UN Sustainable Development Goals (e.g., Goal 16) have highlighted the importance of using policy tools (e.g., through urban planning) to prevent crimes. Existing evidence of the association between green space and crime is mixed. Some studies indicate that the inconsistencies may be due to the variance in types of vegetation and the rates of crime reported across regions and countries. This study aims to assess the conditional association between green space and crime by considering the influence of vegetation type (e.g., grassland, woodland), crime type (e.g., violence, theft) and rates of crime reported in Northern Ireland (NI), United Kingdom. Crime data were obtained from the Police Service NI and green space was determined by Land Cover Map at the Super Output Area (SOA) level provided by the UK Centre for Ecology & Hydrology. Spatial quantile regressions were used to model the adjusted association between green space and crime across areas with different rates of crime. The results showed that more grassland may be associated with lower crime rates, but only in areas with relatively low crime rates. More woodland may also be associated with lower crime rates, but only for areas with relatively high crime rates. Also, we found that associations between green space and crime varied by type of crime. In summary, policymakers and planners should consider green space as a potential crime reduction intervention, factoring in the heterogeneous effects of vegetation type, crime type and crime rate.

中文翻译：

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使用空间分位数回归模型重新思考绿色空间与犯罪之间的关联：植被类型、犯罪类型和犯罪率重要吗？


联合国可持续发展目标（例如，目标 16）强调了使用政策工具（例如，通过城市规划）来预防犯罪的重要性。关于绿色空间与犯罪之间关联的现有证据喜忧参半。一些研究表明，不一致可能是由于不同地区和国家报告的植被类型和犯罪率的差异。本研究旨在通过考虑植被类型（例如草原、林地）、犯罪类型（例如暴力、盗窃）和英国北爱尔兰 （NI） 报告的犯罪率的影响来评估绿色空间与犯罪之间的条件关联。犯罪数据是从北爱尔兰警察局获取的，而绿地是由英国生态与水文中心提供的超级输出区域（SOA）级别的土地覆盖地图确定的。空间分位数回归用于对不同犯罪率区域的绿色空间与犯罪之间的调整关联进行建模。结果表明，更多的草原可能与较低的犯罪率相关，但仅限于犯罪率相对较低的地区。更多的林地也可能与较低的犯罪率相关，但仅限于犯罪率相对较高的地区。此外，我们发现绿色空间与犯罪之间的关联因犯罪类型而异。总之，政策制定者和规划者应考虑将绿色空间作为一种潜在的减少犯罪干预措施，同时考虑植被类型、犯罪类型和犯罪率的异质性影响。