• Geophysics and Geophysical Exploration
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• v.12 no.1
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• pp.163-171
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• 2009

Subcritical crack growth is one of the main causes of time-dependent fracturing in rock. In the present study, we investigated subcritical crack growth in rock in distilled water (pH = 5.7) and in an aqueous solution of sodium hydroxide (NaOHaq, pH = 12), comparing the results to those in air. We also investigated the effect of the pH in an aqueous environment. We used andesite and granite for all our tests. We determined the relationship between the crack velocity and the stress intensity factor using the double-torsion test under conditions of controlled temperature. We showed that crack velocities in water were higher than those in air, in agreement with other research results indicating that crack velocity increases in water. When we compared our results for NaOHaq with those for water, however, we found that the crack velocity at the same stress intensity factor did not change even though the pH of the surrounding environment was different. This result does not agree with the accepted understanding that hydroxide ions accelerate subcritical crack growth in rocks. We concluded that the pH at the crack tip influences subcritical crack growth, and not the bulk pH, which has little effect.

• Korean Journal of Remote Sensing
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• v.21 no.4
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• pp.287-302
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• 2005

Digital Elevation Models (DEMs) were generated by ERS-l/2 and JERS-1 SAR interferometry in Daejon area, Korea. The quality of the DEM's was evaluated by the Ground Control Points (GCPs) in city area where GCPs were determined by GPS surveys, while in the mountain area with no GCPs, a 1:25,000 digital map was used. In order to minimize errors due to the inaccurate satellite orbit information and the phase unwrapping procedure, a Differential InSAR (DInSAR) was implemented in addition to the traditional InSAR analysis for DEM generation. In addition, DEMs from GTOPO30, SRTM-3, and 1:25,000 digital map were used for assessment the resolution of the DEM generated from DInSAR. 5-6 meters of elevation errors were found in the flat area regardless of the usage and the resolution of DEM, as a result of InSAR analyzing with a pair of ERS tandem and 6 pairs of JERS-1 interferograms. In the mountain area, however, DInSAR with DEMs from SRTM-3 and the digital map was found to be very effective to reduce errors due to phase unwrapping procedure. Also errors due to low signal-to-noise ratio of radar images and atmospheric effect were attenuated in the DEMs generated from the stacking of 6 pairs of JERS-1. SAR interferometry with multiple pairs of SAR interferogram with low resolution DEM can be effectively used to enhance the resolution of DEM in terms of data processing time and cost.

• Korean Journal of Remote Sensing
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• v.34 no.6_1
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• pp.925-939
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• 2018

Absorbed shortwave radiation at the surface is an important component of energy analysis among the atmosphere, land, and ocean. In this study, the absorbed shortwave radiation was calculated using a radiation model and surface broadband albedo data for application to Geostationary Earth Orbit Korea Multi-Purpose SATellite (GEO-KOMPSAT-2A; GK-2A). And the results (GWNU algorithm) were compared with CERES data and calculation results using pyranometer and MODIS (Moderate Resolution Imaging Spectroradiometer) data to be selected as the reference absorbed shortwave radiation. This GWNU algorithm was also compared with the physical and statistical algorithms of GOSE-R ABI and two algorithms (Li et al., 1993; Kim and Jeong, 2016) using regression equation. As a result, the absorbed shortwave radiation calculated by GWNU algorithm was more accurate than the values calculated by the other algorithms. However, if the problem about computing time and accuracy of albedo data arise when absorbed shortwave radiation is calculated by GWNU algorithm, then the empirical algorithms explained above should be used with GWNU algorithm.

• Korean Journal of Remote Sensing
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• v.34 no.6_3
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• pp.1369-1382
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• 2018

As the number of multispectral satellites increases, it is expected that it will be possible to acquire and use images for periodically. However, there is a problem of data discrepancy due to different overpass time, period and spatial resolution. In particular, the difference in band bandwidths became different reflectance even for images taken at the same time and affect uncertainty in the analysis of vegetation activity such as vegetation index. The purpose of this study is to estimate the band adjustment factor according to the difference of bandwidth with other multispectral satellites for the application of KOMPSAT-3 satellite in agriculture field. The Spectral band adjustment factor (SBAF) were calculated using the hyperspectral satellite images acquired in the desert area. As a result of applying SBAF to the main crop area, the vegetation index showed a high agreement rate of relative percentage difference within 3% except for the Hapcheon area where the zenith angle was 25. For the estimation of SBAF, this study used only one set of images, which did not consider season and solar zenith angle of SBAF variation. Therefore, long-term analysis is necessary to solve SBAF uncertainty in the future.

• Korean Journal of Remote Sensing
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• v.38 no.5_3
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• pp.901-912
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• 2022

The frequency of disasters is increasing due to global climate change, and unusual heavy rains and rainy seasons are occurring in Korea. Periodic monitoring and rapid detection are important because these weather conditions can lead to drought and flooding, causing secondary damage. Although research using optical images is continuously being conducted to determine the waterbody, there is a limitation in that it is difficult to detect due to the influence of clouds in order to detect floods that accompany heavy rain. Therefore, there is a need for research using synthetic aperture radar (SAR) that can be observed regardless of day or night in all weather. In this study, using Sentinel-1 SAR images that can be collected in near-real time as open data, the UNet model among deep learning algorithms that have recently been used in various fields was applied. In previous studies, waterbody detection studies using SAR images and deep learning algorithms are being conducted, but only a small number of studies have been conducted in Korea. In this study, to determine the applicability of deep learning of SAR images, UNet and the existing algorithm thresholding method were compared, and five indices and Sentinel-2 normalized difference water index (NDWI) were evaluated. As a result of evaluating the accuracy with intersect of union (IoU), it was confirmed that UNet has high accuracy with 0.894 for UNet and 0.699 for threshold method. Through this study, the applicability of deep learning-based SAR images was confirmed, and if high-resolution SAR images and deep learning algorithms are applied, it is expected that periodic and accurate waterbody change detection will be possible in Korea.

• Journal of Korea Water Resources Association
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• v.55 no.4
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• pp.301-308
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• 2022

Algae is an indispensable primary producer in the ecosystem by supplying energy to consumers in the aquatic ecosystem, and is largely divided into green algae, blue-green algae, and diatoms. In the case of blue-green algae, the water temperature rises, which occurs in the summer and overgrows, which is the main cause of the algae bloom. Recently, the change in the occurrence time and frequency of the algae bloom is increasing due to climate change. Existing algae survey methods are performed by collecting water and measuring through sensors, and time, cost and manpower are limited. In order to overcome the limitations of these existing monitoring methods, research has been conducted to perform remote monitoring using spectroscopic devices such as multispectral and hyperspectral using satellite image, UAV, etc. In this study, we tried to confirm the possibility of species classification of remote monitoring through laboratory-scale experiments through algal culture and river water collection. In order to acquire hyperspectral images, a hyperspectral sensor capable of analyzing at 400-1000 nm was used. In order to extract the spectral characteristics of the collected river water for classification of algae species, filtration was performed using a GF/C filter to prepare a sample and images were collected. Radiation correction and base removal of the collected images were performed, and spectral information for each sample was extracted and analyzed through the process of extracting spectral information of algae to identify and compare and analyze the spectral characteristics of algae, and remote sensing based on hyperspectral images in rivers and lakes. We tried to review the applicability of monitoring.

• Korean Journal of Remote Sensing
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• v.39 no.5_2
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• pp.849-858
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• 2023

Investigating disaster sites such as earthquakes and landslides involves significant risks due to potential secondary disasters like facility collapse. In situations where direct access is challenging, there is a need to develop methods for safely acquiring high-precision 3D disaster information using light detection and ranging (LiDAR) equipped drone survey systems. In this study, the feasibility of using drone LiDAR in disaster scenarios was examined, focusing on the collapse accident at Jeongja Bridge in Bundang-gu, Seongnam City, in April 2023. High-density point clouds for the accident bridge were collected, and the bridge's 3D terrain information was reconstructed and compared to the measurement performance of 10 ground control points. The results showed horizontal and vertical root mean square error values of 0.032 m and 0.055 m, respectively. Additionally, when compared to a point cloud generated using ground LiDAR for the same target area, a vertical difference of approximately 0.08 m was observed, but overall shapes showed minimal discrepancies. Moreover, in terms of overall data acquisition and processing time, drone LiDAR was found to be more efficient than ground LiDAR. Therefore, the use of drone LiDAR in disaster sites with significant risks allows for safe and rapid onsite investigations.

• Geophysics and Geophysical Exploration
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• v.21 no.3
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• pp.171-182
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• 2018

We performed the seismic field data processing using an open-source software (Madagascar) to verify if it is applicable to processing of field data, which has low signal-to-noise ratio and high uncertainties in velocities. The Madagascar, based on Python, is usually supposed to be better in the development of processing technologies due to its capabilities of multidimensional data analysis and reproducibility. However, this open-source software has not been widely used so far for field data processing because of complicated interfaces and data structure system. To verify the effectiveness of the Madagascar software on field data, we applied it to a typical seismic data processing flow including data loading, geometry build-up, F-K filter, predictive deconvolution, velocity analysis, normal moveout correction, stack, and migration. The field data for the test were acquired in Gunsan Basin, Yellow Sea using a streamer consisting of 480 channels and 4 arrays of air-guns. The results at all processing step are compared with those processed with Landmark's ProMAX (SeisSpace R5000) which is a commercial processing software. Madagascar shows relatively high efficiencies in data IO and management as well as reproducibility. Additionally, it shows quick and exact calculations in some automated procedures such as stacking velocity analysis. There were no remarkable differences in the results after applying the signal enhancement flows of both software. For the deeper part of the substructure image, however, the commercial software shows better results than the open-source software. This is simply because the commercial software has various flows for de-multiple and provides interactive processing environments for delicate processing works compared to Madagascar. Considering that many researchers around the world are developing various data processing algorithms for Madagascar, we can expect that the open-source software such as Madagascar can be widely used for commercial-level processing with the strength of expandability, cost effectiveness and reproducibility.

• Korean Journal of Remote Sensing
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• v.29 no.4
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• pp.375-387
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• 2013

Accuracy assessment of tide models in polar ocean has to be performed to accurately analyze tidal response of glaciers by using Double-Differential Interferometric SAR (DDInSAR) technique. In this study, we used 120 DDInSAR images generated from 16 one-day tandem COSMO-SkyMed DInSAR pairs obtained for 2 years and in situ tide height for 11 days measured by a pressure type wave recorder to assess the accuracy of tide models such as TPXO7.1, FES2004, CATS2008a and Ross_Inv in Terra Nova Bay, East Antarctica. Firstly, we compared the double-differential tide height (${\Delta}\dot{T}$) for Campbell Glacier Tongue extracted from the DDInSAR images with that predicted by the tide models. Tide height (T) from in situ measurement was compared to that of the tide models. We also compared 24-hours difference of tide height ($\dot{T}$) from in situ tide height with that from the tide models. The root mean square error (RMSE) of ${\Delta}\dot{T}$, T and $\dot{T}$ decreased after the inverse barometer effect (IBE)-correction of the tide models, from which we confirmed that the IBE of tide models should be corrected requisitely. The RMSE of $\dot{T}$ and ${\Delta}\dot{T}$ were smaller than that of T. This was because $\dot{T}$ is the difference of tide height during temporal baseline of the DInSAR pairs (24 hours), in which the errors from mean sea level of the tide models and in situ tide, and the tide constituents of $S_2$, $K_2$, $K_1$ and $P_1$ used in the tide models were canceled. This confirmed that $\dot{T}$ and ${\Delta}\dot{T}$ predicted by the IBE-corrected tide models can be used in DDInSAR technique. It was difficult to select an optimum tide model for DDInSAR in Terra Nova Bay by using in situ tide height measured in a short period. However, we could confirm that Ross_Inv is the optimum tide model as it showed the smallest RMSE of 4.1 cm by accuracy assessment using the DDInSAR images.

• Korean Journal of Remote Sensing
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• v.37 no.5_1
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• pp.1177-1186
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• 2021

As the Arctic melt ponds play an important role in determining the interannual variation of the sea ice extent and changes in the Arctic environment, it is crucial to monitor the Arctic melt ponds with high accuracy. Ice, Cloud, and Land Elevation Satellite-2 (ICESat-2), which is the NASA's latest altimeter satellite based on the green laser (532 nm), observes the global surface elevation. When compared to the CryoSat-2 altimetry satellite whose along-track resolution is 250 m, ICESat-2 is highly expected to provide much more detailed information about Arctic melt ponds thanks to its high along-track resolution of 70 cm. The basic products of ICESat-2 are the surface height and the number of reflected photons. To aggregate the neighboring information of a specific ICESat-2 photon, the segments of photons with 10 m length were used. The standard deviation of the height and the total number of photons were calculated for each segment. As the melt ponds have the smoother surface than the sea ice, the lower variation of the height over melt ponds can make the melt ponds distinguished from the sea ice. When the melt ponds were extracted, the number of photons per segment was used to classify the melt ponds covered with open-water and specular ice. As photons are much more absorbed in the water-covered melt pondsthan the melt ponds with the specular ice, the number of photons persegment can distinguish the water- and ice-covered ponds. As a result, the suggested melt pond detection method was able to classify the sea ice, water-covered melt ponds, and ice-covered melt ponds. A qualitative analysis was conducted using the Sentinel-2 optical imagery. The suggested method successfully classified the water- and ice-covered ponds which were difficult to distinguish with Sentinel-2 optical images. Lastly, the pros and cons of the melt pond detection using satellite altimetry and optical images were discussed.