Earticle

본 연구에서는 교통사고 자료의 특성 및 공간효과를 반영한 교통사고 모형을 개발하였다. 미국 I-5 고속도로를 277개의 동일한 구간으로 구분하여 1999년부터 2007년까지 발생한 교통사고 자료를 활 용하였다. 공간모형의 활용성 여부를 판단하기 위해 모란지수(Moran’s I)를 통하여 구간별 공간상관 성이 존재하는지 검정하였다. 교통사고 발생건수 자료에서 팽창된 0값을 확인하였으며 이러한 특성 을 반영하기 위해 기존의 가산자료 모형이 아닌 영 과잉 모형(Zero Inflated Model)과 허들 모형 (Hurdle Model)을 활용하였다. 본 연구에서는 공간효과를 반영한 공간 영 과잉 모형(Spatial Zero Inflated Model)과 공간 허들 모형(Spatial Hurdle Model)을 적합하였다. 분석 결과, DIC를 통해 팽창된 0의 특성을 반영한 공간 영 과잉 모형과 공간 허들 모형의 우수함을 확인하였다. 따라서 이를 최적의 교통사고 모형으로 제안하고 각 설명변수의 영향력을 통해 교통사고 발생에 영향을 주는 주요 요인 들의 효과를 정확하게 확인할 수 있다.

The purpose of this study is to develop traffic accident models based on spatial effects and traffic accident data characteristics. Statistical models are constructed with the number of traffic injuries observed from 277 segments of interstate highway I-5 in Washington for 9 years from 1999 to 2007 as a response variable. A significance test for Moran’s Index is conducted to determine whether or not spatial autocorrelation exists among the segments. Spatial zero Inflated model and spatial hurdle model are used to reflect excessive zeros in the response variable as well as spatial effects. Those models are found to be appropriate to handle the data according to DIC. Therefore, we propose these models as an optimal traffic accident model, which allows us to determine the effect of major factors of traffic accidents by investigating the influence of each explanatory variable in the models.

본 연구는 철강산업의 수출경쟁력 및 동태적 경쟁관계 분석을 위하여 한국, 중국, 일본을 중심으로 불변시장점유율모형과 공간변이할당모형을 적용하여 철강산업의 수출경쟁력 및 동태적 경쟁관계를 분석하였다. 분석 결과, 한국의 대세계 철강 수출변동의 주요 요인은 세계효과로 나타났다. 한국의 대중국 경쟁력 및 중국의 대세계 경쟁력의 변동 추이를 보여주는 동태적 공간분석에서는 한국 철강의 대중 경쟁력은 2016년과 2017년에는 강화하는 경향을 보였으나, 이후 2022년까지 경쟁력이 지속적으로 약화되는 추이로 나타나고 있다. 반대로, 중국의 대세계 경쟁력은 2017년까지 약화되었으나, 이후 2022년까지 경쟁력이 지속적으로 강화되는 추이를 보이고 있다. 또한 한국의 대일본 동태적 공간분석에서는 한국 철강의 대일 경쟁력 우위는 확대와 축소를 반복하고 있으며, 2017년부터는 좌측 편향 이동하고 있어 대일 경쟁력이 약해지는 추이이다. 중국의 대세계 철강 수출변동의 주요 요인은 세계효과로 나타났다. 그러나 동태적 공간분석에서 중국의 대일 경쟁력 우위는 2015년, 2016년, 2017년 축소되는 추세를 나타냈으나, 2018년부터는 경쟁력우위가 지속적으로 확대되는 추이이며, 특히 2021년과 2022년에 우위가 크게 확대되는 추이를 보이고 있다. 현재, 세계 철강산업은 전반적으로 침체되었지만, 공급과잉으로 인하여 여전히 경쟁이 치열하고 수요가 한계에 봉착된 시점에서, 우리나라 철강산업은 경쟁력을 향상시켜 지속가능한 산업이 되기를 기대한다.

Purpose : This study analyzed the export competitiveness and dynamic competitive relationship of the steel industry. Research design, data, methodology : This study, the export competitiveness and dynamic competitive relationship of the steel industry were analyzed using the constant market share model and spatial shift-share model. Results : In Korea's dynamic spatial analysis of China, the competitiveness of Korean steel against China showed a tendency to strengthen in 2016 and 2017, but the competitiveness continues to weaken until 2022. China's competitiveness against the world weakened until 2017, but its competitiveness continues to strengthen until 2022. Korean steel's competitive advantage against Japan is repeatedly expanding and shrinking, and since 2017, its competitiveness against Japan is weakening. China's competitive advantage over Japan was on the decline in 2015, 2016, and 2017, but it has been continuously expanding since 2018, and in particular, the advantage is showing a significant expansion in 2021 and 2022. Conclusions : Although the global steel industry is currently experiencing an overall recession, competition is still fierce and demand is limited due to oversupply. At this point, our country's steel industry must strengthen its competitiveness and become a sustainable industry.

본 연구의 목적은 기초자치단체 간 사회복지지출의 공간적 자기상관성을 살펴보고, 사회복지지출 규모에 영향을 미치는 요인을 분석하는 데 있다. 본 연구에서는 공간적 자기상관성을 고려한 공간오차모형을 적용하여 복지지출에 영향을 미친 영향요인을 분석하였다. 분석결과 지자체 간 1인당 사회복지지출의 공간적 자기상관성이 나타났다. 그리고 공간회귀분 석을 통해 선행연구에서 도출된 각 요인들이 1인당 사회복지지출에 미치는 영향을 살펴보면, 사회·경제적 요인, 행정적 요인 그리고 재정자주도 요인은 지자체 복지지출에 정(+)의 영향을 미치는 것으로 분석되었다. 반면 전년도 복지예산, 정치적 요인, 지방세 등은 복지지출에 영향을 미치지 않은 것으로 나타났다. 본 연구는 기존 선행 연구와는 달리 지자체 간 복지지출 의 공간적 자기상관성을 확인하고 영향요인을 살펴본 데 의의가 있다. 본 연구에서는 횡단적 분석만을 실시하였기에, 향후에 는 다년도 사회복지지출 자료를 활용한 시계열 분석이 이루어질 필요성이 있다.

The purpose of this study is to analyse the determinants of the change in the welfare expenditure of local governments in 2015. This study analyzed the spatial correlation of welfare expenditure among neighboring local governments and determined the factors affecting the welfare expenditures. According to the results of the study, spatial correlation of welfare expenditure among local governments appears. Determinants, such as socio-economic factors, administrative factors, public financial factors are affecting the amount of the welfare expenditures, but local political factors, and local tax, last year’s budgets are not correlated with the amount of local welfare expenditures. In this study, it is significant to found out that the spatial correlation of welfare expenditure among the local governments and to examine the determinants. If possible, it is necessary to analyze the time-series analysis using the multi-year welfare expenditure data, expecially self-welfare expenditures.

Amenities including natural and sociocultural resources have affected to regional economy development and income distribution. This study intends to analyze the correlation of natural amenities and sociocultural amenities, and clarify the influence between regional economy indicators and diverse amenities using OLS, SLM and SEM. For these purposes, this study chooses 17 natural and sociocultural amenities based on the literature reviews, and collects the statistical data of these amenities. The spatial analysis unit of this study is nationwide 146 Si and Gun except Gu areas of metropolitan city. The main results of this study show that the of SLM and SEM are higher than OLS because natural and sociocultural amenities are relevant to regional spaces and have spatial autocorrelation. In addition, both natural and sociocultural amenities have affected to the regional economy, therefore the policy makers of regions should adopt both amenities in order to boost the regional economy. In conclusion, it is suggested that further researches need to use additional spatial regression models considering diverse amenity resources.

본 연구는 4차 산업 혁명 관련 산업의 집적이 지역 간 인구 이동에 미치는 영향을 실증적으로 분석하고, 산업별 특성에 따른 차별적 효과를 규명하는 데 목적이 있다. 2023년 전국 229개 기초자치단체의 데이터를 활용하여, 산업 특화도는 Flegg's Location Quotient (FLQ)로 측정하였으며, 인접 지역 간의 공간적 파급 효과를 포착하기 위해 공간회귀모형을 적용하였다. 분석 결과, 4차 산업의 집적은 인구 이동 유형에 따라 상이하였다. 첫째, 4차 산업 전체의 집적은 지역의 전입과 전출을 동시에 증가시키는 것으로 나타났다. 이는 4차 산업 기반 지역이 인구의 일방적인 유입지라기보다는, 인구 유입과 유출이 활발히 이루어지는 '흡인-순환 구조'의 거점으로 기능하고 있음을 시사한다. 둘째, 4차 산업을 세부 산업군으로 나누어 분석한 결과, 산업별 영향력은 뚜렷한 이질성을 보였다. 전문·과학 및 기술 서비스업은 전입, 전출, 순이동, 시군구 내 이동 등 모든 유형의 인구 이동에 걸쳐 가장 강력하고 긍정적인 영향을 미쳐 , 연구개발 및 네트워크 기반 지식 산업이 지역 인력의 외부 유입과 내부 순환을 모두 활성화하는 핵심 동력임을 입증하였다. 반면, 제조업은 전출과 시군구 내 이동을 촉진하여 지역 내 근거리 순환에 기여했으나 외부 유입 효과는 제한적이었으며, 금융 및 보험업은 전출과 시군구 내 이동을 억제하여 지역의 정주 안정성을 강화하는 방향으로 작용하였다. 이러한 결과는 향후 지역 정책은 4차 산업을 단일한 산업군으로 접근하기보다 산업별 고용 특성을 고려한 차별화된 전략이 필요함을 시사한다. 특히 전문·과학·기술서비스업과 같은 지식 기반 산업을 중심으로 R&D 허브 조성, 산학연 협력체계 구축 등 '외부 유입형 인력 정책'을 강화할 필요가 있다.

This study examines the relationship between the agglomeration of Fourth Industrial Revolution(4IR) industries and regional population mobility in South Korea. The 4IR sector comprises four sub-industries: manufacturing; publishing, broadcasting, telecommunications and information services; finance and insurance; and professional, scientific and technical services. Using 2023 data for 228 municipal-level jurisdictions, industrial specialization was measured by Flegg’s Location Quotient(FLQ), and a spatial regression model was employed to model spatial dependence across neighboring regions. Higher levels of 4IR industrial agglomeration are associated with increases in both in- and out-migration, indicating a bidirectional mobility pattern rather than simple concentration. Sectoral differences are clear: professional, scientific and technical services are positively related to all mobility types; 4IR-related manufacturing mainly to out-migration and short-distance mobility; finance and insurance show stabilizing effects; and publishing, broadcasting, telecommunications and information services exhibit no significant relationship. These results suggest that 4IR industries reshape regional mobility through sector-specific mechanisms and that policy responses should consider heterogeneous mobility dynamics and spatial interactions among regions.

This study aimed to suggest the direction of sustainable rural development through the analysis of existing rural revitalization policies and rural status. This study also aimed to explore ways to revitalize the agricultural-oriented rural economy and improve the settlement environment in consideration of the characteristics of rural spaces. Based on the results, we created a regional crop-specific agricultural space, planned concentration, farmland maintenance, and joint agricultural facilities to secure agricultural competitiveness. It also plans a walking-oriented settlement environment to create a safe and pleasant rural village. Finally, by overcoming the limitations of the existing land-use plan, a sub-concept rural spatial plan reflecting the characteristics of rural areas was proposed, and the rural revitalization plan was studied.

최근 국내 고농도 미세먼지 발생 빈도가 높아짐에 따라 국민의 건강과 생명이 위협받고 있다. 그래서 본 연구는 한국 미세먼지가 폐질환 사망에 미치는 영향을 분석했다. PM2.5와 PM10에 노출 정도가 폐암과 폐렴 사망률에 미치는 영향을 통계적으로 검증하기 위하여 전국 시군구를 대상으로 2015-2019년 동안의 폐암 및 폐렴 사망자수와 PM2.5와 PM10 노출 시간자료를 이용하여 패널 데이터 모형을 구축하여 통계적으로 분석한다. 또한 SO2, CO 등 다른 대기오염 변수, 온도, 습도 등 기후변수, 제조업, 하수종말처리업 등 산업 변수, 그리고 65세 이상 인구, 의료병상수, 주택가격 등 인구 및 경제변수 등을 모형에 포함하였다. 분석결과는 미세먼지 및 초미세먼지에 노출되는 시간이 많을수록 폐질환 사망자수가 증가할 뿐만 아니라 SO2 노출시간비율도 폐질환 사망자수를 증가시키는 중요한 환경적 요인이라는 분석결과를 제시하고 있다. 또한 온도와 습도가 높을수록 폐질환 사망률이 높아지는 것으로 나타나 이들 변수가 오염물질의 농도와 전이에 영향을 미치고 폐질환에도 직접적 영향을 미친다는 통계적 검정 결과를 제시하고 있다. 예상하는 바와 같이 노인 인구 (65세 인구 비율)가 많을수록, 대기질에 영향을 주는 하수처리업 비율이 높을수록 폐질환 사망률이 높아진다는 분석 결과를 제시하고 있다. 본 연구 결과로부터 도출할 수 있는 시사점은 다음과 같다. 첫째, PM10, PM2.5 그리고 SO2에 대한 노출정도가 폐질환 사망에 영향을 미친다는 본 연구의 결론은 이들 대기 오염이 국민 건강을 위협하는 요인으로 대기오염의 경감을 위한 정부 개입의 당위성을 제시하고 있다. 둘째, 본 연구에서 폐질환 사망에 영향을 미치는 대기오염 물질과 기후 요소는 현재 전 지구적으로 논의되고 있는 지구 온난화에 따른 기후 위기 대응과 탄소 중립 이슈와 밀접한 관련이 있다.

This study investigated the effects of Particulate Matter (PM) on deaths from lung diseases during the period 2015-2019 in Korea. To this end, a spatial panel data model was constructed to statistically test the effects of PM2.5 and PM10 exposure on the number of lung cancer and pneumonia deaths. The analysis results indicate that the more time exposed to high concentration of PM2.5, PM10, and SO2, the number of lung disease deaths increases. In addition, the higher the wind speed, the higher the mortality rate from lung diseases, suggesting that these variables affect the concentration and transition of pollutants and have a direct effect on lung disease. As expected, the analysis results also suggest that the higher the proportion of the elderly population and the higher the proportion of the sewage treatment industry, the higher the mortality rate from lung disease.

생물종 간의 경쟁과 공간적 분포, 생태적 지위에 대한 정보는 생물의 지리학적 진 화을 이해하는 데 중요하다. 본 연구는 한국에 서식하고 있는 동일한 속에 속한 개 구리 2종 (Pelophylax nigromaculatus, P. chosenicus)에 대한 관찰 자료를 통해 종들의 분포 특성과 생태적 지위를 알아보고, 종 분포모델 기법을 바탕으로 두 종간 지리적 분포 유형을 추론하였다. 연구 결과, 참개구리는 전국적으로 넓게 분포한 반면, 금개 구리는 주로 서해안 주변 지역에 분포하였다. 두 종은 비교적 낮은 고도범위를 선호 하였으며, 경사도가 낮은 지역과 농경지에 주로 분포했다. 지리적 기후 변수에 따른 생태적 지위는 2종에서 매우 높게 중첩하였다. 종 분포 모델들을 중첩한 결과, 종 간 중첩된 서식지의 대부분은 낮은 고도의 농경 지역이었고, 참개구리 서식 범위 내에 금개구리의 서식 범위가 대부분 포함되어 있었다. 결론적으로 한국에 서식하고 있는 Pelophylax 속 2종은 유사한 생태적 지위를 차지하고 있었으며, 공존하고 있는 지역은 경기도와 충청남도, 전라북도의 해안 주변 지역으로 동소적인 분포형태를 보였다. 향 후 이러한 분포형태를 일으키는 직접적인 요인 및 두 종 간 경쟁 유무 대한 정보를 확인 위해, 두 종이 공존하고 있는 지역들에서 보다 자세한 생태학적, 행동학적 연구 가 필요하다.

본 연구는 헤도닉 가격모형을 활용하여 혁신도시 개발이 인근 주택(아파트)가격에 미친 영향을 규명하였다. 기존 선행연구는 주로 주택자체 특성과 미시적 공간범위의 단지외부 특성의 영향에 초점을 둔 반면, 본 연구는 거시적 공간범위의 도시공간특성(도심/부도심 접근성)의 역할에 주목하였다. 또한 접근성 변수 측정에 있어 개별 주거동을 기점으로 실제 도로 기반 네트워크 거리 방식을 활용하여 변수 구축에 정확성을 개선하였다. 대구 혁신도시를 대상으로 한 다변량 회귀분석 결과, 노후도(-0.826), 도심까지의 거리(-0.327), 부도심까지의 거리(-0.277), 분양면적(-0.227), 지하철역까지의 거리(-0.217) 변수가 통계적으로 유의미한 수준(p<0.05)에서 주택가격에 비중있는 영향을 미친 요인으로 확인되었다. 특히, 거시적 측면에서 도심/부도심 접근성 변수를 통제한 다핵구조 분석모형 결과, 단핵구조 모형 결과와 다르게 혁신도시 중심 접근성 요인의 통계적 유의미성은 발견되지 않았다. 이외에 이론에 부합한 연구가설을 입증하는데 있어 직선거리 기반의 접근성 측정방식 보다는 실제 네트워크거리 측정 방식이 보다 효과적인 변수측정 방식임을 확인하였다. 따라서 혁신도시 개발이 주변지역 주택가격에 미친 경제적 파급효과는 기존 도심과 인접하여 개발된 경우 보다 거시적인 도시공간구조 특성과 실제 도로 네트워크 접근성에 근거하여 이해될 필요가 있다.

This study investigates the effect of development of Daegu Innovation City on nearby housing (apartment) prices, employing hedonic price model largely specified by housing unit characteristics, site environments, and urban spatial structure. Previous studies often highlighted the influence of housing unit performance or micro-scale site characteristics (e.g., the access to residential facilities). However, this study is more focused on the role of macro-scale urban spatial structure (e.g., the access to urban/sub-center). Moreover, in measuring the distance between housing unit and residential facilities/urban center, a network-based approach was adapted for a more fine-grained resolution. The results from hedonic model revealed that deterioration (-0.826), the distance to urban center (-0.327), the distance to sub-center (-0.277), housing area (-0.227), and the distance to subway (-0.217) are associated with housing price at the statistically significant level (p<0.05). Interestingly, the influence of a newly developed center in a project area was no longer significant when macro-scale urban/sub-centers were controlled. Also, a network-based measurement is more efficient than a straight-line measurement in explaining housing prices within a study area. Therefore, a ripple effect of a new development project on housing market might be properly quantified by a better understanding of macro-scale urban spatial structure and a network-based distance measurement.

Evacuation to disaster shelters can be optimized by giving instructions to evacuees to help them find the most suitable shelters and evacuation paths from their location. To generate such information in real-time, construction of spatial databases and complex spatial analysis models through Web Map Services (WMS) and Web Feature Services (WFS) based on Open Geospatial Consortium Web Services (OWS) is required. Focusing on the implementation of distributed OWS resources to provide more immediate information in the case of an emergency, we propose a Web-based system that identifies suitable shelters and provides the shortest evacuation path to each shelter for civilians who are within the danger zone. Specifically, (1) a search framework based on the OWS architecture is proposed and utilized to develop both Web-based and smartphone applications connected with WMS types of spatial data on the Web; (2) the spatial analysis models proposed include three sub-models, namely, data construction, shelter selection using scores by natural breaks, and an evacuation path model using network analysis. We identify candidate shelters by considering proximity to health care facilities and to major road, and coverage of each shelter in danger zone.

In this paper, an interactive color natural image segmentation method is proposed. The method extends the Gaussian Mixture Model (GMM) by taking into account user markers as useful spatial prior. In this way, a distribution combining with color and spatial location is obtained. The distribution is incorporated in a Bayesian MAP approach. The approach is formalized as an iterative energy minimization problem. A direct global minimization technique based on variational method is employed to get binary solution. After each iteration, the largest connected region from foreground is used to update foreground GMMs and achieve more superior performance than original GrabCut method. Extensive experiments are performed on public benchmark datasets such as GrabCut benchmark, Berkeley segmentation database and Graz benchmark. The results show that the proposed method can extract the object region from the complex background accurately.

The decomposition of the exports of individual ports shows different patterns of performance. Some ports have a mediocre performance and experience a decrease in their share of exports, but other ports record a good export performance. This paper applies constant market share model and shift share model to export variation of individual ports. The constant market shares analysis shows that Incheon Port and Pyeongtaek Port suffering from poor export performance have negative value for the competitiveness effect, while the ports composed of Gwangyang Port, Busan Port, Ulsan Port, and Daesan Port experiencing export increase have positive values for the competitiveness effect between 2016 and 2018. The competitiveness effect has asymmetric effects on export variation since the competitiveness effect has a strong impact on the export decrease but exerts very weak influence for export increase. The shift share analysis also shows that Busan Port, Gwangyang Port, and Ulsan Port have comparative competitive advantage over the other three ports but their export increase is owing to world growth effect rather than their competitiveness.

3차원 도시환경의 디지털기반의 가시화는 도시계획 및 통신계획, 건설, 건축, 입체적인 도시공간정보시스템 구현, 안전 및 방재 등에서 많은 필요와 그 중요성이 크게 부각되고 있다. 현재 2차원적인 지도정보와 등고선을 이용한 DEM 방식은 3차원 공간을 표현하기에는 많은 한계를 가지고 있다. 최근 레이저와 GPS 측량기술을 이용한 높은 정확도와 보정이 용이한 LiDAR Data로 표고값을 측정하는 연구가 선진국에서 시도되고 있다. 본 연구에서는 해외 선진기술을 도입하여 우리 실정에 적합한 유비쿼터스 입체 도시 건설을 위해 3차원 공간영상 도시모델 생성 기법 및 알고리즘을 개발하여 u-City의 최적 관리를 위한 방안을 제시하고자 한다. 이를 위하여 원격탐사 영상 Data를 중심으로 하는 정사보정하고 이에 매칭할 수 있는 벡터와의 실시간 통합 및 전환으로 U-city에서의 3차원 영상 도시 모델의 생성과 다양한 활용을 제시하였다.

The visual implementation of 3-dimensional national environment is focused by the requirement and importance in the fields such as, urban planing, telecommunication facility deployment plan, railway construction, construction engineering, spatial city development, safety and disaster prevention engineering. The currently used DEM system based on the 2-D digital maps and contour lines has limitation in implementation in reproducing the 3-D spatial city. Currently, the LiDAR data which combines the laser and GPS skill has been introduced to obtain high resolution accuracy in the altitude measurement in the advanced country. In this paper, we first introduce the LiDAR based esearches in advanced foreign countries, then we propose the data generation scheme and an solution algorithm for the optima management of our 3-D spatial u-City construction. For this purpose, LiDAR based height data transformed to DEM, and the realtime unification of the vector via digital image mapping and raster via exactness evaluation is transformed to make it possible to trace the model of generated 3-dimensional model with long distance for 3D u-city model generation.

This study is trying to find out the spatial econometrics model in order to reflect the true reality in the housing price analysis. Due to the influence of spatial autocorrelation with respects to the housing price in the housing market, the estimation of the OLS is not preferable. Then the spatial econometrics model reflecting spatial dependence and spatial heterogeneity is the best alternative in terms of housing price estimation, probably. "Everything is related to everything else, but near things are more related than distant things". More realistic spatial weight matrix and spatial model scheme, better performance in the housing price prediction. Therefore, this study can show that the model improvement by spatial model scheme can be achieved by the comparing the spatial econometrics models such as SAR(Spatial Autoregressive Models), SEM(Spatial Errors Models), SAC(General Spatial Models), and GWR(Geographically Weighted Regression). Depends on the perspective of methodology, the SAC and the GWR models are preferable in terms of global(nomothetic approach) or local(idiographic approach) point of view, respectively.

Objectives: The aim of this study was to determine the factors associated with the spatial distribution of the incidence of colorectal cancer (CRC) in the neighborhoods of Tehran, Iran using Bayesian spatial models. Methods: This ecological study was implemented in Tehran on the neighborhood level. Socioeconomic variables, risk factors, and health costs were extracted from the Equity Assessment Study conducted in Tehran. The data on CRC incidence were extracted from the Iranian population-based cancer registry. The $Besag-York-Molli{\acute{e}}$ (BYM) model was used to identify factors associated with the spatial distribution of CRC incidence. The software programs OpenBUGS version 3.2.3, ArcGIS 10.3, and GeoDa were used for the analysis. Results: The Moran index was statistically significant for all the variables studied (p<0.05). The BYM model showed that having a women head of household (median standardized incidence ratio [SIR], 1.63; 95% confidence interval [CI], 1.06 to 2.53), living in a rental house (median SIR, 0.82; 95% CI, 0.71 to 0.96), not consuming milk daily (median SIR, 0.71; 95% CI, 0.55 to 0.94) and having greater household health expenditures (median SIR, 1.34; 95% CI, 1.06 to 1.68) were associated with a statistically significant elevation in the SIR of CRC. The median (interquartile range) and mean (standard deviation) values of the SIR of CRC, with the inclusion of all the variables studied in the model, were 0.57 (1.01) and 1.05 (1.31), respectively. Conclusions: Inequality was found in the spatial distribution of CRC incidence in Tehran on the neighborhood level. Paying attention to this inequality and the factors associated with it may be useful for resource allocation and developing preventive strategies in at-risk areas.

OBJECTIVES: The aim of this study was to explore the spatial pattern of female breast cancer (BC) incidence at the neighborhood level in Tehran, Iran. METHODS: The present study included all registered incident cases of female BC from March 2008 to March 2011. The raw standardized incidence ratio (SIR) of BC for each neighborhood was estimated by comparing observed cases relative to expected cases. The estimated raw SIRs were smoothed by a Besag, York, and Mollie spatial model and the spatial empirical Bayesian method. The purely spatial scan statistic was used to identify spatial clusters. RESULTS: There were 4,175 incident BC cases in the study area from 2008 to 2011, of which 3,080 were successfully geocoded to the neighborhood level. Higher than expected rates of BC were found in neighborhoods located in northern and central Tehran, whereas lower rates appeared in southern areas. The most likely cluster of higher than expected BC incidence involved neighborhoods in districts 3 and 6, with an observed-to-expected ratio of 3.92 (p<0.001), whereas the most likely cluster of lower than expected rates involved neighborhoods in districts 17, 18, and 19, with an observed-to-expected ratio of 0.05 (p<0.001). CONCLUSIONS: Neighborhood-level inequality in the incidence of BC exists in Tehran. These findings can serve as a basis for resource allocation and preventive strategies in at-risk areas.

This study used spatial models to analyze Korea’s official development assistance (ODA) allocation to 55 recipient countries in Asia, Africa, Eastern Europe, the Pacific, and Central America in the 2010s. The spatial lag model with spatial two-stage least squares estimators shows that the first-order spatially lagged dependent variable coefficient of Korea’s ODA to the ODA recipient was highly positive. The democracy level of ODA recipient countries and the world ODA of recipient countries positively influenced Korea’s ODA to recipient countries. However, the spatial error correction estimation of spatial lag and spatial error model shows that while the democracy level of the recipient countries is significant, the distance between Korea and the recipients, trade with recipients, recipients’ gross domestic product (GDP), world ODA, and foreign direct investment (FDI) to recipients does not significantly influence changes to Korea’s ODA in the short run.

For the planning of future land use for economic activities, an essential component is the identification of the vulnerable areas for natural hazard and environmental impacts from the activities. Also, exploration for mineral and energy resources is carried out by a step by step approach. At each step, a selection of the target area for the next exploration strategy is made based on all the data harnessed from the previous steps. The uncertainty of the selected target area containing undiscovered resources is a critical factor for estimating the exploration risk. We have developed not only spatial prediction models based on adapted artificial intelligence techniques to predict target and vulnerable areas but also validation techniques to estimate the uncertainties associated with the predictions. The prediction models will assist the scientists and decision-makers to make two critical decisions: (i) of the selections of the target or vulnerable areas, and (ii) of estimating the risks associated with the selections.

This paper presents proportional odds cure models to allow spatial correlations by including spatial frailty in the interval censored data setting. Parametric cure rate models with independent and dependent spatial frailties are proposed and compared. Our approach enables different underlying activation mechanisms that lead to the event of interest; in addition, the number of competing causes which may be responsible for the occurrence of the event of interest follows a Geometric distribution. Markov chain Monte Carlo method is used in a Bayesian framework for inferential purposes. For model comparison some Bayesian criteria were used. An influence diagnostic analysis was conducted to detect possible influential or extreme observations that may cause distortions on the results of the analysis. Finally, the proposed models are applied for the analysis of a real data set on smoking cessation. The results of the application show that the parametric cure model with frailties under the first activation scheme has better findings.

This study aims to accurately estimate population distribution more specifically than administrative unites using a RK (Regression-Kriging) model. The RK model is the areal interpolation technique that involves linear regression and the Kriging model. In order to estimate a population’s distribution using a sample region, four different models were used, namely; a regression model, RK model, OK (Ordinary Kriging) model and CK (Co-Kriging) model. The results were then compared with each other. Evaluation of the accuracy and validity of evaluation analysis results were the basis RMSE (Root Mean Square Error), MAE (Mean Absolute Error), G statistic and correlation coefficient (ρ). In the sample regions, every statistic value of the RK model showed better results than other models. The results of this comparative study will be useful to estimate a population distribution of the metropolitan areas with high population density