Earticle

최근 지진 발생 빈도가 증가하고 있는 반면 국내 지진 대응 체계는 취약한 현실에서, 본 연구의 목적은 통계분석 기 법과 머신러닝 기법을 활용한 공간분석을 통해 건물의 지진취약도를 비교분석 하는 것이다. 통계분석 기법을 활용한 결과, 최 적화척도법을 활용해 개발된 모델의 예측정확도는 약 87%로 도출되었다. 머신러닝 기법을 활용한 결과, 분석된 4가지 방법 중, Random Forest의 정확도가 Train Set의 경우 94%, Test Set의 경우 76.7%로 가장 높아, 최종적으로 Random Forest 가 선정되었다. 따라서, 예측정확도는 통계분석 기법이 약 87%, 머신러닝 기법이 76.7%로, 통계분석 기법의 예측정확도가 더 높은 것으로 분석되었다. 최종 결과로, 건물의 지진취약도는 분석된 건물데이터 총 22,296개 중, 1,627(0.1%)개의 건물데이 터는 통계분석 기법 사용 시 더 위험하다고 도출되었고, 10,146(49%)개의 건물데이터는 동일하게 도출되었으며, 나머지 10,523(50%)개의 건물데이터는 머신러닝 기법 사용 시 더 위험하게 도출되었다. 기존 통계분석 기법에 첨단 머신러닝 기법 활용결과가 추가로 비교검토 됨으로써 공간분석 의사결정에 있어서, 좀더 신뢰도가 높은 지진대응책 마련에 도움이 되길 기 대한다.

While the frequency of seismic occurrence has been increasing recently, the domestic seismic response system is weak, the objective of this research is to compare and analyze the seismic vulnerability of buildings using statistical analysis and machine learning techniques. As the result of using statistical technique, the prediction accuracy of the developed model through the optimal scaling method showed about 87%. As the result of using machine learning technique, because the accuracy of Random Forest method is 94% in case of Train Set, 76.7% in case of Test Set, which is the highest accuracy among the 4 analyzed methods, Random Forest method was finally chosen. Therefore, Random Forest method was derived as the final machine learning technique. Accordingly, the statistical analysis technique showed higher accuracy of about 87%, whereas the machine learning technique showed the accuracy of about 76.7%. As the final result, among the 22,296 analyzed building data, the seismic vulnerabilities of 1,627(0.1%) buildings are expected as more dangerous when the statistical analysis technique is used, 10,146(49%) buildings showed the same rate, and the remaining 10,523(50%) buildings are expected as more dangerous when the machine learning technique is used. As the comparison of the results of using advanced machine learning techniques in addition to the existing statistical analysis techniques, in spatial analysis decisions, it is hoped that this research results help to prepare more reliable seismic countermeasures.

현 연구는 개별 건물에 대한 지진취약도 예측 및 특정 관심 지역 내 전체 건물의 안전 상태를 예측하는 방법의 제시에 그 목적이 있다. 현 연구의 범위는 지진피해 저감 연구 중, 예방 활동에 속하는 시뮬레이터 모델개발, 모델 유효 성 검증을 포함한다. 연구의 대상은 지역 건물 시스템이다. 선행연구 조사 결과, 국내의 지진 예측 모델링 및 그 결과를 GIS를 활용해 적용한 사례의 성과는 아직은 미비한 것으로 판단되었으며, 이를 다소간이나마 개선하기 위한 방편의 일환으로 현 연구가 진행되었다. 국내·외 총 348개의 데이터를 사용해 통계 분석이 실시되었다. 일련의 통계 분석 결과, 최적화 척도법에 의한 모델이 개발되었고, 모델의 예측 정확도는 87%로 산정되었다. 통계 분석을 통해 개발된 모델 식을 지역 건물 시스템의 지진취약도 예측에 적용하기 위해, 공간 분석 기법이 활용되었다. 서울시 구도심과 신도심의 특성을 대표하는 강남구와 종로구 그리고 종로구와 지반 조건이 유사한 은평구를 대상 지역으로 선정하였고, 분석 결과 건물을 대상으로 강남구가 종로구와 은평구에 비해 위험한 것으로 예측되었다.

The purpose of this study is to suggest a method of predicting seismic vulnerability and safety conditions of each building in a targeted area. The scope of this study includes ‘developing a simulation model for precaution activities,’ ‘testing the validity of the developed model’, From the facility point of view, target of this study is a local building system. According to the literature review, the number of earthquake prediction modeling and cases with GIS applied is extremely few and the results are not proficient. This study is conducted as a way to improve the previous researches. Statistic analyses are conducted using 348 domestic and international data. Finally, as a result of the series of statistical analyses, an adequate model is developed using optimization scale method. The ratio of correct expectation is estimated as 87%. In order to apply the developed model to predict the vulnerability of the several chosen local building systems, spatial analysis technique is applied. Gangnam-gu and Jongro-gu are selected as the target areas to represent the characteristics of the old and the new downtown in Seoul. As a result of the analysis, it is discovered that buildings in Gangnam-gu are relatively more dangerous comparing to those of Jongro-gu and Eunpyeong-gu.

모빌리티 서비스는 구축 대상 지역의 특성과 여건에 따라 변화할 필요가 있다. 이를 위해서 는 해당 지역의 통행행태를 기종점 자료에 반영하여 모빌리티 패턴 및 특성 분석이 요구된다. 그러나 종래의 경우 행정 구역 기반의 존 체계를 기반으로 집계된 기종점 자료를 이용함에 따 라 공간적 동질성을 담보하기 어렵기 때문에 신규 모빌리티와 같은 특수 목적성을 보이는 수 단에 대한 본연의 통행 특성 분석에 한계가 있다. 이에 본 연구는 기존 존 체계에서 벗어나 데이터 기반의 클러스터링 기법 적용을 통해 설정된 집계 방식을 도출하여 기종점 통행패턴에 대한 공간적 분석을 수행한다. 제안 방법은 대중교통버스 및 택시와 같은 종래의 교통수단 뿐 만 아니라 도심형 수요응답형 버스와 같은 신규 모빌리티 서비스에 대한 기종점 데이터 본연 의 특징 벡터들을 기반으로 클러스터링을 하여 유사 공간적 특성을 반영한 지역 모빌리티의 이용 특성 분석을 가능하게 한다.

Mobility services need to change according to the regional characteristics of the target service area. Accordingly, analysis of mobility patterns and characteristics based on Origin-Destination (OD) data that reflect travel behaviors in the target service area is required. However, since conventional methods construct the OD data obtained from the administrative district-based zone system, it is hard to ensure spatial homogeneity. Hence, there are limitations in analyzing the inherent travel patterns of each mobility service, particularly for new mobility service like Demand Responsive Transit (DRT). Unlike the conventional approach, this study applies a data-driven clustering technique to conduct spatial analyses on OD travel patterns of regional mobility services based on reconstructed OD data derived from re-aggregation for original OD distributions. Based on the reconstructed OD data that contains information on the inherent feature vectors of the original OD data, the proposed method enables analysis of the spatial characteristics of regional mobility services, including public transit bus, taxi and DRT.

본 연구는 건강 형평성 관점에서 공공체육시설의 적정 수요를 추정하기 위하여 공간 분석, 베이지안 회귀모형, 역 몬테카를로 시뮬레이션을 통합적으로 적용하였다. 연구 대상은 광역시 시·군·구 단위로, 건강지표, 신체활동, 공공체육시설 접근성의 공간적 분포와 형평성을 분석하였다. 분석 결과, 건강지표와 신체활동은 대체로 평등한 분포를 보였으나 도시 내부에서는 공간적 이질성이 존재하였다. 반면, 공공체육시설 공급은 높은 불평등을 보였으며 접근성은 상대적으로 평등한 수준을 유지하였다. 베이지안 회귀모형 분석에서는 접근성이 비만율과 부적 관계를 보이며 구조적 건강 결정요인으로 작용하는 경향이 확인되었다. 또한 역 몬테카를로 시뮬레이션 결과, 동일한 비만 감소 목표(20%)를 적용하더라도 지역별 요구 접근성과 공공체육시설 수는 크게 상이하게 나타났으며, 일부 지역에서는 접근성 개선만으로 목표 달성이 가능하였으나, 다른 지역에서는 효과가 제한적이거나 달성 자체가 불가능한 것으로 나타났다. 특히 공공체육시설 수요는 독립적 정책목표가 아니라 접근성 조건에 의해 결정되는 파생 변수로 확인되었다. 따라서 공공체육시설 정책은 단순한 공급 확대에서 벗어나 접근성 기반의 지역 맞춤형 전략으로 전환될 필요가 있다.

This study aimed to estimate the demand for public sports facilities from a health equity perspective by integrating spatial analysis, Bayesian regression, and inverse Monte Carlo simulation. Focusing on metropolitan districts in South Korea, the study examined the spatial distribution of health indicators, physical activity, and facility accessibility. The results indicated that although overall inequality appeared relatively low, significant spatial heterogeneity existed within cities. Public sports facility supply showed substantial inequality, whereas accessibility was relatively balanced, highlighting the importance of spatial allocation. The Bayesian model revealed a negative relationship between accessibility and obesity, suggesting that accessibility functions as a structural determinant. Through inverse Monte Carlo simulation, required accessibility and facility demand were estimated to achieve a 20% reduction in obesity. Results varied by region: some areas could reach the target through improved accessibility, while others showed limited or no effect. These findings suggest that facility demand is conditional on accessibility and not an independent target. Therefore, public sports facility policy should shift toward accessibility-based, region-specific planning to enhance health equity and policy effectiveness.

이 연구에서는 무인항공기에 탑재한 라이다(LiDAR) 센서를 활용해 공산성 일대의 정밀 지형 자료를 획득하고, 이를 지리정보시스템으로 분석해 지형과 수문학적 특성을 규명하였으며, 성벽의 위치와 길이 및 높이 등 정량적 정보를 원격으로 추출하였다. 이 결과, 공산성 성벽은 대부분 봉우리 나 능선과 같은 자연지형을 따라 축성하였으나, 일부 구간에서는 성벽을 관통하는 수계망이 있고 안쪽으로 집수역이 형성되는 등 배수 체계에 취약한 지점이 확인되었다. 이러한 장소는 과거 성벽의 붕괴가 발생했거나 구조적 변형으로 보수가 있었던 곳과 일치하는 것으로 보아 지형적 요인이 성벽 의 안정성에 영향을 미치는 요소로 작용함을 지시한다. 또한 사진과 음영기복도에서는 식별이 어려 운 성벽 위치를 곡률분석을 통해 명확히 추출하였으며, 성벽 하단부와 상단부의 고도 차이를 토대로 높이를 산출하였다. 특히 성벽의 높이가 높거나 낮게 나타난 지점에서 높은 상관도를 보였다. 한편 전체 성벽은 석성구간 1,936m와 토성구간 676m로 총 2,612m 길이를 가지나, 측정 간격에 따라 다소 왜곡이 발생하는 것으로 나타났다. 이는 문화유산의 제원 측정에 대한 기준 척도의 필요성을 시사하 는 것이다. 이 연구는 접근이 어려운 문화유산의 정량적 형상정보 구축에 드론라이다와 지리정보분 석 기법의 뛰어난 효용성을 보여주며, 이는 향후 지형적 위험 요소의 사전 평가와 보존관리계획 수립에 유용하게 활용될 수 있을 것이다.

This study acquired high-resolution topography using UAV-mounted LiDAR around the Gongsanseong Fortress and analyzed it in a GIS to characterize hydrological settings, and remotely extract quantitative attributes of the fortress wall, including its position, length and height. As a result, the Fortress walls were primarily constructed along natural topography, as peaks and ridges. However, certain sections, exhibited drainage vulnerabilities identified, such as water system penetrating the walls or the formation of water catchments within them. These locations tend to coincide with areas where the wall collapsed in the past or required repair due to structural deformation, indicating that topographic factors influence wall stability. Furthermore, curvature analysis allowed us to clearly identify locations of the Fortress that were difficult to discern in photographs and shaded relief maps. Wall heights were calculated based on the elevation difference between the upper and lower sections of the Fortress. A high correlation was observed, particularly at points where the Fortress appeared higher or lower. Meanwhile, the Fortress wall measures 2,612m long, with a stone section of 1,936m and an earthen section measuring 676m. However, some distortion occurred depending on the measurement interval. These suggest the need for a standardized scale in measuring the dimensions of cultural heritage sites. This study demonstrates the outstanding utility of UAV–LiDAR combined with GIS analysis techniques in establishing quantitative configuration information for cultural heritage sites that are difficult to access, and can be usefully utilized in the future for preliminary assessment of topographic risk factors and the development of conservation management schemes.

화물의 흐름은 물류시설 투자 및 물류관련 정책 수립에 필요한 핵심적인 기초자료이다. 국 가승인통계인 화물자동차의 기종점 통행량은 분석의 공간적 해상도가 시군구 단위로 집계되 고 있다. 이는 물류시설 방문 및 이용에 관한 상세한 정보로 활용하는데 한계가 있다. 본 연구 에서는 화물차의 이동 정보를 분석함에 있어 공간적 해상도를 시설단위로 식별 추출할 수 있 는 방법론을 트립체인 정보를 활용하여 개발하고자 하였다. 먼저, DTG를 활용하여 개별 화물 차량의 방문지 위치정보를 식별하고, 화물차의 통행 순서정보를 이용하여 화물차량의 방문한 공간적 범위를 H3 기반의 폴리곤으로 생성하였다. 생성된 트립체인 폴리곤 간의 연계성을 전 국 단위로 분석함으로 폴리곤의 H3 해상도를 결정하였으며, 최적의 해상도를 동적으로 도출하 기 위한 파라미터의 결정 알고리즘을 개발하였다. 전국을 대상으로 실증하여 폴리곤을 생성하 고 최적 해상도 결정 결과 공간 적합도는 81.26% 수준으로 확보되고 오차율은 14.8% 수준으로 검증되었다. 본 연구에서 개발한 방법론으로 화물차량의 통행체인 특성과 방문 시설의 특성에 따라 군집화함으로 물류 거점을 기준으로 화물의 특성을 파악할 수 있는 기반을 마련하였다.

This study aims to improve understanding of freight movement, crucial for logistics facility investment and policy making. It addresses the limitations of traditional freight truck traffic data, aggregated only at city and county levels, by developing a new methodology. This method uses trip chain data for more detailed, facility-level analysis of freight truck movements. It employs DTG (Digital Tachograph) data to identify individual truck visit locations and creates H3 system-based polygons to represent these visits spatially. The study also involves an algorithm to dynamically determine the optimal spatial resolution of these polygons. Tested nationally, the approach resulted in polygons with 81.26% spatial fit and 14.8% error rate, offering insights into freight characteristics and enabling clustering based on traffic chain characteristics of freight trucks and visited facility types.

최근 사회기반시설이 밀집한 도심지에서 싱크홀이 빈번히 발생하고 있다. 무엇보다 대부분의 싱크홀이 시민 의 생활영역 주변에서 발생하고 있어, 싱크홀의 주요 발생요인인 도시개발과 지하수관리에 대한 체계적인 대책수립 이 요구되고 있다. 따라서 본 연구에서는 싱크홀과 직간접적으로 관련성이 깊은 지형공간정보를 이용하여 연구지역 에서 발생한 싱크홀의 위험요인을 분석하고자 하였다. 분석에 사용된 지형공간정보는 싱크홀의 발생원인을 지형학 적 관점에서 구축한 정보이며, 정보의 처리와 분석은 GIS를 기초로 한 다양한 공간분석도구를 이용하였다. 연구결과, 지형학적 요인이 싱크홀의 발생원인과 유의미한 관련성이 존재하며, 지하에 설치된 각종 관망과 지하수위의의 이동 특성, 기타 지형학적 특성의 관리가 필요함을 파악할 수 있었다. 이와 같은 연구결과는 향후 도시방재분야의 의사결 정지원자료로 활용 가능하며, 수문지형학 및 공간모델링분야를 접목한 확장 연구가 필요하다고 사료된다.

Sinkholes happen in increasingly higher frequency in downtown areas with a concentration of social infrastructure these days. Most sinkholes occur around the living areas of citizens, which calls for a systematic countermeasure plan for urban development and underground water management, which are parts of the main causes of sinkholes. This study thus set out to analyze the risk factors of sinkholes in the subject area by using geospatial information deeply connected to sinkholes both directly and indirectly. The geospatial information used in analysis was obtained by examining the causes of sinkholes from a topographical perspective. Collected data were treated and analyzed with a range of spatial analysis tools based on GIS. The findings show that topographical factors had significant relations with sinkhole causes and raise a need to manage all kinds of pipe networks underground, the movement characteristics of underground water levels, and other topographical features. The findings may serve as data to support decision-making processes in the field of urban disaster prevention and call for extensive research to incorporate hydro-geomorphology and spatial modeling.

Purpose: The purpose of this study is to identify the spatial distribution of hypertension prevalence and to investigate individual and regional-level factors contributing to the prevalence of hypertension in the region. Methods: This study is a cross-sectional research using the 2015 Community Health Survey. Total 64,473 people from 7 metropolitan cities were used for the final analysis. Geoda program was adopted to identify the regional distribution of hypertension prevalence and analyzed by descriptive statistics, one-way ANOVA and correlation analysis using SPSS statistics 23.0 program. Multi-level analysis was performed using SPSS (GLMM). Results: The prevalence of hypertension was related to individual level factors such as age, monthly household income, normal salt intake, walking practice days, and regional level factors including number of doctors per 10,000 population, number of parks, and fast food score. Besides, regional level factors were associated with hypertension prevalencies independently without the effects of individual level factors even though the influences of individual level factors ware larger than those of regional factors. Conclusion: Respectively, both individual and regional level factors should be considered in hypertension intervention programs. Also, a national level research is further required by exploring various environmental factors and those influences relating to the hypertension prevalence.

A TIN, Triagulated Irregular Network, based topographic modeling method and a distributed rainfall-runoff model using the topographic representation is presented. In the TIN based topographic representation, a watershed basin is modeled as a set of contiguous non-overlapping triagular facets : the watershed basin is subdivided according to streamlines to deal with water movement one-dimensionally ; and each partitioned catchment is approximated to a slope element having a quasi-three-dimensional shape by using cubic spline functions. On an approximated slope element, water movement is represented by combined surface-subsurface kinematic wave equations considering a change of slope gradient and slope width. By using the distributed rainfall-runoff model, the effects of spatial variability of soil properties on runoff response are examined.

The estimation of missing sensor values is an important problem in sensor network applications, but the existing approaches have some limitations, such as the limitations of application scope and estimation accuracy. Therefore, in this paper, we propose a new estimation model based on a spatial-temporal correlation analysis (STCAM). STCAM can make full use of spatial and temporal correlations and can recognize whether the sensor parameters have a spatial correlation or a temporal correlation, and whether the missing sensor data are continuous. According to the recognition results, STCAM can choose one of the most suitable algorithms from among linear interpolation algorithm of temporal correlation analysis (TCA-LI), multiple regression algorithm of temporal correlation analysis (TCA-MR), spatial correlation analysis (SCA), spatial-temporal correlation analysis (STCA) to estimate the missing sensor data. STCAM was evaluated over Intel lab dataset and a traffic dataset, and the simulation experiment results show that STCAM has good estimation accuracy.

Inspired by the success of the High-line project in New York, The Seoul Metropolitan Government launched a project to convert an overpass near Seoul station into a pedestrian park. Seoullo 7017 went through instant success after its opening in May 2017; however, there is a continuous controversy over its long-term impact as shown in the exemplary cases like the High-line project. This study aims for quantitative investigation through the comparative analysis between Seoullo 7017 and the High-Line in the perspectives of spatial configuration. Space Syntax was chosen as the analysis method for this research. Integration (3) in Space Syntax is known to have a high correlation with pedestrian volume; thus, by using this method, spatial structure was analyzed by comparing the statistically verified results of changes in the spatial structure of the Highline with those in Seoul. The results indicated that the influence of Seoullo 7017 was less than that of the High-line in terms of spatial configuration. The reason for this difference is spatial configuration between Manhattan and Seoul. The High-line is located in Manhattan which has an urban grid structure, whereas Seoul has non-geometric urban structure, the neighborhood unit in Korea. Also the center of the overpass isn't connected well with its surroundings.

The wide application of various integrated location-based services (LBS social) and tourism application (app) has generated a large amount of trajectory space data. The trajectory data are used to identify popular tourist attractions with high density of tourists, and they are of great significance to smart service and emergency management of scenic spots. A hot spot analysis method is proposed, based on spatial clustering of trajectory stop points. The DBSCAN algorithm is studied with fast clustering speed, noise processing and clustering of arbitrary shapes in space. The shortage of parameters is manually selected, and an improved method is proposed to adaptively determine parameters based on statistical distribution characteristics of data. DBSCAN clustering analysis and contrast experiments are carried out for three different datasets of artificial synthetic two-dimensional dataset, four-dimensional Iris real dataset and scenic track retention point. The experiment results show that the method can automatically generate reasonable clustering division, and it is superior to traditional algorithms such as DBSCAN and k-means. Finally, based on the spatial clustering results of the trajectory stay points, the Getis-Ord Gi* hotspot analysis and mapping are conducted in ArcGIS software. The hot spots of different tourist attractions are classified according to the analysis results, and the distribution of popular scenic spots is determined with the actual heat of the scenic spots.

In modern times, numerous cities are competing to create the unique skyline adjacent to the water. Tall buildings located across the river have a great contribution to the skyline of a riverfront city and can be a precious asset for the city. Moreover, in several cities, tall buildings and their impact on the urban skyline are a matter that should be considered and regulated in urban design. Therefore, as a prominent element in a larger visual setting of the city, tall buildings should improve the visual quality of the skyline rather than diminish that quality. This research attempts to provide an objective method to analyze the visual quality of the skyline made by a group of tall buildings through their feature of heights and spatial arrangement from riverfront views. The analysis is determined by the design variables of building heights variation, heights transition, density, and spacing of a group of tall buildings. A comparative case study of tall buildings in Yeouido and Lujiazui was conducted to prove the effectiveness of the analysis. The proposed method can be used in a simple way in the quantitative approach to quantify the visual quality of the skyline. In conclusion, Yeuido's skyline is not quite interesting from the riverfront view in terms of height variation and continuity of the skyline view because they are dispersed. Conversely, Lujiazui's skyline from the riverfront vantage points has a good quality in all aspects of the feature of height and spatial arrangements of tall buildings cluster. These factors can be used for the urban designer on how proposed tall buildings within the cluster should appropriately respond to adding image on the skyline.

The focus of this paper is the development of a solution regarding the coexistence of the LTE-LAA and Wi-Fi networks in the 5 GHz bandwidth by using an interference analysis and traffic optimization for which channel selection schemes are used. By implementing an analysis tool based on the Monte Carlo method, named “3DMCAT”, a simulation is applied with the LBT protocol in both the time and frequency domains on the frame based equipment of the spatial, time, spectrum domain; this tool is implemented by combining a Microsoft Excel calculation and the corresponding VBA. 3DMCAT shows the results of transmission performance analysis for the coexistence schemes of the Wi-Fi and LTE-LAA systems in the 5 GHz frequency bands.

The study reported in this paper aimed to evaluate the topics and opinions of COVID-19 discussion found on Twitter. It performed topic modeling and sentiment analysis of tweets posted during the COVID-19 outbreak, and compared these results over space and time. In addition, by covering a more recent and a longer period of the pandemic timeline, several patterns not previously reported in the literature were revealed. Author-pooled Latent Dirichlet Allocation (LDA) was used to generate twenty topics that discuss different aspects related to the pandemic. Time-series analysis of the distribution of tweets over topics was performed to explore how the discussion on each topic changed over time, and the potential reasons behind the change. In addition, spatial analysis of topics was performed by comparing the percentage of tweets in each topic among top tweeting countries. Afterward, sentiment analysis of tweets was performed at both temporal and spatial levels. Our intention was to analyze how the sentiment differs between countries and in response to certain events. The performance of the topic model was assessed by being compared with other alternative topic modeling techniques. The topic coherence was measured for the different techniques while changing the number of topics. Results showed that the pooling by author before performing LDA significantly improved the produced topic models.

Purpose: We aimed to evaluate the accessibility and equity of automated external defibrillators (AEDs)in areas with a high concentration of older adults and to propose evidence-based policy directions usinggeographic information systems (GIS). Methods: For the secondary analysis, multiple datasets were integrated from the Korea's NationalGeographic Information Institute, the Ministry of the Interior and Safety, the Suwon Fire Department,and the Suwon Southern Fire Station, including continuous digital topographic maps, demographicstatistics, AED locations, road networks, and out-of-hospital cardiac arrest incidence data. The clusteringand spatial heterogeneity of AED deployment were examined using kernel density estimation andspatial autocorrelation analysis. Service areas reflecting the walking speeds of older adults weredelineated, and equity was assessed using the Gini coefficient. A two-step floating catchment areaanalysis was used to provide supply-to-demand ratios and accessibility indices. Results: AEDs exhibited clustered patterns centered on public locations, and several areas were identified as potential service blind spots, revealing inequities at the neighborhood level. Several AED siteswere insufficient for the local older-adult population, and only a subset of areas demonstrated relativelyhigh accessibility indices. Conclusion: As the population age structure shifts toward older age groups, AED policy criteria should beredesigned to reflect the mobility and accessibility of older adults. Implementing mixed relocationstrategies that incorporate age-friendly criteria, conducting periodic policy performance evaluations,and enhancing AED visibility and tailored education that accounts for the cognitive characteristics ofolder adults will contribute to improving the health of older populations.

As Japan’s aging rate is projected to reach 39% by 2070, reducing disaster-related mortality risks among the elderly has become an increasingly important urban issue. The fact that approximately 89% of victims during the Great East Japan Earthquake were aged 66 or older highlights the high vulnerability of elderly populations in evacuation settings. Although Welfare Evacuation Shelters (WES) are designated to support such populations, urban areas continue to face challenges related to insufficient capacity and spatial imbalance. This study estimates the potential number of elderly evacuees and the capacity of Welfare Evacuation Shelters in Yokohama City, using GIS (Geographic Information System)-based spatial analysis to examine the gap between evacuation demand and shelter capacity. Evacuation demand was estimated for home-dwelling elderly residents (65+) certified at Long-term Care Level 3, while shelter capacity was calculated based on the characteristics of elderly welfare facilities. The analysis was conducted at the district level (Regional Disaster Prevention Base Districts) to identify spatial disparities and local challenges. In addition, improvement scenarios—such as regional cooperation and the utilization of non-designated facilities—were proposed and evaluated. Through these analyses, the study quantitatively demonstrates the potential of elderly welfare facilities to function as regional disaster prevention hubs in increasingly aging urban environments. The results reveal a severe shortage, with total shelter capacity meeting 14.5% of estimated demand. In addition, approximately half of these districts lack any available capacity, and 10% of these areas overlap with high-risk hazard zones. By assessing the effectiveness of various policy measures, the study provides fundamental data for improving elderly evacuation strategies and enhancing the operation of WES. Furthermore, the results highlight the importance of establishing cooperative frameworks with private facilities and strengthening support systems for home-based evacuees. These efforts are essential for enhancing urban disaster resilience in aging societies.

재난약자는 상대적으로 재난 위험에 더욱 노출되어 있고 회복력도 낮기 때문에 효율적인 재난안전 정책을 수립하는 데에 있어 매우 중요한 고려 요인이다. 이에 따라 본 연구는 재난약자에 초점을 두고, 폭염과 침수를 대상으로 ‘재난위험-재난약자-대응력’ 간의 관계를 공간적으로 분석하였다. 분 석결과는 다음과 같다. 첫째, 지역에 따라 재난약자의 분포특성과 재난안전에 대한 민감도가 다르게 나타났다. 둘째, 재난약자가 재난 위험에 실제로 더 많이 노출되어 있고, 공간적으로 불평등이 발생 하고 있음을 확인하였다. 결과적으로 공간계획과 공간정보가 재난안전정책에 반영되어야 하며, 사 각지대 제거를 위한 대책이 요구되어짐을 확인하였다. 본 연구는 취약성 저감과 회복력 증진의 측면 에서 재난약자에 초점을 두었다는 점에서 의의를 지니며, 정책 우선순위를 결정하고 ‘재난안전정의’ 를 실현하기 위한 기초를 마련하는 데에 기여할 수 있을 것으로 기대된다.

Vulnerable population should be considered in the design of effective disaster and safety polices because they are relatively more exposed but less resilient to damage from disasters. This study examined the spatial relationship among disaster risk, vulnerable population and response capacity for the cases of heat wave and inundation. The results were as follows. First, it was confirmed that the distributional characteristics of vulnerable population and their sensitivity of disaster risks were different by region. Second, spatial inequality was observed for vulnerable populations who are more exposed to disaster risk. These results suggest that spatial data and planning should be used to design disaster and safety policy, focusing on the elimination of “blind spots”. This study was meaningful in that it focused on reducing vulnerability and improving resilience for vulnerable population. The findings of this study are expected to help determine policy priorities and contribute to providing a foundation for “disaster safety justice”.