From Geoblink we want to celebrate the GIS Day by sharing with you our last improvement in the catchment areas computation.
As Carlos explained in this previous post, at Geoblink we take advantage of the benefits of the graph theory for computing the catchment area of a location. Thus, we define our graph as a set of intersections (nodes) connected by street/road segments (links), and we add to both, nodes and links, some properties that define them.
The new property added to our links is the traffic peak, which allows us to compute catchment areas considering rush hours. Therefore, we first define a location of interest. Secondly, we apply our set of algorithms to our graph for computing the catchment area of the location of interest, specifying if the rush hours must be considered or not. As a result, we obtain a set of intersections and streets/roads segments that make up the catchment area of the location of interest with or without considering traffic peaks.
But, how does it work? Let’s compute the Geoblink’s catchment area traveling 5 minutes by car, not considering the rush hours and considering them.
As you can see, the resulting catchment area taking in consideration peak traffic is smaller than the other one. The addition of the traffic peak property to our street/road segments allows us to provide to our clients a more accurate catchment area when rush hours must be considered.