• Korean Journal of Remote Sensing
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• v.39 no.6_1
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• pp.1245-1254
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• 2023

Significant research has been conducted on the W-band synthetic aperture radar (SAR) system that utilizes the 77 GHz frequency modulation continuous wave (FMCW) radar. To reconstruct the high-resolution W-band SAR image, it is necessary to transform the point cloud acquired from the stereo cameras or the LiDAR in the direction of 6 degrees of freedom (DOF) and apply them to the SAR signal processing. However, there are difficulties in matching images due to the different geometric structures of images acquired from different sensors. In this study, we present the method to extract an optimized depth map by obtaining 6 DOF of the point cloud using a gradient descent method based on the entropy of the SAR image. An experiment was conducted to reconstruct a tree, which is a major road environment object, using the constructed W-band SAR system. The SAR image, reconstructed using the entropy-based gradient descent method, showed a decrease of 53.2828 in mean square error and an increase of 0.5529 in the structural similarity index, compared to SAR images reconstructed from radar coordinates.

• Journal of Korean Society of Rural Planning
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• v.2 no.2
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• pp.109-117
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• 1996

The purpose of this study Is to develop water quality management system fort a farm village stream. The framework design of the system and the ecological monitoring of a test watershed were carried out, The system consists of GIS(Geographic Information System ), database, pollution source management, water quality and hydrologic analysis. Suri watershed located on Idong, Yongin city, Kyunggi Province, was selected as the test watershed for the application of the system. The fifteen's monitoring stations were chooses at up- and down-stream of the watershed. The results of an aquatic ecological monitoring were analyzed by the GPI(Group Pollution Index) method. The GPI revealed that water quality was varied within the stream. GPI and DO map for the watershed stream were developed, These maps facilitated to analyze the spatial distribution of the water quality.

• The Journal of Engineering Geology
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• v.20 no.4
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• pp.391-399
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• 2010

We performed a hydraulic analysis based on the wetness index of talus slopes in Jungsun, Gangwon province. We estimated the relation between the degree of development of the temporary water system, and talus topography and distribution. We also assessed the distribution of talus based on a map of the wetness index. We divided areas of tallus into stable and unstable types, and estimated the size, distribution and shape-preferred orientation of clasts. We performed numerical simulations of rockfall events to assess the optimum location of rockfall barriers upon talus slopes.

• Journal of the Korea Convergence Society
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• v.10 no.4
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• pp.33-38
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• 2019

Recently, to support location-based services, there have been many researches which consider the spatial network. For this, there are many experimental data for data processing on the road network. However, the data to process the trajectory of moving objects are not suitable. Therefore, we propose index structure to process the trajectory data on the road network and the trajectory data generation algorithm. In addition, to prove efficiency of our index structure and algorithm, we show that edge-based trajectory data are generated through the proposed algorithm using the map data of San Francisco Bay.

• Proceedings of the National Institute of Ecology of the Republic of Korea
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• v.2 no.1
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• pp.1-14
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• 2021

The study has been carried out with an objective to prepare Siberian roe deer habitat potential maps in South Korea based on three geographic information system-based models including frequency ratio (FR) as a bivariate statistical approach as well as convolutional neural network (CNN) and long short-term memory (LSTM) as machine learning algorithms. According to field observations, 741 locations were reported as roe deer's habitat preferences. The dataset were divided with a proportion of 70:30 for constructing models and validation purposes. Through FR model, a total of 10 influential factors were opted for the modelling process, namely altitude, valley depth, slope height, topographic position index (TPI), topographic wetness index (TWI), normalized difference water index, drainage density, road density, radar intensity, and morphological feature. The results of variable importance analysis determined that TPI, TWI, altitude and valley depth have higher impact on predicting. Furthermore, the area under the receiver operating characteristic (ROC) curve was applied to assess the prediction accuracies of three models. The results showed that all the models almost have similar performances, but LSTM model had relatively higher prediction ability in comparison to FR and CNN models with the accuracy of 76% and 73% during the training and validation process. The obtained map of LSTM model was categorized into five classes of potentiality including very low, low, moderate, high and very high with proportions of 19.70%, 19.81%, 19.31%, 19.86%, and 21.31%, respectively. The resultant potential maps may be valuable to monitor and preserve the Siberian roe deer habitats.

• Atmosphere
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• v.19 no.2
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• pp.169-182
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• 2009

To improve the performance of climate and numerical models, concerns on the land-atmosphere schemes are steadily increased in recent years. For the realistic calculation of land-atmosphere interaction, a land surface information of high quality is strongly required. In this study, a new land cover map over the Korean peninsula was developed using MODIS (MODerate resolution Imaging Spectroradiometer) data. The seven phenological data set (maximum, minimum, amplitude, average, growing period, growing and shedding rate) derived from 15-day normalized difference vegetation index (NDVI) were used as a basic input data. The ISOData (Iterative Self-Organizing Data Analysis), a kind of unsupervised non-hierarchical clustering method, was applied to the seven phenological data set. After the clustering, assignment of land cover type to the each cluster was performed according to the phenological characteristics of each land cover defined by USGS (US. Geological Survey). Most of the Korean peninsula are occupied by deciduous broadleaf forest (46.5%), mixed forest (15.6%), and dryland crop (13%). Whereas, the dominant land cover types are very diverse in South-Korea: evergreen needleleaf forest (29.9%), mixed forest (26.6%), deciduous broadleaf forest (16.2%), irrigated crop (12.6%), and dryland crop (10.7%). The 38 in-situ observation data-base over South-Korea, Environment Geographic Information System and Google-earth are used in the validation of the new land cover map. In general, the new land cover map over the Korean peninsula seems to be better classified compared to the USGS land cover map, especially for the Savanna in the USGS land cover map.

• Spatial Information Research
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• v.2 no.2
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• pp.165-174
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• 1994

Soil loss was estimated by using universal soil loss equation(USLE) through GIS technique in Buyeu area. The expected soil loss is determined from six environmental factors: rainfall, erodibility of selected soil, length and steepness (gradient) of ground slope, crop grown in soil, and land practices used. A scoring system for assessing soil lossrisk has been developed for calculating SLI(Soil Loss Index) by GIS. The scores of six factors multiplied to give a total score which was compared with an chosen classification system to categorize areas of low, moderate and high risk. Finally, a soil loss assessment map was produced by GIS cartographic simulation technique, and this map could be applied in the establishment of regional land use planning.

• Journal of the Korean Association of Geographic Information Studies
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• v.13 no.3
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• pp.1-13
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• 2010

The aim of this study is to analyze gold-silver mineral potential in the Taebaeksan mineralized district, Korea using a Geographic Information System(GIS) and an artificial neural network(ANN) model. A spatial database considering Au and Ag deposit, geology, fault structure and geochemical data of As, Cu, Mo, Ni, Pb and Zn was constructed for the study area using the GIS. The 46 Au and Ag mineral deposits were randomly divided into a training set to analyze mineral potential using ANN and a test set to verify mineral potential map. In the ANN model, training sets for areas with mineral deposits and without them were selected randomly from the lower 10% areas of the mineral potential index derived from existing mineral deposits using likelihood ratio. To support the reliability of the Au-Ag mineral potential map, some of rock samples were selected in the upper 5% areas of the mineral potential index without known deposits and analyzed for Au, Ag, As, Cu, Pb and Zn. As the result, No. 4 of sample exhibited more enrichments of all elements than the others.

• Ecology and Resilient Infrastructure
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• v.4 no.2
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• pp.115-121
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• 2017

This study estimated potential natural vegetation in Gayasan National Park through the occurrence probability distribution by using geographic information system (GIS). in Gayasan National Park. Correlation and factor analysis were analyzed to estimate probability distribution. The presence of the Gaya National Park Vegetation survey results showed that 128 communities were distributed. The analyzed relationship between actual vegetation and distribution factors such as elevation, aspect, slope, topographic index, annual mean temperature, warmth index and potential evapotranspiration in Gayasan national park. The probability distribution of potential natural vegetation communities at least 0.3 odds were the advent of Pinus densiflora communities with the highest 55.80%, Quercus mongolica community is 44.05%, 0.09% is Quercus acutissima communities, Quercus variabilis communities are found to be 0.06%. If you want to limit the factors that affect the distribution of vegetation by factors presented in this study, the potential natural vegetation of the Gaya National Park was expected to appear in Quercus mongolica community (43.1%) and Pinus densiflora communities (56.9%).

• Journal of Korean Society of Forest Science
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• v.99 no.5
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• pp.770-776
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• 2010

This study was conducted to assess the existing flora and fauna, and to develop a spatial map of Alapang communal forest located in the province of Benguet, Philippines. A total of 52 species belonging to 27 families were identified during the inventory in this communal forest using the quadrat method while a total of 30 species belonging to 18 families were recorded using line intercept technique for the assessment of grasses, herbs, vines and other low-lying vegetation. The diversity index of the species in Alapang communal forests using the quadrat method was 2.6649 while for the line intercept technique it was 2.5446. The most dominant species in this area was found to be Pinus kesiya Royle ex Gordon (Benguet pine) under Family Pinaceae with an importance value of 106.74%. In the faunal assessment, four species of birds and a small mammal particularly a rodent were identified during the study. Aside from the high species diversity of this communal forest, the presence of endemic and indicator species in the area denotes that this forest was still in good condition hence must be protected. Spatial maps and database system were generated based from data gathered in the field using Geographic Information System (GIS).