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作者

Bruna Lara Arantes;Nicole Rennó Castro;Leandro Gilio;Jefferson Lordello Polizel;Demóstenes Ferreira da Silva Filho

来源

CITIES,Vol.111,Issue1,Article 103099

语言

英文

关键字

Income;Exploratory Spatial Data Analysis;Environmental justice;Urban forest

作者单位

Graduate Program Forest Resources, Luiz de Queiroz College of Agriculture, São Paulo University (ESALQ-USP), Pádua Dias, 11, Agronomia Piracicaba/SP, Brazil;Economic Sciences Department, Federal University of São João Del-Rei (UFSJ);Economic Researcher at Insper Global Agribusiness Center, Brazil;Forests Sciences Department, Luiz de Queiroz College of Agriculture of São Paulo University (ESALQ-USP), Brazil;Graduate Program Forest Resources, Luiz de Queiroz College of Agriculture, São Paulo University (ESALQ-USP), Pádua Dias, 11, Agronomia Piracicaba/SP, Brazil;Economic Sciences Department, Federal University of São João Del-Rei (UFSJ);Economic Researcher at Insper Global Agribusiness Center, Brazil;Forests Sciences Department, Luiz de Queiroz College of Agriculture of São Paulo University (ESALQ-USP), Brazil

摘要

The integration of natural and social sciences in multidisciplinary research may be the key to improving public policies for urban greening. Analyses on the distribution of urban forests in relation to income are scarce for cities in developing countries, which is a crucial problem in view of the problematic and unplanned urbanization process common in these cities. Our study aims to fill this gap, focusing on the mega-city of Sao Paulo. We analyzed the spatial correlation between tree cover and per capita income and the interaction of these variables with other land covers (lawn, buildings and shadows). The city's land cover was estimated from a digital infrared orthoimage and Exploratory Spatial Data Analysis techniques. We found that Sao Paulo presents two patterns for the spatial correlation between tree cover and income, which may represent other mega-cities with similar characteristics. When considering the entire area of the city, the spatial correlation is negative, result contrary to most of the literature and strongly influenced by the presence of reminiscent forests in the peripheral regions, where lower-income population lives. When considering only more urbanized areas, the spatial correlation is positive, indicating an uneven distribution of urban forest that favors the wealthier neighborhoods.