• Journal of Intelligence and Information Systems
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• v.26 no.2
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• pp.131-145
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• 2020

In line with the trend of industrial innovation, IoT technology utilized in a variety of fields is emerging as a key element in creation of new business models and the provision of user-friendly services through the combination of big data. The accumulated data from devices with the Internet-of-Things (IoT) is being used in many ways to build a convenience-based smart system as it can provide customized intelligent systems through user environment and pattern analysis. Recently, it has been applied to innovation in the public domain and has been using it for smart city and smart transportation, such as solving traffic and crime problems using CCTV. In particular, it is necessary to comprehensively consider the easiness of securing real-time service data and the stability of security when planning underground services or establishing movement amount control information system to enhance citizens' or commuters' convenience in circumstances with the congestion of public transportation such as subways, urban railways, etc. However, previous studies that utilize image data have limitations in reducing the performance of object detection under private issue and abnormal conditions. The IoT device-based sensor data used in this study is free from private issue because it does not require identification for individuals, and can be effectively utilized to build intelligent public services for unspecified people. Especially, sensor data stored by the IoT device need not be identified to an individual, and can be effectively utilized for constructing intelligent public services for many and unspecified people as data free form private issue. We utilize the IoT-based infrared sensor devices for an intelligent pedestrian tracking system in metro service which many people use on a daily basis and temperature data measured by sensors are therein transmitted in real time. The experimental environment for collecting data detected in real time from sensors was established for the equally-spaced midpoints of 4×4 upper parts in the ceiling of subway entrances where the actual movement amount of passengers is high, and it measured the temperature change for objects entering and leaving the detection spots. The measured data have gone through a preprocessing in which the reference values for 16 different areas are set and the difference values between the temperatures in 16 distinct areas and their reference values per unit of time are calculated. This corresponds to the methodology that maximizes movement within the detection area. In addition, the size of the data was increased by 10 times in order to more sensitively reflect the difference in temperature by area. For example, if the temperature data collected from the sensor at a given time were 28.5℃, the data analysis was conducted by changing the value to 285. As above, the data collected from sensors have the characteristics of time series data and image data with 4×4 resolution. Reflecting the characteristics of the measured, preprocessed data, we finally propose a hybrid algorithm that combines CNN in superior performance for image classification and LSTM, especially suitable for analyzing time series data, as referred to CNN-LSTM (Convolutional Neural Network-Long Short Term Memory). In the study, the CNN-LSTM algorithm is used to predict the number of passing persons in one of 4×4 detection areas. We verified the validation of the proposed model by taking performance comparison with other artificial intelligence algorithms such as Multi-Layer Perceptron (MLP), Long Short Term Memory (LSTM) and RNN-LSTM (Recurrent Neural Network-Long Short Term Memory). As a result of the experiment, proposed CNN-LSTM hybrid model compared to MLP, LSTM and RNN-LSTM has the best predictive performance. By utilizing the proposed devices and models, it is expected various metro services will be provided with no illegal issue about the personal information such as real-time monitoring of public transport facilities and emergency situation response services on the basis of congestion. However, the data have been collected by selecting one side of the entrances as the subject of analysis, and the data collected for a short period of time have been applied to the prediction. There exists the limitation that the verification of application in other environments needs to be carried out. In the future, it is expected that more reliability will be provided for the proposed model if experimental data is sufficiently collected in various environments or if learning data is further configured by measuring data in other sensors.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.38 no.3
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• pp.281-293
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• 2020

Recently, large and small fires have been happening more often in Korea. Fire is one of the most frequent disasters along with traffic accidents in korean cities, and this frequency is closely related to the land use and the type of facilities. Therefore, in this study, the significance of fires was analyzed by considering land use, facility types, human and social factors and using 10 years of fire data in Jinju city. Based on this, OLS (Ordinary Least Square) regression analysis, SLM (Spatial Lag Model) and SEM (Spatial Error Model) using space weights, were compared and analyzed considering the location of the fire and each factor, then a statistical model with high suitability was presented. As a result, LISA analysis of spatial distribution patterns of fires in Jinju city was conducted, and it was proved that the frequency of fires was high in the order as follow, central commercial area, industrial area and residential area. Multiple regression analysis was performed by integrating demographic, social, and physical variables. Therefore, the three models were compared and analyzed by applying spatial weighting to the derived factors. As a result of the significance test, the spatial error model was analyzed to be the most significant. The facilities that have the highest correlation with fire occurrence were second type neighborhood facilities, followed by detached house, first type neighborhood facilities, number of households, and sales facilities. The results of this study are expected to be used as significant data to identify factors and manage fire safety in urban areas. Also, through the analysis of the standard deviation ellipsoid, the distribution characteristics of each facility in the residential area, industrial area, and central commercial area among the use areas were analyzed. In, the second type neighborhood facility with the highest fire risk was concentrated in the center. The results of these studies are expected to be used as useful data for identifying factors and managing fire safety in urban areas.

• Journal of the Korean Geographical Society
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• v.28 no.4
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• pp.321-355
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• 1993

This paper focuses on the geographical pattern of financial activities in the Korean urban system during 1975-1990, based on the assumption that financial activities can reveal control points in Korea's urban economy. In terms of spatial evolution of financial insitutions, different locational characteristics are revealed among different types of financial institutions, implying the role of urban hierarchy. Financial resources are highly concentrated in the capital region, Seoul and Kyonggi Province. Both centralization trends into the large metropolitan cities and relative declines of medium and small cities within the Korean urban system, have been experienced over the study period. Financial activities sustain relatively stable hierarchical structure in the urban hierarchy. Regarding the financial flows, dominant flow zones centered on major metropolitan cities are identified, clearly showing a prominant role of Seoul in financial flows in the entire urban system.

• The Journal of Korean society of community based occupational therapy
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• v.11 no.1
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• pp.11-22
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• 2021

Objective : The purpose of this study was to investigate the changes in occupational balance and quality of life caused by COVID-19 in occupational therapy students. Methods : From May 27 to June 26, 2020, questionnaires were distributed to a total of 35 universities among 62 occupational therapy departments nationwide. General characteristics, COVID-19 related characteristics, OBQ and WHOQOL-BREF were used to evaluate and analyze occupational balance and quality of life. The SPSS/PC 24.0 program was used to analyze frequency analysis, crossover analysis, chi-square test, independent t-test, analysis of variance, and Pearson correlation analysis. Results : There were significant differences in school system(years), class, life pattern, quality of life, personal and public schedule depending on whether they are interested in occupational balance. There were significant differences in occupational balance(OBQ) and quality of life(WHOQOL-BREF), 'Hobby', 'new hobbies after COVID-19', 'life patterns', 'use of public transportation', 'maintenance of occupational balance', and 'quality of life'. There was a significant positive correlation occupational balance and quality of life. Conclusion : This study showed that the more people who have changed their lives due to COVID-19 are interested in work balance, and the better they maintain their work balance and emotional well-being, the higher the work balance and quality of life, and the positive correlation between work balance and quality of life was confirmed. This will be the basis for studies related to intervention strategies that can improve occupational balance and quality of life in a time when social isolation is easy due to the COVID-19 epidemic.

• Journal of Nutrition and Health
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• v.55 no.1
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• pp.21-35
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• 2022

The recommended meal composition allows the general people to organize meals using the number of intakes of foods from each of six food groups (grains, meat·fish·eggs·beans, vegetables, fruits, milk·dairy products and oils·sugars) to meet Dietary Reference Intakes for Koreans (KDRIs) without calculating complex nutritional values. Through an integrated analysis of data from the 6th to 7th Korean National Health and Nutrition Examination Surveys (2013-2018), representative foods for each food group were selected, and the amounts of representative foods per person were derived based on energy. Based on the EER by age and gender from the KDRIs, a total of 12 kinds of diets were suggested by differentiating meal compositions by age (aged 1-2, 3-5, 6-11, 12-18, 19-64, 65-74 and ≥ 75 years) and gender. The 2020 Food Balance Wheel included the 6th food group of oils and sugars to raise public awareness and avoid confusion in the practical utilization of the model by industries or individuals in reducing the consistent increasing intakes of oils and sugars. To promote the everyday use of the Food Balance Wheel and recommended meal compositions among the general public, the poster of the Food Balance Wheel was created in five languages (Korean, English, Japanese, Vietnamese and Chinese) along with card news. A survey was conducted to provide a basis for categorizing nutritional problems by life cycles and developing customized web-based messages to the public. Based on survey results two types of card news were produced for the general public and youth. Additionally, the educational program was developed through a series of processes, such as prioritization of educational topics, setting educational goals for each stage, creation of a detailed educational system chart and teaching-learning plans for the development of educational materials and media.

• Proceedings of the Korean Society for Food Science of Animal Resources Conference
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• 1995.11a
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• pp.1-48
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• 1995

식생활은 인간 생활의 주체이고 먹는다는 것은 그 수단이다. 그중 중요한 하나의 명제는 인간이 놓여진 여러 환경에서 어떻게 건강을 유지하고 그 개체가 소유하고 있는 능력을 최대치까지 생리적으로 성장 발전시킴과 동시에 최대한 수명을 연장시키기 위한 식물 섭취방법을 마이크로 레벨까지 해명하는데 있다. 인간은 일생동안 엄청난 양의 음식물을 먹는다(70세 수명일 경우 200만 파운드 즉 체중의 1,400배). 그러나 먹기는 먹되 자신의 건강과 장수를 위하여 어떤 음식을 어떻게 선택하여 어떻게 먹어야 하는 문제가 매우 중요하다. 최근 우리나라도 국민 소득이 늘면서 식생활은 서구화 경향으로 기우는 듯하다. 공해를 비롯한 수입식품 등 여러 가지 문제점이 제기됨에 따라 자연식과 건강식을 주장하는 소리가 높이 일고 있다. 그중에는 축산 식품이 콜레스테롤 함량이 다른 식품에 비하여 높게 함유하고 있다는 것으로 심혈관질환의 주범인양 무차별 강조하는 나머지 육식공포 내지는 계란 등의 혐오감 마저 불러 일으키는 경향까지 있는 듯하다. 따라서 본논고에서는 축산식품중의 콜레스테롤 함량수준이 과연 성인병의 주범인지 아니면 다른 지방산과 관련해서 올바르게 평가하고 그 문제점과 대책을 개관해 보고 요약하면 다음과 같다. 1. 사람은 유사이래 본능적으로 주변의 식물이나 동물의 고기를 먹고 성장하여 자손을 증식시키고 어느 사이에 늙으면 죽음을 맞이 하는 싸이클을 반복하면서 기나긴 세월동안 진화를 하여 오늘날의 인간으로서의 자태를 이루었다. 유인원과 같은 인류의 선조들은 수렵을 통해 육식을 많이 하였을 것이므로 인간은 원래 육식동물이 아닐까? 구석기시대의 유물을 보면 많은 뼈가 출토되고 “얄타미라”나 “라스코” 동굴벽화가 선명하게 묘사되고 있다. 2. 우리나라 선조 승구족의 일파가 백두산을 비롯한 만주 송화강 유역에 유입되면서 수렵과 목축을 주요 식품획득의 수단으로 식품문화권을 형성하면서 남하하여 한반도 민족의 조상인 맥족(貊族)으로 맥적(貊炙)이라고 하는 요리(오늘날의 불고기)를 먹었다는 기록이 있다. 3. 인간의 수명을 1900년대로 거슬러 올라가서 뉴질랜드가 세계최장수국(호주는 2위)로서 평균수명은 남자 58세, 여자 69세인 반면 일본과 한국은 당시 남자 36세, 여자 37세이던 것이 일본은 1989년에 이르러 세계 최장수국으로 등장했으나 1990년 당시 뉴질랜드${\cdot}$호주 등은 목축 및 밀(小麥) 생산국가였기 때문이라는 것과 일본은 오늘날 합리적인 식생활 국가라는 것을 간과해서는 안된다. 4. 우리나라 10대 사망원인중 (1994년도) 뇌혈관질환이 1위, 교통사고 2위, 암이 3위 순위로서 연령별로는 10~30대의 불의의 사고(교통사고), 40~60대는 암, 70대 이상은 뇌혈관질환이 가장 많다. 구미${\cdot}$일 7개국 정상국가들은 심질환 사망이 가장 높다. 5. 식생활의 변화에 있어서 우리나라는 주식으로 섭취해 왔던 곡류는 70년 대비 94년에는 0.7배 감소된 반면 육류 5배, 계란 2.4배, 우유는 무려 29.3배 증가되었다. 식생활 패턴이 서구화 경향으로 바뀌는 것 같다. 6. 71년도 우리나라의 지질섭취량은 국민 1인당 1일 평균 13.1g에 섭취에너지의 5.7%수준이었으나 92년도에는 34.5g으로서 총에너지 섭취량의 16.6%에 달하고 총섭취 지방질중 동물성 섭취 비율은 47%를 차지 한다. 국민 평균 혈청콜레스테롤 농도는 80년에 비해 88년에는 11%가 증가되었고 80년에 210mg/dl 이상 되는 콜레스테롤 혈증인 사람의 비율이 5%에서 88년에는 23%로 크게 증가했다. 7. 세계 정상국가들의 단백질 즉 축산식품의 섭취는 우리나라보다 적게는 2배, 많게는 6~7배 더 섭취하고 90년도 우리나라의 지질섭취량은 일본의 1/3수준에 불과하다. 8. 콜레스테롤은 인체를 비롯한 모든 동물체에 필수적으로 분포하고 있는 것으로 체내 존재하고 있는 총량은 90~150g, 이중 혈청콜레스테롤은 4%(6g)를 차지하고 있음에도 불구하고 이 아주 적은 콜레스테롤에 일희일비(一喜一悲) 논쟁은 60~70년 끄러오고 있다. 9. 콜레스테롤의 생체내 기능으로서는 (1) 세포벽의 지지물질 (2) 신경세포 보호막물질 (3) 담즙산의 합성 (4) 비타민 D의 합성 (5) 임신시에 반듯이 필요한 분자 (6) 기타 여러 가지 기능을 수행하는 것으로 필수적인 물질이다. 10. 우리가 식이를 통해서 섭취 콜레스테롤을 550mg정도를 섭취한다고 하더라도 이 정도의 양은 배설 소모되는 양과 거의 맞먹는 양이다. 피부와 땀샘에서 소실되는 양만도 100~300mg에 달하기 때문에 미국농무성에서 섭취량을 300mg로 제한하는 것은 무의미하다. 11. 콜레스테롤 운반체로서의 지단백질은 그 밀도가 낮은 것으로부터 킬로미크론(chylomicron), 초저밀도 지단백질(VLDL), 저밀도 지단백질(LDL) 및 고밀도 지단백질(HDL)으로 나누는데 LDL은 혈청콜레스테롤 중 약 70%, HDL은 약20%를 함유한다. 12. 혈중 콜레스테롤 수준에 영향을 미치는 요인을 열거하여 보면 다음과 같다. 1) 음식을 통해서 섭취되는 콜레스테롤 중 단지 10~40%정도가 흡수되고, 체내에서 합성되는 콜레스테롤이 증가할수록 식이콜레스테롤은 실제 혈청콜레스테롤 수준에 거의 영향을 미치지 않으므로 식이중함량에 대하여 공포를 느끼고 기피할 필요가 없다. 2) 고도불포화지방산, 단가불포화지방산, 포화지방산의 비 즉 P/M/S의 비가 균형되도록 권장한다. 3) 동맥경화를 비롯한 성인병의 원인이 되는 혈전증에는 EPA의 양을 높여줌으로서 성인병을 예방할 수 있다. 4) 오메가6지방산 아라키도닉산과 오메가3지방산인 EPA로 유도되는 에이코사에노이드 또는 프로스타노이드는 오메가6와 3지방산을 전구체로 하여 생합성되는 중요한 생리활성 물질이다. 5) 사람은 일반적으로 20세에서 60세까지 나이를 먹어감에 따라 혈중 콜레스테롤 수준이 증가하고 60세 이후부터는 일정한 수준을 유지하며 심장보호성 HDL-콜레스테롤은 감소하는 반면에 죽상경화성 LDL콜레스테롤은 증가한다. 6) 높은 HDL콜레스테롤 수준이 심장병 발생 위험요인을 감소시키는 기능을 갖고 있기 때문에 좋은 HDL이라 부르고, LDL은 나쁜 콜레스테롤이라 부르기도 하는데, 이것은 유전적 요인보다도 환경적 요인이 보다 큰 영향을 미친다. 7) 이것은 생활 형태와 영양섭취상태를 포함해서 개인적 생활패턴에 영향을 받는다. 8) 많은 실험에서 혈중 콜레스테롤 상승은 노년의 가령(加齡)에 적응하기 위한 자연적 또는 생리적인 세포의 생화학적이고 대사적인 기능을 위해 필수적일 수 있다는 것을 간과해서는 안될 것이다. 이 점으로 미루어 노년의 여성들을 위한 콜레스테롤 농도를 200mg/dl이 가장 알맞은 양이 아닌 듯하다. 9) 스트레스는 두가지 모양으로 유발되는데 해로은 스트레스(negative), 이로운 스트레스(positive)로서 긴장완화는 혈중 콜레스테롤 농도를 10% 떨어진다. 10) 자주 운동을 하는 사람들은 혈중 HDL콜레스테롤치가 운동을 하지 않는 사람보다 높다. 육체적인 운동의 정도와 혈중 HDL콜레스테롤 농도와는 정비례한다. 11) 흡연은 지방을 흡착시키므로 혈전증의 원이이 되며 혈관속의 HDL농도를 감소시킨다. 12) 에너지의 과잉섭취에 의한 체중 증가느 일반적으로 지단백질대사에 영향을 미치고, 간에서는 콜레스테롤 과잉 생산과 더불어 VLDL콜레스테롤의 LDL콜레스테롤 혈증을 나타냄으로 운동과 더불어 비만이 되지 않도록 하여야 한다. 13. 콜레스테롤 함량에 대한 조절기술 1) 식품의 우열을 평가할 때 단순히 동물성 또는 식물성 식품으로 분류해서 총괄적으로 논한다는 것은 지양되어야 한다. 이것은 그 식품에 함유하고 있는 지방산의 종류에 따라서 다르기 때문이다. 2) 인체의 원할한 기능 유지를 위해서는 P /M /S비율 뿐만 아니라 섭취 지방질의 오메가6 /오메가3계 지방산의 비율이 모두 적절한 범위에 있어야 하며 한두가지 지방산만이 과량일 때는 또 다른 불균형을 일으킬 수 있다는 점을 알아야 한다. 3) 닭고기는 오메가6지방산 함량을 높이기 위하여 사료중에 등푸른 생선이나 어분이나 어유를 첨가하여 닭고기는 첨가수준에 따라 증가됨을 알 수 있다. 4) 오늘날 계란내의 지방산 조성을 변화시켜 난황내의 오메가 3계열 지방산 함량을 증가시킨 계란의 개발이 활발해졌다. 14. 계란 콜레스테롤에 대한 소비자들의 부정적 인식을 불식시키고자 계란의 클레스테롤 함량을 낮추는 과제가 등장하면서 그 기술개발이 여러모로 시도되고 있으나 아직 실용 단계에 이르지 못했다. 15. 계란의 콜레스테롤 문제에 대한 대책으로서 난황의 크기를 감소시키는 방법에 대한 연구도 필요하다. 16. 계란 중 콜레스테롤 함량 분석치는 표현 방식에 따라서 소비자들을 혼란시킬 가능성이 있다. 또한 과거에는 비색법으로 분석했으나 오늘날은 효소법으로 분석하면 분석치에 상당한 차이가 있다. 17. 소비자의 요구를 만족시키고 버터 소비를 촉진시키기 위해 콜레스테롤을 감소시키는 물리적${\cdot}$생물학적 방식이 제안되어 있으나 현장적용이 가능한 것은 아직 없다. 18. 우리나라에서 이미 시판되고 있는 DHA우유가 선보였고 무콜레스테롤 버터의 경우 트란스(trans)형 지방산에 관해서는 논란의 여지가 많을 것이다. 끝으로 국가 목표의 하나는 복지사회 건설에 있고 복지국가 실현에는 국민 기본 욕망의 하나인 식생활 합리화가 선행되어야 한다. 소득이 늘고 국가가 발전해감에 따라 영양식${\cdot}$건강식 및 기호식을 추구하게 됨을 매우 당연한 추세라 하겠다. 우리의 식생활이 날로 향상되어 지난날의 당질 위주에서 점차 축산물쪽으로 질적 개선이 이루어진다는 것은 고무적임에 틀림없다. 이 축산물을 통한 풍요로운 식의 문화를 창출하면서 건강과 장수 그리고 후손에 이르기까지 번영하고 국가 경쟁력 강화에 심혈을 기우려야 할 때이다.

• Journal of the Korean Association of Geographic Information Studies
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• v.23 no.3
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• pp.100-119
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• 2020

During recent years, the heat environment and particulate matter (PM₁₀) have become serious environmental problems, as increases in heat waves due to rising global temperature interact with weakening atmospheric wind speeds. There exist urban heat islands and urban pollution islands with higher temperatures and air pollution concentrations than other areas. However, few studies have examined these issues together because of a lack of micro-scale data, which can be constructed from spatial data. Today, with the help of satellite images and big data collected by private telecommunication companies, detailed spatial distribution analyses are possible. Therefore, this study aimed to examine the spatial distribution patterns of urban heat islands and urban pollution islands within Busan Metropolitan City and to compare the distributions of the two phenomena. In this study, the land surface temperature of Landsat 8 satellite images, air temperature and particulate matter concentration data derived from a private automated meteorological observation system were gridded in 30m × 30m units, and spatial analysis was performed. Analysis showed that simultaneous zones of urban heat islands and urban pollution islands included some vulnerable residential areas and industrial areas. The political migration areas such as Seo-dong and Bansong-dong, representative vulnerable residential areas in Busan, were included in the co-occurring areas. The areas have a high density of buildings and poor ventilation, most of whose residents are vulnerable to heat waves and air pollution; thus, these areas must be considered first when establishing related policies. In the industrial areas included in the co-occurring areas, concrete or asphalt concrete-based impervious surfaces accounted for an absolute majority, and not only was the proportion of vegetation insufficient, there was also considerable vehicular traffic. A hot-spot analysis examining the reliability of the analysis confirmed that more than 99.96% of the regions corresponded to hot-spot areas at a 99% confidence level.

• KIPS Transactions on Software and Data Engineering
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• v.7 no.9
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• pp.351-360
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• 2018

The LWR (Locally Weighted Regression) model, which is traditionally a lazy learning model, is designed to obtain the solution of the prediction according to the input variable, the query point, and it is a kind of the regression equation in the short interval obtained as a result of the learning that gives a higher weight value closer to the query point. We study on an incremental ensemble learning approach for LWR, a form of lazy learning and memory-based learning. The proposed incremental ensemble learning method of LWR is to sequentially generate and integrate LWR models over time using a genetic algorithm to obtain a solution of a specific query point. The weaknesses of existing LWR models are that multiple LWR models can be generated based on the indicator function and data sample selection, and the quality of the predictions can also vary depending on this model. However, no research has been conducted to solve the problem of selection or combination of multiple LWR models. In this study, after generating the initial LWR model according to the indicator function and the sample data set, we iterate evolution learning process to obtain the proper indicator function and assess the LWR models applied to the other sample data sets to overcome the data set bias. We adopt Eager learning method to generate and store LWR model gradually when data is generated for all sections. In order to obtain a prediction solution at a specific point in time, an LWR model is generated based on newly generated data within a predetermined interval and then combined with existing LWR models in a section using a genetic algorithm. The proposed method shows better results than the method of selecting multiple LWR models using the simple average method. The results of this study are compared with the predicted results using multiple regression analysis by applying the real data such as the amount of traffic per hour in a specific area and hourly sales of a resting place of the highway, etc.

• Korean Journal of Remote Sensing
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• v.36 no.5_3
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• pp.1053-1066
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• 2020

Sulfur dioxide (SO₂) is primarily released through industrial, residential, and transportation activities, and creates secondary air pollutants through chemical reactions in the atmosphere. Long-term exposure to SO₂ can result in a negative effect on the human body causing respiratory or cardiovascular disease, which makes the effective and continuous monitoring of SO₂ crucial. In South Korea, SO₂ monitoring at ground stations has been performed, but this does not provide spatially continuous information of SO₂ concentrations. Thus, this research estimated spatially continuous ground-level SO₂ concentrations at 1 km resolution over South Korea through the synergistic use of satellite data and numerical models. A stacking ensemble approach, fusing multiple machine learning algorithms at two levels (i.e., base and meta), was adopted for ground-level SO₂ estimation using data from January 2015 to April 2019. Random forest and extreme gradient boosting were used as based models and multiple linear regression was adopted for the meta-model. The cross-validation results showed that the meta-model produced the improved performance by 25% compared to the base models, resulting in the correlation coefficient of 0.48 and root-mean-square-error of 0.0032 ppm. In addition, the temporal transferability of the approach was evaluated for one-year data which were not used in the model development. The spatial distribution of ground-level SO₂ concentrations based on the proposed model agreed with the general seasonality of SO₂ and the temporal patterns of emission sources.

• Journal of the Korean Association of Geographic Information Studies
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• v.22 no.1
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• pp.1-18
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• 2019

This research measured and visualized the spatial dependency and the spatial heterogeneity of the small business in Cheonan-si, Asan-si with $100m{\times}100m$ grids based on global and local spatial autocorrelation. First, we confirmed positive spatial autocorrelation of small business in the research area using Moran's I Index, which is ESDA(Exploratory Spatial Data Analysis). And then, through Getis-Ord $GI{\ast}$, one kind of LISA(Local Indicators of Spatial Association), local patterns of spatial autocorrelation were visualized. These verified that Spatial Regression Model is valid for the location factor analysis on small business commercial buildings. Next, GWR(Geographically Weighted Regression) was used to analyze the spatial relations between the distribution of small business, hourly mobile traffic-based floating population, land use attributes index, residence, commercial building, road networks, and the node of traffic networks. Final six variables were applied and the accessibility to bus stops, afternoon time floating population, and evening time floating population were excluded due to multicollinearity. By this, we demonstrated that GWR is statistically improved compared to OLS. We visualized the spatial influence of the individual variables using the regression coefficients and local coefficients of determinant of the six variables. This research applied the measured population information in a practical way. Reflecting the dynamic information of the urban people using the commercial area. It is different from other studies that performed commercial analysis. Finally, this research has a differentiated advantage over the existing commercial area analysis in that it employed hourly changing commercial service population data and it applied spatial statistical models to micro spatial units. This research proposed new framework for the commercial analysis area analysis.