The document discusses the transport planning team's capabilities in geographic information systems (GIS) analysis. GIS allows them to use big data to provide insights into areas of interest, such as identifying neighborhoods with high unemployment or populations educated to degree level or above. Examples are given showing unemployment and education level analyses for the Derby and Nottingham areas that could aid in locating labor resources or research facilities.

1. GEOGRAPHIC INFORMATION SYSTEMS
SOCIO-ECONOMIC CAPABILITY
The transport planning team have developed a significant capability in geographic information
systems, used for analysis. This enables ‘big data’ to be used to provide insight into particular
areas of interest.
Contact: Ian Kirk-Ellis, MSc,
I.Eng, FIHE, MCIHT, MTPS.
ACIWEM
Email: ian.kirk-
ellis@rodgersleask.co.uk
Rodgers Leask Ltd, St
James House,
St Marys Wharf, Mansfield
Road,
Derby, DE1 3TQ
Telephone 01332 285000
www.rodgersleask.co.uk
The analysis to the right has
been undertaken to illustrate
the percentage of unem-
ployed people within the local
super output area (between
1000-1500 residents).
From this clear areas of
higher unemployment can be
seen. This could be used to
identify areas of potential la-
bour resources.
An analysis undertaken ex-
amining the number of peo-
ple qualified at level 4 or
above has been undertaken
to identify areas where large
numbers of people are edu-
cated to HNC / Degree level
or above reside within the
Derby and Nottingham ar-
eas.
From this examination, the
areas that benefit from a
higher educated population
can clearly be seen.
This could be used to aid
identification of where to lo-
cate research facilities.
EXAMPLE 2: PERCENTAGE UNEMPLOYED (Derby / Nottingham Area)
EXAMPLE 1: LEVEL 4 (HNC / DEGREE OR ABOVE) - Derby / Nottingham Area