• The Journal of Engineering Geology
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• v.32 no.3
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• pp.411-420
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• 2022

Recently, research using remote sensing has been active in various fields such as environment, science, and society. The results of research using remote sensing are not only numerical results, but also play an important role in solving and preventing social and scientific problems. The purpose of this thesis is to tell the correlation between the data provided and each data by using remote sensing technology for the tidal flat environment. The purpose of this study is to obtain high-resolution data using artificial satellites during remote sensing to find out information on tidal flat currents. Tidal flats created by erosion, sedimentation, low tide, and high tide contain information about the tidal flat slope and information about the ecosystem. Therefore, it can be considered as one of the very important studies to analyze the overall tidal flow channel. This paper creates a DEM (Digital Elevation Model) through TanDEM-X, and DEM is used as the most basic data to create a tidal channel. The research area is a tidal flat located in the middle of the west coast of Ganghwado tidal flat. By analyzing the tidal channel created, various information such as the slope direction of Ganghwado tidal flat and the shape of the tidal channel can be grasped. It is expected that the results of this study will increase the importance and necessity of using DEM data for tidal flat research in the future, and that high-quality results can be obtained.

• Korean Journal of Remote Sensing
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• v.28 no.4
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• pp.393-407
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• 2012

This study focuses on the correction of topographic effects caused by a combination of solar elevation and azimuth, and topographic relief in single optical remote sensing imagery, and by a combination of changes in position of the sun and topographic relief in comparative analysis of multi-temporal imageries. For the Jeju Island, Republic of Korea, where Mt. Halla and various cinder cones are located, a Landsat 7 ETM+ imagery and ASTER GDEM data were used to normalize the topographic effects on the imagery, using two topographic normalization methods: cosine correction assuming a Lambertian condition and assuming a non-Lambertian c-correction, with kernel sizes of $3{\times}3$, $5{\times}5$, $7{\times}7$, and $9{\times}9$ pixels. The effects of each correction method and kernel size were then evaluated. The c-correction with a kernel size of $7{\times}7$ produced the best result in the case of a land area with various land-cover types. For a land-cover type of forest extracted from an unsupervised classification result using the ISODATA method, the c-correction with a kernel size of $9{\times}9$ produced the best result, and this topographic normalization for a single land cover type yielded better compensation for topographic effects than in the case of an area with various land-cover types. In applying the relative radiometric normalization to topographically normalized three multi-temporal imageries, more invariant spectral reflectance was obtained for infrared bands and the spectral reflectance patterns were preserved in visible bands, compared with un-normalized imageries. The results show that c-correction considering the remaining reflectance energy from adjacent topography or imperfect atmospheric correction yielded superior normalization results than cosine correction. The normalization results were also improved by increasing the kernel size to compensate for vertical and horizontal errors, and for displacement between satellite imagery and ASTER GDEM.

• Korean Journal of Remote Sensing
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• v.33 no.5_1
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• pp.469-480
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• 2017

This study aims to understand the relationship between lineaments and epicenters in Geochang region, Gyungsangnam-do, South Korea. An instrumental observation of earthquakes has been started by Korea Meteorological Administration (KMA) since 1978 and there were 6 earthquakes with magnitude ranging 2 to 2.5 in Geochang region from 1978 to 2016. Lineaments were extracted from LANDSAT 8 satellite image and shaded relief map displayed in 3-dimension using Digital Elevation Model (DEM). Then, lineament density was statistically examined by hotspot analysis. Hexagonal grids were generated to perform the analysis because hexagonal pattern expresses lineaments with less discontinuity than square girds, and the size of the grid was selected to minimize a variance of lineament density. Since hotspot analysis measures the extent of clustering with Z score, Z scores computed with lineaments' frequency ($L_f$), length ($L_d$), and intersection ($L_t$) were used to find lineament clusters in the density map. Furthermore, the Z scores were extracted from the epicenters and examined to see the relevance of each density elements to epicenters. As a result, 15 among 18 densities,recorded as 3 elements in 6 epicenters, were higher than 1.65 which is 95% of the standard normal distribution. This indicates that epicenters coincide with high density area. Especially, $L_f$ and $L_t$ had a significant relationship with epicenter, being located in upper 95% of the standard normal distribution, except for one epicenter in $L_t$. This study can be used to identify potential seismic zones by improving the accuracy of expressing lineaments' spatial distribution and analyzing relationship between lineament density and epicenter. However, additional studies in wider study area with more epicenters are recommended to promote the results.

• Korean Journal of Remote Sensing
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• v.36 no.5_1
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• pp.847-860
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• 2020

The 2-pass DInSAR (Differential Interferometric SAR) processing steps for DEM generation consist of the co-registration of SAR image pair, interferogram generation, phase unwrapping, calculation of DEM errors, and geocoding, etc. It requires complicated steps, and the accuracy of data processing at each step affects the performance of the finally generated DEM. In this study, we developed an improved method for enhancing the performance of the DEM generation method based on the 2-pass DInSAR technique of TanDEM-X bistatic SAR images was developed. The developed DEM generation method is a method that can significantly reduce both the DEM error in the unwrapped phase image and that may occur during geocoding step. The performance analysis of the developed algorithm was performed by comparing the vertical accuracy (Root Mean Square Error, RMSE) between the existing method and the newly proposed method using the ground control point (GCP) generated from GPS survey. The vertical accuracy of the DInSAR-based DEM generated without correction for the unwrapped phase error and geocoding error is 39.617 m. However, the vertical accuracy of the DEM generated through the proposed method is 2.346 m. It was confirmed that the DEM accuracy was improved through the proposed correction method. Through the proposed 2-pass DInSAR-based DEM generation method, the SRTM DEM error observed by DInSAR was compensated for the SRTM 30 m DEM (vertical accuracy 5.567 m) used as a reference. Through this, it was possible to finally create a DEM with improved spatial resolution of about 5 times and vertical accuracy of about 2.4 times. In addition, the spatial resolution of the DEM generated through the proposed method was matched with the SRTM 30 m DEM and the TanDEM-X 90m DEM, and the vertical accuracy was compared. As a result, it was confirmed that the vertical accuracy was improved by about 1.7 and 1.6 times, respectively, and more accurate DEM generation was possible with the proposed method. If the method derived in this study is used to continuously update the DEM for regions with frequent morphological changes, it will be possible to update the DEM effectively in a short time at low cost.

• Economic and Environmental Geology
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• v.51 no.2
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• pp.167-176
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• 2018

It is necessary to consider various geological parameters such as lithology, geological structure, earthquake, hydraulic geology, geochemistry, geological engineering, and geothermal in order to select potential sites for HLW(high-level radioactive waste) geological disposal. In particular, the geological lineament reflects the characteristics of various geological parameters and can be used as an important criterion for site selecting such as nuclear power plants and HLW repositories. In this paper, the Finnish lineament classification method for HLW disposal site selection through the lineament analysis was applied to the lineament data in the Korean peninsula. For this purpose, we used previous lineament data from the KIGAM(Korea Institute of Geoscience and Mineral Resources) and obtained new lineament data from the field geologists such as structural geologist, paleoseismologist, and geomorphologist. To ensure the reliability of the new lineament analysis data, we used high-resolution satellite images and hill-shade relief maps which were constructed by a digital elevation model. In the prevailing direction analysis from the acquired lineament data, the NNE-SSW direction was the most dominant, but the ENE-WSW and NNW-SSE directions also showed highly frequency depending on the experts. Applying the Finnish classification method, the geometrical development characteristics of the lineament corresponding to the Class 1 and 2 used for the wide-wide candidate site were compared. As a result of direction analysis for Class 1, the NNE-SSW direction was the most dominant and the WNW-ESE direction also showed a high frequency. In the case of Class 2, the NNE-SSW is the most prevalent and WNW-ESE or ENE-WSW direction also had highly frequency depending on the experts. Different lineament analysis results based on the same data are interpreted as a result of subjective experience and analytical criteria from the every experts. Therefore, it is necessary to establish integrated criteria and consider geophysical data for the publication of reliable nation-wide lineament map.

• Korean Journal of Agricultural and Forest Meteorology
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• v.22 no.3
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• pp.215-231
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• 2020

Forest landscape models (FLMs) can be used to investigate the complex interactions of various ecological processes and patterns, which makes them useful tools to evaluate how environmental and anthropogenic variables can influence forest ecosystems. However, due to the large spatio-temporal scales in FLMs studies, parameterization and validation can be extremely challenging when applying to new study areas. To address this issue, we focused on the parameterization and application of a spatially explicit forest landscape model, LANDIS-II, to Mt. Gyebang, South Korea, with the use of the National Forest Inventory (NFI) and long-term ecological research (LTER) site data. In this study, we present the followings for the biomass succession extension of LANDIS-II: 1) species-specific and spatial parameters estimation for the biomass succession extension of LANDIS-II, 2) calibration, and 3) application and validation for Mt. Gyebang. For the biomass succession extension, we selected 14 tree species, and parameterized ecoregion map, initial community map, species growth characteristics. We produced ecoregion map using elevation, aspect, and topographic wetness index based on digital elevation model. Initial community map was produced based on NFI and sub-alpine survey data. Tree species growth parameters, such as aboveground net primary production and maximum aboveground biomass, were estimated from PnET-II model based on species physiological factors and environmental variables. Literature data were used to estimate species physiological factors, such as FolN, SLWmax, HalfSat, growing temperature, and shade tolerance. For calibration and validation purposes, we compared species-specific aboveground biomass of model outputs and NFI and sub-alpine survey data and calculated coefficient of determination (R²) and root mean square error (RMSE). The final model performed very well, with 0. 98 R² and 8. 9 RMSE. This study can serve as a foundation for the use of FLMs to other applications such as comparing alternative forest management scenarios and natural disturbance effects.

• Journal of Life Science
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• v.25 no.5
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• pp.557-567
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• 2015

To increase the marketability of Dolsan leaf mustard Kimchi, seasonings were prepared by sea tangle and Lentinus edodes. Gat Kimchi A (GK-A) and Gat Kimchi B (GK-B) were prepared by addition of complex seasoning with Sea tangle (CSS), complex seasoning with Lentinus edodes (CSL), respectively and evaluated the quality characteristics. GK-A contained high minerals and dietary fiber and showed the effect of delaying pH-lowering and acidity-rising. There were no significant differences in salinity test after 70 days. Reducing sugar of test groups was higher than control. During the fermentation, Leuconostoc sp. was grown in GK-A and GK-B than control. Growth of control's Lactobacillus sp. increased 20 days after. Up to 30 days, lightness of control was high. Yellowness were increased browning potential in GK-B, 20 days after. From the initial to 10 days, Hardness of GK-A showed higher than the others. glutamic acid and aspartic acid content of GK-A was higher significantly than the others in the entire fermentation period (p<0.05). At 0, 10, 30 days, sweet-tasty amino acids of GK-A showed a significantly higher level than the others (p<0.05). From 10 days to 40 days of fermentation, the sensory evaluation of GK-A is better than the other groups. Comprehensively reviewed the above results, the conclusion is as follows: CSS made with sea tangle as a main ingredient. GK-A by seasoning the CSS to 90 g GK-A is expected as a new Dolsan leaf mustard products that can provide flavor and nutrition to the consumer at the same time.

• Korean Journal of Agricultural and Forest Meteorology
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• v.18 no.4
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• pp.208-220
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• 2016

Automatic Mountain Meteorology Observation System (AMOS) is an important ingredient for several climatological and forest disaster prediction studies. In this study, we select the optimal sites for AMOS in the mountain areas of Honam and Jeju in order to prevent forest disasters such as forest fires and landslides. So, this study used spatial dataset such as national forest map, forest roads, hiking trails and 30m DEM(Digital Elevation Model) as well as forest risk map(forest fire and landslide), national AWS information to extract optimal site selection of AMOS. Technical methods for optimal site selection of the AMOS was the firstly used multifractal model, IDW interpolation, spatial redundancy for 2.5km AWS buffering analysis, and 200m buffering analysis by using ArcGIS. Secondly, optimal sites selected by spatial analysis were estimated site accessibility, observatory environment of solar power and wireless communication through field survey. The threshold score for the final selection of the sites have to be higher than 70 points in the field assessment. In the result, a total of 159 polygons in national forest map were extracted by the spatial analysis and a total of 64 secondary candidate sites were selected for the ridge and the top of the area using Google Earth. Finally, a total of 26 optimal sites were selected by quantitative assessment based on field survey. Our selection criteria will serve for the establishment of the AMOS network for the best observations of weather conditions in the national forests. The effective observation network may enhance the mountain weather observations, which leads to accurate prediction of forest disasters.

• Korean Journal of Environmental Biology
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• v.25 no.2
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• pp.168-177
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• 2007

By using DEM and digital actual vegetation map with MGE GIS software program, topographic features (altitude, slope, latitude, etc.) quantitatively were analysed and their data integrated as the index of climatic conditions (WI, CI, air temperature, etc.) in South Korea. Warmth Index (WI) decreases $5.27^{\circ}C{\cdot}month$ with latitudinal $1^{\circ} degree, and $3.41^{\circ}C{\cdot}month$ with attitudinal 100 m increase. The relationship between CI and WI values is expressed as a linear regression, $WI=116.01+0.96{\times}CI,\;R^2=0.996$. The distributional peaks of different plant communities along Warmth Index gradient showed the sequence of Abies nephrolepis, Taxus cuspidata, Abies koreana, Quercus mongolica, Carpinus laxiflora, Q. dentata, C. tschonoskii, Q. serrate, Pinus densiflora, Q. aliena, Q. variabilis, Q. acutissima, P. thunbergii, Q. acute, Castanopsis cuspidata var. sieboldii, Camellia japonica, Machilus thunbergii community from lower to higher values. The Quercus mongolica forest occurred frequently on E-NW and SE slope aspect within WI $70{\sim}80^{\circ}C{\cdot}month$ optimal range at mesic sites, NW and SE slope than xeric sites S and SW slope. The Q. serrata forest showed the most distributional frequency in NW and W slope aspect within WI $90{\sim}100^{\circ}C{\cdot}month$ range, Q. variabilis and Q. acutissima forest showed the high frequency of distribution in SE slope in WI $95{\sim}100^{\circ}C{\cdot}month$ range. By the slope gradient analysis, five groups were found: 1. Abies nephrolepis, Machilus thunbergii, 2. Taxus cuspidata, Abies koreana, Quercus mongolica, Q. dentata, Q. serrata, Q. variabilis, Castanopsis cuspidata var. sieboldii 3. Pinus densiflora, Q. aliena, Q. acutissima, P. thunbergii, Q. acuta 4. Carpinus laxiflora, Camellia japonica 5. C. tschonoskii from steep slope to gentle slope sequence.

• Economic and Environmental Geology
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• v.54 no.2
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• pp.161-176
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• 2021

In this study, one of the distributed hydrologic models, VELAS, was used to analyze the variation of hydrologic elements based on water balance analysis to evaluate the groundwater recharge in more detail than the annual time scale for the past and future. The study area is located in Yanggok-ri, Seobu-myeon, Hongseong-gun, Chungnam-do, which is very vulnerable to drought. To implement the VELAS model, spatial characteristic data such as digital elevation model (DEM), vegetation, and slope were established, and GIS data were constructed through spatial interpolation on the daily air temperature, precipitation, average wind speed, and relative humidity of the Korea Meteorological Stations. The results of the analysis showed that annual precipitation was 799.1-1750.8 mm, average 1210.7 mm, groundwater recharge of 28.8-492.9 mm, and average 196.9 mm over the past 18 years from 2001 to 2018 in the study area. Annual groundwater recharge rate compared to annual precipitation was from 3.6 to 28.2% with a very large variation and average 14.9%. By the climate change RCP 8.5 scenario, the annual precipitation from 2019 to 2100 was 572.8-1996.5 mm (average 1078.4 mm) and groundwater recharge of 26.7-432.5 mm (average precipitation 16.2%). The annual groundwater recharge rates in the future were projected from 2.8% to 45.1%, 18.2% on average. The components that make up the water balance were well correlated with precipitation, especially in the annual data rather than the daily data. However, the amount of evapotranspiration seems to be more affected by other climatic factors such as temperature. Groundwater recharge in more detailed time scale rather than annual scale is expected to provide basic data that can be used for groundwater development and management if precipitation are severely varied by time, such as droughts or floods.