• Journal of Forest and Environmental Science
• /
• v.40 no.1
• /
• pp.24-34
• /
• 2024

Fire, being primarily a natural phenomenon, is impossible to control, although it is feasible to map the forest fire risk zone, minimizing the frequency of fires. The spread of a fire starting in any stand in a forest can be predicted, given the burning conditions. The natural cover of the land and the safety of the population may be threatened by the spread of forest fires; thus, the prevention of fire damage requires early discovery. Satellite data and geographic information system (GIS) can be used effectively to combine different forest-fire-causing factors for mapping the forest fire risk zone. This study mainly focuses on mapping forest fire risk in the Madikhola watershed. The primary causes of forest fires appear to be human negligence, uncontrolled fire in nearby forests and agricultural regions, and fire for pastoral purposes which were used to evaluate and assign risk values to the mapping process. The majority of fires, according to MODIS events, occurred from December to April, with March recording the highest occurrences. The Risk Zonation Map, which was prepared using LULC, Forest Type, Slope, Aspect, Elevation, Road Proximity, and Proximity to Water Bodies, showed that a High Fire Risk Zone comprised 29% of the Total Watershed Area, followed by a Moderate Risk Zone, covering 37% of the total area. The derived map products are helpful to local forest managers to minimize fire risks within the forests and take proper responses when fires break out. This study further recommends including the fuel factor and other fire-contributing factors to derive a higher resolution of the fire risk map.

• Spatial Information Research
• /
• v.10 no.2
• /
• pp.331-343
• /
• 2002

Recently, as various fields of applications using space-borne imagery have been emphasized, interests on integrated analysis or fusion using multi-sources are also increasing. In this study, to investigate applicability of multiple imageries for further regional-scaled application, DN value analysis and multi-resolution classification by using KOMPSAT EOC imagery and Landsat 7 ETM+image data in the Namyangju-city area were performed, and then this classified results were compared to land-use thematic data at the same area. In case of classified results by using muff-resolution image data, it is shown that linear-type features can be easily extracted. furthermore, it is expected that multi-resolution classified image can be effectively utilized to urban environment analysis, according to results of similar pattern by comparative study based on multi-buffered zone analysis or so-called distance analysis along main road features in the study area.

• Korean Journal of Remote Sensing
• /
• v.36 no.6_3
• /
• pp.1653-1667
• /
• 2020

In this study, we coupled a computation fluid dynamics (CFD) model to the local data assimilation and prediction system (LDAPS), a current operational numerical weather prediction model of the Korea Meteorological Administration. We investigated the characteristics of fine particulate matter (PM2.5) distributions in a building-congested district. To analyze the effects of road emission on the PM2.5 concentrations, we calculated road emissions based on the monthly, daily, and hourly emission factors and the total amount of PM2.5 emissions established from the Clean Air Policy Support System (CAPSS) of the Ministry of Environment. We validated the simulated PM2.5 concentrations against those measured at the PKNU-AQ Sensor stations. In the cases of no road emission, the LDAPS-CFD model underestimated the PM2.5 concentrations measured at the PKNU-AQ Sensor stations. The LDAPS-CFD model improved the PM2.5 concentration predictions by considering road emission. At 07 and 19 LST on 22 June 2020, the southerly wind was dominant at the target area. The PM2.5 distribution at 07 LST were similar to that at 19 LST. The simulated PM2.5 concentrations were significantly affected by the road emissions at the roadside but not significantly at the building roof. In the road-emission case, the PM2.5 concentration was high at the north (wind speeds were weak) and west roads (a long street canyon). The PM2.5 concentration was low in the east road where the building density was relatively low.

• The Journal of the Korea Contents Association
• /
• v.19 no.10
• /
• pp.179-189
• /
• 2019

Korea's transportation paradigm is shifting from a vehicle-centered to a pedestrian-oriented society. Therefore, the interest in pedestrian safety and the improvement of pedestrian environment is also increasing. However, the level of traffic safety in Korea is still severe. It is needed to improve pedestrian safety and pedestrian environment. This study studied pedestrian-vehicle accident data provided by the Traffic Accident Analysis System(TAAS) for 2013-2015 to build a safe walking environment around school zones, and the relation between the school zones and pedestrian-vehicle traffic accidents were identified through the geographic information system(GIS) and spatial regression model. The main results are as follows. First, both road and public transportation factors are likely to increase pedestrian traffic accidents in school zones. Second, regarding land-use factors, residential, commercial, and industrial areas are found to increase pedestrian traffic crashes. On the other hand, mixed use is likely to play a role on the reduction of pedestrian traffic accidents. Finally, it has been shown that high development density also has a positive effect on pedestrian traffic accidents in school zones.

• Journal of the Economic Geographical Society of Korea
• /
• v.11 no.1
• /
• pp.59-77
• /
• 2008

The purpose of this study is to investigate the impact of traffic-related air pollution on the urban population in the Metropolitan Seoul area. In particular, this study analyzes urban population exposure to traffic-related particulate materials(PM). For the purpose, this study examines the relationships between traffic flows and PM concentration levels during the last fifteen years. Traffic volumes have been decreased significantly in recent year in Seoul, however, PM levels have been declined less compare to traffic volumes. It may be related with the rapid growth in the population and vehicle numbers in Gyenggi, the outskirt of Seoul, where several New Towns have been developed in the middle of 1990's. The spatial pattern of commuting has changed, and thus and travel distances and traffic volumes have increased along the main roads connecting CBDs in Seoul and New Towns consisting of large residential apartment complexes. These changes in traffic flows and travel behaviors cause increasing exposure to traffic-related air pollution for urban population over the Metropolitan Seoul area. GIS techniques are applied to analyze the spatial patterns of traffic flows, population distributions, PM distributions, and passenger flows comprehensively. This study also analyzes real time base traffic flow data and passenger flow data obtained from T-card transaction database applying data mining techniques. This study also attempts to develop a space-time model for assessing journey-time exposure to traffic related air pollutants based on travel passenger frequency distribution function. The results of this study can be used for the implications for sustainable transport systems, public health and transportation policy by reducing urban air pollution and road traffics in the Metropolitan Seoul area.

• Journal of Cadastre & Land InformatiX
• /
• v.50 no.1
• /
• pp.75-85
• /
• 2020

This study examines machine learning cross-validation to utilized create ROI for classification of land cover. The study area located in Sejong and one KOMPSAT-3A image was used in this analysis: procedure on October 28, 2019. We used four bands(Red, Green, Blue, Near infra-red) for learning cross validation process. In this study, we used K-fold method in cross validation and used SVM kernel type with cross validation result. In addition, we used 4 kernels of SVM(Linear, Polynomial, RBF, Sigmoid) for supervised classification land cover map using extracted ROI. During the cross validation process, 1,813 data extracted from 3,500 data, and the most of the building, road and grass class data were removed about 60% during cross validation process. Based on this, the supervised SVM linear technique showed the highest classification accuracy of 91.77% compared to other kernel methods. The grass' producer accuracy showed 79.43% and identified a large mis-classification in forests. Depending on the results of the study, extraction ROI using cross validation may be effective in forest, water and agriculture areas, but it is deemed necessary to improve the distinction of built-up, grass and bare-soil area.

• Journal of Korea Multimedia Society
• /
• v.14 no.7
• /
• pp.933-939
• /
• 2011

Recent heavy rains have caused natural disasters such as flooding and landslides nationwide. Because of flooding occurrence in most of the roads, traffic congestion and isolation caused many loss especially at rush hour. Constant monitoring and analysis of past disaster history data are needed to prevent disasters on areas prone to floods and disaster risk areas. If we managed to obtain traffic volume, speed, phase around intersection using disaster history data when disasters occurred, we can analyse traffic congestion, change of disaster scale and rainfall. In this study, We select a target district to develop by using a route from Dae-nam intersection in Busan Namgu Daeyoeon-dong, over Gwangan large bridge up until Haeundae Olympic intersection, We developed a system which searches disaster history information, traffic volume using disaster history data based on user selection of the road.

• Journal of Korean Society of Water and Wastewater
• /
• v.26 no.5
• /
• pp.669-683
• /
• 2012

The water supply pipes are buried across wide range of areas, so it is hard to spot them using excavation and takes a large amount of expense. Thus, there is a high risk for direct research and application, accompanying many difficulties in implementation of them. Therefore, it is more economical and convenient to use indirect evaluation variables than direct evaluation of the buried pipes in assessing the degree of pipe deterioration. To assess the degree of pipe deterioration using the indirect evaluation variables, it should be done first to identify how and to what extent they affect the degree of deterioration. This study measured the evaluation variables for pipe deterioration using the pipe endoscope and analyzed the measurement results and the degree of impact on the pipes. In addition, this study attempted to evaluate the adequateness of the pipe deterioration evaluation using the indirect variables based on the analysis results. The evaluation variables measured through the pipe endoscope were the thickness of sediments, size of scale, degree of desquamation and condition of connections. For the indirect evaluation variables, the data such as the property data from GIS pipe network map as well as the material, diameter, age and pipe lining material of the pipe, road type, leakage frequency, average water velocity and water pressure using the leakage repair records was collected. Using the collected data, this study comparatively analyzed the indirect evaluation variables for the degree of pipe deterioration and the results from the pipe endoscope to choose appropriate variables for pipe deterioration evaluation and calculated the weights of the indirect variables on the degree of deterioration. The results showed that the order of the impact of indirect variables on deterioration was pipe age > pipe lining material > road type > leakage frequency > average water velocity with their weights of 0.45, 0.20, 0.15, 0.10, and 0.10, respectively. Conclusively, the results suggest that the measures of sediment thickness, scale size, degree of desquamation and condition of connections are appropriate for the evaluation of pipe deterioration and sufficient for the analysis of the impact of the indirect variables on deterioration.

• Journal of Korean Society of Transportation
• /
• v.17 no.2
• /
• pp.55-68
• /
• 1999

Many ITS services require map databases in digital form to meet desired needs. Due to the dynamic nature of ITS and the sheer diversity of applications, the design and development of spatial databases to meet those needs pose a major challenge to both the public and private sectors. This challenge is further complicated by the necessity to transfer locationally referenced information between different kinds of databases and spatial data handling systems so that ITS products will work seamlessly across the region and nation. The Purpose of this paper is to develop the framework-models commonly to reference locations in the various applications and systems-the ITS Map Datum and LRS(Location Referencing System). The ITS Map Datum consists of the around control points which are the prime intersections (nodes) of the nationwide road network In this study, the major points have been determined along wish link-node modeling procedure. LRS, defined as a system for determining the position (location) of an entity relative to other entities or to some external frame of reference, has also been set up using CSOM type method. The method has been implemented using ArcView GIS software over the Kangnam and Seocho districts in the city of Seoul, showing that the implemented LRS scheme can be used successfully elsewhere. With the proper advent of the K.ITS architecture and services, the procedure can be used to improve the data sharing and to inter operate among systems, enhancing the efficiency both in terms of money and time.

• Journal of the Korean Regional Science Association
• /
• v.34 no.2
• /
• pp.21-34
• /
• 2018

The purpose of this study is to analyze the spatial-temporal proliferation of individual factories in the Seoul Metropolitan Area and to provide policy implications. The location of the factory is divided into individual locations and planned locations. In the case of individual locations, it takes a long time to establish factories. Also, due to high cost and regulation, the establishment of individual factories is not easy. However, since the establishment process is simple and the price of land is low, the establishment of individual factories has led to an increase in the number of individual factories. The problem of the undeveloped factories is that the lack of infrastructure such as the road and environmental pollution treatment facilities around the factory deteriorates the pleasant environment and the cityscape and deteriorates the health of the residents in the surrounding area. In this study, we analyzed the location of individual factories established in the Seoul metropolitan area from 2001 to 2016 by using ArcGIS Pro. The results of the analysis are as follows. First, individual location factories are formed around existing industrial complexes and industrial sites. The reason for this is considered to be the external effect that can be obtained from the surrounding area. Secondly, since the Seoul city's individual location factories are established in many residential areas, it shows the conflicting result of the mixture of residence and factory. Third, the Gyeonggi province's individual location factories have a high proportion of non-urban areas. This is because the Gyeonggi province's management area occupies a larger proportion than other areas in Gyeonggi province. This study analyzed the spatial - temporal spreading process of individual factories and the unfolding of individual factories in the metropolitan area, and it can provide policy implications to control the over development of individual factories in the future.