Subject: Spatial Networks / Congestion Heatmaps
Spatial network Analysis systems are a graph based analysis tools. A kind of Computational design tools which are used to analyze the interrelations between the correlated elements in a system.
we tend to analyze the different relation between randomly scattered items in the space using computation and parametric tools. In these comparative studies, you can study elements relations by measuring distances, or compare the sizes, color or heights. you can group results according to similarities or segregate according to differentiations. In Networked systems, elements don’t react directly with each other. participants are organized and placed in a kind of structuring that doesn’t feature linearity. it’s more like a matrix. An element is connected to a network of other approximated(adjacent) elements. the form of connectivity itself vary from element to another. some elements are connected to more neighbors, and that what we call a topological attribute. some elements are typically interrelated, but however, it comes with different geometrical attributes, for example, it would be placed within unique distance, or it may be angled(tilted) reversibly, but still within the network matrix.
One of the advantages of this computational tool that it allows us to figure out the map and the settings of a graph we are working on, it visualizes its nodes and the connecting graphs. usually, it’s represented as a network of numbered nodes within circles, and each circle is connected to a number of neighboring nodes by an arc. the tool can also help as to analyze and rank nodes according to their topological and geometrical attributes. We can deconstruct the network into its original form as points and curves(lines), or we can convert it into a complex Surface(Mesh). The unique thing about these tools its ability to use the syntax to draw a flow system which can optimize the connectivity between the nodes; that mean you can connect all the nodes by the minimum number of graphs, or you can jump from point A to point B using the shortest path or the fastest one.
we use spatial analysis to work with dynamic systems and flowing interactions.It’s a kind of systems which we need it to solve complex interactive problems, for example when we have clusters of elements with multiple data layers( attributes or time) . this kind of data is not enough once it’s classified (categorized ) and visualized, its aggregation requires another level of analysis, sometimes it requires scaling, weighing or measuring density.
it’s widely used in solving problems of graph coloring, drainage water flow or connecting imbricated structures. it’s also used to measure probabilities and risks. it mainly uses algorithms accrediting properties of reachability, gravity, betweenness, and closeness. it can deviate between a status of straightforwardness or manoeuvring. for example, you can calculate the possibilities of going from your location (A) to your destination (B), using conditions of passing by nodes(C & D) and at the same time to prohibit nearing the Node(E).
In Urbanism and city planning, you can benefit from these tools in understanding the complex issues related to your city tectonics. the GIS data are enriched with loads of information which can be used to indicate patterns or investigate the hidden characteristics of elements of cities, and therefore reveal the unseen issues, or predict what future bringing.
In this experiment, as I am working on a bigger research project concerned with the city of Khartoum. It’s a project which investigateس metropolitan characteristics of a metropolitan we didn’t recognize yet. it’s a kind of a proving effort for the city potentials. so ÷ needed to recall multiple computational design tools. ÷ started with GIS tools, Network analysis tool, and many other tools. this experiment initially trying to visualize the scale of congestion and disturbance caused by the central attraction points on the city streets matrix, its a kind of magnifying glass of the densification patterns and magnitudes.