14TH INTERNATIONAL CONGRESS OF THE
INTERNATIONAL SOCIETY OF PHOTOGRAMMETRY
HAMBURG 1980
COMMISSION VII
Stamatis Sekliziotis
Ministry of Co-ordination and Planning,
Athens, Greece .
W. Gordon Collins
Remote Sensing Unit,
University of Aston in Birmingham (U.K.)
URBAN OPEN SPACE AND SOCIO-ECONOMIC CLASS:
AN AIR PHOTO BASED STUDY
Abstract
A methodology has been developed for identifying, classifying
and measuring open space in cities.
A sample survey was
carried out in the Merseyside Metropolitan County in which
the type, condition and extent of urban open space was
derived from colour infra red aerial photography.
The results were mapped and digitised, and the provision of
open space was compared with the socio- economic class of the
population.
The results of this comparison are presented.
This study of open space was carried out with the support
and co-operation of the Greek Government;
the Department
of Environment, London;
and the Metropolitan County Planning
Department of Merseyside County U.K.
839.
There has been a dramatic change in the U . K. government
policy regarding the establishment o£ new towns .
The
emphasis is now on the redevelopment o£ existing cities
rather than on building new ones to rehouse the urban popul ation .
This has created an urgent need to carry out detailed
surveys and inventories o£ many aspects o£ urban land use 1n
metropolitan areas :
this study concentrates on just one
aspect - urban open space .
In the first stage a comparison was made between 1 : 10,000
scale black and white and 1 : 10,000 scale colour infra- red
aerial photographs, to compare the type and amount o£ open
space information which could be obtained £rom these two
sources . The advantage o£ using colour infra-red photography was clearly demonstrated in this comparison .
The second stage was the use o£ colour infra- red photography
as the sole source o£ data to survey and map the urban open
space o£ a sample area in Merseyside Metropolitan County .
This sample area comprised eleven ~km2 squares, on each o£
which a 20m x 20m grid cell was placed to record, directly
£rom the photography, 625 sets o£ data .
Each set o£ data
recorded the. type and amount o£ open space, its surface
cover, maintenance status and management (derived £rom its
condition) .
The data recorded were fed into a computer
and a suite o£ programs was developed to provide a wide
variety o£ data;
output in both computer map and statistical
form, £or each o£ the eleven ~km2 sample areas .
The third stage involved a comparison o£ open space data
with socio- economic status .
Merseyside County Planning
Authority had previously conducted a socio- economic survey
of the county , and this information was used to identify
the socio- economic status o£ the population in the eleven
~km2 areas o£ this project .
A number o£ interesting results emerge £rom this comparison ,
one example o£ which is outlined in this paper .
An initial requirement was to define ' open space ' and
compile a classification which was suited to the problem ,
and was related to what the source o£ data - in this case
colour infra- red aerial photographs - could supply . ' Open
space ' was simply defined as "Land which was not covered
by buildings " and Figure 1 shows the notation which was
compiled in close co- operation with Merseyside County
Planning Authority . The Authority also suggested the eleven
~km2 areas which they selected as samples to represent a
£air cross section o£ the population and environment o£ the
County .
Ten groups o£ open space were identified, and these were
broken down into thirty nine sub groups , or Units .
Because
840.
the colour infra- red photography was so useful for distinguishing the various types of surface cover, sixteen surfaces
were identified and included in the description of the open
space units .
A 20m x 20m grid of squares was superimposed over each \kffi 2
sample area on the colour infra- red photographs, and 625
sets of data were recorded for each . Six digits were used to
record the information on each 20m x 20m square :
the
1 dominant 1 use 1n each square was recorded
01
02
3
I
4
01 The open space type (unit)
02 Surface category
3 Degree of maintenance of surface
4 Condition of surface, from which was derived its
management status
Because the information was recorded systematically in rows
on a 25m x 25m matrix, the subsequent handling of the data
was made easier . Each 6 digit unit represented 400m2, hence
both the distribution and amount of each type of open space
and its surface cover , could easily be derived from computer
handling .
One matrix (Figure 2} was compiled to show , in four categories, the degree of maintenance of the various types of
surface cover , related to the various types of open space
units . Another matrix (Figure 3} was compiled to show in
four categories , the management situation of the various
types of surface cover, related to the various types of open
space units . The management situation was derived indirectly
from the observed condition of the surface cover .
Figure 4 shows an example of one of the computer/calcomp
maps which were compiled of each of the eleven \km2 sample
areas .
All this data was fed into a computer which , in addition to
producing maps , provided a substantial amount of quantitative
data which were printed out as statistical lists .
A set of manual maps (Figure 5) was also produced which
showed the distribution pattern and amount of the ' quality
of management ' of the open space .
The eleven \km 2 sample areas were part of a major socioeconomic study carried out by the County Planning Authority .
Each of t h e sample areas contained a population which
84:1...
comprised a specific socio- economic class. This class, or
status, was identified in £our categories £rom High (1) to
Very low (4), and the open space data was re-organised to
relate to these £our categories .
The first step was, in each o£ the ~km 2 sample areas, to
relate socio- economic status with the amount and type o£
the ten urban open space groups . (Figure 6) .
In this case
the ' Neglected Land' category is selected as an example,
but the data has been recorded £rom the ·aerial photographs
su.c b that any o£ the ten open space groups or even any o£
the chirty nine open space units which occur in the sample
areas can be correlated with the socio- economic status o£
the population .
The second step was to relate each urban open space group,
such as ' Neglected Land', together with details about its
extent, surface cover, maintenance and condition, with the
£our grades o£ socio-economic status (Figure 7) .
In the case o£ Neglected Land it is interesting to note that
there is a direct relation between the amount o£ neglected
land and socio- economic status :
the lower the status o£ the
area the greater the extent o£ neglected land .
On the other
hand there is no such obvious and direct relationship between
status and surface condition : whilst the percentage o£
neglected land with a surface cover o£ bare soil shows a
random distribution .
The combination o£ remote sensing £or data collection, and
computers £or data presentation and analysis, provide a
very powerful system which can be applied to a wide range
o£ environmental planning problems .
The value o£ aerial· photography in general, and colour infra
red photography in particular, has been emphasised in this
detailed urban land use study .
A suitable methodology has
been developed , and some interesting man/land relationships
have emerged, which the authors hope will be o£ some value
to those concerned with planning the future redevelopment
o£ our cities .
BLJ:2.
URBA.J.~
CODE
NUMBER
01
02
03
04
OPEN SPACE USE NOTATION
06
URBAN OPEN SPACE UNITS
Heathland
Woodland
Moss- land
Sand Dunes
Beaches
Marshland
07
08
09
10
11
Streams and Rivers
Canals
Lakes and Ponds
Reservoirs
Oceans
12
Private Gardens
13
14
Parks
Amenity Open Space- general
access .
Amenity Open Space- limited
access, Institutional etc .
Amenity Open Space Industrial, Commercial .
05
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
1 . Semi- natural Environments
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2 . Water bodies
3 . Private Gardens
4 . Amenity Open Space
Streets lined with trees
Streets not lined with
trees
Railways
Motorways
Open air car parks
Airfields
5 . Space £or Transportation
Children ' s Playgrounds
Sports£ields and Stadia
Gol£ Courses
Educational Playspace
Industrial Sports
Facilities
Other Open Air Playspaces
6 . Play and Recreation
1
32
33
34
35
36
37
Allotment Gardens
7 Agriculture and
Agriculture & Horticulture _ • Horticulture
Industrial/Commercial
Ancillary Open Space (othe~
Rough grassland
Scrubland
8 . Neglected land
Derelict land
Mineral Extraction
Waste Di.sposal Sites
Cleared Land
38
Cemeteries
]
9 . Cemeteries
39
Other Open Spaces
J
10 . Other
31
00
Built Environment
Figure 1 .
843.
OPEN SPACE MAINTENANCE CATEGORIES
High maintenance
Low maintenance
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.
~
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H
Gt
846.
100
20
sao
400
. 300
20C
METERS
legend
~ open space well managed
II open space badly managed
!
c._j
management of open space
good
bad
ha
15.64
0;
10
%
62.6
4.16
16 .6
built-up area
Management of urban open space .
Data from 1 : 10 000 false colour air- photography .
Sherdley Park .
Square No . 4 .
High socioeconomic status .
Fi gure
5.
built-up area
ha
Manual map .
8£:1:7.
ha
%
5.16
20.64
SPACE GROUP 8 NEGLECTED LAND
OPEN
50
15
l:3 10
<{
Bi35
z
~ 30
0
l:; 25,_
z
0
Q?
>
20
0
~ 15
10
5
I
e
I
2
3
SOCIOECONCMIC STATUS
Figure 6.
Amount of neglected land related to socioeconomic class.
OPEN SPACE GROUP No.8
NEGLECT!:D LAND
n,,
'1
I
r
n
II,,
u
i : 10
n9
:--1
1
ws
I
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i
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7
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~3
i !1
INTERMEDIATE
Ill
121
Ii
~
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I !
I
HIGH
I!
1 Is
:I
H,
H7
III
I is
MAINTENANCE
HIGH
1·'::'/.•.·c:·.•:l
LOW~
NONE
c==J
CONDITION
GOOD
•·: ·.. ··" ·' ''l
BAD
-
SURFACE TYPES
I
. I
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! I
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I!
rig
1
I!
I
I
I
n
LOW
VERY LOW
(3 1
141
SOCIOECONOMIC STATUS
Figure
7.
Type of neglected land related to socioeconomic class .
aqa.