1

Quantitative assessment of view from within high density development using a perverted

light modelling approach

Dr Marcus White

Faculty of Architecture, Building and Planning

The University of Melbourne

VIC 3010, AUSTRALIA

T: +61 403 439 494

E: mrwhite@unimelb.edu.au

Nano Langenheim

Faculty of Architecture, Building and Planning

The University of Melbourne

VIC 3010, AUSTRALIA

T: +61 421 217 569

E: nlangenheim@unimelb.edu.au

Paper Presented at the

7th Making Cities Liveable Conference

Kingscliff (NSW), 10 – 11 July 2014

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Quantitative assessment of view from within high density development using a perverted

light modelling approach

Abstract: Cities throughout the world are currently experiencing increased levels of

urbanisation resulting in pressure for densification. Questions about the impact on mental

health and general liveability are being raised in response to very dense developments

proposed in many cities including Melbourne, Australia. In some cases, high density towers in

close proximity are proposed with anticipated ‘views’ facing directly into other residential

towers. Though not a problem for ‘off-the-plan’ investors, ongoing users may be impacted,

potentially not able see water, any form of vegetation or even glimpse the sky.

As city densities increase, ‘view-quality’ becomes increasingly important. There is a

growing need for tools which can quantify how much water, sky or vegetation can be seen

from each dwelling to assess and guide the form of development.

This paper explores a new analysis and design approach which perverts light

simulation modelling within animation and game production software, combined with Java

based raster image-processing software ImageJ, to calculate the quality of view from within

buildings at a precinct scale.

This approach results in the quantification of view-quality based on visual access to

these specific elements either separately or simultaneously. The approach can weight view

elements depending on preference using different weighting. Existing urban morphology can

be assessed, as can potential urban form of proposed developments.

The approach could be used by urban designers and planners when setting up

precinct design guidelines to respond to the ‘visual amenity’ aspect of liveability; by

architects and developers during design process; by mental health researchers exploring

benefits of water, vegetation and sky views. The approach also has potential for application at

ground level in assessing the visual amenity of streets as a contributing factor of walkability.

Key words: Sky View Factor; Aspect; Outlook; urban modelling; liveability.

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Introduction

Cities throughout the world are currently experiencing increased levels of urbanisation

resulting in pressure for densification of urban form (DOIT 2013, pp.9, 211). Questions about

the impact on quality of life; mental health; and general liveability are being raised in

response to dense developments proposed in many cities including Melbourne, Australia

(COM 2013, p.63). In some cases, high density towers in close proximity are proposed with

anticipated ‘views’ facing directly into other residential towers due to a ‘lack of regulation’

(Johanson & Perkins 2012).

As city densities increase, aspect or ‘view-quality’ becomes increasingly important

(Zhang et al. 2012). There is a growing need for tools to assess and guide the form of

development which can quantify how much sky, water or vegetation can be seen from each

dwelling.

In the first half of this paper we give a brief background into the growing pressure for

high density apartment development in Melbourne and the impact on visual amenity within

these dwellings. We discuss the complex relationship between the developer and investor

driven market; touch on the current legislative protection of visual amenity; the potential

impact of view on real-estate values; and the impact views of vegetation, sky and water have

on liveability and health.

In the second half of this paper, we go on to outline our method of ‘perverted light

modelling’ for view analysis, describing the steps involved. We report the preliminary results

of the new method applied to a large scale test case in the Melbourne central activity district

and continue with a brief discussion and conclusion based on the findings.

Background

Melbourne’s Growing Pains – urbanisation, densification, apartments and liveability:

Melbourne is experiencing rapid urbanisation and densification with over 600,000 new

residences in the past decade (DTPLI 2014, pp.6, 9, 18). The population is expected to grow

from approximately 4 million to between 5.6 and 6.4 million people by 2050 (MPSM 2012,

p.6) or potentially even higher - 7.7 million people by 2051 (DTPLI 2014, p.5). The bulk of

the future development of Melbourne will be concentrated in inner urban renewal areas as

medium to high density development (DTPLI 2014, p.60).

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There is also an aspiration to provide suitable new housing for an ageing population and a

desire for this population to downsize from their detached housing and ‘age in place’ in high

density apartments within their local area (DTPLI 2014, p.65).

There is growing concern about the liveability of very dense developments being

constructed in many cities including Melbourne, Australia. Birrell and Heally suggest that the

the apartment boom is degrading the city’s liveability (2013, p.7). They suggest that the high

density development areas where towers are built adjacent other towers are ‘little better than

dog boxes […] Those buying off-the-plan may imagine panoramic views across the Bay but

things change however, when banks of these towers are built. They obscure each other’s

view. They collectively create a great wall’ (Birrell & Healy 2013, p.31).

As city densities increase, there is a need for tower locations, shapes and sizes to be

considered collectively and, as suggested by the City of Melbourne in its recent document

Future Living: A discussion paper identifying issues and options for housing our community,

there is a need for good internal amenity, for towers to be well-spaced to equitably distribute

access to sunlight and outlook (veiw from within apartments) (COM 2013, p.63).

The Victorian State Government shares the City of Melbourne concerns, with the

recently released document Plan Melbourne, stating in the section titled Initiative 2.1.5

Improve the Quality of Amenity of Residential Apartments that “there are major concerns

about apartment developments which include”:

• the small size of many apartments

• the tendency for a large number of apartments to be designed with habitable rooms (notably bedrooms) that have no direct access to daylight and ventilation

• lack of consideration of the amenity impacts of adjacent apartment development (DTPLI 2014, p.69)

Though the impact on adjacent development is listed as a ‘major concern’, measures to

mitigate this concern are not detailed other than to suggest that improvements to ResCode

(Clause Clauses 54, 55, 56 of the Victoria Planning Provisions) need to be made and that local

governments will need to review and refresh their housing strategies in line with Plan

Melbourne Objectives (DTPLI 2014, p.67). The City of Melbourne’s document suggests

controlling distance between buildings to address the critical issues of privacy, sunlight,

daylight and outlook (COM 2013, p.65). To set minimum front and side setbacks or set

minimum distances between towers may improve view-quality from within apartments, but as

Melbourne architect Callum Fraser argues, the key is how the buildings and neighbouring

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buildings are designed. There are many ways of achieving the sharing of light, views and

ventilation, not necessarily having 25-metre spaces between the buildings’ (Johanson &

Perkins 2012). Fraser’ practice illustrates this point in the Watergate twin-tower development

in the Melbourne Docklands which comprises two separate towers less than eight metres apart

with wedge shaped building ends that allow all apartments to maintain high quality views

despite their close proximity. Though Fraser may be correct in his assertion that good

architects can design high quality buildings that can be shaped to allow close proximity

without loss of internal visual amenity, it is difficult for council town-planners to assess

individual tower forms against the complex three-dimensional urban context of the city.

Real estate and view-quality – a complex relationship:

The relationship between real estate markets and quality of views from within high density

dwellings is not straight forward. Though there is evidence that suggests that high quality

views of water, sky and vegitation attract a premium (D’Acci 2014; Luttik 2000), reliance on

this potential premium involves substantial risk.

Though the uncertainty of views might be seen as a major deterant to this housing

typology, the majority of apartments in Melbourne are a result of Asian developers and

investors (Birrell & Healy 2013, p.5), with only 31% of apartments currently owner-occupier

(COM 2013, p.56). Liveability, visual outlook amenity and quality of urban living is not a

major concern for those purchasing and financing contextless ‘off-the-plan’ investments as

the ultimate occupiers are predominantly renters (Cramer 2012, p.29). ‘Unlike

owner-occupiers, who would be strongly motivated to assess their purchase from a future

resident’s perspective, these investors are primarily concerned about the financial [short term]

consequences of their purchase’ (Birrell & Healy 2013, p.14).

If stricter controls over high density tower development proximity were implemented

such as those proposed by the City of Melbourne (COM 2013, p.65), it might be possible to

capture and quantify value associated with view-quality from apartments, as is the case in

other forms of real estate where methods such as Hedonic Pricing can be used.

The Hedonic Pricing Method has been applied to house pricing since the middle of the

20th Century to determine the impact of ‘bads’ (e.g. pollution), or ‘goods’ (e.g. access to

public parks) (D’Acci 2014). By using multiple regression analysis of a collection of complex

data sets including variables such as house price; house size; house age; pollution; distance

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from school or parks; views of green open space and views of water, it is possible to assess

the financial impacts of each variable.

Real estate and water views:

Water is a highly prized component of a view. In a hedonic pricing study of house

transactions in the Netherlands, Luttik (2000) found that ‘the most influential environmental

attribute in the study is the presence of water features’ and that a view of water attracted a

price premium of 8 to 10% (D’Acci 2014; Luttik 2000) but could be as much an additional

65% for panoramic water views (D’Acci 2014).

There are a number of hedonic pricing studies seeking to value scenic amenity in an

Australian context (Ambrey & Fleming 2011), with river views found to have a particularly

strong positive influence on the selling price of housing in Perth, Western Australia. Pearson

et al. (2002) found that views of the ocean had a greater impact on pricing than views of the

parkland in Noosa National Park, Queensland.

Real estate and vegetation views:

Human ‘responses to trees and other vegetation relate to economic benefits of visual quality’

(Ulrich 1986). Proximity and access to green space has long been recognised as important in

planning for health and social reasons (Ulrich 1979) and has been empirically demonstrated to

impact house pricing up to 117% (D’Acci 2014). Views of vegetation at the scale of a single tree

through to private gardens, urban parks, reserves and large scale national parks have also been

shown to increase real estate prices from 4 to 23% and a generalized ‘pleasant view’

increasing house prices by up to 50% (D’Acci 2014).

In the study by Ambrey and Fleming (2011) the view of the National Park is shown to

increase property values by approximately 7% while access to the National Park had no effect

on the price.

Impact of view on health and liveability:

While most studies treat the real estate and health benefits of views separately, D’Acci (2014)

suggest that the Hedonic Pricing Method can also be used to measure urban quality of life

based on the ‘willingness to pay’. There is a quantifiable relationship between the health of

residents and increase in property value attributed to the view from their living quarters.

Studies concerned with the physical and emotional health impacts of both ‘pleasant’ and

‘unpleasant’ views provide empirical evidence that residents in prisons display a decreased

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level of violence (Moore 1981); hospitals patients have decreased medication requirements

and recovery rates improve (Ulrich 1984); elderly citizens have a greater sense of wellbeing

and shorter recovery times when injured (Raanaas et al. 2012); and offices workers who’s

desks were located facing natural views take less sick days (Farley & Veitch 2001).

Liveability and water views:

A study by Volker and Kistermann (2011) reviews the small pool of literature on the benefits

of ‘blue space’ (water view) found that the health benefits of water as part of therapeutic

landscapes in urban environments could clearly be identified and that ‘blue space has

manifold influences on human health and wellbeing’(Völker & Kistemann 2011). The review

shows the strong predilection humans have for landscapes which contain water.

There is a need for disciplines such as urban planning and landscape architecture to

recognise and design for maximising both the environmental and health impacts of blue

spaces not only in health facilities and institutions but in residential situations also (Völker &

Kistemann 2011).

Liveability and sky views:

The impacts of decreased exposure to the sky leads to a reduction in visual comfort, requiring

extensive artificial lighting during day time (Zhang et al. 2012). From a psychological

perspective, being able to see the sky and experience natural light and to determine day from

night is an important aspect of wellbeing with ‘natural light denial’ even used as an extreme

form of torture (Ojeda 2006). Reduced exposure to the sky ‘may lead to [the] increase in

perceived confinement of space that may have negative impacts on people's satisfaction to the

living environment’ (Zhang et al. 2012).

Liveability and vegetation views:

The belief that viewing vegetation, water and other natural elements reduces stress and has an

impact on the speed of healing dates as far back as the earliest large cities in Persia, China and

Greece (Ambrey & Fleming 2011; Velarde et al. 2007)

Studies performed by Ulrich (1984) where patients were given either a ‘wall view’ or

a ‘vegetation view’ location for their post-operative recovery revealed substantial health

benefits for the ‘vegetation view’ patients, who recovered more quickly, required less

frequent and lower strength doses of pain relief and received less negative comments in

nurses notes than patients with the ‘wall view’ (Raanaas et al. 2012).

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Kaplan’s study of the psychological benefits of the view from the home (2001)

suggests that there is strong evidence that well-being and neighbourhood satisfaction can be

partially attributed to the ‘window effect’ where views of ‘even a few trees’ can have ‘micro

restorative’ effects.

Aim

In the above paragraphs, we have outlined how as cities densify, protection of visual amenity

in apartment developments is needed for health and wellbeing as well as real estate value.

The aim of this study is to develop and test a new three-dimensional analysis approach

to assess internal ‘visual amenity’ or ‘view-quality’ of apartment developments providing

rapid visual and numeric feedback in a 3D modelling and visualisation environment. The

approach is to be used by urban designers and architects working with planners when setting

up precinct design guidelines to maximise the quality of views and thus liveability of dense

urban development.

Method

The second part of this paper explores a new analysis and design approach which perverts

light simulation modelling within animation and game production software, combined with

Java based raster (pixels) image-processing software ImageJ, to calculate the amount of

water, vegetation or sky visible from within buildings at a precinct scale.

The approach we have used to develop and test this rapid three-dimensional

view-quality analysis technique involved six parts – firstly to model polygon meshes of urban

precincts to test; secondly to apply a ‘sky-globe’ light based sky view factor assessment

method; thirdly to apply an ‘objects as light source’ method to assess visibility of water and

vegetation; fourthly to ‘bake’ resulting light levels onto polygon meshes outputting results to

a flattened raster image; and finally, to assess the raster outputs using image-processing

software ImageJ. We then tested this approach on a large scale urban model to validate the

applicability in precinct development scenario modelling.

Results

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17

As reported in previous study (White & Langenheim 2014), the level of accuracy for

the SVF modelling was found to be very good – with a maximum error of ± 0.03. The level of

accuracy of the ‘object as light source’ for direct an-attenuated (no fall-off) was found have a

similar level of accuracy to the SVF modelling, though further verification is required here.

Weighting of variables and a potential view-quality rating system:

The amount of fall-off according to distance was not interrogated in detail and we feel that

there is a need for more research in this area to answer questions such as – what is the

relationship between distance of water or vegetation and how much it improves a view? And,

does a very large tree that is far away improve a view as much as a small tree that is very

close?

The weightings for the different light channels also raises questions – is a water

preferable than a view of vegetation? Is a view with a lot of water worth more than a view

that has some water but also some vegetation? How much sky does one need to see to

experience physiological benefits? It may be that the weighting of these variables would

depend on the purpose of assessment – purely real estate value or liveability.

For these reasons, a simple star rating system has not yet been defined, though there

seems to great potential to develop such a system. With further research, it may be possible to

develop a view-quality rating system that could be used by policy makers, urban designers,

architects in developing high density dwelling guidelines and then by planners in assessing

design proposals.

Ground level assessment:

Though the aim of this study was focused on apartment view amenity, the level of

view-quality at street level was also displayed. The impact on view was apparent in each of

the city renders for sky-view and vegetation (Figure 11 and Figure 12), though the impact of

water at ground level was less evident (Figure 10). There is potential for view-quality

assessment tools to used when considering public open space and be incorporated into

walkability assessment tools such as those developed by Badland et al (2013).

Views from punch windows?

For the initial studies we have we have worked at an urban design massing scale, using highly

simplified abstractions of building facades that represent only the potential of views from

within the buildings as though they were entirely floor to ceiling clear glass curtain walls.

18

Though fully curtain walled residential towers do occur, they not common in Melbourne. In

future testing, we will investigate individual buildings in more detail looking at window

opening sizes and shapes; distance from windows (if an occupier stands two metres from a

window do they still get a view?); and solid balcony balustrades versus transparent.

Complex three dimensional:

The method described has the potential benefits of being truly three-dimensional, allowing

view-quality analysis of complex urban scenarios allowing urban designers to have a greater

understanding of existing city forms and identifying potential impacts of urban additions or

subtractions as well as the impact of complex forms of urbanism including cantilevering

buildings, stepped or sloping building forms, buildings with holes or ‘cut outs’.

Potential to extend previous research on real estate and health:

There is potential to use this view-quality assessment approach to extend many of the existing

view related studies. More highly detailed hedonic analysis would be possible if view-quality

model outputs could be brought into GIS environment and used as part of the regression

analysis.

It is also possible that by developing more detailed hedonic models, a greater understanding

of relationships and weighting of the aforementioned variables could be gained. It may be

possible to use these findings to further inform a view-quality rating system.

Conclusion

To encourage downsizing, owner-occupying and emotionally healthy occupants, it is essential

to offer high density housing that retains value, but more importantly, provides liveable and

healthy conditions for occupants with high quality views of the sky and vegetation or water.

The perverted light modelling approach described in this paper has the potential to be

used by urban designers, architects and planners when setting up precinct design guidelines to

respond to the ‘visual amenity’ aspect of liveability; by architects and developers during

design process to maximise the quality of views to maximise profits; and by mental health

researchers to maximise health and liveability in dense urban developments.

19

Figures

Figure 1: ‘Urban canyon’ or ‘sky view factor’ calculated for a distinct location using

projected rays through the single point and surrounding building form, intersecting with a

hemisphere to assess level of ‘openness to the sky’. .................................................................. 9 

Figure 2: Sequence of test screen grabs of four boxes (buildings) with height parameter

changed – the higher the boxes, the darker the shadowing and lower the SVF level. ............. 10 

Figure 3: Vegetation view model showing cops of trees as a ‘light-object’ casting light onto

surrounding urban from. Where adjacent buildings are well lit by the tree ‘light-objects’, they

have a good visual access, where the surrounding buildings are black, they have no direct

view of the vegetation. ............................................................................................................. 11 

Figure 4: Water views – river as blue light-source. Building facades with good light view to

river are shown bright blue. Brighter blue indicates better water views. ................................ 11 

Figure 5: Sky view analysis – using sky-dome light source for SVF calculation. Bright red

areas of façade or roof have high levels of SVF and areas that are dark have low levels. ...... 12 

Figure 6: Model showing simultaneous analysis with vegetation, water and sky view light

sources on. ................................................................................................................................ 12 

Figure 7: Texture baking process involves rendering the object with lights and materials and

then 'baking’ the rendered result to an ‘unfolded’ flat raster image texture (diagram produced

by Burman, Solanki and Amineh in Studio B subject University of Melbourne). .................. 13 

Figure 8: Threshold adjusted to identify five levels of view from ‘5’ being the best and ‘1’ the

worst (diagram produced by Burman, Solanki and Amineh in Studio B subject University of

Melbourne). .............................................................................................................................. 14 

Figure 9: ImageJ pixel value assessment of baked texture to quantify view allowing

comparative urban scenario studies (diagram by Sarah Skillington as part of the University of

Melbourne FDUM subject). ..................................................................................................... 14 

Figure 10: Aerial test render of water-view analysis applied to 3D mesh model of Melbourne

central activity district – showing visual impact of the Yarra River. ....................................... 15 

20

Figure 11: Aerial test render of Vegetation-view model tool applied to 3D mesh model of

Melbourne central activity district. Areas that receive green light have visual connection with

vegetation. Note: light levels at street level are also shown. .................................................... 15 

Figure 12: Aerial render of SVF tool applied to 3D mesh model of Melbourne CBD – aerial

view. Note the dark areas have low levels of SVF. .................................................................. 16 

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