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A new approach to vegetation growth modelling in urban areas using geographical Information systems

Grant number: 17/24038-8
Support type:Scholarships in Brazil - Master
Effective date (Start): March 01, 2018
Effective date (End): August 23, 2019
Field of knowledge:Agronomical Sciences - Agronomy - Agricultural Meteorology
Cooperation agreement: Coordination of Improvement of Higher Education Personnel (CAPES)
Principal researcher:Vandoir Bourscheidt
Grantee:Elton Vicente Escobar Silva
Home Institution: Centro de Ciências Biológicas e da Saúde (CCBS). Universidade Federal de São Carlos (UFSCAR). São Carlos , SP, Brazil
Associated scholarship(s):18/12428-9 - Development of a vegetation growth model adapted to urban areas, BE.EP.MS

Abstract

The way urban settlements and human activities are organized in geographic space, along with high rates of population growth, are important concerns in modern society, especially considering the social and environmental impacts. In this context are natural urban ecosystems (with green areas as their main element), which in addition to contributing to public health also improve life quality of its citizens. One way to ensure an adequate relationship between natural urban ecosystems and the population is to optimize the conservation process of these areas, which implies on monitoring vegetation growth and green areas management. The study of vegetation growth and the variables involved in this process have motivated research in the fields of agriculture, forestry and environmental sciences, with the creation of different models. On the other hand, there are no similar models analyzing considering urban areas, where vegetation growth is influenced by different situations and goes through a regular cutting process. In this sense, this project aims to create a vegetation growth model integrated with GIS and adapted to the urban areas, considering the vegetation development in different conditions, which may provide subsidies to optimize public green areas management. In this way, it might contribute to the optimization of the cleaning processes, reducing costs and impacts to the ecosystem, and to improving the life quality of the population. (AU)

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