Mapping resources can be used for any manner of data collection, of which a variety of*geostatistical analysis can occur, one of the more familiar of these being graphs. Creating a*graph from multiple data sets sourced from multiple maps can be an easy, straightforward*process when broken down into steps.*The example I’ll be using here is an athletics map, one created to mark the locations of*upcoming events for a collegiate sports team. By taking the location data and gathering the*information on match wins, it’s possible to take initial points displaying a particular manner of*information and extend them to portray a new perspective on the data; more specifically,*analyzing the number of wins for a women’s football team in relation to both location (away vs.*home) and weather.This data surveying took place over a span of a month, with individual weeks being broken*down into their own respective diagrams.Creating the aforementioned diagrams from this data is relatively easy, and can be shown*through any basic bar graph, as displayed. Two were made per each week, one displaying the*away matches vs. the amount of wins that were achieved, while the other displayed the same*information regarding home games.
While bringing in this information, I concurrently incorporated data from The Weather Channel’s*interactive map. Weather information here could be utilized in two main ways, the first being the*weather during the event itself, causing a direct action on the match. The second is the average*weather forecast, which could have an indirect effect such as a change in location or other*modifications.http://geoawesomeness.com/wp-content/uploads/2017/03/Video.mp4
When extracting this data and presenting it in a new format, it can then be displayed alongside*the match data points, showing possible correlations between wins, location and weather. In this*instance, this was achieved by taking the average weather per week, and creating a scatter plot*representation that can then be analyzed in correlation with the accompanying match results, as*shown below.
There’s a wide variety of visual representations that can be made using GIS data, and being*able to create these graphs allows for further analysis that builds on the base map and its core*information.The post Utilizing map data to project a simplistic graph analysis appeared first on Geoawesomeness.
While bringing in this information, I concurrently incorporated data from The Weather Channel’s*interactive map. Weather information here could be utilized in two main ways, the first being the*weather during the event itself, causing a direct action on the match. The second is the average*weather forecast, which could have an indirect effect such as a change in location or other*modifications.http://geoawesomeness.com/wp-content/uploads/2017/03/Video.mp4
When extracting this data and presenting it in a new format, it can then be displayed alongside*the match data points, showing possible correlations between wins, location and weather. In this*instance, this was achieved by taking the average weather per week, and creating a scatter plot*representation that can then be analyzed in correlation with the accompanying match results, as*shown below.