eprintid: 10193458
rev_number: 7
eprint_status: archive
userid: 699
dir: disk0/10/19/34/58
datestamp: 2024-06-14 09:38:26
lastmod: 2024-06-14 09:38:26
status_changed: 2024-06-14 09:38:26
type: article
metadata_visibility: show
sword_depositor: 699
creators_name: Li, Ruidong
creators_name: Sun, Ting
creators_name: Ghaffarian, Saman
creators_name: Tsamados, Michel
creators_name: Ni, Guangheng
title: GLAMOUR: GLobAl building MOrphology dataset for URban hydroclimate modelling
ispublished: pub
divisions: UCL
divisions: B04
divisions: C06
divisions: ZZ3
keywords: Atmospheric science,
Hydrology
note: Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.
abstract: Understanding building morphology is crucial for accurately simulating interactions between urban structures and hydroclimate dynamics. Despite significant efforts to generate detailed global building morphology datasets, there is a lack of practical solutions using publicly accessible resources. In this work, we present GLAMOUR, a dataset derived from open-source Sentinel imagery that captures the average building height and footprint at a resolution of 0.0009° across urbanized areas worldwide. Validated in 18 cities, GLAMOUR exhibits superior accuracy with median root mean square errors of 7.5 m and 0.14 for building height and footprint estimations, indicating better overall performance against existing published datasets. The GLAMOUR dataset provides essential morphological information of 3D building structures and can be integrated with other datasets and tools for a wide range of applications including 3D building model generation and urban morphometric parameter derivation. These extended applications enable refined hydroclimate simulation and hazard assessment on a broader scale and offer valuable insights for researchers and policymakers in building sustainable and resilient urban environments prepared for future climate adaptation.
date: 2024-06-12
date_type: published
publisher: Springer Science and Business Media LLC
official_url: http://dx.doi.org/10.1038/s41597-024-03446-2
oa_status: green
full_text_type: pub
language: eng
primo: open
primo_central: open_green
verified: verified_manual
elements_id: 2284997
doi: 10.1038/s41597-024-03446-2
lyricists_name: Sun, Ting
lyricists_name: Ghaffarian, Saman
lyricists_id: TSUNA36
lyricists_id: SGHAF69
actors_name: Sun, Ting
actors_id: TSUNA36
actors_role: owner
full_text_status: public
publication: Scientific Data
volume: 11
number: 1
article_number: 618
issn: 2052-4463
citation:        Li, Ruidong;    Sun, Ting;    Ghaffarian, Saman;    Tsamados, Michel;    Ni, Guangheng;      (2024)    GLAMOUR: GLobAl building MOrphology dataset for URban hydroclimate modelling.                   Scientific Data , 11  (1)    , Article 618.  10.1038/s41597-024-03446-2 <https://doi.org/10.1038/s41597-024-03446-2>.       Green open access   
 
document_url: https://discovery.ucl.ac.uk/id/eprint/10193458/1/s41597-024-03446-2.pdf