Of all the things that can be bought and sold, is there anything that’s more important for building your life around it, than a home? There’s nothing I can think of right now, and that’s probably why selling it is so stressful. It’s hard to see your home as an empty shell, stripped of all your stuff and even harder to have its value pinned down to money. When we have to put a price tag on anything that’s dear to us, it just feels like a misfit translation of values. Market value of your home cannot reflect all the special moments shared in it, a part of your life “left” in it, that special value that makes is a home for you.

A home by K_M Architektur at Lake Walensee, Switzerland;

photo by JoeInSouthernCA

Those values can be completely unrelated, too. You can spend a very happy period of your life in a home with a lower market value, and live very poorly in an expensive home. It seems that when we’re selling a home, we’re very aware the fact that we’re selling bare walls and not our experience of a home, but when we’re buying a new one, we are trying to capture those feelings of a special place and homey feeling nonetheless (and real estate agents know it!). We look out for cues that reveal a potential for happiness, and, like with all purchases, we’re willing to let go of completely objective, logical reasoning and also act emotionally, impulsively, “fall in love” with some features. While quantitative variables like square footage and number of bedrooms might be the most important for making a reasonable decision about home buying, the most intriguing material for falling in love is the view.

Schminke by Hans Scharoun, Loebau, Germany;

photo by Wojtek Gurak

A decision whether a particular view is worth that much money might be an intuitive, subjective one for any potential buyer, but it has to be more objective for real estate agents, home sellers, and, when it comes to architecture that is yet to be built, for investors and architects. Research dealing with measuring the value of a view started out with using single dummy variables (comparing apartments with and without the view), or a number of dummy variables (taking type and quality of the view into account – full or partial ocean view, mountain view, lake view etc.).

Stahl House, CA, US; photo by dalylab

While many of those research found the substantial impact of the view on the property value, results varied considerably. For instance, Seiler, Bond and Seiler (2001, according to Yu et al. 2007) conclude from the analysis of appraisal-based data around Lake Erie that lake view adds 56% to home values whereas those same researchers (Bond, Seiler and Seiler, 2002, , according to Yu et al, 2007) using transaction-based data around the same Lake found that lake view adds an 90% premium to a house. The Lighthouse in Glasgow,UK; photo by Wojtek Gurak In another research, premiums were much lower. Comparing harbour and mountain views in Hong Kong, Jim and Chen (2009) found that harbor view was preferred and reflected in housing value. A broad harbor view could increase the value of an apartment by 2.97%, while a confined harbor view could lift price by 2.18%. On the contrary, a broad mountain view would depress apartment price by 6.7%, whereas a confined mountain view didn’t have statistically significant effect on the apartment price. Linked Hybrid by Steven Holl, Beijing, China; photo by Wojtek Gurak

However, in these research views were categorised by qualitative aspects determined by visual inspection which makes the definition of each category subjective and raises the risk of inequity in valuation. Kahonde and Whittal (2007) define equity in real estate valuation as the fair treatment of all property owners i.e. the achievement of comparable market values for comparable properties.

Areal view can be a starting point for 3-D visualization, Vancouver, Canada;

photo by ecstaticist

Another (and related) problem with these broad categories it that they just can’t take into consideration all the details that matter. That’s why the latest research use 3-D modeling techniques (through the use of geographic information systems -GIS) that capture the influence of surrounding buildings’ height, the surrounding topography, as well as the height and orientation of the subject property itself. Spatial statistics within a GIS makes possible the development of accurate, consistent, and unbiased explanatory variables. Using this method, Yu et al. (2004) focused on the valuation of sea view in private high-rise residential properties in Singapore. Their results show that an unobstructed sea view will add an average premium of 15% to the house price.

St Paul’s Cathedral seen from Tate Modern, London, UK;

photo by Wojtek Gurak

Benson et al. (2007) purpose the use od multi-criteria decision analysis (MCDA) combined with GIS to make the valuation process even more objective. MCDA (Malczewski, 1999) is a concept used to solve problems which are not easy to understand, have conflicting interests, and which are not well-defined. This should speed up the process of making an unbiased decision about the value of a view.

Queensland Gallery of Modern Art by Architectus, Brisbane, Australia; photo by Wojtek Gurak Presuming all the effort experts put into this field will help you get a view that’s both subjectively and objectively highly valuable, there still remains the question of how well you’ll do using its potential. Part of the questions is for the architects to answer properly – by positioning of the rooms, and size and positioning of the windows, balconies and terraces. Another part is on you – how often will you take time to enjoy your view and make memories that create the experience of a home?

References Jim, C.Y. and Chen, Y.(2009) Value of scenic views: Hedonic assessment of private housing in Hong Kong. Landscape and Urban Planning 91, 4, 226-234. ( link

Kahonde, J. and Whittal, J. (2007) Towards the modelling of view for CAMA property valuations. PositionIT (link)

Yu, S.M., Han, S.S., Chai, C.H. (2004) Modelling The Value Of View in Real Estate Valuation: A 3-D GIS Approach”, working paper. (link)