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Collecting and validating geospatial data for every commercial location in the USA and Canada is not an easy task. It requires aggregation of data from multiple sources and formats. This data then needs to be validated and decisions need to be made about which data sources represent the truth in the case of conflicting data. Safegraph does this weighing datasets based on certain criteria and using a voting system.
Data is being scraped and curated from multiple different sources but it some cases it is also necessary to create data. Think of the use case of a shopping center. If you think of the shopping center as being a collection of geometries where the entire shopping center is the parent geometry and the individuals business in the shopping center are child objects. In this situation, Safegraph has had to digitize entire shopping centers manually in order to properly represent the parent/ child geometry relationships.
This episode is sponsored by HiveMapper
A platform that takes video and creates 3D mapping layers based on that data. The video can be from avariety of different sensors, does not need to be vertically looking down on the geography and each 3D output is georeferenced!
For most people, when they think aboutthe relationship between GIS and COVID-19, the obvious solution is tracking data. At the highest level, if there is any spatial relationship between where we are in our societies, where we go, who we interact with, and spread the disease, our measurements, thenour policy tools must also have a geospatial component to capture that effect.It's not a question of whether spatial data and spatial analysis matter for COVID-19. The problem is understanding what tools exactly can be used for specific insights and decisions.