The effect of street trees on property value in Perth, Western Australia

Pandit, Ram; Polyakov, Maksym; Tapsuwan, Sorada; Moran, Timothy H.

doi:10.1016/j.landurbplan.2012.11.001

Cited by 107 publications

(69 citation statements)

References 38 publications

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“…Home buyers or renters' willingness to pay for a particular level of environmental quality is revealed when other house, property and neighbourhood features are held constant (Anthon, et al, 2005;Baranzini, 2008;Conway, et al, 2010;Donovan and Butry, 2010;Escobedo, et al, 2015;Garrod and Willis, 1992b;Glaesener and Caruso, 2015;Kong, et al, 2007;Mansfield, et al, 2005;Melichar, et al, 2009;Pandit, et al, 2014;Pandit, et al, 2013;Panduro and Veie, 2013;Payton, et al, 2008;Sander, et al, 2010;Saphores and Li, 2012;Tyrväinen, 1997).…”

Section: Methods Of Valuing Esmentioning

confidence: 99%

“…However, studies of the effect of street trees on property values have reported significant variations between and within cities (Anderson and Cordell, 1988b;Donovan and Butry, 2010;Drake-McLaughlin and Netusil, 2010;Pandit, et al, 2014;Pandit, et al, 2013;Wachter and Bucchianeri, 2006). This suggests that seeking a generic property value algorithm for international versions of "i-tree" may be as inappropriate as the one in the US version of "iTree Streets" which is based on the results of one 1988 study of front-yard trees in Athens, Georgia (Anderson and Cordell, 1988).…”

Section: The Research Problemmentioning

confidence: 99%

“…This algorithm has been applied to BCAs in many different cities (i-Tree 2014). Although Pandit et al (2013) reported that houses with a broad-leaved street tree on the verge in Perth sold for 4.27 per cent more than the median sale price, given the variations in results of more recent studies, as outlined below, it would be inappropriate to apply the existing i-Tree Streets property value benefit algorithm, or the Perth study result to other Australian street tree assessments.…”

Section: 7mentioning

confidence: 99%

“…This study applies similar methods as those used by authors such as Donovan and Butry (2010), and Pandit et al (2013Pandit et al ( , 2014 to investigate the effect of tree cover on and nearby house sales in Brisbane, especially street trees, on the frontage and on footpaths up to 100m…”

Section: 7mentioning

confidence: 99%

“…As described above in section 2.7, the value of trees, growing on and nearby residential properties, revealed in interdisciplinary studies of home-buyers preferences, have varied and effects have been both positive and negative (Anderson and Cordell, 1988b;Anthon, et al, 2005;Conway, et al, 2010;Dombrow, et al, 2000;Donovan and Butry, 2010;DrakeMcLaughlin and Netusil, 2010;Kong, et al, 2007;Luttik, 2000;Melichar and Kaprová, 2013;Melichar, et al, 2009;Morales, 1980;Netusil, et al, 2014;Pandit, et al, 2014;Pandit, et al, 2013;Payton, et al, 2008;Sander, et al, 2010;Saphores and Li, 2012;Tyrväinen, 1997;Tyrvainen and Miettinen, 2000;Wachter and Bucchianeri, 2006;Wolf, 2007). Despite similarities in methods, street tree canopy cover within 20 metres of houses sold in Perth in 2009 added a 1.8 per cent premium to median sale price (Pandit, et al, 2014), yet street tree canopy within a similar proximity (30.5 metres) of houses in Portland, Oregon sold for 3 per cent more in 2006(Donovan and Butry, 2010.…”

Section: Introductionmentioning

confidence: 99%

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Making the case for planning and investment in green infrastructure: a case study of street trees and property value impacts in Brisbane, Australia

Plant¹

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Trees in cities grow closest to where people live, work and travel, and offer a wide range of ecosystem services (ES). Emerging urban forest research has focused on helping communities and urban tree managers build awareness of the connections between urban forest structure, ES and the quality of human life in rapidly growing cities. Yet translation of the proliferation of urban ES scholarship to urban forest policy, planning and investment has been inconsistent. This study focuses on the robustness and relevance of measures and values of urban ES being presented to decision makers. Opportunities were identified to improve contemporary techniques for gathering and applying evidence to strengthen the case for strategic planning and investment in street trees. For example, a new approach to pre-stratification in sample survey design to account for unevenness in the density and distribution of street trees across 115 residential suburbs, in the case study city of Brisbane, Australia, was used to confirm that their goal of increasing residential footpath tree shade cover from 35 per cent in 2010 to 50 per cent by 2031 was achievable. A strong case for continuing to invest was also justified by analysing additional data about 2,299 houses that sold between 2008 and 2010, gathered from within the same 80 sample sites as the street tree sample survey.Hedonic price modelling revealed that home-buyers were willing to pay a premium for houses with 35 per cent street tree cover nearby. These premiums translated to annual property value benefits that exceeded annual costs of street tree planting and maintenance in Brisbane in 2009-10 by a ratio of between 2.06 and 2.20:1. Returns of almost AU$1 million per year to the local government and an additional AU$1-1.2 million per year to the state government in property tax revenues were also identified. This approach advances the broader use of ES valuation as both a business case development and policy revision tool.

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Section: Methods Of Valuing Esmentioning

confidence: 99%

Section: The Research Problemmentioning

confidence: 99%

Section: 7mentioning

confidence: 99%

Section: 7mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Making the case for planning and investment in green infrastructure: a case study of street trees and property value impacts in Brisbane, Australia

Plant¹

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The impact of water quality in Narragansett Bay on housing prices

Liu

Opaluch

Uchida

2017

Water Resources Research

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We examine the impact of water quality in Narragansett Bay on housing prices in coastal towns and cities using a hedonic housing‐price model. Unlike other hedonic studies of water quality, we test whether housing market responds to average water quality or more to extreme events. We also test the spatial and temporal extent of effects of water quality on housing prices. We find that poor coastal water quality, measured in terms of the concentration of chlorophyll, has a negative impact on housing prices that diminishes with distance from the shoreline. Furthermore, our finding suggests that housing prices are most influenced by the extreme environmental conditions, which may be accompanied by unpleasant odors, discoloration, and even fish kills. We further predict potential increases in home values associated under water quality improvement scenarios and find an increase in the values of homes in coastal communities along Narragansett Bay of about $18 million up to $136 million.

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