This document discusses incorporating Google Street View imagery into a local land and property gazetteer (LLPG) using FME. It introduces the speaker and the LLPG. It then describes a workflow in FME that takes OS Highways data, finds the closest street point to each address point, calculates the viewing angle, and generates a Street View URL template with the coordinates and angle for each address. Examples of the generated Street View URLs are provided. The document concludes that FME is capable of handling complex tasks like processing millions of points and automatically generating URLs.

1. Incorporating Google Street
View Imagery with the
LLPG
Sam Tizzard, London
Borough of Harrow

2. About Me
Studied:
• Geography with Natural Hazards (BSc) at
Coventry University
• Volcanology and Geological Hazards
(MSc) at Lancaster University
I am currently a GIS Analyst/Technician
for the London Borough of Harrow (since
January 2015).
I have been using FME for around 8 months
now.
Sam Tizzard – just a little bit about me

3. The LLPG?
The LLPG (local land and property gazetteer):
• Is an address database of all land and property within
an authority
• Forms part of the NLPG (national land and property
gazetteer)
• Integrated with many systems at Harrow and used for
property searches within our ‘Harrow Address Lookup’.

4. Current Address Look Up

5. Provides a 360 degree
view of the world along
mapped routes or
spheres.
Accessible via an API:
https://developers.google.com/
maps/documentation/streetview/
Free for under 25,000
hits a day!!!

6. Why not use FME?
LLGP Address Data
from the LLPG
Integrator Process
‘LLPG Features’
Street Data from
OS Highways Data
‘Road Points’
Calculate:
Nearest ‘Road Point’ to
each ‘LLPG Feature’
WGS84 Conversion of
the ‘Road Points’
Co-ordinates stored as
attributes only
Angle between each
‘LLPG feature’ and
nearest ‘Road Point’
Build
Google
Street view
API URL and
wrap in
href’s

7. 1. Takes OS Highways Data
(currently BETA).
2. Removes unwanted
records.
3. Merges street
information and road
network.
4. Tidies attributes.
5. Divides streets into
points at every metre.
The Workspace (part 1)

8. 1. Finds the closest street
point to every address
point
2. Creates an extra vertex
per features using the
road points .
3. Calculates the azimuth
of the line between
address point and road
point
4. Calculates actual angle
5. Creates Streetview URL
The Workspace (part 2)

9. The Generated URL
Template URL:
https://maps.googleapis.com/maps/api/streetview?size=600x600&location=@
Value(URL_LATITUDE),@Value(URL_LONGITUDE)&heading=@Value(AZIMUTH_
ANGLE)8&pitch=0&key=[API KEY]
Working URL:
https://maps.googleapis.com/maps/api/streetview?size=640x640&location=51
.5702293,-0.3451858&heading=326.5473190230258&pitch=0&key=[API KEY]

10. Example 1
In Inspector: URL And Image:
https://maps.googleapis.com/maps/api/streetview?size=600x600&loc
ation=51.5702293,-0.3451858&heading=326.5473190230258&pitch=
0&key=[API KEY]

11. Example 2
In Inspector: URL And Image:
https://maps.googleapis.com/maps/api/streetview?size=600x600&loc
ation=51.5873401,-0.3426364&heading=153.9711372925798&pitch
=0&key=[API KEY]

12. Concluding Points
1. FME has a great capability to
use ‘templates’ (e.g. a URL)
2. FME can almost handle any
task (even when processing
nearly six million points!)
3. Workspaces can always be
improved

13. Thank you!
For not making me use the
sprinklers.
Any questions?
Feel free to contact me at:
Sam.Tizzard@harrow.gov.uk