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Structure of Urban Landscape and Surface Temperature: a Case Study in Philadelphia, PA
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  • Erik Mitz,
  • Peleg Kremer,
  • Neele Larondelle,
  • Justin Stewart
Erik Mitz
Department of Political Science, Villanova University, Villanova, Pennsylvania, United States of America; E-mail: [email protected], Department of Political Science, Villanova University, Villanova, Pennsylvania, United States of America; E-mail: [email protected]
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Peleg Kremer
Department of Geography and the Environment, Villanova University, Villanova, Pennsylvania, United States of America, Department of Geography and the Environment, Villanova University, Villanova, Pennsylvania, United States of America
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Neele Larondelle
Potsdam-Institut für Klimafolgenforschung, Potsdam-Institut für Klimafolgenforschung
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Justin Stewart
Department of Geography and the Environment, Villanova University, Villanova, Pennsylvania, United States of America, Department of Geography and the Environment, Villanova University, Villanova, Pennsylvania, United States of America

Corresponding Author:[email protected]

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Abstract

Discerning the relationship between urban structure and function is crucial for sustainable city planning and requires examination of how components in urban systems are organized in three-dimensional space. The Structure of Urban Landscape (STURLA) classification accounts for the compositional complexity of urban landcover structures including the built and natural environment. Building on previous research, we develop a STURLA classification for Philadelphia, PA and study the relationship between urban 1 structure and land surface temperature. Finally, we evaluate the results in Philadelphia as compared to previous case studies in Berlin, Germany and New York City, USA. In Philadelphia, STURLA classes hosted ST that were unique and significantly different as compared to all other classes. We find a similar distribution of STURLA class composition across the three cities, though NYC and Berlin showed strong correlation with each other but not with Philadelphia. Our research highlights the use of STURLA classification to capture a physical property of the urban landscape.