事件模式分析:峰值检测和模式比较

IF 3.3 3区 地球科学 Q1 GEOGRAPHY Geographical Analysis Pub Date : 2023-07-18 DOI:10.1111/gean.12372
Yukio Sadahiro
{"title":"事件模式分析:峰值检测和模式比较","authors":"Yukio Sadahiro","doi":"10.1111/gean.12372","DOIUrl":null,"url":null,"abstract":"<p>This article proposes two exploratory methods for analyzing event patterns. Events in this article refer to zero-dimensional objects in the spatiotemporal dimension, such as crimes, earthquakes, and traffic accidents. One method detects the peaks in event patterns, evaluates the degree of event concentration at the peaks, and visualizes its spatial variation. Another method evaluates the similarity between different event patterns and visualizes its spatial variation. The methods help us understand events' properties, consider their underlying mechanisms, and permit us to prevent events if they represent undesirable phenomena such as crimes and traffic accidents. The proposed methods are applied to analyze the population distribution in the central area of Tokyo in May 2019. The application revealed the spatial variation of population peaks in this area and the differences in population patterns between different types of days.</p>","PeriodicalId":12533,"journal":{"name":"Geographical Analysis","volume":"56 1","pages":"143-162"},"PeriodicalIF":3.3000,"publicationDate":"2023-07-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/gean.12372","citationCount":"0","resultStr":"{\"title\":\"Event Pattern Analysis: Peak Detection and Pattern Comparison\",\"authors\":\"Yukio Sadahiro\",\"doi\":\"10.1111/gean.12372\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p>This article proposes two exploratory methods for analyzing event patterns. Events in this article refer to zero-dimensional objects in the spatiotemporal dimension, such as crimes, earthquakes, and traffic accidents. One method detects the peaks in event patterns, evaluates the degree of event concentration at the peaks, and visualizes its spatial variation. Another method evaluates the similarity between different event patterns and visualizes its spatial variation. The methods help us understand events' properties, consider their underlying mechanisms, and permit us to prevent events if they represent undesirable phenomena such as crimes and traffic accidents. The proposed methods are applied to analyze the population distribution in the central area of Tokyo in May 2019. The application revealed the spatial variation of population peaks in this area and the differences in population patterns between different types of days.</p>\",\"PeriodicalId\":12533,\"journal\":{\"name\":\"Geographical Analysis\",\"volume\":\"56 1\",\"pages\":\"143-162\"},\"PeriodicalIF\":3.3000,\"publicationDate\":\"2023-07-18\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://onlinelibrary.wiley.com/doi/epdf/10.1111/gean.12372\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Geographical Analysis\",\"FirstCategoryId\":\"89\",\"ListUrlMain\":\"https://onlinelibrary.wiley.com/doi/10.1111/gean.12372\",\"RegionNum\":3,\"RegionCategory\":\"地球科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"GEOGRAPHY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Geographical Analysis","FirstCategoryId":"89","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1111/gean.12372","RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"GEOGRAPHY","Score":null,"Total":0}
引用次数: 0

摘要

本文提出了两种分析事件模式的探索性方法。本文中的事件是指时空维度上的零维对象,如犯罪、地震和交通事故。其中一种方法可检测事件模式中的峰值,评估峰值处的事件集中程度,并将其空间变化可视化。另一种方法是评估不同事件模式之间的相似性,并将其空间变化可视化。这些方法可以帮助我们了解事件的特性,考虑其潜在机制,并在事件代表犯罪和交通事故等不良现象时进行预防。所提出的方法被应用于分析 2019 年 5 月东京中心地区的人口分布。该应用揭示了该地区人口高峰的空间变化以及不同类型日子的人口模式差异。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

摘要图片

查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
Event Pattern Analysis: Peak Detection and Pattern Comparison

This article proposes two exploratory methods for analyzing event patterns. Events in this article refer to zero-dimensional objects in the spatiotemporal dimension, such as crimes, earthquakes, and traffic accidents. One method detects the peaks in event patterns, evaluates the degree of event concentration at the peaks, and visualizes its spatial variation. Another method evaluates the similarity between different event patterns and visualizes its spatial variation. The methods help us understand events' properties, consider their underlying mechanisms, and permit us to prevent events if they represent undesirable phenomena such as crimes and traffic accidents. The proposed methods are applied to analyze the population distribution in the central area of Tokyo in May 2019. The application revealed the spatial variation of population peaks in this area and the differences in population patterns between different types of days.

求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
CiteScore
8.70
自引率
5.60%
发文量
40
期刊介绍: First in its specialty area and one of the most frequently cited publications in geography, Geographical Analysis has, since 1969, presented significant advances in geographical theory, model building, and quantitative methods to geographers and scholars in a wide spectrum of related fields. Traditionally, mathematical and nonmathematical articulations of geographical theory, and statements and discussions of the analytic paradigm are published in the journal. Spatial data analyses and spatial econometrics and statistics are strongly represented.
期刊最新文献
Issue Information Impacts of improved transport on regional market access Testing Hypotheses When You Have More Than a Few* Beyond Auto‐Models: Self‐Correlated Sui‐Model Respecifications Issue Information
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1