遇见数据集

GapMaps Crime Risk Data (AGS) | USA| Latest Crime Risk Index & Projections | Trusted for 25 years

收藏
Datarade2024-06-22 收录
官方服务:

资源简介:

GapMaps provides Crime Risk data sourced from Applied Geographic Solutions (AGS) which has been used by thousands of companies for over 20 years, providing valuable comparative information on the spatial patterns of crime. This dataset includes crime risk indexes and projections on detailed crime types like murder and motor vehicle theft, and summary indexes of crimes against persons, crimes against property and overall crime risk. Crime Risk is available at the highly detailed census block level to capture the different risk levels of business and residential land use. Use cases: 1. Insurance underwriting and risk mitigation. 2. Evaluating the security measures needed to protect employees and customers at retail facilities. 3. The study of the effects of neighborhood crime on wellness and health care outcomes. Methodology: Crime is tracked for multiple years using both FBI aggregate crime reports and for many parts of the country at the individual incident level. A complex set of statistical models are used to estimate and forecast risk of each individual crime type by using land use data in conjunction with demographic and business characteristics. For more information visit www.appliedgeographic.com

GapMaps 提供的犯罪风险数据源自应用地理解决方案公司(Applied Geographic Solutions,AGS),该数据源已被数千家企业使用二十余年,可为犯罪活动的空间分布模式提供极具价值的对比分析信息。本数据集涵盖针对谋杀、机动车盗窃等细分犯罪类型的犯罪风险指数与预测数据,以及人身犯罪、财产犯罪与整体犯罪风险的综合指数。犯罪风险数据可精准至高度精细的人口普查街区层级,以捕捉商业与住宅用地的差异化风险等级。该数据集的应用场景包括:1. 保险核保与风险缓释;2. 评估零售场所保护员工与客户所需的安保措施;3. 研究社区犯罪对健康及医疗保健结局的影响。研究方法层面,团队通过多年犯罪数据追踪,既采用联邦调查局(FBI)的汇总犯罪报告,也针对美国国内多数地区获取单起犯罪事件的详细数据。随后借助一套复杂的统计模型,结合土地利用数据、人口统计特征与商业属性,对各类犯罪的风险进行估算与预测。如需了解更多信息,请访问 www.appliedgeographic.com

提供机构:
GapMaps
搜集汇总
数据集介绍
GapMaps Crime Risk Data (AGS) | USA| Latest Crime Risk Index & Projections | Trusted for 25 years 数据集图片
背景与挑战
背景概述
GapMaps犯罪风险数据集提供美国普查区块级别的详细犯罪风险指数和预测,涵盖人身犯罪、财产犯罪等类型,适用于保险、零售安全及健康研究。数据源自FBI报告和土地利用统计模型,具有25年行业应用历史。
以上内容由遇见数据集搜集并总结生成
二维码
社区交流群
二维码
科研交流群
商业服务