Visualizing 3d Climate Data in Urban 3d Models

Abstract

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.

Visualizing Invisible Environmental Data in VR: Development and Implementation of Design Concepts for Communicating Urban Air Quality in a Virtual City Model

“…Among participants, there was satisfaction with the solution using volumetric particles and the small cut planes. One reason for the preference towards the volumetric visualization could be that, as suggested by Gautier and Brédif [36], it provides a quick overview of the entire distribution of data in the model. The volumetric particles were visible as default and the small cut planes were created and manipulated easily, with one button press and direct hand movements.…”

“…In our case, getting an overview of the particles was facilitated by wind simulation movement, ensuring that these did not obscure the same background space across time. This also avoided potential misinterpretation of random movement [22,36], which was discussed as an option. To solve this problem, Christman et al [22] suggests that a user could be given the option to restrict the area showing the air flow.…”

“…Today, the rainbow scale is widely used for visualizing air quality data [33][34][35], however this scale is also criticized for being difficult to perceptually interpret [34]. Gautier and Brédif [36] suggest that an interactive 3D-visualization of data therefore should provide the possibility to dynamically change between a rainbow color scale and alternative color scales, based on a range in luminance. Other suggestions include the use of a single-color ranging from low to high intensity, or to use other attributes, such as shapes [35].…”

An Extension of Cityjson to Support Point Clouds

“…It can thus represent information along the three dimensions of space and their entire scale of values. It offers solutions to render simulation results as value-related 3D point cloud (Gautier et al, 2020). Supporting point clouds directly in the schema model is a gain to achieve an integration from a semantic perspective.…”

The State of the Art in Visual Analytics for 3D Urban Data

“…For example, the Urban Heat Island (UHI) effect, which is characterized by a sharp rise in urban temperature, poses a significant threat to public health, the ecological environment, and urban livability [EMM17,HW19b]. 3D models can help mitigate the UHI effect by providing a deeper understanding of factors such as the sky view, building bulk, and horizontal reflectance [CG17,GLU09, BRV*17, GCB20,RcH*22]. Additionally, 3D analysis is crucial in the realm of urban disaster management, enabling the accurate identification of catchment areas in events such as flooding [WHM*19], earthquakes [RTCVBS17], or even the outbreaks of infectious disease [MG20,ETVF20,Els21,XGY*23].…”