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Conference object . 2023
https://dx.doi.org/10.48494/re...
Conference object . 2023
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From Pixels to Planning: Large-scale Mapping of Urban Morphology and Population Distribution with the World Settlement Footprint 3D

Authors: Palacios Lopez, Daniela; Marconcini, Mattia; Zeidler, Julian; Esch, Thomas; Brzoska, Elisabeth;

From Pixels to Planning: Large-scale Mapping of Urban Morphology and Population Distribution with the World Settlement Footprint 3D

Abstract

Urban morphology and human population distribution are two interrelated aspects of our urbanization that play a critical role in shaping the sustainability, resilience and liveability of cities. In recent years, the advent of global datasets with 3D information derived from Earth Observation (EO) technologies has revolutionised our ability to study and analyse these two aspects of urbanisation, providing information that is essential for designing cities that can accommodate the needs of their residents while minimizing their environmental impact. One such dataset is the novel World Settlement Footprint 3D (WSF3D) produced by the German Aerospace Center (DLR). The WSF3D was the first global dataset providing detailed information of the fraction, area, average height and total volume of buildings, at unprecedented spatial resolution, coverage and consistency. Since its development, researchers from different organizations (e.g. WorldBank, United Nations, WorldPop) have employed the dataset as input data for large-scale studies in urban morphology and population distribution, with a level of detail that was previously impossible. In this paper we present a selection of WSF3D-driven applications with the objective of demonstrating how the new data can be used to support urban planning and management. First, the WSF3D has been employed to demonstrate how the four layers of the dataset can be used to determine a building's functional use, and how this information can be leveraged to improve large-scale models of population distribution at large-scale. Thereafter, the WSF3D has been used to determine the relationships among building height/volume, population density and income, which can provide insights into the efficient use of space (e.g. crowding vs layering) on the one hand, and shed light into infrastructure disparities and variations, on the other. With that being said, due to the global nature of the WSF3D dataset, the previous analyses were conducted from local to regional scales, which can also help identify opportunities for interventions that can be replicated across different locations. Overall, with the results of this research, the authors aim to provide planners and policy-makers with valuable insights into usability of the globally available WSF3D dataset. By demonstrating its potential as reliable and robust input data, this study seeks not only to empower evidence-based decision-making, but also to advocate for the widespread adoption of geospatial layers in the implementation of strategies towards sustainable development strategies of the built environment.

LET IT GROW, LET US PLAN, LET IT GROW. Nature-based Solutions for Sustainable Resilient Smart Green and Blue Cities. Proceedings of REAL CORP 2023, 28th International Conference on Urban Development and Regional Planning in the Information Society, 1013-1019

Countries
Germany, Austria
Keywords

GA Mathematical geography. Cartography, Large-scale Urban Morphology, Earth Observation Data, 910, Sustainability World Settlement Footprint 3D Earth Observation Data, Large-scale Population Distribution Large-scale Urban Morphology, Sustainability, HA Statistics, World Settlement Footprint 3D, Large-scale Population Distribution, GE Environmental Sciences

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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
Green