method to remove the topographic phase distortion. After correcting the distortion, the topographic phase distortion on the MAI interferogram is reduced to about $7.82{\times}10^{-6}$ rad./m. This means that the proposed method can effectively remove the topographic distortion on the MAI interferogram to improve along-track surface deformation measurement.

• Korean Journal of Remote Sensing
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• v.27 no.2
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• pp.163-170
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• 2011

In this paper, we analyzed the phase change of 5-triangular trihedral comer reflectors by using X-band Ground-Based Synthetic Aperture Radar (GB-SAR) system. Each reflector was set as a stationary target at a different distance from the system. We obtained total 123 full-polarization images during 40 hours continuously at 20 minute interval. Results of SAR interferometric analysis showed phase changes of maximum 2 radians and followed similar pattern with atmospheric data. Through a GB-SAR phase formula that includes refractive index in the air, we performed regression analysis for refractive index as a function of atmospheric humidity, temperature and pressure. As a result, refractive index of air in X-band showed relatively high coefficient of determination with humidity and temperature (0.72 and 0.76 on average, respectively) but not so with pressure (0.34). The refractive index of air in X -band changed by 3.14\;{\times}\;10^{-5}$ during the measuring time with a humidity range of 50% ~ 90% and a temperature range of $-1^{\circ}C$ ~ $9^{\circ}C$. We expect that a total expression of refractive index of air including humidity, temperature and pressure can be calculated when more extensive data would be collected at various atmospheric conditions.