Abstract: By considering the influencing factors such as time and distance, crime rate, population, police, geography and environment, victims’ occupation, etc, the authors use mathematical modeling to establish the evaluation function of crime probability in the research area, calculate the probability of crime, and then combine it with GIS-related technology to get the most likely crime areas, namely, the geographic portrait of crime. The authors conduct method validation and analysis through examples. This new probabilistic crime model could provide geospatial data for detecting serial criminal cases and narrow down the scope of police surveillance. This new investigative technique with high precision is suitable for various geographic regions and helpful for detecting serial criminal cases.

Key words: criminal probability model, serials crime, GIS, geography of crime, geographical profile

摘要： 考虑时间距离因素、犯罪率因素、人口数量因素、警察因素、地理环境因素和被害人职业因素等影响因子, 采用数学建模方法, 建立研究区域的犯罪概率评价函数。采用这种评价函数计算研究区域的犯罪概率, 然后融合GIS相关技术, 得到犯罪分子下一步最有可能犯罪的预测区域, 即犯罪的地理画像, 并通过实例对方法进行验证和分析。这种新的犯罪概率模型的应用, 可以为连环犯罪的侦破提供空间地理数据, 缩小警方布控范围, 是一种精确性较高、适宜各种地理区域的新型侦查手段, 能够对连环犯罪案件的侦破起到很大的作用。

关键词: 犯罪概率模型, 连环犯罪, GIS, 犯罪地理学, 地理画像