Mapping Urban Structure Types Based on Remote Sensing Data—A Universal and Adaptable Framework for Spatial Analyses of Cities

Andreas Braun (), Gebhard Warth, Felix Bachofer, Michael Schultz and Volker Hochschild
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Andreas Braun: Department of Geosciences, Institute of Geography, University of Tübingen, 72070 Tübingen, Germany
Gebhard Warth: Department of Geosciences, Institute of Geography, University of Tübingen, 72070 Tübingen, Germany
Felix Bachofer: Remote Sensing Data Center (DFD), German Aerospace Center (DLR), 82234 Weßling, Germany
Michael Schultz: Department of Geosciences, Institute of Geography, University of Tübingen, 72070 Tübingen, Germany
Volker Hochschild: Department of Geosciences, Institute of Geography, University of Tübingen, 72070 Tübingen, Germany

Land, 2023, vol. 12, issue 10, 1-41

Abstract: In the face of growing 21st-century urban challenges, this study emphasizes the role of remote sensing data in objectively defining urban structure types (USTs) based on morphology. While numerous UST delineation approaches exist, few are universally applicable due to data constraints or impractical class schemes. This article attempts to tackle this challenge by summarizing important approaches dealing with the computation of USTs and to condense their contributions to the field of research within a single comprehensive framework. Hereby, this framework not only serves as a conjunctive reference for currently existing implementations, but is also independent regarding the input data, spatial scale, or targeted purpose of the mapping. It consists of four major steps: (1) the collection of suitable data sources to describe the building morphology as a key input, (2) the definition of a spatial mapping unit, (3) the parameterization of the mapping units, and (4) the final classification of the mapping units into urban structure types. We outline how these tasks can lead to a UST classification which fits the users’ needs based on their available input data. At the same time, the framework can serve as a protocol for future studies where USTs are mapped, or new approaches are presented. This article closes with an application example for three different cities to underline the flexibility and applicability of the proposed framework while maintaining maximized objectivity and comparability. We recommend this framework as a guideline for the use-specific mapping of USTs and hope to contribute to past and future research on this topic by fostering the implementation of this concept for the spatial analysis and a better understanding of complex urban environments.

Keywords: urban geography; remote sensing; earth observation; geospatial information; urban morphology; buildings; urban typology; spatial indicators; physical structures (search for similar items in EconPapers)
JEL-codes: Q15 Q2 Q24 Q28 Q5 R14 R52 (search for similar items in EconPapers)
Date: 2023
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