Many data are not readily in spatial format. For example, data from wearable devices, surveys, and social media platforms such as Facebook and Twitter have GPS location information, but usually in raw Lat/Long format. For social scientists who do not have strong background in Geographic Information System (GIS), compiling and analyzing spatial data from the aforementioned sources can be tedious and error-prone.
GPS2space is an open source solution to this issue and can ease the processes of compiling and calculating activity spaces based on raw Lat/Long coordinate pairs.
The primary goals of
GPS2space are: 1) to build spatial data from raw Lat/Long coordinate pairs and make the process less painful for social scientists with little GIS background; 2) to build minimum bounding geometry from Points using buffer, convex hull methods, and use activity space as building box to calculate shared space at different scales; 3) to calculate the nearest distance from user-defined landmarks (currently only support Point-Point nearest distance query).