• Journal of the Korean GEO-environmental Society
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• v.25 no.9
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• pp.5-14
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• 2024

In Korea, torrential rain frequency and intensity have surged over the past five years (2019-2023), breaking rainfall records. Due to insufficient observation facilities for rainfall and runoff data in small mountainous catchments, preparing for unexpected floods is challenging. This study examines the Bidogyo catchment in Goesan-gun, Chungcheongbuk-do, comparing design flood discharge calculated with optimized parameters versus standard guidelines. Using HEC-HMS and Q-GIS for model construction, five rainfall events were analyzed with data from the National Water Resources Management Information System. The time of concentration (Tc) and storage constant (K) were calculated using the Seokyeongdae formula and model optimization. Results showed that optimized parameters produced higher objective function values for flood events. The design flood discharge varied by -10.7% to 17.3% from the standard guidelines when using optimized parameters. Moreover, optimized parameters yielded flood discharges closer to observed values, highlighting limitations of the Seokyeongdae formula for all catchments. Further research aims to develop suitable parameter estimation methods for small mountainous catchments in Korea.

• Journal of the Korean Association of Geographic Information Studies
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• v.19 no.3
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• pp.61-74
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• 2016

The purpose of this paper is to analyze the relationship between the location of the epicenter of a medium-sized earthquake(magnitude 4.8) that occurred on January 20, 2007 in the Odaesan area with lineament features using a shaded relief map(1/25,000 scale) and satellite images from LANDSAT-8 and KOMPSAT-2. Previous studies have analyzed lineament features in tectonic settings primarily by examining two-dimensional satellite images and shaded relief maps. These methods, however, limit the application of the visual interpretation of relief features long considered as the major component of lineament extraction. To overcome some existing limitations of two-dimensional images, this study examined three-dimensional images, produced from a Digital Elevation Model and drainage network map, for lineament extraction. This approach reduces mapping errors introduced by visual interpretation. In addition, spline interpolation was conducted to produce density maps of lineament frequency, intersection, and length required to estimate the density of lineament at the epicenter of the earthquake. An algorithm was developed to compute the Value of the Relative Density(VRD) representing the relative density of lineament from the map. The VRD is the lineament density of each map grid divided by the maximum density value from the map. As such, it is a quantified value that indicates the concentration level of the lineament density across the area impacted by the earthquake. Using this algorithm, the VRD calculated at the earthquake epicenter using the lineament's frequency, intersection, and length density maps ranged from approximately 0.60(min) to 0.90(max). However, because there were differences in mapped images such as those for solar altitude and azimuth, the mean of VRD was used rather than those categorized by the images. The results show that the average frequency of VRD was approximately 0.85, which was 21% higher than the intersection and length of VRD, demonstrating the close relationship that exists between lineament and the epicenter. Therefore, it is concluded that the density map analysis described in this study, based on lineament extraction, is valid and can be used as a primary data analysis tool for earthquake research in the future.

• Journal of the Korean Association of Geographic Information Studies
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• v.20 no.4
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• pp.126-138
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• 2017

Recently, the national interest in environment is increasing and for dealing with water environment-related issues swiftly and accurately, the demand to facilitate the analysis of water environment data using a GIS is growing. To meet such growing demands, a spatial network data-based stream network analysis map(Korean Reach File; KRF) supporting spatial analysis of water environment data was developed and is being provided. However, there is a difficulty in delineating catchment areas, which are the basis of supplying spatial data including relevant information frequently required by the users such as establishing remediation measures against water pollution accidents. Therefore, in this study, the development of a computer program was made. The development process included steps such as designing a delineation method, and developing an algorithm and modules. DEM(Digital Elevation Model) and FDR(Flow Direction) were used as the major data to automatically delineate catchment areas. The algorithm for the delineation of catchment areas was developed through three stages; catchment area grid extraction, boundary point extraction, and boundary line division. Also, an add-in catchment area delineation module, based on ArcGIS from ESRI, was developed in the consideration of productivity and utility of the program. Using the developed program, the catchment areas were delineated and they were compared to the catchment areas currently used by the government. The results showed that the catchment areas were delineated efficiently using the digital elevation data. Especially, in the regions with clear topographical slopes, they were delineated accurately and swiftly. Although in some regions with flat fields of paddles and downtowns or well-organized drainage facilities, the catchment areas were not segmented accurately, the program definitely reduce the processing time to delineate existing catchment areas. In the future, more efforts should be made to enhance current algorithm to facilitate the use of the higher precision of digital elevation data, and furthermore reducing the calculation time for processing large data volume.

• 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.

• Korean Journal of Remote Sensing
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• v.38 no.6_1
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• pp.1371-1383
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• 2022

In this study, the amount of coal waste dump was calculated using six Digital Elevation Models (DEMs) produced between 2006 and 2018 in Jangseong-dong, Taebaek-si, Gangwon-do, and the subsidence was observed by applying the Persistent Scatterer Interferometric SAR (PSInSAR) technique on the Sentinel-1 SAR images. As a result of depositing activities using DEMs, a total of 1,668,980 m³ of coal waste was deposited over a period of about 12 years from 2006 to 2018. The observed subsidence rate from PSInSAR was -32.3 mm/yr and -40.2 mm/yr from the ascending and descending orbits, respectively. As the thickness of the waste pile increased, the rate of subsidence increased, and the more recent the completion of the deposit, the faster the subsidence tended to occur. The subsidence rates from the ascending and descending orbits were converted to vertical and horizontal east-west components, and 22 random reference points were set to compare the subsidence rate, the waste rock thickness, and the time of depositing completion. As a result, the subsidence rate of the reference point tended to increase as the thickness of the waste became thicker, similar to the PSInSAR results in relation to the waste thickness. On the other hand, there was no clear correlation between the completion time of the deposits and the rate Of subsidence at the reference points. This is because the time of completion of the deposits at all but 5 of the 22 reference points was too biased in 2010 and the correlation analysis was meaningless. As in this study, the use of DEM and PSInSAR is expected to be an effective alternative to compensate for the lack of field data in the safety management of coal waste deposits.

• Journal of Environmental Impact Assessment
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• v.27 no.2
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• pp.203-214
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• 2018

The purpose of this study is to estimate the concentrated distribution area of nutria (Myocastor coypus) and potential suitable habitat and to provide useful data for the effective management direction setting. Based on the nationwide distribution data of nutria, the cross-validation value was applied to analyze the distribution density. As a result, the concentrated distribution areas thatrequired preferential elimination is found in 14 administrative areas including Busan Metropolitan City, Daegu Metropolitan City, 11 cities and counties in Gyeongsangnam-do and 1 county in Gyeongsangbuk-do. In the potential suitable habitat estimation using a MaxEnt (Maximum Entropy) model, the possibility of emergency was found in the Nakdong River middle and lower stream area and the Seomjin riverlower stream area and Gahwacheon River area. As for the contribution by variables of a model, it showed DEM, precipitation of driest month, min temperature of coldest month and distance from river had contribution from the highest order. In terms of the relation with the probability of appearance, the probability of emergence was higher than the threshold value in areas with less than 34m of altitude, with $-5.7^{\circ}C{\sim}-0.6^{\circ}C$ of min temperature of the coldest month, with 15-30mm of precipitation of the driest month and with less than 1,373m away from the river. Variables that Altitude, existence of water and wintertemperature affected settlement and expansion of nutria, considering the research results and the physiological and ecological characteristics of nutria. Therefore, it is necessary to reflect them as important variables in the future habitable area detection and expansion estimation modeling. It must be essential to distinguish the concentrated distribution area and the management area of invasive alien species such as nutria and to establish and apply a suitable management strategy to the management site for the permanent control. The results in this study can be used as useful data for a strategic management such as rapid management on the preferential management area and preemptive and preventive management on the possible spreading area.

• Korean Journal of Remote Sensing
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• v.33 no.5_3
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• pp.835-854
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• 2017

Government regulations and policies are important means of restraining the indiscreet expansion of urban areas. According to the standards from those means, it is clear that the fluctuation of forest green proportion encroached by the increase of urban space is obvious. In this study, we interpreted the changes of urban areas as well as the green ones owing to the urban expansion by the decades from 1996, with focusing on the cities of Seoul and Daegu highly developed in South Korea. The purpose of this study is to analyze the spatial expansion and morphological characteristics of urban land cover using not only satellite imageries (1996, 2006, 2016). but also the urban expansion intensity index (UEII) and GUIDOS program. Ultimately, this study is to compare the changes in the rate of forests due to urban expansions annually analyzed based on areas of forest elevation, slope, and the area of single forest patch. In Seoul, the expansion begun from urban space to suburban areas was comparatively rapid, which led the forest fragmentation and the gradual decline of the single patch. However, when it comes to DEM (Digital elevation model) and slope above a certain standard, by the development regulations, there was little decrease in area by anthropogenic developments. The city of Daegu has increased at a slow speed since 1996 in urban and suburban areas, whereas green forests have greatly increased through green forest conservation campaigns. In this way, as to the government policies and regulations, the quantitative and morphological expansion of cities owing to development could be controlled and forest spaces could be preserved as well. Therefore, regulations and policies by the government should be appropriately utilized for sustainable cities.

• Korean Journal of Agricultural and Forest Meteorology
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• v.18 no.4
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• pp.233-241
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• 2016

Experiments were carried out to quantify the topographic effects on attenuation of sunshine in complex terrain and the results are expected to help convert the coarse resolution sunshine duration information provided by the Korea Meteorological Administration (KMA) into a detailed map reflecting the terrain characteristics of mountainous watershed. Hourly shaded relief images for one year, each pixel consisting of 0 to 255 brightness value, were constructed by applying techniques of shadow modeling and skyline analysis to the 3m resolution digital elevation model for an experimental watershed on the southern slope of Mt. Jiri in Korea. By using a bimetal sunshine recorder, sunshine duration was measured at three points with different terrain conditions in the watershed from May 15, 2015 to May 14, 2016. The brightness values of the 3 corresponding pixel points on the shaded relief map were extracted and regressed to the measured sunshine duration, resulting in a brightness-sunshine duration response curve for a clear day. We devised a method to calibrate this curve equation according to sky condition categorized by cloud amount and used it to derive an empirical model for estimating sunshine duration over a complex terrain. When the performance of this model was compared with a conventional scheme for estimating sunshine duration over a horizontal plane, the estimation bias was improved remarkably and the root mean square error for daily sunshine hour was 1.7hr, which is a reduction by 37% from the conventional method. In order to apply this model to a given area, the clear-sky sunshine duration of each pixel should be produced on hourly intervals first, by driving the curve equation with the hourly shaded relief image of the area. Next, the cloud effect is corrected by 3-hourly 'sky condition' of the KMA digital forecast products. Finally, daily sunshine hour can be obtained by accumulating the hourly sunshine duration. A detailed sunshine duration distribution of 3m horizontal resolution was obtained by applying this procedure to the experimental watershed.

• 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.

• Korean Journal of Remote Sensing
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• v.37 no.2
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• pp.321-335
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• 2021

Particulate matter (PM10 and PM2.5 with a diameter less than 10 and 2.5 ㎛, respectively) can be absorbed by the human body and adversely affect human health. Although most of the PM monitoring are based on ground-based observations, they are limited to point-based measurement sites, which leads to uncertainty in PM estimation for regions without observation sites. It is possible to overcome their spatial limitation by using satellite data. In this study, we developed machine learning-based retrieval algorithm for ground-level PM10 and PM2.5 concentrations using aerosol parameters from Geostationary Ocean Color Imager (GOCI) satellite and various meteorological parameters from a numerical weather prediction model during January to December of 2019. Gradient Boosted Regression Trees (GBRT) and Light Gradient Boosting Machine (LightGBM) were used to estimate PM concentrations. The model performances were examined for two types of feature sets-all input parameters (Feature set 1) and a subset of input parameters without meteorological and land-cover parameters (Feature set 2). Both models showed higher accuracy (about 10 % higher in R2) by using the Feature set 1 than the Feature set 2. The GBRT model using Feature set 1 was chosen as the final model for further analysis(PM10: R2 = 0.82, nRMSE = 34.9 %, PM2.5: R2 = 0.75, nRMSE = 35.6 %). The spatial distribution of the seasonal and annual-averaged PM concentrations was similar with in-situ observations, except for the northeastern part of China with bright surface reflectance. Their spatial distribution and seasonal changes were well matched with in-situ measurements.