Lin Ge, Elmes Gregory, Walnoha Mike, Chen Xiannian
Department of Health Services Research & Administration, University of Nebraska Medical Center, Omaha, NE 98198-4350, USA.
J Forensic Sci. 2009 Jan;54(1):152-8. doi: 10.1111/j.1556-4029.2008.00913.x.
This article examines the potential of a spatial-temporal method for analysis of forensic shoeprint data. The large volume of shoeprint evidence recovered at crime scenes results in varied success in matching a print to a known shoe type and subsequently linking sets of matched prints to suspected offenders. Unlike DNA and fingerprint data, a major challenge is to reduce the uncertainty in linking sets of matched shoeprints to a suspected serial offender. Shoeprint data for 2004 were imported from the Greater London Metropolitan Area Bigfoot database into a geographic information system, and a spatial-temporal algorithm developed for this project. The results show that by using distance and time constraints interactively, the number of candidate shoeprints that can implicate one or few suspects can be substantially reduced. It concludes that the use of space-time and other ancillary information within a geographic information system can be quite helpful for forensic investigation.
本文探讨了一种时空方法在法医鞋印数据分析中的潜力。在犯罪现场采集到的大量鞋印证据，在将鞋印与已知鞋型进行匹配以及随后将匹配的鞋印集与犯罪嫌疑人相联系的过程中，成功率各不相同。与DNA和指纹数据不同，一个主要挑战是减少将匹配的鞋印集与疑似连环犯罪者相联系时的不确定性。2004年的鞋印数据从大伦敦都会区大脚数据库导入到地理信息系统中，并为该项目开发了一种时空算法。结果表明，通过交互使用距离和时间约束，可以大幅减少可能牵涉一名或少数嫌疑人的候选鞋印数量。得出的结论是，在地理信息系统中使用时空及其他辅助信息对法医调查可能会很有帮助。
