Análise espacial e mineração de dados de arborização urbana em Belo Horizonte

• Ano de defesa: 2020
• Autor(a) principal: Gabriel de Oliveira Campos Pacheco
• Tipo de documento: Dissertação
• Tipo de acesso: Acesso aberto
• Idioma: por
• Instituição de defesa: Universidade Federal de Minas Gerais; Brasil; ICX - DEPARTAMENTO DE CIÊNCIA DA COMPUTAÇÃO; Programa de Pós-Graduação em Ciência da Computação; UFMG
• Palavras-chave em Português: Arborização das cidades; Banco de dados geográficos; Mineração de dados; Computação – Teses; Arborização das cidades – Teses; Mineração de dados (Computação) – Teses; Banco de dados geográficos – Teses
• Link de acesso: http://hdl.handle.net/1843/45047

Tree coverage in urban spaces is a theme of great importance for current societies, given all the benefits that green spaces provide to the population, especially in large cities. Trees fulfill a very important role to ensure quality of urban living and urban environmental quality, and as a result trees are considered to be an element of urban infrastructure. In spite of the recognition of the importance of tree coverage, events in which a street tree falls or needs to be preventively cut down are quite frequent, damaging property and causing disturbances in the routine of the population. From a rich dataset on urban trees for the city of Belo Horizonte (MG, Brazil), this paper proposes contributions towards the identification and solution of problems related to tree coverage, with special emphasis on felled trees. Data mining techniques are employed in search of consistent patterns, expressed as association rules or temporal sequences, that are related to felling events. The analyses show a set of attributes that frequently appear next to trees that have suffered a fall process, and also indicate that about 12 % of a set of trees analyzed in the central region of Belo Horizonte have similar characteristics to the set of perished trees analyzed. The informational components that served as a basis for building a tool for collecting geographic information on urban afforestation were also identified, aiming to keep the tree database up to date with the collaboration of citizens