• Korean Journal of Agricultural and Forest Meteorology
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• v.16 no.4
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• pp.389-395
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• 2014

This technical note describes about the base stages of technology implementation for establishing "Early Warning System for Weather Hazard Management in Climate-smart Agriculture" to national onsite service. First of all, a special weather report service at catchment was represented sequential risk of 810 units of catchment by spatial statistical methods to existing 150 counties units special weather report released in KMA. The second, chronic hazard alarm service based on daily data of 76 Synoptic stations was monitor about 810 Catchment of mid-long term lapse weather and represented as a relative risk index chronic hazard risk of this time in preparation for the climatological normal conditions in the same period. Finally, we establish the foundation for delivering individually calculated field specific in hazard risk about volunteer farmer of early warning service demonstration area in seomjin downstream watershed. These three types of information were built a near real-time map service on the VWORLD background map of Ministry of Land as superposed layers nationwide catchment and demonstration areas within the farm unit weather hazard.

• Journal of Korean Society of Forest Science
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• v.81 no.1
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• pp.40-52
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• 1992

The use of meteorological information is essential in the industrial society. More specialized weather services are required to perform better industrial activities including forestry. A topoclimatological technique, in this study, which makes use of empirical relationships between the topography and the weather in Cheju Island was applied to produce reasonable estimates of monthly air temperatures over remote land area where routine observations are rare. Altitude values of the 250m grid points were first read from a 1 : 25000 topographic map. The mean altitude and other valuable topographical variables were then determined for each $1km^2$ land area. Daily minimum, maximum and mean air temperature data were collected from 19 points in Cheju Island from June 1987 to September 1988. The data were analyzed and grouped into 36 sets by type of air temperature and by month. Each of data set was regressed to the topographical variables to delineate empirical relationships between the local air temperature and the site topography. The total of 36 regression equations were finally selected and the equations were used to calculate the monthly air temperature for each $1km^2$ land area. The outputs were presented in a fine-mesh grid map with a 6-level contour capability.

• Korean Journal of Remote Sensing
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• v.36 no.6_1
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• pp.1367-1377
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• 2020

The purpose of this study is to assess the seismic vulnerability of buildings in Gyeongju city starting with the earthquake that occurred in the city on September 12, 2016, and produce a seismic vulnerability map. 11 influence factors related to geotechnical, physical, and structural indicators were selected to assess the seismic vulnerability, and these were applied as independent variables. For a dependent variable, location data of the buildings that were actually damaged in the 9.12 Gyeongju Earthquake was used. The assessment model was constructed based on random forest (RF) as a mechanic study method and support vector machine (SVM), and the training and test dataset were randomly selected with a ratio of 70:30. For accuracy verification, the receiver operating characteristic (ROC) curve was used to select an optimum model, and the accuracy of each model appeared to be 1.000 for RF and 0.998 for SVM, respectively. In addition, the prediction accuracy was shown as 0.947 and 0.926 for RF and SVM, respectively. The prediction values of the entire buildings in Gyeongju were derived on the basis of the RF model, and these were graded and used to produce the seismic vulnerability map. As a result of reviewing the distribution of building classes as an administrative unit, Hwangnam, Wolseong, Seondo, and Naenam turned out to be highly vulnerable regions, and Yangbuk, Gangdong, Yangnam, and Gampo turned out to be relatively safer regions.

• Korean Journal of Agricultural and Forest Meteorology
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• v.23 no.4
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• pp.268-279
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• 2021

The geospatial schemes based on topo-climatology have been developed to produce digital climate maps at a site-specific scale. Their development processes are reviewed here to derive the needs for new schemes in the future. Agricultural and forestry villages in Korea are characterized by complexity and diversity in topography, which results in considerably large spatial variations in weather and climate over a small area. Hence, the data collected at a mesoscale through the Automated Synoptic Observing System (ASOS) operated by the Korea Meteorological Administration (KMA) are of limited use. The geospatial schemes have been developed to estimate climate conditions at a local scale, e.g., 30 m, lowering the barriers to deal with the processes associated with production in agricultural and forestry industries. Rapid enhancement of computing technologies allows for near real-time production of climate information at a high-resolution even in small catchment areas and the application to future climate change scenarios. Recent establishment of the early warning service for agricultural weather disasters can provide growth progress and disaster forecasts for cultivated crops on a farm basis. The early warning system is being expanded worldwide, requiring further advancement in geospatial schemes and digital climate mapping.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.14 no.12
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• pp.2730-2736
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• 2010

Recently, various networks have been introduced in the car of the internal and external sides. These have been integrated by one HMI(Human Machine Interface) to control devices of each network and provide information service. The existing vehicle navigation system, providing GPS based vehicle positioning service, has been included to these integrated networks as a default option. The GPS has been used to the most universal device to provide position information by using satellites' signal. But It is impossible to provide the position information when the GPS can't receive the satellites' signal in the area of tunnel, urban canyon, or forest canopy. Thus, this paper propose and implement the method of measuring vehicle position by using the sensing data of internal CAN network and external Wi-Fi network of the integrated car navigation circumstances when the GPS doesn't work normally. The results obtained by implementation shows the proposed method works well by map matching.

• Proceedings of the KSRS Conference
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• 2001.03a
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• pp.49-55
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• 2001

본 연구에서는 GIS를 이용하여 산불관련 데이터베이스를 구축하고 효과적인 산불 현황정보 검색시스템을 개발하녀 산불 관리자에게 효율적인 공간분석 도구를 제공함으로서 산불에 관한 종합적인 공간정보를 빠른 시간 내에 분석하여 속성을 갱신·추출 할 수 있도록 하는 효과적인 GUI(Graphic User Interface)를 개발하였다. 이를 위하여 최근 10년간의 산불현황 통계자료를 이용한 전국 시·군단위의 공간분포도를 작성하여 전국 산불 발생현황을 시·공간적으로 분석하고 산불 발생에 미치는 다양한 요인들과의 상관성을 분석 가능하였다. 특히 최근 산불발생이 빈번한 삼척시의 지형도 및 임상도, 위성영상, 현지사진을 이용하여 GIS 데이터베이스를 구축함으로서 산불 발생위험지역에 대한 보다 상세한 정보를 얻을 수 있다. 본 시스템은 응용프로그램 개발을 위한 플랫폼은 IBM호환 PC에서 Windows 98을 운영체 제로 하여 DBMS는 Access 2000을 이용하였고 프로그래밍 언어로는 객체지향언어인 Visual Basic 6.0과 GIS 기능을 구현하기 위해서 Component GIS인 MapObjects 2.0을 사용 하였다. 그 결과 산불관리자는 진화에 필요한 관리구역내의 정보를 신속하게 제공받을 뿐만 아니라 산불방제사업에 대한 효과적인 의사결정지원과 함께 실무자 중심의 산불관리행정을 도모하 고 산림자원관리비가 효율적으로 이용될 것이다.

• Proceedings of the Korean Association of Geographic Inforamtion Studies Conference
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• 2003.04a
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• pp.77-82
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• 2003

The purpose of this study is to develop landslide susceptibility analysis techniques using artificial neural network and to apply the developed techniques to the study area of janghung in Korea. Landslide locations were identified in the study area from interpretation of satellite image and field survey data, and a spatial database of the topography, soil, forest and land use were consturced. The 13 landslide-related factors were extracted from the spatial database. Using those factors, landslide susceptibility was analyzed by artificial neural network methods, and the susceptibility map was made with a e15 program. For this, the weights of each factor were determinated in 5 cases by the backpropagation method, which is a type of artificial neural network method. Then the landslide susceptibility indexes were calculated using the weights and the susceptibility maps were made with a GIS to the 5 cases. A GIS was used to efficiently analyze the vast amount of data, and an artificial neural network was turned out be an effective tool to analyze the landslide susceptibility.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.12 no.4
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• pp.1-10
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• 2009

This study has intended to build ecological networks in consideration of life-zones inside Cheongju city through biotope grade, GIS network analysis etc. This study consisted of following three steps. First, we selected core districts and core spot districts using land use patten and biotope grade. The core district included the first grade of biotope and forest land. The core district consisted of two sectors : east axis core, Uam mountain; west axis core, Bumo mountain. The core spot district included the first grade of biotope. The core spot districts consisted of two sectors : north axis base core, Myongshim park; south axis base core, Guryong park. Second, the base district included the second grade of biotope and park and school. We used buffering analysis within 500m of the base district and selected the new base district. Third, we connected core districts and base core districts using least cost analysis of GIS. Thus we built comprehensive ecological networks in consideration of life-zones through GIS.

• Korean Journal of Remote Sensing
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• v.34 no.1
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• pp.45-74
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• 2018

Landslide is a natural hazard that threats lives and properties in many areas around the world. Landslides are difficult to recognize, particularly in rainforest regions. Thus, an accurate, detailed, and updated inventory map is required for landslide susceptibility, hazard, and risk analyses. The inconsistency in the results obtained using different features selection techniques in the literature has highlighted the importance of evaluating these techniques. Thus, in this study, six techniques of features selection were evaluated. Very-high-resolution LiDAR point clouds and orthophotos were acquired simultaneously in a rainforest area of Cameron Highlands, Malaysia by airborne laser scanning (LiDAR). A fuzzy-based segmentation parameter (FbSP optimizer) was used to optimize the segmentation parameters. Training samples were evaluated using a stratified random sampling method and set to 70% training samples. Two machine-learning algorithms, namely, Support Vector Machine (SVM) and Random Forest (RF), were used to evaluate the performance of each features selection algorithm. The overall accuracies of the SVM and RF models revealed that three of the six algorithms exhibited higher ranks in landslide detection. Results indicated that the classification accuracies of the RF classifier were higher than the SVM classifier using either all features or only the optimal features. The proposed techniques performed well in detecting the landslides in a rainforest area of Malaysia, and these techniques can be easily extended to similar regions.

• Advances in environmental research
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• v.9 no.4
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• pp.251-273
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• 2020

Soil degradation has become a major worldwide environmental problem, particularly in arid and semi-arid climate zones due to irregular rainfall and the intensity of storms that frequently generate heavy flooding. The main objective of this study is the use of geographic information system and remote sensing techniques to quantify and to map the soil losses in the Wadi Saida watershed (624 ㎢) through the revised universal soil loss equation model and a proposed model based on the surface erosive runoff. The results Analysis revealed that the Wadi Saida watershed showed moderate to moderately high soil loss, between 0 and 1000 t/㎢/year. In the northern part of the basin in the region of Sidi Boubkeur and the mountains of Daia; which are characterized by steep slopes, values can reach up to 3000 t/㎢/year. The two models in comparison showed a good correlation with R = 0.95 and RMSE = 0.43; the use of the erosive surface runoff parameter is effective to estimate the rate of soil loss in the watersheds. The problem of soil erosion requires serious interventions, particularly in basins with disturbances and aggressive climatic parameters. Good agricultural practices and forest preservation areas play an important role in soil conservation.