• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.1D
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• pp.195-202
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• 2006

The infiltration route analysis is a military application using geospatial information technology. The result of the analysis would present vulnerable routes for potential enemy infiltration. In order to find the susceptible routes, optimal path search algorithms (Dijkstra's and $A^*$) were used to minimize the cost function, summation of detection probability. The cost function was produced by capability of TOD (Thermal Observation Device), results of viewshed analysis using DEM (Digital Elevation Model) and two related geospatial information coverages (obstacle and vegetation) extracted from VITD (Vector product Interim Terrain Data). With respect to 50m by 50m cells, the individual cost was computed and recorded, and then the optimal infiltration routes was found while minimizing summation of the costs on the routes. The proposed algorithm was experimented in Daejeon region in South Korea. The test results show that Dijkstra's and $A^*$ algorithms do not present significant differences, but A* algorithm shows a better efficiency. This application can be used for both infiltration and surveillance. Using simulation of moving TOD, the most vulnerable routes can be detected for infiltration purpose. On the other hands, it can be inversely used for selection of the best locations of TOD. This is an example of powerful geospatial solution for military application.

• Journal of Environmental Impact Assessment
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• v.32 no.6
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• pp.545-555
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• 2023

This study aimed to predict the distribution density and potential habitat of domestic cats (Felis catus) in order to identify core distribution areas. It also aimed to overlay protected areas to identify priority areas for cat management. Kernel density estimation was used to determine the distribution density, and areas with high density were classified in Greater Seoul, Chungnam, Daejeon, and Daegu. Elevation, distance from the used area and roughness were identified as important variables in predicting potential habitat using the MaxEnt model. In addition, the classification of suitable and unsuitable areas based on thresholds showed that the predicted presence of habitat was more extensive in Seoul, Sejong, Daejeon, Chungnam, and Daegu. Core distribution areas were selected by overlapping high-density areas with suitable areas. Priority management areas were identified by overlaying core distribution areas with designated wildlife sanctuaries. As a result, Gyeonggi, and Chungnam have the largest areas. In addition, buffer zones will be implemented to effectively manage the core distribution area and minimize the potential for additional introductions in areas of high management priority, such as protected areas. These results can be used as a basis for investigating the status of the cat's habitat and developing more effective management strategies.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.26 no.5
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• pp.19-32
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• 2023

The fragmentation of habitats resulting from human activities leads to the isolation of wildlife and it also causes wildlife-vehicle collisions (i.e. Road-kill). In that sense, it is important to predict potential habitats of specific wildlife that causes wildlife-vehicle collisions by considering geographic, environmental and transportation variables. Road-kill, especially by large mammals, threatens human safety as well as financial losses. Therefore, we conducted this study on roe deer (Capreolus pygargus tianschanicus), a large mammal that causes frequently Road-kill in Jeju Island. So, to predict potential wildlife habitats by considering geographic, environmental, and transportation variables for a specific species this study was conducted to identify high-priority restoration sites with both characteristics of potential habitats and road-kill hotspot. we identified high-priority restoration sites that is likely to be potential habitats, and also identified the known location of a Road-kill records. For this purpose, first, we defined the environmental variables and collect the occurrence records of roe deer. After that, the potential habitat map was generated by using Random Forest model. Second, to analyze roadkill hotspots, a kernel density estimation was used to generate a hotspot map. Third, to define high-priority restoration sites, each map was normalized and overlaid. As a result, three northern regions roads and two southern regions roads of Jeju Island were defined as high-priority restoration sites. Regarding Random Forest modeling, in the case of environmental variables, The importace was found to be a lot in the order of distance from the Oreum, elevation, distance from forest edge(outside) and distance from waterbody. The AUC(Area under the curve) value, which means discrimination capacity, was found to be 0.973 and support the statistical accuracy of prediction result. As a result of predicting the habitat of C. pygargus, it was found to be mainly distributed in forests, agricultural lands, and grasslands, indicating that it supported the results of previous studies.

• Journal of Korea Water Resources Association
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• v.56 no.12
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• pp.837-844
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• 2023

Small and medium-sized mountain rivers that flow through steep, confined valleys carry large amounts of coarse-grained sediment and woody debris during floods. It causes an increase in flood water level by aggrading the riverbed and the cross-section blockage due to driftwood accumulation during flooding. However, the existing flood level calculation in the river basic plan does not consider these changes. In this study, using the Typhoon Hinnamnor flood in September 2022 as an example, we performed numerical simulations using the HEC-RAS model, taking into account the blockage of a cross-section at the bridge and changes in riverbed elevation that occurred during floods, and analyzed the flood level to predict flood risk. This study's results show that flooding occurs if more than 30% of the cross-section is blocked. The rise of flood water levels corresponds to that of the riverbed due to sediment deposition. These results can be used as basic data to prevent and effectively manage flood damage and contribute to establishing flood defense measures that consider actual phenomena.

• Journal of Korea Water Resources Association
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• v.57 no.9
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• pp.615-626
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• 2024

To accurately and efficiently monitor soil moisture (SM) across South Korea, this study developed a SM estimation model that integrates the cloud computing platform Google Earth Engine (GEE) and Automated Machine Learning (AutoML). Various spatial information was utilized based on Terra MODIS (Moderate Resolution Imaging Spectroradiometer) and the global precipitation observation satellite GPM (Global Precipitation Measurement) to test optimal input data combinations. The results indicated that GPM-based accumulated dry-days, 5-day antecedent average precipitation, NDVI (Normalized Difference Vegetation Index), the sum of LST (Land Surface Temperature) acquired during nighttime and daytime, soil properties (sand and clay content, bulk density), terrain data (elevation and slope), and seasonal classification had high feature importance. After setting the objective function (Determination of coefficient, R² ; Root Mean Square Error, RMSE; Mean Absolute Percent Error, MAPE) using AutoML for the combination of the aforementioned data, a comparative evaluation of machine learning techniques was conducted. The results revealed that tree-based models exhibited high performance, with Random Forest demonstrating the best performance (R² : 0.72, RMSE: 2.70 vol%, MAPE: 0.14).

• Journal of the Korean earth science society
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• v.24 no.3
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• pp.205-215
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• 2003

A precise and dense Bouguer anomaly is one of the most important data to improve the knowledge of our environment in the aspect of geophysics and physical geodesy. Besides the precise absolute gravity station net, we should consider two parts; one is to improve the precision in gravity measurement and correction of it, and the other is the density of measurement both in number and distribution. For the precise positioning, we have tested how we could use the GPS properly in gravity measurement, and deduced that the GPS measurement for 5 minutes would be effective when we used DGPS with two geodetic GPS receivers and the baseline was shorter than 40km. In this case we should use a precise geoid model such as PNU95. By applying this method, we are able to reduce the cost, time, and number of surveyors, furthermore we also get the benefit of improving in quality. Two kind of computer programs were developed to correct crossover errors and to calculate terrain effects more precisely. The repeated measurements on the same stations in gravity surveying are helpful not only to correct the drifts of spring but also to approach the results statistically by applying network adjustment. So we can find out the blunders of various causes easily and also able to estimate the quality of the measurements. The recent developments in computer technology, digital elevation data, and precise positioning also stimulate us to improve the Bouguer anomaly by more precise terrain correction. The gravity data of various sources, such as land gravity data (by Choi, NGI, etc.), marine gravity data (by NORI), Bouguer anomaly map of North Korea, Japanese gravity data, altimetry satellite data, and EGM96 geopotential model, were collected and processed to get a precise and dense Bouguer anomaly in and around the Korean Peninsula.

• 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.

• Journal of Life Science
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• v.23 no.6
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• pp.812-824
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• 2013

Reserpine, an anti-hypertensive drug, is able to positively modulate several phenotypes associated with $A{\beta}$ toxicity in a Caenorhabditis elegans model of Alzheimer's disease (AD). We investigated into the therapeutic effects of reserpine on mammalian neurodegenerative disorders, and found that significant alteration of the key factors influencing AD was detected in Tg2576 mice after reserpine treatment for 30 days. The aggressive behavior of Tg2576 mice was significantly improved upon reserpine treatment, whereas their social contact was consistently maintained. Furthermore, the levels of $A{\beta}$-42 peptide in the hippocampus of the brain and blood serum were lower in the reserpine-treated group than in the vehicle-treated group. Among g-secretase components, the expression levels of PS-2, Pen-2, and APH-1 were slightly lower in reserpine-treated Tg2576 mice, although a significant change in nicastrin (NCT) expression was not detected. Furthermore, the serum level of nerve growth factor (NGF) increased in reserpine-treated Tg2576 mice compared with vehicle-treated mice. Among down-stream effectors of the NGF receptor TrkA signaling pathway, reserpine treatment induced elevation of TrkA phosphorylation and reduction of ERK phosphorylation. In addition, in the NGF receptor $p75^{NTR}$ signaling pathway, the expression levels of $p75^{NTR}$ and Bcl-2 were enhanced in reserpine-treated Tg2576 mice compared with vehicle-treated mice, whereas the expression level of RhoA declined. Overall, these results suggest that reserpine can help relieve AD pathogenesis in Tg2576 mice through downregulation of $A{\beta}$-42 deposition, alteration of ${\gamma}$-secretase components, and regulation of NGF metabolism.

• Journal of the Korean Institute of Landscape Architecture
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• v.48 no.1
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• pp.25-34
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• 2020

Land use in watersheds has been shown to be a major driving factor in determining the status of the water quality of streams. In this light, scientists have been investigating the roles of riparian vegetation on the relationships between land use in watersheds and the associated stream water quality. Numerous studies reported that riparian vegetation could alleviate the adverse effects caused by land use in watersheds and on stream water quality through various hydrological, biochemical and ecological mechanisms. However, this concept has been criticized as the true effects of riparian vegetation must be assessed by comprehensive models that mimic real environmental settings. This study aimed to estimate a comprehensive structural equation model integrating topography, land use, and characteristics of riparian vegetation. We used water quality data from the Nakdong River system monitored under the National Aquatic Ecosystem Monitoring Program (NAEMP) of the Korean Ministry of Environment (MOE). Also, riparian vegetation data and land use data were extracted from the Land Use/Land Cover map (LULC) produced by the MOE. The number of structural equation models (SEMs) were estimated in Amos of IBM SPSS. Study results revealed that land use was determined by elevation, and developed areas within a watershed significantly increased the concentration of Total Nitrogen (TN) in streams and LDI in riparian vegetation. On the contrary, developed areas significantly reduced LPI and PLAND. At the same time, PLAND and LDI significantly reduced the concentration of TN in streams. Thus, it was clear that developed areas in watersheds had both a direct and an indirect impact on the concentration of TN in streams, and spatial pattern and the amount of vegetation of riparian vegetation could significantly alleviate the negative impacts of developed areas on TN concentration in streams. To enhance stream water quality, reducing developed areas in a watershed is critical for long-term watershed management plans, restoration patterns for riparian vegetation could be immediately implemented since riparian areas were less developed than most other watersheds.

• Korean Journal of Agricultural and Forest Meteorology
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• v.19 no.3
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• pp.153-163
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• 2017

The objective of this study is to enhance the model's speed of estimating weather variables (e.g., minimum/maximum temperature, sunshine hour, PRISM (Parameter-elevation Regression on Independent Slopes Model) based precipitation), which are applied to the Agrometeorological Early Warning System (http://www.agmet.kr). The current process of weather estimation is operated on high-performance multi-core CPUs that have 8 physical cores and 16 logical threads. Nonetheless, the server is not even dedicated to the handling of a single county, indicating that very high overhead is involved in calculating the 10 counties of the Seomjin River Basin. In order to reduce such overhead, several cache and parallelization techniques were used to measure the performance and to check the applicability. Results are as follows: (1) for simple calculations such as Growing Degree Days accumulation, the time required for Input and Output (I/O) is significantly greater than that for calculation, suggesting the need of a technique which reduces disk I/O bottlenecks; (2) when there are many I/O, it is advantageous to distribute them on several servers. However, each server must have a cache for input data so that it does not compete for the same resource; and (3) GPU-based parallel processing method is most suitable for models such as PRISM with large computation loads.