August 2016 has been chosen to coincide with campus survey. 12th to 22nd August is the period with largest amount of data, limited by car counters.
Pilot will be constrained to mesh block 30114560000 (same as SA1 30403109615)
Some stats might be only available on SA2 level (304031096 area St Lucia)? But that will be problematic since it includes non-campus part of St Lucia.
Estimated at 2,153 people for SA1 (place of usual residence)
Destination Zones (DZN) geography code: 310961711 (equivalent to SA1?).
Estimated population 8,695 (place of work).
These can be disaggregated by place of origin (DZN or SA2 and above)
Both resident and working pops can come split by characteristics covered in the census.
From the Aug UQ survey:
Collating information from the websites of each of the 10 residential colleges and Unilodge yielded a resident population of 2,747 for the St Lucia Campus as of August 2016. It is assumed that the resident population represents the overnight population of the campus.
Data comes from
UQ Saint Lucia Boardings & Alightings 12th - 29th August 2016
spreadsheet. With following metadata on it:
Author: Pearl Gariano Created: 2nd September 2016
Assumptions & Limitations:
Two ‘clusters’ of bus stops and ferry terminal:
‘Lakes’ and ‘UQ’ stops clusters were merged. 4962 public transport aggregated counts for three aggregated stop, separating boardings and alightings.
# A tibble: 5 × 5
date type site direction count
<dttm> <chr> <chr> <chr> <dbl>
1 2016-08-12 00:00:00 public_transport ferry outbound 0
2 2016-08-12 00:15:00 public_transport ferry outbound 0
3 2016-08-12 05:45:00 public_transport ferry outbound 1
4 2016-08-12 06:00:00 public_transport ferry outbound 0
5 2016-08-12 06:15:00 public_transport ferry outbound 0
Example data for 2016-08-16
from 4AM onwards:
No split between staff and student (as in goCard).
Automatic & manual counts are available for locations 1 (bikes) and 9 (pedestrians & bikes):
15 minutes interval directional infrared counters for bikes and pedestrians (separately) from 2016-08-12 to 2016-08-22 23:45:00.
# A tibble: 5 × 5
date type site direction count
<dttm> <chr> <chr> <chr> <dbl>
1 2016-08-12 00:00:00 cyclists green_bridge inbound 0
2 2016-08-12 00:15:00 cyclists green_bridge inbound 1
3 2016-08-12 00:30:00 cyclists green_bridge inbound 0
4 2016-08-12 00:45:00 cyclists green_bridge inbound 0
5 2016-08-12 01:00:00 cyclists green_bridge inbound 0
Example counts for 2016-08-16
across type and
direction.
2102 records of pneumatic bike counts for ‘Brisbane River Bike Path near Rowing Club E/W’ station in 15 or 5 minutes intervals from 2016-08-12 to 2016-08-22 23:15:00.
# A tibble: 5 × 5
date type site direction count
<dttm> <chr> <chr> <chr> <dbl>
1 2016-08-12 00:00:00 cyclists Macquarie inbound 0
2 2016-08-12 00:15:00 cyclists Macquarie inbound 0
3 2016-08-12 00:30:00 cyclists Macquarie inbound 0
4 2016-08-12 00:45:00 cyclists Macquarie inbound 0
5 2016-08-12 01:00:00 cyclists Macquarie inbound 0
Example counts for 2016-08-16
across type and direction
from 4AM onwards.
Pneumatic vehicle counts for
sites in 15 minutes intervals. 6336 records from 2016-08-12 to 2016-08-22 23:45:00.
# A tibble: 5 × 5
date type site direction count
<dttm> <chr> <chr> <chr> <dbl>
1 2016-08-12 00:00:00 vehicles Chancellors inbound 2
2 2016-08-12 00:15:00 vehicles Chancellors inbound 5
3 2016-08-12 00:30:00 vehicles Chancellors inbound 0
4 2016-08-12 00:45:00 vehicles Chancellors inbound 2
5 2016-08-12 01:00:00 vehicles Chancellors inbound 3
Few data points exist for observarions of car occupancy for weekday from the 2015 Survey (Tue 18th Aug).
loess.smooth
is fitted using data points plus mean
values added at the begining and end of the day.
Better data are available for weekend occupancy of cars from 13th Aug 2016.
Again, loess.smooth
is fitted using data points plus
mean values added at the begining and end of the day.
Counts of cars were corrected with average occupancy for week/weekends and rounded to integers.
Example counts for 2016-08-16
across type and
direction.
public_transport
, green_bridge
,
macquarie_bikes
, vehicles_occupancy
datasets
were combined.
With transport mode, example of one day:
Ignoring transport mode, example of one day:
Calculated by mode & site without modifications