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Demand modelling with static data – GeoIT Wherecamp 2019

On the 14th of November, the 9th GeoIT Wherecamp was held at the TU Berlin. The conference focuses on the latest research and insights around GeoIoT, GNSS, digital mapping, (autonomous) mobility and spatial intelligence of the GeoIT domain including industry and academic institutions. Jesse Hinrichsen presented an approach on how to predict movements with geostatic data.

Information on how people move within urban areas enables a wide range of application. Shared mobility companies can use this information to optimize their business areas, public transportation companies can enhance their timetables and routes. Recently, mobile network providers have started distributing their data as origin-destination matrices as a basis for such use-cases. civity is developing a demand model trained on aggregated mobile network data to address areas not covered by the provider’s data. In contrast, a lot of open, geospatial data exists which can describe the underlying area in detail. Applying statistical methods and recent machine learning approaches enables the possibility to predict movements with geostatic data.