Korean | English

pISSN : 1598-6160

2020 KCI Impact Factor : 0.84
Home > Explore Content > All Issues > Article List

2019, Vol.19, No.1

  • 1.

    A Thought on Survey Education in Cartography in the Enlightening Period: Focusing on the Department of Forestry Short Term, Bosung College

    Son Seungho | Nam Young-Woo | 2019, 19(1) | pp.1~16 | number of Cited : 0
    Abstract
    It has already been revealed in a prior study that the first modern map of the Korean Peninsula wasproduced by the Japanese Military Surveys. The Korean Empire government established an intellectual departmentin 1895 and established the Yangjiamun in 1898 and attempted to train the survey for mapping and development,but there was some discussion among the Chungchuwon about the abolition of the issue. Map and surveyeducation for making modern maps of Korea was first conducted at Yungheung Agricultural Training Centerin 1909. It was the implementation of the new education and forest law that the survey education became anurgent matter for Korea. As a result, surveying schools and institutes have been established in Seoul and otherparts of the country, stimulating survey education. It is believed that the year 1908 to 1909 was the heydayof surveying school. At this time, Yungheung Agricultural Training Center of Bosung Primary School wastransferred to the forestry properties of Bosung College. However, the four short years of surveying have beenshort-lived due to financial difficulties and the annexation of Korea.
  • 2.

    The Characteristics of Police Station Names in South Korea: Focused on the Comparison between 1945 and 2018

    Song Hoyul | 2019, 19(1) | pp.17~34 | number of Cited : 4
    Abstract
    It has been 73 years since the Korean national police were founded. However, there has been neitherprofessional nor academic studies about police station names. This study investigates the linguistic and geographiccharacteristics of police station names by comparing two different time periods: 1945 and 2018. The results areas follows. In syllable analysis, names with ‘two-syllable’ in 1945 showed the highest portion with 95.2%, butin 2018 ‘two-syllable’ was 52.9% and ‘four-syllable’ was 42.7%. In word type analysis, ‘Sino-Korea word’ washigh with 100% in 1945 and 87.8% (in fact, 100%) in 2018. In name source analysis, administrative district namehas major influence showing 97.8% in 1945 and 93.3% in 2018. Some incongruent police station names wereobserved. However, the incongruity has been greatly improved. Continuous efforts have been made to matchpolice station names with administrative district names for enhancing citizens’ convenience.
  • 3.

    Spatio-Temporal Analysis of Attractive Regions of Seoul Tourists using Geotagged Photos

    Nayeon Kim | Youngok Kang | 2019, 19(1) | pp.35~46 | number of Cited : 1
    Abstract
    The purpose of this study is to analyze the tourist characteristics of tourist attractions and culturalareas of tourists who visited Seoul through spatial analysis of photograph posts posted on Flickr. We collectedgeotagged data from Flickr between January 1, 2013 and December 31, 2017 in downtown Seoul, and classifiedall users as tourists and residents. After that, RoA, which is the area visited mainly by tourists, was derivedand the tendency of visiting RoA was analyzed. In addition, hotspot areas visited by many tourists in Seoulcity were also analyzed. A total of 167,410 data were used in the analysis, and the number of users was 3,921. In order to derive RoA, we derive 11 RoA in Seoul and 12 RoA in Seoul by DBSCAN algorithm. In the wholeof Seoul, Jongno, Hongdae, Namsan, Shinchon, Gangnam Station, COEX, Itaewon, Jamsil, Street, War Memorial,RoA was derived from Insadong, Namdaemun, Plaza Mayor, Changgyeonggung, and Hangangganggil. In orderto confirm the difference of tourism trends of tourists by culture, we confirmed the tourism trends of Asian,American, and European tourists.
  • 4.

    Analyses on the Characteristics and the Changes in Spatial Distribution Patterns of the School Bullying in the Daejeon Metropolitan City

    Seyoon Song | Kirl Kim | 2019, 19(1) | pp.47~57 | number of Cited : 0
    Abstract
    School is a place where students who will take care of the future societies spend most of time justlike their houses. The school should be a safe space where children and adolescents live happily in both physicaland mental ways. However, the school bullying problem is becoming the biggest obstacle in the course of keepingschool safe. Therefore, protecting students from the school bullying should be a priority for schools and societies. This study analyzed the characteristics and the changes in the spatial distribution patterns of the school bullyingin Daejeon Metropolitan City. The results are as follows; First, the school bullying was the highest in middleschool. By gender, more school bullying occurred in boy students than in girl students. Considering the typeof school bullying, violence accounted for more than half of the total. Cyber bullying was a type of schoolbullying that showed high increase rate in recent years. Second, the distribution of school bullying in DaejeonCity was clustered and segregated in the specific schools and administrative dong. This study suggests that itis important to develop and apply the school CPTED reflecting spatial characteristics of city.
  • 5.

    Extraction of Estimated Areas Vulnerable to Crime Using Seamless Digital Topographic Map and Floating Population

    Kim, Eui Myoung | SongPyo Hong | Jinyi Park | 2019, 19(1) | pp.59~68 | number of Cited : 4
    Abstract
    It is important to prevent crime in advance rather than take action after the crime has occurred, because crime causes human or material harm. In addition, in order to prevent crime, areas vulnerable to crime should be extracted. Therefore, in this study, the research was carried out to extract crime vulnerable areas considering the temporal and spatial characteristics without using crime location information directly, considering the domestic circumstance where crime location information is not provided. Spatial information was extracted from a seamless digital topographic map using road width, road intersection, road angle, pavement material, and types of buildings adjacent to the road. Temporal information was also extracted by analyzing kernel density from floating population data provided in point form. For the spatio-temporal analysis, two characteristics information were overlaid to extract vulnerable areas. In order to verify the vulnerable areas, the road view images provided by Daum portal were checked. As a result, it was found that the areas were mostly deteriorated detached houses and the roads were not well maintained.
  • 6.

    Network Analysis of Swine Farms and Slaughters: Based on Automobile GPS Data

    Minje Jeong | Ik-Hoon Jang | Youngchan Choe | 2019, 19(1) | pp.69~79 | number of Cited : 2
    Abstract
    This study is to conduct a network analysis between hog farms and slaughters using GPS based vehiclemovement data. In order to cope with foot and mouth disease, early response and preemptive prevention ofepidemics can be crucial role. Analysis of vehicle movement that is a major agent for disease spread andrelationship between slaughters and hog farms needs to be conducted for the above strategies. This studyconducted network analysis between slaughters and swine farms with vehicle movement data from KAHIS (Korea Animal Health Integrated System). For this analysis, we constructed binary matrix data between slaughters andswine farms. We applied ‘Rasch Model’ to estimate risk scores for each slaughters and swine farms. After that,we also used ‘Latent Class Analysis (LCA)’ to cluster swine farms. Results from ‘Rasch Model’ said that farmsin Jeollabuk-do Province and Gyeonggi-do Province have high level risk scores which indicates high risks fordisease spread. Results from LCA said that the proper number of clusters is seven. Considering the risk scoresfrom ‘Rasch Model’, which indicates level of relationship with diverse slaughters, government agency needs toconcentrate upon clustering group 4, followed by cluster group 1, 3, 5, 6. In the case of cluster group 2, 7, whichhave low scores, they have relatively lower risks for disease spread. The results considered, it can be a betterstrategy that government agency restricts only a few paths in Jeollabuk-do Province and Chungcheongnam-doProvince instead of all paths in the outbreak of disease.
  • 7.

  • 8.

    옛지도 속의 하늘과 땅

    Ki-Suk Lee | 2019, 19(1) | pp.93~94 | number of Cited : 0