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VISUALIZING 3D CLIMATE DATA IN URBAN 3D MODELS

Authors :
Jacques Gautier
Sidonie Christophe
Mathieu Brédif
Laboratoire des Sciences et Technologies de l'Information Géographique (LaSTIG)
École nationale des sciences géographiques (ENSG)
Institut National de l'Information Géographique et Forestière [IGN] (IGN)-Institut National de l'Information Géographique et Forestière [IGN] (IGN)
N. Paparoditis
C. Mallet
F. Lafarge
S. Zlatanova
S. Dragicevic
G. Sithole
G. Agugiaro
J. J. Arsanjani
P. Boguslawski
M. Breunig
M. A. Brovelli
S. Christophe
A. Coltekin
M. R. Delavar
M. Al Doori
E. Guilbert
C. C. Fonte
J. Haworth
U. Isikdag
I. Ivanova
Z. Kang
K. Khoshelham
M. Koeva
M. Kokla
Y. Liu
M. Madden
M. A. Mostafavi
G. Navratil
D. R. Paudyal
C. Pettit
A. Spanò
E. Stefanakis
W. Tu
G. Vacca
L. Díaz-Vilariño
S. Wise
H. Wu
and X. G. Zhou
European Project: Grant No. 690462,URCLIM
Laboratoire sciences et technologies de l'information géographique (LaSTIG)
Ecole des Ingénieurs de la Ville de Paris (EIVP)-École nationale des sciences géographiques (ENSG)
Institut National de l'Information Géographique et Forestière [IGN] (IGN)-Université Gustave Eiffel-Institut National de l'Information Géographique et Forestière [IGN] (IGN)-Université Gustave Eiffel
Source :
International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, International Archives of Photogrammetry, Remote Sensing and Spatial Information Sciences, XXIV ISPRS Congress, XXIV ISPRS Congress, Aug 2020, Nice (en ligne), France. pp.781-789, ⟨10.5194/isprs-archives-XLIII-B4-2020-781-2020⟩, The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol XLIII-B4-2020, Pp 781-789 (2020)
Publication Year :
2020
Publisher :
Copernicus GmbH, 2020.

Abstract

In order to understand and explain urban climate, the visual analysis of urban climate data and their relationships with the urban morphology is at stake. This involves partly to co-visualize 3D field climate data, obtained from simulation, with urban 3D models. We propose two ways to visualize and navigate into simulated climate data in urban 3D models, using series of horizontal 2D planes and 3D point clouds. We then explore different parameters regarding transparency, 3D semiologic rules, filtering and animation functions in order to improve the visual analysis of climate data 3D distribution. To achieve this, we apply our propositions to the co-visualization of air temperature data with a 3D urban city model.

Details

ISSN :
21949034 and 16821750
Database :
OpenAIRE
Journal :
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
Accession number :
edsair.doi.dedup.....e1fba0c654215d5ffa8ddc7e51055162
Full Text :
https://doi.org/10.5194/isprs-archives-xliii-b4-2020-781-2020