spatialdatavis

Visualizations using QGIS

Hotspot Clustering

The purpose of this visualization was to identify clusters of health facilities in the London Borough of Haringey in order to support healthcare service planning.

I discovered that certain areas of Haringay contained well-defined hotspots such as Crouch End, West Green, and Bowes. The pattern of areas which reflect these hotspots are the areas in Haringay which have the highest population density and the areas which have the greatest transportation links, as would be expected.

Network Analysis

The purpose of this visualization was to identify and measure the spatial accessibility to GP surgeries from London Underground stations in the London Borough of Haringey.

It was difficult to identify a pattern regarding spatial accessibility between transport and GP surgeries, however, it appears that there is not high accesibility in this borough. This was discovered because as seen in the visualization below, areas which are not overly accessible to underground stations contain large clusters. The large clusters are represented by the dark red triangles. Ideally, a transportation map would be overlaid behind the clusters, but this was not possible due to resolution challenges with transport maps.

Thematic Mapping

The purpose of this visualization was to create thematic maps to show spatial pattern of crimes in London.

To create this map a data set containing various crime variables was analyzed. The variables included in this data set were buglary, crime damage, drug offences, vehicle theft, and violent crime. All of which were based on counts per 1000 persons. The map below displays that crime rates are highest in the inner boroughs of London. In general it can be seen that crime rates are reduced as the boroughs reach further away.