Submission Type
Poster
Abstract
Cites are novel ecosystems. Understanding the complex interactions between urban abiotic and biotic attributes is important for managing future urban expansion. Using urban scaling theory (UST) combined with global datasets raises the prospect of deriving predictive rules for scaling urban greenspace with city size. Aspects of the city, such as greenspace, are influenced by several social and ecological factors that scale with a city's size. Empirical data from European cities showed superlinear scaling, in which greenspace increased disproportionately with city size. However, the comprehension of global greenspace scaling still needs to be understood. A macroecological perspective using a scaling approach is needed to understand how urban environments function on broader spatial scales. We aim to develop predictive measures of how urban greenspace scales with various attributes by answering the following question: i) How does greenspace scale with city size and population globally? Our study is a first look at global greenspace scaling, providing statistical information about how greenspace is changing with city size globally. In this study, we use an open-access database called the Global Human Settlement Layer (GHSL) to analyze greenspace, population, and area in cities around the world. Using Rstudio and data from the GHSL, we examine the scaling properties of greenspace globally. Our results show greenspace superlinear scaling for 7 countries out of 19 from the GHSL dataset. We present this information for city planners to look beyond the scope of the Global North when thinking about greenspace in cities.
Included in
Environmental Design Commons, Other Ecology and Evolutionary Biology Commons, Urban, Community and Regional Planning Commons
Scaling Global Urban Greenspace
Cites are novel ecosystems. Understanding the complex interactions between urban abiotic and biotic attributes is important for managing future urban expansion. Using urban scaling theory (UST) combined with global datasets raises the prospect of deriving predictive rules for scaling urban greenspace with city size. Aspects of the city, such as greenspace, are influenced by several social and ecological factors that scale with a city's size. Empirical data from European cities showed superlinear scaling, in which greenspace increased disproportionately with city size. However, the comprehension of global greenspace scaling still needs to be understood. A macroecological perspective using a scaling approach is needed to understand how urban environments function on broader spatial scales. We aim to develop predictive measures of how urban greenspace scales with various attributes by answering the following question: i) How does greenspace scale with city size and population globally? Our study is a first look at global greenspace scaling, providing statistical information about how greenspace is changing with city size globally. In this study, we use an open-access database called the Global Human Settlement Layer (GHSL) to analyze greenspace, population, and area in cities around the world. Using Rstudio and data from the GHSL, we examine the scaling properties of greenspace globally. Our results show greenspace superlinear scaling for 7 countries out of 19 from the GHSL dataset. We present this information for city planners to look beyond the scope of the Global North when thinking about greenspace in cities.
Comments
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