• Journal of Advanced Navigation Technology
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• v.18 no.6
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• pp.546-554
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• 2014

For improvement of network RTK performance in survey field, Spatial Information Research Institute (SIRI), LX Korea Cadastral Survey Corporation installed 30 GNSS permanent stations in Korea Peninsula, and has been running the MAC-based network RTK service as a test version. In this paper, we introduce the LX GNSS network and analyze the positioning accuracy of the LX MAC RTK service. For field test of the LX MAC RTK service, we installed temporally fixed anchor points and observed simultaneously with VRS of National Geographic Information Institute. As a result, the horizontal position differences and initial times of LX MAC with respect to NGII VRS are $1{\sim}2{\pm}1cm$ and <10 seconds, respectively.

• Proceedings of the Korean Association of Geographic Inforamtion Studies Conference
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• 2004.03a
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• pp.481-486
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• 2004

본 연구에서는 분석된 산사태 발생원인을 근거로 산사태 발생 가능 지역에 대한 산사태 발생원인에 대한 등급값을 이용하여, 인접한 연구지역에 교차 적용하여 위험성을 평가하여 취약성도를 작성하고 산사태 피해 예방을 위한 방재 사업, 국토개발 계획 및 건설계획을 위한 기초 자료로 적용 및 활용할 수 있도록 하였다. 연구대상 지역은 여름철 집중호우시 산사태가 많이 발생하는 지역으로 정하였으며, 행정구상으로 강원도 강릉시 사천면 사기막리와 주문진읍 삼교리에 해당한다. 산사태가 발생할 수 있는 요인으로 지형도로부터 경사, 경사방향, 곡률, 수계추출을, 정밀토양도로부터 토질, 모재, 배수, 유효토심, 지형을, 임상도로부터 임상, 경급, 영급, 밀도를, 지질도로부터 암상을, Landsat TM 영상으로부터 토지이용도와 추출하여 격자화 하였으며, 아리랑1호 영상으로부터 선구조를 추출하여 l00m 간격으로 버퍼링한 후 격자화 하였다. 이렇게 구축된 산사태 발생 위치 및 발생요인 데이터베이스를 이용, Frequence ratio를 이용하여 각 요소간의 분류를 산사태와의 상관관계를 바탕으로 취약성도를 구하였다. 그리고 계산된 산사태 취약성 지수의 기존 산사태 발생을 설명하는 능력을 정량적으로 표현하기 위하여 추정능력을 계산하였다 또한 이를 교차적용 하여 산사태 취약성도를 각각의 경우에 맞게 만들었다 이러한 평가는 산사태 피해 예방을 위한 방재 사업, 국토개발 계획, 건설계획 등에 기초자료로서 적용 및 활용될 수 있다.

• Spatial Information Research
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• v.9 no.2
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• pp.341-352
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• 2001

This study was carried out to developed that appraisement model of Potential Productivity Index(PPI). PPI model was used Farmland Productivity Index(FPI) and Labor Productivity Index(LPI) by GIS, and PPI model applied to farm land consolidation region which has been completed recently. FPI was determined by overlapping Poly Grid of the soil properties at the analyzed project region. LPI was estimated by addition productive wages ratio of total direct productive cost. Addition productive wages determined by GIS Network analysis GIS Network analysis of working distance between farm house to paddy and each paddy. PPI variation of each the analyzed paddy of Masu and Weoncheon region was 0.967~0.780 respectively, and could be showed relative largely PPI value. PPI will provide basic element for large scaling and gathering of farm land and a substitute lot of farm land consolidation, and will be maximize productivity of paddy.

• Journal of the Korean Association of Geographic Information Studies
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• v.17 no.2
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• pp.156-172
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• 2014

This research measures and compares on-site net radiation energy, air temperature, wind speed, and surface temperature considering various spatial characteristics with a focus on land use types in urban areas in Changwon, Southern Gyeongsangnam-do, to analyze the accuracy of an ENVI-met model, which is an analysis program of microclimate. The on-site measurement was performed for three days in a mobile measurement: two days during the daytime and one day during the nighttime. The analysis using the ENVI-met model was also performed in the same time zone as the on-site measurement. The results indicated that the ENVI-met model showed higher net radiation than the on-site measurement by approximately $300Wm^{-2}$ during the daytime whereas the latter showed higher net radiation energy by approximately $200Wm^{-2}$ during the nighttime. The temperature was found to be much higher by approximately $2-6^{\circ}C$ in the on-site measurement during both the daytime and nighttime. The on-site measurement also showed higher surface temperature than the ENVI-met by approximately $7-13^{\circ}C$. In terms of the wind speed, there was a significant difference between the results of the ENVI-met model and on-site measurement. As for the correlation between the results of the ENVI-met model and on-site measurement, the temperature showed significantly high correlation whereas the correlations for the net radiation energy, surface temperature, and wind speed were very low. These results appear to be affected by excessive or under estimation of solar and terrestrial radiation and climatic conditions of the surrounding areas and characteristics of land cover. Hence, these factors should be considered when applying these findings in urban and environment planning for improving the microclimate in urban areas.

• Journal of the Korean Association of Geographic Information Studies
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• v.22 no.4
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• pp.39-58
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• 2019

This study performed the dam watershed storm runoff modeling using GPM(Global Precipitation Measurement) satellite rain and KIMSTORM2(KIneMatic wave STOrm Runoff Model 2) distributed model. For YongdamDam watershed(930㎢), three heavy rain events of 25th August 2014, 11th September 2017, and 26th June 2018 were selected and tested for 4 cases of spatial rainfalls such as (a) Kriging interpolated data using ground observed data at 7 stations, (b) original GPM data, (c) GPM corrected by CM(Conditional Merging), and GPM corrected by GDA(Geographical Differential Analysis). For the 4 kinds of data(Kriging, GPM, CM-GPM, and GDA-GPM), the KIMSTORM2 was calibrated respectively using the observed flood discharges at 3 water level gauge stations(Cheoncheon, Donghyang, and Yongdam) with parameters of initial soil moisture contents, stream Manning's roughness coefficient, and effective hydraulic conductivity. The total average Nash-Sutcliffe efficiency(NSE) for the 3 events and 3 stations was 0.94, 0.90, 0.94, and 0.94, determination coefficient(R²) was 0.96, 0.92, 0.97 and 0.96, the volume conservation index(VCI) was 1.03, 1.01, 1.03 and 1.02 for Kriging, GPM, CM-GPM, and GDA-GPM applications respectively. The CM-GPM and GDA-GPM showed better results than the original GPM application for peak runoff and runoff volume simulations, and they improved NSE, R², and VCI results.

• Journal of the Korean Association of Geographic Information Studies
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• v.24 no.3
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• pp.73-82
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• 2021

Rural roads are the significant infrastructure for developing and managing the rural areas, hence the utilization of the remote sensing datasets for managing the rural roads is necessary for expanding the rural transportation infrastructure and improving the life quality of the rural residents. In this research, the two different methods such as image classification and image segmentation were compared for mapping the rural road based on the given high-resolution satellite image acquired in the rural areas. In the image classification method, the deep learning with the multiple neural networks was employed to the given high-resolution satellite image for generating the object classification map, then the rural roads were mapped by extracting the road objects from the generated object classification map. In the image segmentation method, the multiresolution segmentation was employed to the same satellite image for generating the segment image, then the rural roads were mapped by merging the road objects located on the rural roads on the satellite image. We used the 100 checkpoints for assessing the accuracy of the two rural roads mapped by the different methods and drew the following conclusions. The image segmentation method had the better performance than the image classification method for mapping the rural roads using the give satellite image, because some of the rural roads mapped by the image classification method were not identified due to the miclassification errors occurred in the object classification map, while all of the rural roads mapped by the image segmentation method were identified. However some of the rural roads mapped by the image segmentation method also had the miclassfication errors due to some rural road segments including the non-rural road objects. In future research the object-oriented classification or the convolutional neural networks widely used for detecting the precise objects from the image sources would be used for improving the accuracy of the rural roads using the high-resolution satellite image.

• Journal of the Korean Association of Geographic Information Studies
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• v.25 no.1
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• pp.133-149
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• 2022

Existing domestic studies on estimating rice yield were mainly implemented at the level of cities and counties in the entire nation using MODIS satellite images with low spatial resolution. Unlike previous studies, this study tried to estimate rice yield at the level of eup-myon-dong in Gimje-si, Jeollabuk-do using Sentinel-2 satellite images with medium spatial resolution, rainfall and soil data, and then to evaluate its accuracy. Five vegetation indices such as NDVI, LAI, EVI2, MCARI1 and MCARI2 derived from Sentinel-2 images of August 1, 2018 for Gimje-si, Jeollabuk-do, rainfall and paddy soil-type data were aggregated by the level of eup-myon-dong and then rice yield was estimated with gamma generalized linear model, an expanded variant of multi-variate regression analysis to solve the non-normality problem of dependent variable. In the rice yield model finally developed, EVI2, rainfall days in September, and saline soils ratio were used as significant independent variables. The coefficient of determination representing the model fit was 0.68 and the RMSE for showing the model accuracy was 62.29kg/10a. This model estimated the total rice production in Gimje-si in 2018 to be 96,914.6M/T, which was very close to 94,470.3M/T the actual amount specified in the Statistical Yearbook with an error of 0.46%. Also, the rice production per unit area of Gimje-si was amounted to 552kg/10a, which was almost consistent with 550kg/10a of the statistical data. This result is similar to that of the previous studies and it demonstrated that the rice yield can be estimated using Sentinel-2 satellite images at the level of cities and counties or smaller districts in Korea.

• Journal of the Korean association of regional geographers
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• v.2 no.2
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• pp.49-73
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• 1996

This study produces quantitatively weather entropy and information ratio using information theory about frequency in the appearance of precipitation phenomenon and monthly change, and then applies them to observation of the change of their space scale by time. As a result of these, this study defines Pusan, Chongju and Kwangju's weather representativeness and then establishes the range of weather representativeness. Based on weather entropy (statistical parameter)-the amount of average weather information-and information ratio, we can define each area's weather representativeness, which can show us more constant form included topographical, geographical factors and season change. The data used for this study are the daily precipitotion and cloudiness during the recent five years($1990{\sim}1994$) at the 69 stations in Korea. It is divided into class of no precipitation, that of precipitation. The results of this study can be summarized as follows: (1) The four season's mean value of information ratio is the highest value. as 0.641, on the basis of Chongju. It is the lowest as 0.572, on the basis of Pusan. On a seasonal basis, the highest mean value of information rate is April's (spring) in Chongju, and the lowest is October's(fall) in Pusan. Accordingly weather representativeness has the highest in Chongju and the lowest in Pusan. (2) To synthesize information ratio of decaying tendancy and half-decay distance, Chonju's weather representativeness has the highest in April, July and October. And kwangju has the highest value in January and the lowest in April and July. Pusan's weather representativeness is not high, that of Pusan's October is the lowest in the year. (3) If we establish the weather representative character on the basis of Chongju-Pusan, the domain of Chongju area is larger than that of Pusan area in October, July and April in order. But Pusan's is larger than Chongju's in January. In the case of Chongju and Kwangju, the domain of Chongju area is larger than that of Kwangju in October, July and April in order, but it is less than that of Kwangju area in January. In the case of Kwangju-Pusan, the domain of Kwangju is larger than that of Pusan in October, July in order. But in April it is less than Pusan's.

• Journal of the Korean earth science society
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• v.21 no.6
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• pp.719-733
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• 2000

Normally, a digital geologic map can be defined as mappable one whose spatial information with geographic information details and geologic database attribute, recorded in a digital format that is readable by computer. It shows fundamentally two different conceptual perspectives: cartography for digital mapping and analysis for geo-data processing. While, as both aspects basically relate to natural entities and their interpretation of complex features fused with multi-sources, digital geo-data mapping or geologic mapping, it should be distinguished from digital mapping in engineering such as UIS(Urban Infomation System) and AM/FM(Automated Mapping/Facilities Management). Furthermore, according to short-cycled development of GIS(Geographic Information System) software architecture based on IT(Information Technology) and wide expansion of GIS applications' fields, the importance of domain analysis and application model is emphasized at digital geologic informatizaion. In this paper, first terms and concepts of geo-data model with general data modeling aspects are addressed, and then case histories for geo-data modeling and several approaches for data modeling in GIS application fields are discussed. Lastly, tentative conceptual geo-data modeling by using UML(Unified Modeling Language) of OO(Object-oriented) concepts with respect to USGS/AASG geo-data mode is attempted. Through this approach, the main benefits for standardization and implementation lineage with conceptual model in consideration to reusability are expected. Conclusively, it is expected that geo-information system and its architecture by UML is the new coming key approach for the GIS application in geo-sciences.

• Convergence Security Journal
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• v.20 no.4
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• pp.143-151
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• 2020

The cyber battlefield called the fifth battlefield, is not based on geological information unlike the existing traditional battlefiels in the land, sea, air and space, and has a characteristics that all information has tightly coupled correlation to be anlayized. Because the cyber battlefield has created by the network connection of computers located on the physical battlefield, it is not completely seperated from the geolocational information but it has dependency on network topology and software's vulnerabilities. Therefore, the analysis for cyber battlefield should be provided in a form that can recognize information from multiple domains at a glance, rather than a single geographical or logical aspect. In this paper, we describe a study on the development of the cyber operation COP(Common Operational Picture), which is essential for command and control in the cyber warfare. In particular, we propose an architecure for cyber operation COP to intuitively display information based on visualization techniques applying the multi-layering concept from multiple domains that need to be correlated such as cyber assets, threats, and missions. With this proposed cyber operation COP with multi-layered visualization that helps to describe correlated information among cyber factors, we expect the commanders actually perfcrm cyber command and control in the very complex and unclear cyber battlefield.