MORPHOLOGICAL MAPPING
ASSIGNMENT ONE Tara Shokouhi 635693
Exercise 1: Home Territory
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1. Aerial Photo
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50m
100m
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2. Cadastral Map
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3. Building Footprints
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4. Private Open Space
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5. Public Open Space
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6. Pedestrian Space
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150m
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i. Multi-layered Map 1
In the Suburb of Doncaster East, Private Open spaces are equally as predominant as the Public Open spaces. One does not out-number the other . Within a 5 minute walking distance there exists; 2 primary schools and a petrol station. A10 minute walking distance; a small shopping precinct with medical facilities, the post office, supermarkets etc as well as another petrol station, and within a 20 minute walking distance; a high school across the road from some restaurants and more medical facilities. The area has a good balance between nature and private spaces.
Legend Cadastral Map
Private Open Space
Public Open Space
Building Footprints
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150m
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ii. Multi-layered Map 2
The number of existing building footprints, with an average of 2.8 people per household, is disproportionate to the existing footpaths in the area. While the suburb is infused with facilities and schools to assist in the daily life of the residents, basic necessities like pedestrian footpaths need to be evaluated.
Legend Cadastral Map
Private Open Space
Building Footprints
Pedestrian Space
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50m
100m
150m
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Exercise 2: Experiential Mapping - Senses and the Transect
Parter: Oliver Poland Site Visit: Saturday 12.3.2016 at 13:00-15:30pm Tara Shokouhi 635693
I. Crowding
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100
200
400m
0
100
200
400m
LEGEND High Density Pedestrian Activity Medium Density Pedestrian Activity Low Density Pedestrian Activity Vehicle Density
Within a city, crowding can extend beyond physical human scale crowding. As a car-dependant era, cars are also a large part of our society. For this reason, my partner and I defined crowding on two levels, human scale and vehicular crowding in order to properly map the precinct to more depth.
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II. Safety
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LEGEND Construction/Machinery Obstructions Unsafe Trees J-Walking/Unsafe pedestrian crossings Blockages/Driving obstructions
0 100
100
200
200
400m
400m
Safety is a term that differentiates between various people. Personally, my partner and I interpreted safety, not as an emotion or sensation that we felt while walking around the site, but physical aspects and the manner in with humans interacted with one another that resulted in an over-all sense of safety within the space. Aspects such as potentially dangerous trees, construction sites and machinery can’t be controlled by the people using the site. However, J-walking/un-safe walking and blocking/driving obstacles were ones that were caused by the users. Tara Shokouhi 635693
III. Crowding & Safety Overlay
0
0
LEGEND Construction/Machinery Obstructions0
Unsafe Trees J-Walking/Unsafe pedestrian crossings
100
100
200
400m
200 100
400m 200
400m
N.B: After class feedback, I readjusted the thickness of the cadastral Map on illustrator. It is now thin in order to make the graphics clearer. When zooming in the lines will show up better.
Blockages/Driving obstructions High Density Pedestrian Activity Medium Density Pedestrian Activity Low Density Pedestrian Activity Vehicle Density
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Exercise 3: Behavioural Mapping
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Survey Count Analysis of Activities and Social Groups at The Steps of Federation Square
Thursday: Weather was warm and Sunny Monday: cool and cloudy with a few moments of sunshine
THURSDAY 3-3:20PM
MONDAY 11:50-12:10 PM
Observing/Daydreaming
23
21
Reading
12
14
Eating
10
14
Talking to Others (2+ people)
8
17
Sketching/Working
2
3
Talking on Phone
6
8
playing
5
4
TOTAL
66 people
81 people
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Sketch of Map 1
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Sketch of Map 2
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THURSDAY 3:00-3:20PM
LEGEND Observing
Reading Eating Talking to one another (2+ people)
Sketching/working Talking on the phone
1:250
Playing
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MONDAY 11:50AM12:10PM
LEGEND Observing
Reading Eating Talking to one another (2+ people)
Sketching/working
1:250
Talking on the phone Playing
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OVERLAY
General Notes The larger steps on either side of the middle steps, appeared to be greatly occupied at both times of analysis. People appeared to enjoy the space as they could use it in any way they wanted, meanwhile, keeping the majority of the central steps free for people to move up and down.
Less Static Activity Users of the site moved around a lot more in this area as there weren’t as much seating opportunities and were open walking spaces.
Difficulties
LEGEND Observing
Reading Eating Talking to one another (2+ people)
Sketching/working Talking on the phone Playing
Thursday 3pm Monday 11am
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The Difficulties with doing a behaviour map such as this, in an area such as Federation Square, is that there is often a large amount of users in the space, constantly moving, constantly leaving therefore it was often difficult at times to keep up with the number of people in the space.
Exercise 4: Flows
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Issues and Restrictions
Zone ‘O’ When collecting data as a large group, there will continue to be inconsistencies as not all people will go during the same day and at the same time. Unless groups pre-plan to visit together and start at the exact same time, the pedestrian flow will be inconsistent as it will not reflect the pedestrian flow in an entire day across all zones.
Do we all count in the same way? Some people may count a car as 1,2 or 3 in their count, others may completely disregard cars passing as they’re only looking at people walking. Where do pets fall?
When analysing the data collected for the same zone by several different people, another issue arises. The exact location where people have sat/stood to take the data may differ and impact the results gathered.
T1
T2
T3
T4
T5
T6
1
161
126
132
139
149
107
2
102
67
113
116
98
82
3
194
124
165
261
166
96
4
216
206
249
288
159
151
5
111
106
192
276
218
163
6
168
164
214
377
382
259
7
211
103
198
117
101
91
8
174
98
169
133
125
118
In analysing the results gathered for my zone by all other tutorial groups, there appears to be slight differences in our results. It is not clear as to when we each visited the location, where we stood specifically, and it is very possible that many of us may have missed a few pedestrians while writing. Tara Shokouhi 635693
Tutorial 3 Counts F (Avg)
G
H
I
J
K
L
M
N
93
193
56
78
51
59
11
28
16
132 107
60
150 105 112
84
63
76
62
23
37
36
113
134
54
71
126 98.5 216
69
46
12
40
32
41
70
165
93
67
67
47
145
116
65
53
25
18
18
3
55
249 103
46
72
63
67
212 139.5 68
31
89
39
67
12
4
42
192
29
20
37
75
96
36
144
92
81
70
45
72
10
11
29
214
38
21
19
44
49
70
75
135 105 157
77
44
29
33
14
24
42
198
84
23
14
39
37
55
48
166 107 162
85
51
32
68
32
15
29
169
64
A
B
C
D
E
F
1
8
19
35
39
125
44
142
2
6
22
40
63
52
3
9
13
26
81
4
3
21
31
5
8
27
6
13
7
8
96
90
O
P
N.B: Data that was not provided by Tuesday the 5th of April is Italicised and underlines. For this data the average figures provided were used Tara Shokouhi 635693
0+
Legend
Tutorial Counts and Colour coordination for Map
50+ 100+ 150+ 200+
F (Avg)
G
H
I
J
K
L
M
N
O
P
93
193
56
78
51
59
11
28
16
132
107
60
150 105 112
84
63
76
62
23
37
36
113
134
54
71
126 98.5 216
69
46
12
40
32
41
70
165
93
67
67
47
145
116
65
53
25
18
18
3
55
249
103
46
72
63
67
212 139.5 68
31
89
39
67
12
4
42
192
29
20
37
75
96
36
144
92
81
70
45
72
10
11
29
214
38
21
19
44
49
70
75
135 105 157
77
44
29
33
14
24
42
198
84
23
14
39
37
55
48
166 107 162
85
51
32
68
32
15
29
169
64
A
B
C
D
E
F
1
8
19
35
39
125
44
142
2
6
22
40
63
52
3
9
13
26
81
4
3
21
31
5
8
27
6
13
7
8
96
90
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Average Cohort Count
A
B
C
D
E
F
G
H
I
J
K
L
M
N
O
P
1
18
18
34
40
76
37
149
56
57
59
56
22
62
33
136
87
2
8
18
43
65
69
74
129
84
59
53
47
19
52
41
96
103
3
10
13
41
83
68
86
107
69
35
21
38
29
60
59
168
34
4
7
18
36
68
88
93
116
65
30
23
27
22
14
69
212
18
5
13
33
50
71
81
98
167
31
63
41
55
11
20
37
178
84
6
21
22
43
72
95
95
183
81
50
25
65
21
16
49
261
108
7
26
25
43
49
103
99
122
77
46
27
35
25
26
31
137
122
8
24
11
38
37
88
87
141
85
42
52
51
28
29
26
136
93
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Pedestrian Flow Map [based on Tutorial Counts]
A.
O.
N.
P.
B.
L.
C.
D.
E.
F.
G.
H.
I.
J.
K.
M.
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Legend
0+ 50+ 100+ 150+ 200+ Tara Shokouhi 635693
. O
Tutorial Overlays
Tu tor ial
O.
Tu tor ial
On e
Zone ‘O’ - Tutorial 1-3
When mapping and overlapping the data collected for Zone O by Tutorials one and two against my data (Tutorial three), the maps appear very different from one another. While they all appear to have similar colours present across all 3 (green 100+, orange 150+ and red 200+), they are not the exact same figures. From this we can make several conclusions: That none of us visited the zone on the same day. If we did, we may have recorded the data at different times that day
2.
It is very possible that we all counted differently, disregarding certain things that others may have counted.
3.
Pedestrian flows are constantly changing. At no two instances in time will the data be identical.
Tutorials 4-6 had slightly larger figures for the same zone. Where students of Tutorials 1-3 counted and did not exceed 200-250 people, the others collected data well beyond this. Therefore the conclusions drawn remain consistent. All collected data is applicable, and correct however the data is constantly changing. Therefore creating a map based on the averages will be more pertinent.
. O
1.
Tw o
Tu tor ial
Th ree
N.B: The maps used here are based on the mapping system I used prior to class. After receiving feedback, I altered the above map map and how I represented the data, however I kept these maps as is.
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