Prior research has indicated lower crime rates in areas with greater tree canopy cover predominantly in the Global North. There are few studies from the Global South, and more specifically in Latin America. Given the high prevalence of crime in Latin American cities, the need to address social and environmental inequalities using nature-based solutions is urgent. This study examines crime and tree canopy cover through a series of spatial analyses for São Paulo city, Brazil, while controlling for potential confounders. We tested six levels of data aggregation that were combined with three different crime types and two denominators of crime, to account for spurious findings from Modifiable Areal Unit Problems (MAUP). Of the 36 models, a majority of 27 models (75 %) indicate a negative relationship between crime and tree cover canopy, while 4 models (11 %) show a positive correlation, and 5 models (14 %) suggest no statistically significant relationship. Our best models allow us to infer that 10 % greater tree canopy cover is associated with a 1.20 % fewer property, personal and total reported crimes, with statistical significance at the p < 0.001 level. These findings support our hypothesis that there is a negative relationship between tree canopy cover and crime, with a stronger association observed for property crime than personal or total crime. The negative relationship persisted independently of the level of data aggregation, crime types, crime denominator and spatial models specifications (lag and SARMA), avoiding statistical bias of MAUP. The results follow the literature that have observed tree cover associated with lower crime rates, for different types of crime, while adding a new climatic and cultural context to the evidence base.

中文翻译：

---

巴西圣保罗市城市树冠覆盖物与犯罪之间的关系


先前的研究表明，在树冠覆盖率较高的地区，犯罪率较低，主要是在北半球。来自全球南方的研究很少，更具体地说是在拉丁美洲。鉴于拉丁美洲城市的犯罪率很高，迫切需要使用基于自然的解决方案来解决社会和环境不平等问题。本研究通过对巴西圣保罗市的一系列空间分析来检查犯罪和树冠覆盖率，同时控制潜在的混杂因素。我们测试了六个级别的数据聚合，这些数据聚合与三种不同的犯罪类型和两个犯罪分母相结合，以解释可修改区域单位问题 （MAUP） 的虚假发现。在这 36 个模型中，27 个模型中的大多数 （75%） 表明犯罪与树冠之间存在负相关关系，而 4 个模型 （11%） 显示正相关，5 个模型 （14%） 表明没有统计学上的显着关系。我们的最佳模型使我们能够推断，树冠覆盖率增加 10% 与财产、个人和报告犯罪总数减少 1.20% 相关，统计显着性为 p < 0.001 水平。这些发现支持了我们的假设，即树冠覆盖与犯罪之间存在负相关，观察到的财产犯罪比个人犯罪或总犯罪的关联更强。负相关独立于数据聚合水平、犯罪类型、犯罪分母和空间模型规范 （滞后和 SARMA） 而持续存在，避免了 MAUP 的统计偏差。结果遵循了观察到树木覆盖率与不同类型犯罪率相关的文献，同时为证据基础增加了新的气候和文化背景。