Eight things you can do with GIS

Exploratory spatial data analysis

At the heart of what we do for clients, the spatial statistical analysis and visualisation of data across space, as well as the combination of multiple datasets unified by location, reveals insights which two-dimension stats analysis rarely can. We are also currently developing spatial data mining techniques that build on our expertise in this area.

Analysis of customer and survey data in relation to spatial distribution and contextual social, economic and demographic data

Our work for Turley Associates added layers of insight to retail survey data through geographic analysis of respondents, revealing strong transport-link and socio-economic drivers to shoppers’ location choices; we are also working with local authorities and their market research providers to analyse results of statutory performance surveys.

Creation of added-value composite datasets

We created the Index of Town Centre Activity for DCLG, based on multiple unrelated urban indicators brought together to derive a single, comparable national metric to define the extent and boundaries of town centres in England and Wales. Given appropriate data, this methodology is readily applied to other combinations of data, creating single metrics which are readily understood and compared over time or space.

Location analysis in the context of catchment, drivetime and contextual social, economic and demographic data

Having refined these techniques in work for various clients, we are now making our data warehouse, analysis and visualisation tools available to clients online. We’re also in development with a tool providing UK urban retail and property data down to street and individual building scales.

Geographically weighted regression

A key statistical technique which enables the spatial distribution of data to be meaningfully incorporated and given appropriate weight within their analysis; again, highly relevant to commercial location and survey result analysis.

Hedonic modelling of market drivers

Successfully applied in our work isolating the contribution of the 1990s extension to London’s Jubilee underground line to residential property value uplift around its new stations, this technique tests the influence of multiple drivers in complex markets.

Sampling framework analysis

We created the spatial sampling strategy methodology for the UK’s Consumer Price Index (the key measure of inflation in the UK economy), which combined the statistical requirement for the sample to be spatially representative of the consumer economy, with an operational requirement for the data collectors to travel efficiently around robustly defined sample areas.

Historic and predictive commercial modelling

Grosvenor Estates use our applications to identify relatively under- and over-valued properties in their premium Central London property portfolio; time series data can also be used (with care) to future cast according to multiple market scenarios.

No Comments Yet.

Leave a comment