Arborização viária e criminalidade: um estudo na cidade de Lavras/MG

Abstract

Brazil is a country with high population density, as well as high urbanization associated with the removal of vegetation and soil sealing. It is known that urban vegetation present in cities provides ecosystem services that contribute to the mitigation of environmental problems, providing a better quality of life for people. Some researchers have found results showing that increasing trees in cities can impact crime reduction. However, such research was carried out in countries of the global north, with social, ecological and political characteristics different from the Latin American scenario. With the objective of understanding the relationship between street tree and crime, in the light of the Brazilian reality in a medium-sized city, a research organized in two articles was developed. The first article used the integrative systematic literature review method to understand the role of Urban Forestry in promoting safety. We found 198 published works, 66% of which were from the last five years, and the main language was English. The affiliations of the most prominent authors and research funding agencies are from the United States of America, which is also the country with the highest number of publications, 46.9%. The most cited article showed that tall trees and low vegetation contribute to the reduction of crime. The main research fronts, denote interest in understanding the social aspects of Urban Forestry. The second article is empirical, and used a database of roberry of the Military Police from the years 2014 to 2018, the location of the trees surveyed in the Municipality of Lavras inventory and some socioeconomic indices provided by the Brazilian Institute of Geography and Statistics. The objective was to analyze the existence of a relationship between street tree and roberry crime in Lavras/Minas Gerais. The following tools were used: Kernel estimation, which is an alternative to geographic analysis of the behavior of spatial patterns and Poisson and negative binomial regression models (Generalized Linear Models). The results showed that in areas with high crime rates, there was low street tree, as well as the predictive model obtained an inverse association with robberies. The results of this study integrate the literature already published, adding analysis with data from a medium-sized city, something little explored. In addition to contributing to the reflection of the development of public policies that benefit the inclusion and integration of street trees in the urban planning of cities. The limitations of the research are recognized by its authors, and can be addressed in future studies.