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Abstract and Figures

From 1974 to 2011 the average new New Zealand house almost doubled in size while occupancy reduced over the same period. A first study indicates the features of large houses include several bathrooms, double/triple garaging, extra bedrooms/living areas and specialized rooms although there is no study of how these extra spaces are used. As a part of a larger study of how resources are used in different sized houses, the aim of this pilot study is to find the overall time small households in New Zealand spend in the rooms of their houses. Two questionnaires were developed to investigate the type/number of spaces/furniture in NZ houses and ask households to report time spent in each space over 14 consecutive days. The results show that irrespective of house size, households spend most time in the usual bedroom of each member(s), and the space(s) for living, dining and the kitchen and less than 10% of time using extra rooms available. In this pilot study people with larger houses spend more time at home. Analysis also reveals time spent at home is highly patterned and very similar on working days but different at weekends.
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R.H. Crawford and A. Stephan (eds.), Living and Learning: Research for a Better Built Environment: 49th International
Conference of the Architectural Science Association 2015, pp.153162. ©2015, The Architectural Science Association
and The University of Melbourne.
How do people use large houses?
Iman Khajehzadeh and Brenda Vale
Victoria University of Wellington, Wellington, New Zealand
iman.khajehzadeh@vuw.ac.nz, brenda.vale@vuw.ac.nz
Abstract: From 1974 to 2011 the average new New Zealand house almost doubled in size while
occupancy reduced over the same period. A first study indicates the features of large houses include
several bathrooms, double/triple garaging, extra bedrooms/living areas and specialized rooms although
there is no study of how these extra spaces are used. As a part of a larger study of how resources are
used in different sized houses, the aim of this pilot study is to find the overall time small households in
New Zealand spend in the rooms of their houses. Two questionnaires were developed to investigate the
type/number of spaces/furniture in NZ houses and ask households to report time spent in each space
over 14 consecutive days. The results show that irrespective of house size, households spend most time
in the usual bedroom of each member(s), and the space(s) for living, dining and the kitchen and less
than 10% of time using extra rooms available. In this pilot study people with larger houses spend more
time at home. Analysis also reveals time spent at home is highly patterned and very similar on working
days but different at weekends.
Keywords: Large housing; occupant behaviour; time use; house size.
1. Introduction
While crowded houses remain a problem in many parts of the world (Shelter (2004;2005;2006), RIBA
(2011), ODPM (2004), Friedman (2010), Murray (1974), BSHF (2013) and DBH (2010)) a new
phenomenon here called large housing (in terms of floor area as it relates to the whole housing stock)
has appeared in some developed countries especially in Australia, Canada, New Zealand and the United
States. According to QV (2011a), the average floor area of new houses in New Zealand has increased
from 112.7 m2 in the 1940s to 205.3 m2 by 2010 and later. Building consent figures by Statistics NZ
(2014a) also show the average floor area of new houses in New Zealand has almost doubled from 1974
(108.7 m2) to 2011 (191.6 m2). The same source also indicates that most large houses are in suburbs of
major cities with the top 3 in New Zealand being Shamrock Park in Auckland (306 m2), Kennedys Bush in
Christchurch (279 m2) and Lake Hayes in Queenstown Lakes (274 m2) (QV, 2011b). At the same time
average household size has decreased from 3.7 persons in 1951 to 2.6 in 2011 (Statistics NZ, 2008). This
suggests the average floor area per person in the household has increased.
154 I. Khajehzadeh and B. Vale
Crowding indices are used to show the relationship between house and household size, although
different crowding indices have different definitions. Statistics NZ uses Canadian National Occupancy
Standard (CNOS) and a study by Goodyear et al. (2011) suggests this is the most precise index for New
Zealand. CNOS uses number of bedrooms as an indicator of house size. Based on CNOS each couple, any
pair of children under 5, pairs of children aged 5-17 of the same sex, single adults over 18 and any other
remaining unpaired children need a separate bedroom (Goodyear et al., 2011). According to Statistics
NZ (2014b) in 2006, 6.9% of New Zealand households were severely crowded, 3.5% crowded, 25.1% had
no extra-no spare, 33.4% had one bedroom spare and 31.1% 2+ spare bedrooms. This means studies on
crowded houses are focussed on 10.4% of households while other housing which covers 64.5% of New
Zealand households is ignored. Statistics NZ (2014b) indicate houses with 2+ spare bedrooms increased
from 22.4% in 1991 to 31.1% in 2006. Comparing the average number of available bedrooms for 2006
NZ households with having one bedroom per occupant reveals large housing mostly occurs in small
households with 4 or fewer members (Figure 1). In addition, Statistics NZ (2002a, 2011a and 2014c)
indicate that the number of houses with 1, 2 and 3 bedrooms decreased in 1986-2013, and those with 4,
5, 6, 7 and 8+ increased in the same period.
Figure 1 Number of bedrooms and usual residents in New Zealand houses-2006 (Statistics NZ, 2011a)
compared with one bedroom per household member
According to Statistics NZ (2014d) European ethnicities are most likely to live in houses with spare
bedrooms, and Pacific, Middle Eastern, Latin American, African, and Maori ethnicities are least likely.
While 72% of Europeans live in houses with at least 1 spare bedroom, relevant figures for Asian, Maori
and Pacific are respectively 46.4%, 43.6% and 26.5%. Accepting the number of bedrooms has a great
influence on total house area, according to Statistics NZ (2011b) houses with 1 and 2 bedrooms (small
houses) are mostly for rent while those with 3+ bedrooms (medium and large houses) are mostly owner
occupied.
Because of the lack of studies on large houses, there is little knowledge about their features. A
preliminary unpublished study as part of this research showed these houses have extra bedrooms, extra
living rooms, en-suite bathrooms, double and triple garaging and more rooms with specialized functions.
A study by BRANZ (2007) indicates double garaging was the most important feature for people buying a
0
1
2
3
4
5
6
7
8
9
1 2 3 4 5 6 7 8+
Number of bedrooms
Number of usual residents
Ideal number of bedrooms
(one bedroom per person)
Number of available
bedrooms according to
household size (Based on
census 2006)
155
How do people use large houses?
new house in New Zealand, and this corresponds with an increase in household total car ownership
(Statistics NZ (2002b, 2013 and 2014c)). BRANZ (2007) also discovered a room as a study was an
important feature for those buying new houses as was a games room. Vale and Vale (2009) mention
separate formal and family living rooms in modern houses. While there are signs of new spaces in large
houses, there is no study of how much people use them.
Large houses use more construction resources and more operating energy over their life (Vale and
Vale, 2009). A study by BRANZ (2010) indicates that the typical estimated monthly winter energy costs
of dwellings increases with floor area. An investigation in the Netherlands by Guerra-Santin and Itard
(2012) also indicates a positive relationship between energy consumption and number of bedrooms in
dwellings built after 1996. Large houses are also filled with more furniture and appliances (Mithraratne,
2013). Vale and Vale (2009, p. 134) conclude that living in smaller houses is the quickest and simplest
way to reduce housing impact. Mithraratne (2013, p. 94) also believes that “Having a smaller house
could also be beneficial in increasing the area of the site available for growing food and generating
energy on-site, which could further reduce the dwelling footprint”. As large houses occur in richer and
more developed countries an equity issue is raised, “concern about sustainability must be based on
moral obligations towards future generations - not just personal self-interest” (Dresner, 2008, p. 2). It,
therefore, seems vital to know how large houses are used and whether resources are being wasted.
2. Methodology
In this study time spent in different spaces of a house was selected as an indicator of occupant behavior
(Brauer, 1974). Prior studies by Brasche and Bischof (2005) and Schweizer et al. (2007) use overall time
spent indoors (but not sub spaces) as a necessary assessment of occupant exposure to possible harmful
substances. Here, the number/size of spaces and type/number of available furniture/appliances were
selected as indicators of resources used, together with presence of a garden and car parking facilities. As
mentioned before, large housing is mostly seen in small families of European ethnicity living in owner
occupied houses in New Zealand, so all participants surveyed were from this group, in households of
single person, couples and couples with 1 or 2 children. The original list of possible rooms and furniture
was developed from the Trade Me website (Trade me, 2014), although participants could add to this.
In this first pilot study the intention was to have at least two participating households from each
group but in the end participants were 1 single household, 1 couple and 1 couple with a child who lived
in small houses and 1 single household, 2 couples and 1 couple with a child who lived in large houses,
making 7 households (1.A-1.H) and 14 individuals.
CNOS was selected as the base for defining small and large houses. Houses with at least one of the
following feature were categorized as large and others as small:
Houses with 1+ extra bedroom(s) (bedrooms with no usual nightly occupants) or
1+ extra living area(s) other than 1 living room, 1 kitchen and 1 dining room or any combination
of these or
1+ specialized room(s) (i.e. play room, workshop, etc. excluding 1 study room/office/library).
A questionnaire was prepared in 3 parts and participants were asked to fill each out on 3 different
days. The first asked about occupants, type/number of spaces and presence of different types of
furniture/appliances in their house. The second questionnaire was then based on day 1 answers to avoid
asking questions about absent furniture and spaces and to add any new ones. This asked about location
of furniture and large appliances in each space. The third questionnaire was a timetable prepared
156 I. Khajehzadeh and B. Vale
according to available spaces and number of occupants. This timetable was designed for each
participant to draw a line below the time of day he/she used that space of the house in 15 minutes
intervals. This form was prepared for each occupant/day separately (Figure 2). In comparison to the
methodology used by Brasche and Bischof (2005) and Schweizer et al. (2007), this gives more accurate
data on the time of the day a space has been used and when spaces were in shared use by occupants.
Report for: Occupant1 Reported day: Monday
Bedroom
Combined Living
room/Dining room
Kitchen
Bathroom/Toilet
Garage
Garden
Figure 2 Proforma to give use of each space by each occupant
All households were asked to fill out the day 1 and 2 questionnaires and the timetables for each
family member for 14 consecutive days starting from a Monday during different weeks in June, July or
August 2014. This produced data for 98 household/days or 196 person/days. Adults were asked to fill
out children’s timetables. For analysis, a 24 hour timetable was categorized into 5 parts: Early morning
(6-9am), Working/School time (9am-4pm), Evening/Early night (4-9pm), Sleep time (9pm-6am) and
Overall time used. Figures for each participant/day/space were extracted from the original timetables
into this format. Given the large amount of data for most participants (4500 entries for some) a platform
file was produced in SPSS for each participant and figures were transferred to SPSS for further analysis.
3. Results
3.1. Difference between weeks 1 and 2
Overall times indoors over 2 consecutive weeks were very similar for all participants. The biggest
difference was 8.65% and the smallest 1.31% with an average of 5.94% for 7 participant households.
Further analysis indicates big differences were caused by time spent in living rooms and extra bedrooms
while times spent in other spaces were almost constant over the 2 weeks. The situation for outdoor
spaces was very different (the study was done in winter) as time patterns were completely different for
the 2 weeks. The biggest difference was 100.00%, the smallest 0.00% while the average was 58.33%.
Further analysis showed a combination of weather parameters was the main reason behind these big
differences.
3.2. Time spent at home on different days of a week
To find differences in time usages on different days each week a “Paired-Samples T Test” was
undertaken using SPSS, yielding 21 different pairs of days for each week. For each household, times
157
How do people use large houses?
spent in weeks 1 and 2 were considered separately. Analysis showed pairs of Monday-Wednesday,
Monday-Sunday, Tuesday-Sunday, Wednesday-Saturday, Wednesday-Sunday, Thursday-Sunday, Friday-
Sunday and Saturday-Sunday are different for the 7 case studies over the 2 weeks, suggesting that
Sunday is the only different day from all other days of the week (even Saturdays). Further analysis
showed big differences between working days and weekends were mainly rooted in use of extra
bedrooms and extra living areas, which were used more at weekends.
3.3. Average daily time spent in rooms by each household
As each house has a different combination of rooms, it is difficult to compare time usages. For this
reason, spaces within a house were put into 12 categories (Table 1). For all households, bedrooms with
nightly use were considered usual bedrooms and other bedrooms as extras. The living room, dining
room and kitchen (or combination of these) that was used more than other similar rooms by a
household is considered as the usual living area and others as extra. The same categorisation was
applied to the bathroom/toilet. Garages are not considered unless they have a different function from
housing cars (one in this study was a music room). For each household the average time spent in each
room by the household over a day was calculated.
Analysis of average daily time usages showed very different time patterns for each household. The
most constant space uses were bedrooms used for 34-43% of a day. Biggest differences came from time
spent out of home and usual/extra living areas. Table 1 presents average time spent in each space
category and the households which were included in each average (only households with at least one
room in each space category are included in that particular average). As seen in Table 1, for an average
household, the majority of time at home (76%) is spent in usual bedrooms and usual living areas.
Table 1 Time spent in different space categories as a percentage of 24 hours and in hours and minutes
(average of 7 households scaled to 24 h)
Space category
Average time as
percentage of 24 hours
Average time as
hours and minutes
Usual bedroom
35.98%
8:38
Extra bedrooms
x1.15%
0:17
Usual living areas
20.13%
4:50
Extra living areas
x7.83%
1:53
Study room/Office
x1.71%
0:25
Specialized rooms
x1.25%
0:18
Usual Bathroom/Toilets
x2.84%
0:41
Extra Bathroom/Toilets
x0.56%
0:08
Laundry
x0.44%
0:06
Sheds and sleep outs
x0.67%
0:10
Storage
x0.18%
0:03
Open spaces
x1.02%
0:15
Out of home
26.24%
6:18
To compare time usage in different space categories in small and large houses, Figure 3 was created
to represent an average for all small and large houses. The left graph in Figure 3 gives the time usage for
the small houses (1.A, 1.D and 1.H) and the right graph for the large houses (1.B, 1.C, 1.F and 1.G).
158 I. Khajehzadeh and B. Vale
Figure 3 Time spent in different spaces in a typical 24 hour day by households in small (left) and large
houses (right)
Figure 3 shows, for this small sample size, that house size is highly correlated with overall time spent
at home. This time at home shows as utilisation of usual living areas and extra spaces. Prior study by
Brasche and Bischof (2005) shows individuals living in 6+ bedroom houses spend 1.7 hours more indoors
in comparison to those living in 3- bedroom houses and this difference is bigger for males. However, this
could also be related to demographic factors, as older people might have larger houses as a result of
having bought them when house prices relative to income were cheaper, or have larger houses because
children have now left the family home. This will be something investigated in the larger study. Time
spent in usual bedrooms is very similar in both size categories. In addition, households who have extra
bathroom/toilets divide their usages between the main and the extra bathroom/toilet(s), with the main
bathroom/toilet being used for 81% of all uses and the extra one(s) only for 19%. Time spent in the open
spaces of large houses is three times that of small houses, which could be related to spending more time
at home, or to having a larger outside space with a larger house.
3.4. Use of outdoor spaces
To find out more about outdoor space use, weather data including maximum and minimum
temperatures, rainfall, and wind speed were collected (NIWA, 2014) for 16 June to 17 August 2014.
Acknowledging this is a very small sample outdoor space usage, not unexpectedly, is more probable on
warmer, less rainy and less windy days. However, this is not necessarily true for everyone. It seems
there are priorities in the influential parameters. For instance, using outdoors at weekends is more
important than temperature, noting that NZ winters are not severe and for many people the coldest
days are around 9C. The situation for wind and rain are different. It seems people will use the outside
space in light but not heavy rain. High winds are also a different to using the outside space. In this study
people generally use outdoors in their free time (mostly weekends) if it is not too rainy and windy, with
greater usage in fine weather. It should be noted that the results only reflect winter usage.
159
How do people use large houses?
3.5. Day and night spaces
The method used in this study for timetables not only provides information about the total time spent in
each space but also the time a space was used. Time spent in each sub space is calculated as follows:
Time spent in room A Early morning time frame (6am-9am) = [(Subtotal of time spent in room A
by household for timeframe 6am-9am over two weeks) ÷ 14] ÷ (Household population)
Time spent in room A Working/School time frame (9am-4pm) = [(Subtotal of time spent in room
A by household for timeframe 9am-4pm over two weeks) ÷ 14] ÷ (Household population)
Time spent in room A Evening/Early night time frame (4pm-9pm) = [(Subtotal of time spent in
room A by household for timeframe 4pm-9pm over two weeks) ÷ 14] ÷ (Household population)
Time spent in room A Sleep time frame (9pm-6am) = [(Subtotal of time spent in room A by
household for timeframe 9pm-6am over two weeks) ÷ 14] ÷ (Household population)
Figures 4 presents average time usages for all space categories. The four time frames cover different
times (i.e. early morning covers 3 hours, working/school time 7 hours, evening/early night 5 hours and
sleep time 9 hours). To make time frames comparable, figures in each are divided by the relevant hours.
Figure 4: Time spent in all space categories by households over four scaled time frames as a percentage
of the total time spent in each.
As seen in Figure 4, usual bedrooms are mostly used at night and in early morning and are less used
over the day. The situation for extra bedrooms is very different meaning that though they have a
sleeping facility (a permanent bed) they are used for other functions. Usage of usual and extra living
areas is very similar indicating similar activities. They are also used during sleep time but this usage is
very small and occurs between 9 pm and midnight. Study/Offices are also day spaces. Based on Figure 4,
on average specialized rooms are usually used in working/school and evening/early night time frames,
with the latter used more. Usual and extra bathroom/toilets are similarly used in all time frames but
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
Early morning
(6am-9am)
Working/School time
(9am-4pm)
Evening/Early night
(4pm-9pm)
Sleep time
(9pm-6am)
160 I. Khajehzadeh and B. Vale
more in the early morning. Laundries, sheds and sleep outs and storage are spaces used in the day but
rarely at night. As seen in Figure 4, on average open spaces (gardens and decks) are mostly used in
working/school time (daylight), being probably the warmest parts of the day. In addition, because this is
time when people go to work/school it is clear why open spaces are mostly used at the weekends. It
should also be noted that because of personal work schedules this time pattern changes for some
households.
This analysis shows that a great proportion of time at home is spent over night in a very small area
(the usual bedrooms), while other spaces are mostly used in the day time. This should reinforce
designers to make good decisions about the internal layout of a house for good natural light/sunlight. It
can also affect decisions regarding heating devices, especially programmable ones so these work most
effectively. It is also important for those designing passive solar houses.
3.6. Furniture
A big difference between small and large houses is the resources, including furniture and appliances in
each type. Furniture, large appliances, tools (hand held and power tools and gardening tools) and
equipment were categorized into 8 types according to usage and usual location. Table 2 presents the
number of furniture/large appliances/equipment and average total number of these for the small and
large houses investigated. Considering this is a very small sample, for most categories large houses have
more types and numbers of furniture/large appliances/equipment. The biggest difference between
small and large houses seems to be in the living room/dining spaces. Bedrooms, kitchens and
bathroom/toilet/laundries of small and large houses have similar types of furniture/appliances even
though larger houses have more of these. Games equipment (e.g. table tennis table, exercise cycle) is
only found in large houses. Large houses seem to have more types and numbers of outdoor furniture
and gardening equipment/tools. In addition, both small and large houses have similar types of small
appliances but larger houses have more items.
Table 2: Average number of furniture types and total number of each category in small and large
houses.
House
size
Furniture/Large appliances/Equipment
Gardening
equipment
Small
appliances
Bedroom
Living
/Dining
Kitchen
Bath/Laundry
Outdoor
Games
Furniture
types
Small
x8.0
10.0
4.0
5.3
x4.3
0.0
2.7
12.7
Large
x7.5
15.3
4.5
5.3
x5.3
0.5
3.5
13.8
Furniture
frequency
Small
15.3
16.3
4.3
6.3
x9.7
0.0
2.7
13.3
Large
20.3
39.3
9.0
5.3
11.5
0.5
4.3
16.8
4. Discussion
Because of the small number of participant households the findings are mostly indicative, and need to
be proved through a bigger study with more participants, for which this pilot was a preparation.
However, this study has shown the times spent in different spaces of a house are good indicators of
occupant behaviour. In addition, time spent at home usually follows a similar weekly pattern. Times at
home on work days are similar for most people while weekends are different. Working schedules, family
combination and age group all affect the time spent at home. This supports findings by Brasche and
Bischof (2005) and Schweizer et al. (2007). There are signs indicating, not unexpectedly, that full time
working couples spend less while families with young children spend more time at home. It is also
161
How do people use large houses?
obvious from the pilot study that larger houses contain more furniture. Large houses tend to have more
types and numbers of each type of furniture/appliance, with particularly large differences in living room
furniture. Considering the energy embodied in furniture and that it has a much shorter life than the
house (Mithraratne et al., 2007), this points to the increased resource use of having large houses.
This study also shows that apart from house size all families spend the majority of time at home in
the same spaces, and that in all houses these have a similar floor area. In other words, people who live
in large houses actually spend most of the day living in a small area within the house. The big difference
between the way people live in small and large houses is that people who live in larger houses tend to
spend more time at home and this spare time is spent in extra spaces (i.e. extra living rooms, extra
bedrooms, music rooms etc.) noting this only covers 10% of time during a day. It seems that occupants
of larger houses are able to have more activities at home. This will be further investigated in the larger
study.
Environmental factors are also important when talking about large houses. Spare bedrooms and
extra spaces within large houses use resources for construction, operation (cleaning, possible heating,
maintenance) and furnishing. Accepting that living in larger houses could give more flexibility to
occupants for 10% of each day, this flexibility in housing activities is coming at a cost. In other words, by
considering the embodied energies of furniture, appliances and materials used in the extra spaces of a
house it becomes clearer how inefficient these spaces are. This will also be investigated in later stages of
this project on owner-occupied houses and small households. It is clear that house spaces can be
categorized into night and day spaces. Usual bedrooms are the only night spaces while other spaces are
day ones. Further analysis indicates almost 50% of the time households are at home (8:38 hours) is
spent in usual bedrooms or night spaces. This figure is similar to the time reported in the Time Use
Survey 2009/2010 by Statistics NZ (2011b) which indicates New Zealanders aged 12+ spend 8:48 hours
sleeping per day.
This study is still ongoing and aims to validate the findings of this paper using a large group of
participant households, by comparing results of resources used for each type of housing. The aim is to
find an efficiency rate of living in different sized houses for different households.
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Vale, R. and Vale, B. (2009) Time to eat the dog? The real guide to sustainable living, London: Thames and Hudson.
... Building consent figures from Statistics NZ (2014a) also show that the average floor area of new houses in New Zealand has almost doubled from 1974 (108.7m 2 ) to 2011 (191.6m 2 ). Preliminary studies undertaken as part of this research show that one feature of these larger houses are their double and triple garages, along extra bedrooms, extra living rooms, multiple bathrooms, and specialized rooms, such as a designated study (Khajehzadeh and Vale, 2015a). These studies also found New Zealand houses had carports and hard-standings for parking, usually coupled with the opportunity to park in the road (Khajehzadeh and Vale, 2015a). ...
... Preliminary studies undertaken as part of this research show that one feature of these larger houses are their double and triple garages, along extra bedrooms, extra living rooms, multiple bathrooms, and specialized rooms, such as a designated study (Khajehzadeh and Vale, 2015a). These studies also found New Zealand houses had carports and hard-standings for parking, usually coupled with the opportunity to park in the road (Khajehzadeh and Vale, 2015a). This all suggests the presence of unused parking facilities in many New Zealand houses. ...
... This study shows that on average garages of NZ houses are vacant for 14.4 hours/day. The results of our pilot study for this project (Khajehzadeh and Vale, 2015a) indicate that a ...
... Living room, bedroom, kitchen, and dining room are the most attended spaces within homes. This result echoes previous work that using traditional methods reported that living rooms and bedrooms are the most used places in small and large homes by occupants [43], and extends this previous finding by showing that for the specific case of young people on weekend nights, kitchens and dining rooms are also frequently used indoor spaces. As mentioned previously, a few videos avoid capturing directly the physical spaces by turning the camera to the ceiling and floor. ...
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Private nightlife environments of young people are likely characterized by their physical attributes, particular ambiance, and activities, but relatively little is known about it from social media studies. For instance, recent work has documented ambiance and physical characteristics of homes using pictures from Airbnb, but questions remain on whether this kind of curated data reliably represents everyday life situations. To describe the physical and ambiance features of homes of youth using manual annotations and machine-extracted features, we used a unique dataset of 301 crowdsourced videos of home environments recorded in-situ by young people on weekend nights. Agreement among five independent annotators was high for most studied variables. Results of the annotation task revealed various patterns of youth home spaces, such as the type of room attended (e.g., living room and bedroom), the number and gender of friends present, and the type of ongoing activities (e.g., watching TV alone; or drinking, chatting and eating in the presence of others.) Then, object and scene visual features of places, extracted via deep learning, were found to correlate with ambiances, while sound features did not. Finally, the results of a regression task for inferring ambiances from those features showed that six of the ambiance categories can be inferred with R 2 in the [0.21, 0.69] range. Our work is novel with regard to the type of data (crowdsourced videos of real homes of young people) and the analytical design (combined use of manual annotation and deep learning to identify relevant cues), and contributes to the understanding of home environments represented through digital media.
... Based on house layout, a time-use diary was prepared for each person to report the time he/she spent in each room as well as "out of home" for 14 consecutive days in winter. A full description of this study and the results are presented elsewhere (Khajehzadeh and Vale, 2015b). ...
Conference Paper
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In most developed countries censuses and crowding indices measure house size in terms of number rooms or bedrooms, even though the average house size varies in different countries. According to Statistics New Zealand and studies by BRANZ, recently New Zealand houses have changed both in terms of overall floor area and types of rooms. A floor plan study of 287 New Zealand houses revealed new houses have many specialized rooms and normal room types (sleeping bedrooms, living rooms) are bigger. Though bathrooms/laundries are never counted as habitable rooms, some in new houses are exceed the size of a bedroom in a 3-bedroom New Zealand state house. The study also shows the floor area of a 3 bedroom house in New Zealand varies from 79-225m 2 , thereby questioning whether using number of bedrooms could be underestimating house size in New Zealand and other developed countries. This paper uses evidence to propose that censuses and crowding indices need more complicated tools for predicting house size and discusses the form these might take.
... Based on house layout, a time-use diary was prepared for each person to report the time he/she spent in each room, garden/deck (if available) and "out of home" for 14 consecutive days in winter. A full description of this study and the results are presented elsewhere (Khajehzadeh and Vale, 2015a). ...
Conference Paper
Full-text available
New Zealand is a large land area with a low population and consequently a country of gardens. It also has a temperate climate and according to Statistics New Zealand in 2013, 81.1% of NZ dwellings were detached, and therefore had open space. There is also a growing trend for buying more outdoor furniture for New Zealand houses. However, a time‐use microenvironment study on 538 individuals living in 212 owner‐occupied houses in New Zealand shows that on average New Zealanders spend 0.52 hours/day using the gardens/decks of their home in summer. Analysis shows that time‐use at home‐outdoors differs by day type and age, and that having more outdoor furniture does not necessarily lead to more time‐use at home‐outdoors by the household. This paper presents the life cycle implications of making and furnishing the outdoor spaces of this sample of New Zealand homes, and further investigates this as a proportion of the total life‐cycle environmental impact of the house. It also discusses the productive nature of private gardens, and how the use of gardens has changed.
... Based on house layout, a time-use diary was prepared for each person to report the time he/she spent in each room as well as "out of home" for 14 consecutive days in winter. A full description of this study and the results are presented elsewhere (Khajehzadeh and Vale, 2015a The third and main study was an on-line survey administered in February-April 2015 in New Zealand. The survey was limited to single people, couples and couples with 1 or 2 children living in owner occupied houses. ...
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Governments have developed energy performance regulations in order to lower energy consumption in the housing stock. Most of these regulations are based on the thermal quality of the buildings. In the Netherlands, the energy efficiency for new buildings is expressed as the EPC (energy performance coefficient). Studies have indicated that energy regulations are successful in lowering the energy consumption in residential buildings. However, the actual energy consumption is usually different from the expected energy consumption. This paper explores the effectiveness of energy performance regulations in lowering the energy consumption of dwellings built in the Netherlands after 1996. The effect of the EPC and thermal characteristics on energy consumption was determined by statistical analyses of data on actual energy consumption. The results showed that energy reductions are seen in dwellings built after the introduction of energy performance regulations. However, results suggest that to effectively reduce energy consumption, the tightening of the EPC in not enough. Policies aimed at controlling the construction quality and changing occupant behaviour are also necessary to achieve further energy reductions.
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Full-text available
Personal exposure to environmental substances is largely determined by time-microenvironment-activity patterns while moving across locations or microenvironments. Therefore, time-microenvironment-activity data are particularly useful in modeling exposure. We investigated determinants of workday time-microenvironment-activity patterns of the adult urban population in seven European cities. The EXPOLIS study assessed workday time-microenvironment-activity patterns among a total of 1427 subjects (age 19-60 years) in Helsinki (Finland), Athens (Greece), Basel (Switzerland), Grenoble (France), Milan (Italy), Prague (Czech Republic), and Oxford (UK). Subjects completed time-microenvironment-activity diaries during two working days. We present time spent indoors--at home, at work, and elsewhere, and time exposed to tobacco smoke indoors for all cities. The contribution of sociodemographic factors has been assessed using regression models. More than 90% of the variance in indoor time-microenvironment-activity patterns originated from differences between and within subjects rather than between cities. The most common factors that were associated with indoor time-microenvironment-activity patterns, with similar contributions in all cities, were the specific work status, employment status, whether the participants were living alone, and whether the participants had children at home. Gender and season were associated with indoor time-microenvironment-activity patterns as well but the effects were rather heterogeneous across the seven cities. Exposure to second-hand tobacco smoke differed substantially across these cities. The heterogeneity of these factors across cities may reflect city-specific characteristics but selection biases in the sampled local populations may also explain part of the findings. Determinants of time-microenvironment-activity patterns need to be taken into account in exposure assessment, epidemiological analyses, exposure simulations, as well as in the development of preventive strategies that focus on time-microenvironment-activity patterns that ultimately determine exposures.
Article
This study examines how people read and comprehend house floor plans, by conducting a psychological experiment. In the experiment, 94 people are asked to classify 48 cards on which various types of floor plans differing along 5 dimensions were printed. Participants’ categorization data are analyzed in terms of (a) which attributes of floor plans people attend to when classifying them, and (b) whether and how people differ in the way of conceiving and classifying floor plans. Results show the existence of (a) a systematic pattern in people’s perception and conceptualization of house floor plans, and (b) group differences among people in the attributes of plans that they think important and attend to in classification. Implications for a housing information search and provision are discussed, particularly the possibility of providing information about floor plans in ways that are tailored to the recipient’s type of information search.
Article
Comprehensive time-activity studies, for use as a basis for estimates of personal exposure, are not readily available in Germany. This analysis of time spent indoors at home is based on data from "Dampness and mould in homes" (2000/ 2001)--a study of about 12,000 persons living in 5530 randomly selected apartments and houses in Germany. The results show the mean times per day people in Germany spend in their homes, classified by gender, age group, building location, city size, region, building type, owner-occupier status, number of people at home, smoking and ventilation habits, moisture emission and ill health factors such as asthma, allergy and number of acute respiratory infections per year. The overall mean time spent at home, 15.7 h per, is in accordance with results from US-American (15.6 h/day) and Canadian (15.8 h/day) human activity surveys carried out in the nineties, as well as being consistent with the German Environmental Survey (1990/92) and a small German study in 1987.
Changing housing need
BRANZ (2007) Changing housing need, Wellington: BRANZ.
  • N Isaacs
  • M Camilleri
  • L Burrough
  • A Pollard
  • K Saville-Smith
  • R Fraser
  • P Rossouw
  • J Jowett
BRANZ (2010) Isaacs, N. Camilleri, M. Burrough, L. Pollard, A. Saville-Smith, K. Fraser, R. Rossouw, P. Jowett, J. Energy use in New Zealand households, Final report on the household energy end-use project (HEEP). Wellington: BRANZ.