Original: http://tecdat.cn/?p=4001
Overview
Done O2O (Online To Offline, online and offline / online to offline) small partner knows, require specific data to GIS fine location (i.e., latitude and longitude); for the chain stores, the GIS, and other data-intensive services follow a simple logic: data can help companies save money, but also to prevent the wrong decisions because the companies set up shop in inappropriate locations leading to the waste of money.
Metro is not only a transportation track, it is a city of blood, is observed and recorded one of the most important entry point for urban economic life, is characterized by subway, subway and down, such people are FMCG crowd. For users FMCG brand positioning, through our acquisition of the mobile client the surrounding area of Singapore subway station location data, combined with data decision model to help clients avoid risks.
data collection
The collected data is divided into two parts: 1, subway station latitude and longitude information. 2, the client user location information
Subway station latitude and longitude information
User client location data
Then we count the number of users within 200m of each subway station nearby, descriptive analysis and GIS data visualization.
Data Summary
Each position of FIG subway station
Statistics of the overall proportion of the number of users in different subway station 200m
By analyzing data description, we can see that the number of users in each subway station location and a single subway station 200m.
GIS Visualization
In order to visually express the number of users per metro station, the data we visualized on the map, with the size and depth of color dots to represent the number of users.
Subway shop location for chain stores, can not simply look at a single subway flow of people, the flow of people surrounding the subway's "interaction effect" is also very important to find high traffic metro station "area" tend to be more reliable results. Therefore, we draw the number of users by contour map to determine which area subway stations have more people traffic.
Finally, considering the popular subway stations, and the number of single people flow subway station siting decisions.
Follow outlook
We hope to be able to add more in the future dimensions of data and analysis methods, to determine the number of potential customers by age, gender, comprehensive improve the evaluation system, the subway station to rate observed trajectory of business change and economic development.