This week’s guest blog is an update to a previous blog, Do Scenic Spots Benefit our Health?, by Chanuki Illushka Seresinhe, now a visiting researcher at the Alan Turing Institute. Chanuki offers more detail around the difference between natural and built-up environments and their wellbeing effects, based on data from machine learning.
Instinctively, we often seek out beautiful scenery when we want a respite from our busy lives or to boost our happiness. But do such settings actually help to increase our wellbeing?
Governments around the world value beautiful places, as evidenced by the protection of areas of outstanding natural beauty and the aesthetically-driven regeneration of deprived urban areas. Architects and designers often place emphasis on the aesthetics of what they create, not just the utilitarian function. As individuals, we often seek out beautiful places when we want to lift our spirits, or simply to relax.
The Department for Environment, Food and Rural Affairs’ report A Green Future: Our 25 Year Plan to Improve the Environment emphasises the importance of natural beauty:
“Environment is – at its roots – another word for nature, for the planet that sustains us, the life on earth that inspires wonder and reverence, the places dear to us we wish to protect and preserve. We value those landscapes and coastlines as goods in themselves, places of beauty which nurture and support all forms of wildlife.”
The plan goes on to state that is the government’s commitment to conserve and enhance the beauty of the natural environment, and make sure it can be enjoyed, used by and cared for by everyone.
However, until now, quantitative evidence supporting the argument that beautiful places, whether natural scenery or built-up environments, are beneficial to human beings has been lacking.
In our latest paper, Using deep learning to quantify the beauty of outdoor places, we explore whether we can provide quantitative evidence of such a link.
Crowdsourcing data
As I explained in my previous blog, we again explore over a million ratings of over 200,00 images of our environment across all of England via an online game called Scenic-Or-Not. However, this time we combine it with three years of everyday happiness measurements of over 15,000 users of the iPhone app Mappiness.
From this, we have been able to provide the first large-scale, quantitative evidence that people are happier in more beautiful surroundings. We find that our results hold even after accounting for a range of factors such as the activity the person was engaged in at the time, weather conditions and the income of local inhabitants.
Scenic doesn’t always mean natural, green or rural
You might ask how beauty per se might differ from other environmental factors. We may understand scenic environments to be akin to natural environments or green spaces. Most scenic areas of the country may be rural areas rather than urban areas. While we find that scenic environments and natural, rural or green environments are indeed highly related, we also find that they are not exactly the same.
In a previous study where we analysed the composition of the photos rated on Scenic-Or-Not, (see previous blog), we find the old adage ‘natural is beautiful’ seems to be incomplete: while nature features such as coastlines, mountains and canals can improve the beauty of a scene, flat and uninteresting green spaces are not considered beautiful. Interestingly, characterful buildings and stunning architectural features can improve the beauty of a scene.
The case for building beautiful built-up areas
This leads to our most interesting finding: that the effect of environmental aesthetics goes beyond the effect of whether an individual is in a natural, green or rural environment. Crucially, we find that even in built-up environments, people are still happier when they visit an area that is more scenic. So it no longer has to be the case that to seek beauty and boost our wellbeing, we have to flee to the countryside: we might be able to boost our happiness in beautiful built-up areas too.
Read our practice example of Citizen-led asset mapping