depthmapX (formerly UCL Depthmap)

A specialized and lightweight piece of software designed to analyze your urban built environment by generating a map of open space elements.

Download Now

depthmapX (formerly UCL Depthmap) Description

depthmapX is a complex software application that specializes in performing a series of spatial network analyses meant to make you understand the social processes within the designed environment.

The base of this application relies on the ‘Embodied Space’ theory that explains the natural visual interaction between an individual and its surrounding environment. To test this theory, depthmapX was developed to enable you to create a model architecture that simulates the natural movement of patterns in constructions and urban areas.

Create a link between the individual and the environment

depthmapX operates at a variety of scales from houses to small or large cities, and even states. With each scale, the purpose of the application is to generate a map of open space elements, connect them through intervisibility or overlap relationships, then perform the graph analysis of the resulted network.

To generate an agent analysis, firstly you need to create a new graph, then import a drawing file in either DXF or MIF format. The imported drawing should have closed boundaries in order to create the Visibility Graph before starting with the agent tool. Once you have imported the file, you need to follow a few steps in order to create the visibility graph. You can set the grid by clicking the ‘Set Grid’ button and fill the enclosed spaces with the ‘Fill’ button. Then, click inside the area of interest to fill it with a color marking that highlights the space where agents can move.

Apart from allowing you to prepare the space for agent analysis, the application enables you to define the grid resolution and the boundary of your analysis in order to create the visibility graph using the ‘Tools’ menu.

Powerful spatial network analyzer

Overall, depthmapX is a professional multi-platform software whose objective is to derive variables from generated spatial network analyses that may have social or experimental importance. Due to its high level of complexity this application is destined for professionals but can be a starting point for novice users.

Leave a Reply

Your email address will not be published. Required fields are marked *