Spatio-temporal changes pattern in the hotspot's footprint: a case study of confirmed, recovered and deceased cases of Covid-19 in India

Mohd Shamsh Tabarej,Sonajharia Minz 대한공간정보학회 2022 Spatial Information Research Vol.30 No.4

Hotspot detection and the analysis for the hotspot’s footprint recently gained more attention due to the pandemic caused by the coronavirus. Different countries face the effect of the virus differently. In India, very little research has been done to find the virus transmission. The paper’s main objective is to find changing pattern of the footprint of the hotspot. The confirmed, recovered, and deceased cases of the Covid-19 from April 2020 to Jan 2021 is chosen for the analysis. The study found a sudden change in the hotspot district and a similar change in the footprint from August. Change pattern of the hotspot’s footprint will show that October is the most dangerous month for the first wave of the Corona. This type of study is helpful for the health department to understand the behavior of the virus during the pandemic. To find the presence of the clustering pattern in the dataset, we use Global Moran’s I. A value of Global Moran’s I greater than zero shows the clustering in the data set. Dataset is temporal, and for each type of case, the value Global Moran’s I > 0, shows the presence of clustering. Local Moran’s I find the location of cluster i.e., the hotspot. The dataset is granulated at the district level. A district with a high Local Moran’s I surrounded by a high Local Moran’s I value is considered the hotspot. Monte Carlo simulation with 999 simulations is taken to find the statistical significance. So, for the 99% significance level, the p-value is taken as 0.001. A hotspot that satisfies the p-value threshold is considered the statistically significant hotspot. The footprint of the hotspot is found from the coverage of the hotspot. Finally, a change vector is defined that finds the pattern of change in the time series of the hotspot’s footprint.

Factors influencing fatal vehicle-involved crash consequence metrics at spatio-temporal hotspots in South Korea: application of GIS and machine learning techniques

Tamakloe Reuben,Park D. 서울시립대학교 도시과학연구원 2023 도시과학국제저널 Vol.27 No.3

Studies have employed several techniques to identify the effect of individual risk factors influencing crashes at hotspot locations. Nevertheless, as crashes are sometimes influenced by a combination of risk factors, identifying the chains of factors collectively contributing to fatal crashes at hotspot locations could provide added insights for improving traffic safety. By employing fatal crash data from Korea, this study identifies hotspots with increasing (critical) and decreasing (diminishing) temporal trends using a spatio-temporal hotspot analysis tool in GIS. Further, a machine learning technique is employed to explore the chains of factors influencing the number of vehicles and the number of casualties involved in fatal crashes at intersections and midblocks in each hotspot type identified. In general, results showed that minibuses/vans and construction vehicles were mainly at fault for fatal single-vehicle pedestrian-involved crashes. While many casualties and vehicles are likely to be involved in crashes at midblocks during the daytime regardless of the hotspot type, the nighttime variable was particularly associated with large casualty-size crashes at critical intersection hotspots. Further, while reckless driving was mostly associated with single-vehicle crashes at intersections in diminishing hotspots, pedestrian protection, and improper centreline crossing violations were more pronounced at midblocks in diminishing hotspots. This analysis identified groups of factors that could be collectively controlled to improve road safety and proposed countermeasures to mitigate fatal crashes on roadways.

원격탐사자료를 이용한 참나무시들음병 피해목의 공간분포특성 분석

차성은,이우균,김문일,이슬기,조현우,최원일,Cha, Sungeun,Lee, Woo-Kyun,Kim, Moonil,Lee, Sle-Gee,Jo, Hyun-Woo,Choi, Won-Il 한국산림과학회 2017 한국산림과학회지 Vol.106 No.3

본 연구는 참나무시들음병이 수도권에 피해가 집중되어 있는 점을 고려해 북한산, 청계산, 수리산의 시계열 항공사진을 사용하여 감독분류기법(supervised classification)으로 피해목을 분류하였으며, 피해지의 공간적인 특성을 분석하기 위해 피해목 위치의 지형적 특성을 통계처리 하여 고도와 경사와의 밀접한 상관관계를 확인하였다. 또한, Moran's I 통계분석을 이용한 북한산의 Moran's I 값은 2009, 2010, 2012년 각 0.25, 0.32, 0.24, 청계산은 2010, 2012, 2014년 각 0.26, 0.32, 0.22, 수리산은 2012, 2014년 각 0.42, 0.42의 값을 갖으며, 이는 피해목이 군집하여 분포함을 의미한다. 아울러, 피해목 군집의 이동성을 파악하기 위해 hotspot 분석을 실시하여 시계열적으로 hotspot이 이동하는 특성을 확인하였다. 참나무 시들음병의 전체 hotspot 면적(z-score>1.65) 중 고도 200~400 m, 경사 $20{\sim}40^{\circ}$에 분포하는 활엽수 및 혼효림에서의 발생비율은 약 80%로 나타났다. 이는 미래의 피해지역 hotspot은 상기의 지형 및 임상조건에서 발생 또는 이동될 수 있음을 시사한다. 본 연구의 결과는 참나무시들음병의 이동경로 예측의 기초자료로 이용될 수 있으며, 향후 병해충 피해의 사전 방제 및 시스템 구축에 사용될 수 있다. This study categorized the damaged trees by Supervised Classification using time-series-aerial photographs of Bukhan, Cheonggae and Suri mountains because oak wilt disease seemed to be concentrated in the metropolitan regions. In order to analyze the spatial characteristics of the damaged areas, the geographical characteristics such as elevation and slope were statistically analyzed to confirm their strong correlation. Based on the results from the statistical analysis of Moran's I, we have retrieved the following: (i) the value of Moran's I in Bukhan mountain is estimated to be 0.25, 0.32, and 0.24 in 2009, 2010 and 2012, respectively. (ii) the value of Moran's I in Cheonggye mountain estimated to be 0.26, 0.32 and 0.22 in 2010, 2012 and 2014, respectively and (iii) the value of Moran's I in Suri mountain estimated to be 0.42 and 0.42 in 2012 and 2014. respectively. These numbers suggest that the damaged trees are distributed in clusters. In addition, we conducted hotspot analysis to identify how the damaged tree clusters shift over time and we were able to verify that hotspots move in time series. According to our research outcome from the analysis of the entire hotspot areas (z-score>1.65), there were 80 percent probability of oak wilt disease occurring in the broadleaf or mixed-stand forests with elevation of 200~400 m and slope of 20~40 degrees. This result indicates that oak wilt disease hotspots can occur or shift into areas with the above geographical features or forest conditions. Therefore, this research outcome can be used as a basic resource when predicting the oak wilt disease spread-patterns, and it can also prevent disease and insect pest related harms to assist the policy makers to better implement the necessary solutions.

시공간검정통계량을 이용한 도시범죄의 핫스팟분석

정경석 ( Kyeong Seok Jeong ),문태헌 ( Tae Heon Moon ),정재희 ( Jae Hee Jeong ) 한국지리정보학회 2010 한국지리정보학회지 Vol.13 No.3

본 연구의 목적은 공간적 분포 특성만을 고려하고 있는 기존의 핫스팟분석에 대한 대안적인 방법으로서 공간상에서 나타나는 사건간의 인과관계를 시간영역으로까지 확장하여 동시적 분석이 가능한 시공간분석 방법을 제안하는 것이다. 분석방법으로는 먼저 지리정보시스템을 이용하여 지방중소도시인 M시의 범죄자료를 데이터화 하였고, Ripley K함수와 시공간검정통계량 분석을 통해 M시의 범죄분포 패턴을 지도화 하였다. 연구결과, 범죄위험도가 유의미하게 높은 지역들이 나타났으며, 이들 시공간적 범죄 집중지역들은 기존의 공간분포만을 고려한 범죄분포 패턴과는 다소 차이가 있음을 발견할 수 있었다. 본 연구결과는 시공간적인 범죄분포 특성에 맞는 맞춤형의 경찰 인력 배치와 배분, 그리고 치안행정 서비스 등의 조정을 위한 참고자료로서, 또한 시공간적인 집중을 보이는 이들 지역을 중심으로 물리적 환경 변화의 유도와 공간이용의 개선 효과를 통해 범죄율을 줄여나가는 범죄예방 활동 및 정책수립을 위한 기초자료로도 유용하게 활용될 수 있을 것으로 기대된다. The aim of this study is to investigate crime hotspot areas using the spatio-temporal cluster analysis which is possible to search simultaneously time range as well as space range as an alternative method of existing hotspot analysis only identifying crime occurrence distribution patterns in urban area. As for research method, first, crime data were collected from criminal registers provided by official police authority in M city, Gyeongnam and crime occurrence patterns were drafted on a map by using Geographic Information Systems(GIS). Second, by utilizing Ripley K-function and Space-Time Scan Statistics analysis, the spatio-temporal distribution of crime was examined. The results showed that the risk of crime was significantly clustered at relatively few places and the spatio-temporal clustered areas of crime were different from those predicted by existing spatial hotspot analysis such as kernel density analysis and k-means clustering analysis. Finally, it is expected that the results of this study can be not only utilized as a valuable reference data for establishing urban planning and crime prevention through environmental design(CPTED), but also made available for the allocation of police resources and the improvement of public security services.

셉테드 사업 및 범죄예방 시설물의 효과 연구

오하늘,손동필,강석진 대한건축학회 2023 대한건축학회논문집 Vol.39 No.8

This study aims to assess the effectiveness and scope of influence of crime prevention facilities implemented within the context of the CrimePrevention Through Environmental Design (CPTED) project area. The analysis, which focused on 13 types of 351 facilities across sevenresearch areas, studied crime patterns before and after the project. The research methodology encompassed various analyses, including crimerate changes in project areas and administrative dongs, alterations in crime types and hotspot distributions, facility density’s correlation withcrime, and crime analysis within a specific radius. This study innovatively employed a facility-centric buffer analysis coupled with hotspotanalysis, distinct from prior research. The average reduction rate for the five primary crime types was -61.0% within one year. Crimedecreased in three areas post-project, with a higher reduction rate compared to administrative dongs. The most effective areas in the CPTEDproject included theft or burglary, property crimes, and street crimes. Areas around crime prevention facilities exhibited diminished crimeclusters and concentrations or hotspots. Statistically significant crime reductions were noted on streets with three to four installed facilities. Lastly, through a facility-oriented buffer analysis at intervals of 10 meters, this study identified the longest impact ranges of certain facilities. CCTV information signs and village etiquette signs displayed an impact range of 60 meters and 50 meters, respectively. External pipeintrusion prevention facilities and safety village information signs proved effective in deterring intrusion-related crimes. Meanwhile,logo-jecters, CCTV information signs, reflectors, and electric pole maintenance with location numbers demonstrated effectiveness in curbingstreet crimes. Additionally, door reflection sheets and electric pole maintenance with location numbers were found effective in reducinginterpersonal crimes, and logo-jecters along with CCTV information signs were successful in addressing night-time crimes. In particular, doorreflection sheets and wall maintenance including painting, which despite doubts about their efficacy, are extensively utilized in CPTEDprojects, and they have indeed demonstrated certain crime prevention effects. 본 연구는 셉테드 사업지역에 설치된 범죄 예방 시설물의 효과 및 영향 범위를 규명하기 위해 진행되었다. 7개의 연구 대상지역에서 총 351개(13개 유형)의 시설물을 중심으로 사업 전후 발생한 범죄를 유형별로 분석한 결과는 다음과 같다. 첫째, 연구 방법론 관점에서 사업지역과 상위 행정동의 범죄증감률 분석, 사업 전후 변화된 범죄유형과 Hotspot 분석, 시설물 밀도와 범죄 분석, 일정한 반경별로 발생한 범죄 분석을 진행하였다. 특히, 범죄 발생 지점 중심의 Hotspot 분석과 함께 시설물 중심의 Buffer 분석을 함께 활용한 것은 기존 연구와 차별성을 가진다. 둘째, 사업 후 1년간 5대 범죄 감소율은 평균 –61.0%였고, 3개 지역에서 사업 전에 비해 범죄가 감소했다. 이들 지역의 범죄 감소율은 상위 행정동보다 더 높았다. 셉테드 사업을 통해 효과가 확인된 범죄는 절도 범죄, 대물 범죄, 노상 범죄였다. 셋째, 범죄 예방 시설물이 적용된 장소를 중심으로 범죄의 군집성과 밀집성(Hotspot)이 감소했고, 시설물이 3~4개 설치된 가로에서 범죄가 통계적으로 유의한 수준에서 감소하였다. 마지막으로 10m 간격으로 시설물 중심의 Buffer 분석을 진행한 결과 영향 범위가 가장 긴 것은 CCTV 안내표지판(60m)과 마을 에티켓 표지판(50m)이었다. 침입 범죄에는 외벽 배관 침입 방지 시설, 안전마을 안내표지판이 효과적이고, 노상 범죄에는 고보조명, CCTV 안내표지판, 반사경, 전봇대 정비 및 위치번호 등이 효과적이었다. 그리고, 대인 범죄에는 출입문 반사시트, 전봇대 정비 및 위치번호가, 야간 범죄에는 고보조명과 CCTV 안내표지판 등이 효과가 있었다. 특히 최근 셉테드 사업에서 많이 적용되는 출입문 반사시트와 효과에 논란이 있던 벽면 정비(도색 포함)의 경우 일정 부분 범죄 예방 효과가 있음도 확인되었다.

한국인 암 발병 데이터를 이용한 공간검색통계량과 에셜론분석의 핫스팟 지역 비교

신영서,김동재 한국데이터정보과학회 2018 한국데이터정보과학회지 Vol.29 No.4

The Spatial Scan Statistic proposed by Kulldorff (1997) is a method of finding hotspots by searching for this original area with the center of the circle around which the data is acquired. This method is often used to find hot spots. However, this method has disadvantages in detecting only the circular hotspot. Echelon Analysis is not limited to circular type and can detect hotspots in all areas. Therefore, the paper compared the Echelon analysis and Kulldorff’s method. we analyzed the actual data on 24 cancers outbreaks from 1999 to 2013. The Echelon analysis analyzed hotspot areas based on incidence rate and Age Standardization Rate. Kulldorff (1997)가 제안한 공간검색통계량은 데이터가 얻어진 영역의 중심을 원의 중심으로 해서 이 원상의 영역을 검색해서 핫스팟을 발견하는 방법으로 핫스팟지역을 찾기 위해 많이 쓰이고 있다. 하지만 이 방법은 원상의 핫스팟밖에 검출하지 못한다는 단점이 있다. 따라서 이를 보완하기 위해 본 논문에서는 원상에 국한되지 않고 모든 영역에서의 핫스팟 검출이 가능한 에셜론 분석법과 핫스팟지역을 비교해보았다. 본 논문에서는 1999∼2013년도의 24개 암 발병에 대한 실제 데이터를 가지고 분석하였다. 에셜론 분석에서는 발병 비율과 연령표준화발생률을 기준으로 나온 핫스팟지역 결과와 원형 검색 방법을 비교하였다.

핫스팟 분석을 통한 거창지역의 선구조선과 진앙의 상관관계 분석

조현우,지광훈,차성은,김은지,이우균,Jo, Hyun-Woo,Chi, Kwang-Hoon,Cha, Sungeun,Kim, Eunji,Lee, Woo-Kyun 대한원격탐사학회 2017 大韓遠隔探査學會誌 Vol.33 No.5

본 연구는 기상청에서 지진의 계기관측이 시작된 1978년부터 2016년까지, 규모 2.0~2.5사이의 소규모 지진이 6회 발생한 경상남도 거창군 일원지역을 대상으로 수치표고모델을 이용한 3차원의 LANDSAT 8호 위성영상과 음영기복도로부터 선구조선을 추출하여 선구조선과 진앙(지진발생위치)간의 상관관계를 분석하였다. 선구조선의 통계분석 방법으로는 직각격자에 의한 단절현상 문제점을 완화하고 선구조선의 공간적 분포를 정확히 표현해줄 수 있는 육각격자 모양과, 격자크기에 따라 변화하는 밀도 값이 안정되는 지점의 격자크기를 사용하여 핫스팟 분석을 수행하였다. 핫스팟 분석방법은 선구조선이 집단화되어 나타나는 지역을 통계적으로 파악할 수 있기 때문에, 선구조선의 각 통계요소별(빈도, 교차점, 길이)로 도출되는 Z score를 통해 선구조선 밀집지역을 확인하였다. 또한 연산된 선구조선의 밀도와 진앙간의 상관성을 분석하기 위해 진앙에서의 Z score를 표준정규분포 상에 나타내어 선구조선의 밀도가 통계적으로 의미 있는 수준인지를 확인하였다. 그 결과, 6개의 진앙에서 3개 종류의 통계요소로 기록된 총 18개의 Z score 중 약 83%에 달하는 15개 값이 1.65 이상으로 나타났다. 이는 표준정규분포 상에서 95% 이상의 높은 밀도 값을 의미하여, 진앙이 선구조선 고밀도지역에 위치함을 알 수 있었다. 특히 선구조선 빈도는 모든 진앙에서, 교차점은 하나의 진앙을 제외한 나머지 진앙에서 밀도 값이 표준정규분포 상 95% 이상을 나타내어, 선구조선의 빈도와 교차점 밀도가 진앙과 높은 상관성이 있음을 확인하였다. 선구조선의 밀도 분포를 정확하게 표현하고, 진앙과의 상관관계를 분석한 본 연구는 잠재적인 지진발생 위험 지역을 추출하기 위한 기초연구로써 의미가 있다. 그러나 상기와 같은 결과를 조금 더 명확하게 하기 위해서는 지진의 발생빈도가 많고 더 광역적인 지역을 대상으로 한 추가적 연구의 필요성이 있다고 사료된다. This study aims to understand the relationship between lineaments and epicenters in Geochang region, Gyungsangnam-do, South Korea. An instrumental observation of earthquakes has been started by Korea Meteorological Administration (KMA) since 1978 and there were 6 earthquakes with magnitude ranging 2 to 2.5 in Geochang region from 1978 to 2016. Lineaments were extracted from LANDSAT 8 satellite image and shaded relief map displayed in 3-dimension using Digital Elevation Model (DEM). Then, lineament density was statistically examined by hotspot analysis. Hexagonal grids were generated to perform the analysis because hexagonal pattern expresses lineaments with less discontinuity than square girds, and the size of the grid was selected to minimize a variance of lineament density. Since hotspot analysis measures the extent of clustering with Z score, Z scores computed with lineaments' frequency ($L_f$), length ($L_d$), and intersection ($L_t$) were used to find lineament clusters in the density map. Furthermore, the Z scores were extracted from the epicenters and examined to see the relevance of each density elements to epicenters. As a result, 15 among 18 densities,recorded as 3 elements in 6 epicenters, were higher than 1.65 which is 95% of the standard normal distribution. This indicates that epicenters coincide with high density area. Especially, $L_f$ and $L_t$ had a significant relationship with epicenter, being located in upper 95% of the standard normal distribution, except for one epicenter in $L_t$. This study can be used to identify potential seismic zones by improving the accuracy of expressing lineaments' spatial distribution and analyzing relationship between lineament density and epicenter. However, additional studies in wider study area with more epicenters are recommended to promote the results.

Detection of Hotspots on Multivariate Spatial Data

문승호 한국데이터정보과학회 2006 한국데이터정보과학회지 Vol.17 No.4

Statistical analyses for spatial data are important features for various types of fields. Spatial data are taken at specific locations or within specific regions and their relative positions are recorded. Lattice data are synoptic observation covering an entire spatial region, like cancer rates corresponding to each county in a state. Until now, the echelon analysis has been applied only to univariate spatial data. As a result, it is impossible to detect the hotspots on the multivariate spatial data In this paper, we expand the spatial data to time series structure. And then we analyze them on the time space and detect the hotspots. Echelon dendrogram has been made by piling up each multivariate spatial data to bring time spatial data. We perform the structural analysis of temporal spatial data.

하둡 및 Spark 기반 공간 통계 핫스팟 분석의 분산처리 방안 연구

김창수,이주섭,황규문,성효진 한국정보과학회 2018 정보과학회논문지 Vol.45 No.2

One of the spatial statistical analysis, hotspot analysis is one of easy method of see spatial patterns. It is based on the concept that "Adjacent ones are more relevant than those that are far away". However, in hotspot analysis is spatial adjacency must be considered, Therefore, distributed processing is not easy. In this paper, we proposed a distributed algorithm design for hotspot spatial analysis. Its performance was compared to standalone system and Hadoop, Spark based processing. As a result, it is compare to standalone system, Performance improvement rate of Hadoop at 625.89% and Spark at 870.14%. Furthermore, performance improvement rate is high at Spark processing than Hadoop at as more large data set. 공간통계 분석중 하나인 핫스팟 분석은 “인접해 있는 것은 멀리 있는 것 보다 더 연관성이 있다”는 법칙에 따라 공간속성이나 사건의 공간 패턴을 쉽게 파악할 수 있는 기법 중 하나 이지만, 공간의 인접성이 고려되어야 하므로 분산 처리하기 용이하지 않다. 본 논문에서는 핫스팟 분석의 분산처리 방안을 기술하고 성능을 하둡 및 인메모리 기반인 Spark으로 평가한 결과 단일 시스템 대비 하둡기반 처리는 625.89%, Spark기반 처리는 870.14%의 성능향상을 확인하였으며, 하둡 기반과 Spark기반의 비교에서는 대용량 데이터 셋을 처리 할수록 Spark기반의 성능향상율이 높아짐을 확인하였다.

기존/개선 수치 해석 기법을 이용한 계류 체인 링크의 면외 굽힘 강성

정준모(Joonmo Choung),이재빈(Jae-bin Lee),김영훈(Young Hun Kim) 한국해양공학회 2018 韓國海洋工學會誌 Vol.32 No.5

After an accident involving mooring link failures in an offloading buoy, verification of the fatigue safety in terms of the out-of-plane bending (OPB) and in-plane bending (IPB) moments has become a key engineering item in the design of various floating offshore units. The mooring links for an 8 MW floating offshore wind turbine were selected for this study. To identify the OPB stiffness (OPB moment versus interlink angle), a numerical simulation model, called the 3-link model, is usually composed of three successive chain links closest to the fairlead or chain hawse. This paper introduces two numerical simulation techniques for the 3-link analyses. The conventional and advanced approaches are both based on the prescribed rotation approach (PRA) and direct tension approach (DTA). Comparisons of the nominal stress distributions, OPB stiffnesses, hotspot stress curves, and stress concentration curves are presented. The multiple link analyses used to identify the tension angle versus interlink angle require the OPB stiffness data from the 3-link analyses. A convergence study was conducted to determine the minimum number of links for a multi-link analysis. It was proven that 10 links were sufficient for the multi-link analysis. The tension angle versus interlink angle relations are presented based on multi-link analyses with 10 links. It was found that the subsequent results varied significantly according to the 3-link analysis techniques.