Remote sensing-supported generation of surface descriptors for a highly detailed urban climate model

Publikation: Beitrag in Buch/Bericht/Sammelwerk/KonferenzbandAufsatz in KonferenzbandForschungPeer-Review

Autoren

  • Wieke Heldens
  • Björn Maronga
  • Julian Zeidler
  • Farah Kanani-Sühring
  • Wiebke Hanke
  • Thomas Esch

Externe Organisationen

  • Deutsches Zentrum für Luft- und Raumfahrt e.V. (DLR) Standort Oberpfaffenhofen
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Details

OriginalspracheEnglisch
Titel des Sammelwerks2019 Joint Urban Remote Sensing Event (JURSE)
UntertitelProceedings
Herausgeber (Verlag)Institute of Electrical and Electronics Engineers Inc.
Seiten1-4
Seitenumfang4
ISBN (elektronisch)978-1-7281-0009-8
ISBN (Print)978-1-7281-0010-4
PublikationsstatusVeröffentlicht - Mai 2019
Veranstaltung2019 Joint Urban Remote Sensing Event, JURSE 2019 - Vannes, Frankreich
Dauer: 22 Mai 201924 Mai 2019

Publikationsreihe

NameJoint Urban Remote Sensing Event
ISSN (Print)2334-0932
ISSN (elektronisch)2642-9535

Abstract

Urban climate models become increasingly important for academic research and sustainable urban planning. The turbulence-resolving micro climate model PALM-4U is currently being developed to better meet the high demands of urban planning related to the spatial detail of modeling scenarios. The study presented here, shows which data sources and approaches can be used to supply models like PALM-4U with the required highly detailed urban surface layers. It is thereby jointly made use of remote sensing, municipal and open data to generate surface layers at 1m spatial resolution. The surface layers describe buildings, vegetation, terrain, water, pavement, streets and bridges. The heterogeneous data sources and their differing quality and standards require the utilization of various remote sensing and GIS techniques. In this study it is demonstrated that the surface layers can successfully be generated for urban climate simulations. To ensure easy transferability, it should be considered to use thematically and/or coarser but more standardized data, after a sensitivity analysis of PALM-4U.

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Remote sensing-supported generation of surface descriptors for a highly detailed urban climate model. / Heldens, Wieke; Maronga, Björn; Zeidler, Julian et al.
2019 Joint Urban Remote Sensing Event (JURSE) : Proceedings. Institute of Electrical and Electronics Engineers Inc., 2019. S. 1-4 8809010 (Joint Urban Remote Sensing Event).

Publikation: Beitrag in Buch/Bericht/Sammelwerk/KonferenzbandAufsatz in KonferenzbandForschungPeer-Review

Heldens, W, Maronga, B, Zeidler, J, Kanani-Sühring, F, Hanke, W & Esch, T 2019, Remote sensing-supported generation of surface descriptors for a highly detailed urban climate model. in 2019 Joint Urban Remote Sensing Event (JURSE) : Proceedings., 8809010, Joint Urban Remote Sensing Event, Institute of Electrical and Electronics Engineers Inc., S. 1-4, 2019 Joint Urban Remote Sensing Event, JURSE 2019, Vannes, Frankreich, 22 Mai 2019. https://doi.org/10.1109/JURSE.2019.8809010
Heldens, W., Maronga, B., Zeidler, J., Kanani-Sühring, F., Hanke, W., & Esch, T. (2019). Remote sensing-supported generation of surface descriptors for a highly detailed urban climate model. In 2019 Joint Urban Remote Sensing Event (JURSE) : Proceedings (S. 1-4). Artikel 8809010 (Joint Urban Remote Sensing Event). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/JURSE.2019.8809010
Heldens W, Maronga B, Zeidler J, Kanani-Sühring F, Hanke W, Esch T. Remote sensing-supported generation of surface descriptors for a highly detailed urban climate model. in 2019 Joint Urban Remote Sensing Event (JURSE) : Proceedings. Institute of Electrical and Electronics Engineers Inc. 2019. S. 1-4. 8809010. (Joint Urban Remote Sensing Event). doi: 10.1109/JURSE.2019.8809010
Heldens, Wieke ; Maronga, Björn ; Zeidler, Julian et al. / Remote sensing-supported generation of surface descriptors for a highly detailed urban climate model. 2019 Joint Urban Remote Sensing Event (JURSE) : Proceedings. Institute of Electrical and Electronics Engineers Inc., 2019. S. 1-4 (Joint Urban Remote Sensing Event).
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