Coupling Real-Time 3D Landscape Models with Microclimate Simulations

Coupling Real-Time 3D Landscape Models with Microclimate Simulations

Lewis Gill, E. Abigail Hathway, Eckart Lange, Ed Morgan, Daniela Romano
Copyright: © 2013 |Pages: 19
DOI: 10.4018/ijepr.2013010101
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Abstract

With urban design, it is becoming increasingly important to both visualise spatial changes and quantify the effect of these changes on the local microclimate: the former often for public consultation and the latter to develop landscapes that provide resilience to warmer weather thus reducing the urban heat island effect. It is possible to automatically construct 3D landscape models from vector site plans and height data sources through procedural generation. However, the generation of the inputs for microclimate models remains a time consuming process even though 3D visualisations or site plans may already exist. In this paper, a method to link procedurally generated 3D landscape models to microclimate simulations is demonstrated. Using this method, a case study is presented that allows initial calibration of the model and then several distinct alterations in the base design are tested alongside the variation in weather conditions looking forward to 2080. Finally, graphics card shaders are used to incorporate the temperature data within the interactive 3D procedural models, allowing both real-time manipulation of view point and simulation time.
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Introduction

Increasing urbanisation and the changing climate mean that consideration of the Urban Heat Island (UHI) effect and methods to mitigate it are becoming a key concern in urban planning. Within planning frameworks, it is becoming accepted that adaption and resilience to climate change must be provided rather than simple focus on mitigation (S. E. Gill, Handley, Ennos, & Pauleit, 2007). The prospect of a warmer climate and more intense heat waves presents a particular concern to urban habitats where air temperatures can be significantly higher than surrounding rural areas. For instance London, UK has been measured to have a nocturnal heat island of nearly 9˚C in urban areas during clear sky periods (Kolokotroni & Giridharan, 2008). Such heating creates both uncomfortable night time temperatures, but also reduces the cooling of the urban fabric. The European heat waves of 2003 showed the devastating effect of increased air temperatures on the mortality of elderly people, particularly in urban areas, and risk analysis has shown a direct correlation between risk of death and the availability of local vegetation (Vandentorren et al., 2006). It is unsurprising, therefore, that there is an interest in the mitigation of the UHI. General rules for mitigation generated from the literature include: increased amount of green space, design of street canyons to increase the “sky view factor” and presence of natural porous surfaces to improve local evaporation. For example, Keeble, Collins, & Ryser (1991) state that landscape design can have a significant impact on the microclimate of a built-up area with the solar access and wind protection being critical to the effectiveness of the design. Smith & Levermore (2008) provide a substantial review of the issue and methods appropriate for mitigation in the UK. However, the process of the local microclimate is a complex one and large scale changes to site design may be difficult to quantify for their impact on the local climate. The interrelation between sensible heat exchange, evaporation and evapotranspiration, the absorption of solar radiation (which changes due to diurnal variations in shading and fluctuating wind speeds) mean that it can be beneficial to use numerical models to assess the impact of design changes instead of simple “rules of thumb”.

Regarding the landscape planning process, rather than proposals being imposed top-down, there is an increasing trend to shift decision making to be more inclusive (Lange & Hehl-Lange, 2011). To this end, visualisations of future landscapes are increasingly common as a method of communication of designs to both technical and non-technical participants of the landscape design and planning process. These range from two dimensional (2D) plans and photo-montages, through physical models to fully interactive three dimensional (3D) computer visualisations (Gill & Lange, 2012). However, 3D visualisations tend to remain focused on the spatial and visual nature of change, rather than the performance of the proposed landscape, such as UHI mitigation efficacy. Zlatanova, Itard, Kibria, & van Dorst (2010) assert that although design professionals are confident with plans, the same professionals doubt if the public is as au fait with maps and plans as they are. Therefore, considering that microclimate results often come in the form of 2D plans or sections, public consultation techniques should be adapted to consider this mismatch.

So, consider a landscape proposal drawn as a 2D master plan that will require both an interactive 3D model for public participation purposes and a microclimate numeric simulation to consider UHI resilience. Both the inputs to microclimate numeric modelling and interactive 3D models can require large amounts of time to construct and tend to be undertaken as a manual process, which can lead to inherent problems. Procedures such as these can be error prone, due to inaccurate translation of a 2D design plan into another system. If both a microclimate simulation and a 3D model of a proposal are to be constructed, it becomes a duplication of effort to create both the inputs to the microclimate modelling and the 3D visualisation. Design data becomes distributed in three places (2D plans, 3D model and microclimate simulation) and, as the designs evolve, keeping everything synchronized becomes increasingly difficult.

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