• ETRI Journal
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• 제43권2호
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• pp.272-287
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• 2021

This article presents a multi-dimensional spatial pattern analysis of crime events in San Francisco. Our analysis includes the impact of spatial resolution on hotspot identification, temporal effects in crime spatial patterns, and relationships between various crime categories. In this work, crime prediction is viewed as a classification problem. When predictions for a particular category are made, a binary classification-based model is framed, and when all categories are considered for analysis, a multiclass model is formulated. The proposed crime-prediction model (HotBlock) utilizes spatiotemporal analysis for predicting crime in a fixed spatial region over a period of time. It is robust under variation of model parameters. HotBlock's results are compared with baseline real-world crime datasets. It is found that the proposed model outperforms the standard DeepCrime model in most cases.

• 한국CDE학회논문집
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• 제17권1호
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• pp.7-16
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• 2012

One distinguishing feature of BIM(Building Information Modeling) is the objectification of spatial elements independently, which makes it easy to represent spatial network. From this perspective, this study aimed to develop the spatial network analysis tool based on open BIM technologies. From the literature review, an object model of spatial network with nodes and links and a process model from construction to visualization were established. A prototype system implementing the proposed models, named SNAT(Spatial Network Analysis Tool), was developed in Java platform with using its open source packages. SNAT can create a spatial network from IFC-BIM model, calculate the indices of spatial network analysis, and visualize it with the representing types(map, graph, matrix and table).

• 한국디지털건축인테리어학회논문집
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• 제12권2호
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• pp.61-66
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• 2012

In space syntax, the mathmatical process to get a integration could be restrictive in understanding spatial configuration since it is based on only one behavior model. In this study, As another approach to spatial configuration analysis based on behavioral model, there is the simulation tracking analysis model that simulates the movements of human in the space and analyze them. In this study, the relationship between integration and behavioral model will be defined and the similarities and the differences between space syntax and the simulation tracking analysis model will be demonstrated. Furthermore, these two analysis models will be understood as a variety of tools that can analyze an object in multiple viewpoints.

• 한국측량학회지
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• 제32권3호
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• pp.225-231
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• 2014

When a spatial regression model that uses kernel density values as a dependent variable is applied to retail business data, a unique model cannot be selected because kernel density values change following kernel bandwidths. To overcome this problem, this paper suggests how to use the point pattern analysis, especially the L-index to select a unique spatial regression model. In this study, kernel density values of retail business are computed by the bandwidth, the distance of the maximum L-index and used as the dependent variable of spatial regression model. To test this procedure, we apply it to meeting room business data in Seoul, Korea. As a result, a spatial error model (SEM) is selected between two popular spatial regression models, a spatial lag model and a spatial error model. Also, a unique SEM based on the real distribution of retail business is selected. We confirm that there is a trade-off between the goodness of fit of the SEM and the real distribution of meeting room business over the bandwidth of maximum L-index.

• 한국정보과학회논문지:컴퓨팅의 실제 및 레터
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• 제6권1호
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• pp.1-10
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• 2000

Spatial analysis in GIS provides an important way that helps the end-users decision-making. For such a reason, query model for analysis should be able to support the users view conceptually in constructing query statements. The traditional approaches in design of query model used to extend the functionality of model that basically designed for manipulation of attribute-operations by appending operators for spatial operations to the query statements of model. However, by the reason of spatial operation's characteristics that are different from those of attribute operations In nature, the structures of query statements in previous approaches are unnatural, inconsistent, and therefore those query models in previous approaches are not able to support the users view in retrieving analysis. In this paper, we proposed the methodology for constructing of user query and internal processing this query based on object-oriented paradigm, in the view of spatial operations by using the basic concept that spatial query is a methodology for spatial analysis. In addition, we presented a strong possibility of designing spatial query model that might actively have interaction with its user by implementing CIW(Class-Information Window) query interface corresponded with the methodology proposed in this paper.

• Journal of the Korean Data and Information Science Society
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• 제17권4호
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• pp.1271-1278
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• 2006

Recently, a profit analysis in hospital management is considered as an important marketing concept. When spatial variability is presented, we must analyze the hospital data with spatial statistical methods. In this study, we present a regression model using spatial covariance for adjustment. And we compare the nonspatial model with spatial model.

• 대한산업공학회지
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• 제41권1호
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• pp.64-73
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• 2015

Recent emergence of spatial big data attracts the attention of various research groups. This paper analyzes the research trend on spatial big data by text mining the related Scopus DB. We apply topic model and network analysis to the extracted abstracts of articles related to spatial big data. It was observed that optics, astronomy, and computer science are the major areas of spatial big data analysis. The major topics discovered from the articles are related to mobile/cloud/smart service of spatial big data in urban setting. Trends of discovered topics are provided over periods along with the results of topic network. We expect that uncovered areas of spatial big data research can be further explored.

• 한국공간정보시스템학회 논문지
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• 제3권1호
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• pp.49-62
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• 2001

공간정보 및 속성정보를 저장 및 관리하여 서비스하는 지리정보시스템은 최근 네트워크 및 분산환경의 기술개발과 더불어 급격히 변화하고 있다. 이러한 지리정보시스템은 컴포넌트 기반 기술로 자리매김하고 있으며 OGC(OpenGIS Consortium)에서는 지리정보시스템의 설계 및 구현에 대한 다양한 사양과 토픽을 제시하고 있다. OGC의 사양을 충족하는 개방형 지리정보시스템은 다양한 컴포넌트들로 구성되어 있으며, 이러한 컴포넌트 기반의 시스템에 추가적인 요소로써 공간분석 컴포넌트를 구현하였다. 지리정보시스템에서 공간분석기능은 중요한 요소 중 하나이며 전체 시스템의 성능적, 기능적 평가 기준이 되기도 한다. OGC에서 제시하는 기본 공간데이터 모델인 Geometry 모델은 기본 기하공간객체를 관리하는 모델이며, 다양한 분석 컴포넌트들의 연동을 위하여 확장이 필요하다. 즉 기본 기하공간데이터 모델뿐 아니라, 기본 위상공간데이터 모델을 제공해야 하며 또한 이러한 기본 위상공간모델을 다양한 분석기능에 맞게끔 확장이 필요하다. 본 논문에서는 개방형 GIS컴포넌트의 전체 아키텍쳐와 이와 연동되는 분석 컴포넌트로써 네트?p 분석, TIN 분석 컴포넌트에 대하여 살펴보고 또한 기본 기하 데이터 모델인 OGC Simple Feature Geometry의 확장과 연등방법에 대하여 논의해 볼 것이다.

• 대한건축학회논문집:계획계
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• 제34권11호
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• pp.23-32
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• 2018

The purpose of this study is to establish a walking energy weighted ERAM model that can predict the pedestrian volume by the connection structure of the vertical and horizontal spaces within a three-dimensional building. The process of building a walking-energy weighted ERAM model is as follows. First, the spatial graph was used to reproduce three-dimensional buildings with vertical and horizontal spatial connection structures. Second, the walking energy was measured on the spatial graph. Third, ERAM model was used to apply weights with spatial connection properties in random walking environment, and the walking energy weights were applied to the ERAM model to calculate the walk energy weighted ERAM values and visualize the distribution of pedestrian flow. To verify the validation of the established model, existing and proposed spatial analysis models were compared to real space. The results of this study are as follows : The model proposed in this study showed as much elaborated estimation of pedestrian traffic flow in real space as in traditional spatial analysis models, and also it showed much higher level of forecasting pedestrian traffic flow in real space than existing models.

• 조명전기설비학회논문지
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• 제29권7호
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• pp.80-86
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• 2015

As wind farm outputs depend on natural wind resources that vary over space and time, spatial correlation analysis is needed to estimate power outputs of wind generation resources. As a result, geographic information such as latitude and longitude plays a key role to estimate power outputs of spatially distributed wind farms. In this paper, we introduce spatial correlation analysis to estimate the power outputs produced by wind farms that are geographically distributed. We present spatial correlation analysis of empirical power output data for the JEJU Island and ERCOT ISO (Texas) wind farms and propose the Correlation Decay Distance (CoDecDist) model based on geographic correlation analysis to enhance the estimation of wind power outputs.