The NetMob23 dataset offers a unique opportunity for researchers to access comprehensive spatiotemporal data on population density and origin-destination (OD) matrices across four low- and middle-income countries (India, Mexico, Indonesia, and Colombia) over the course of 2019 and 2020.
The population density (PD) dataset provides insights into the presence and density of mobile app users at different spatial (Geohash 3, Geohash 5) and temporal (3-hourly, daily) resolutions. It includes the number of data points and unique users within each spatial unit over time, enabling analysis of spatial and temporal population patterns.
The OD matrix dataset captures the flow of app users between different locations, offering information on the number of trips, trip duration, trip length, and number of data points per trip between origin-destination pairs at Geohash 3, Geohash 5, and H3 level 7 resolutions, across 3-hourly, daily, weekly, and monthly intervals. This allows for the study of travel patterns and spatial interactions.
The dataset was developed in collaboration with Cuebiq, using privacy-preserving aggregated data from mobile app users who have voluntarily consented to anonymous data collection for research purposes. Several measures were taken to ensure a high level of privacy, including spatial encoding, temporal aggregation, and exclusion of cells with fewer than 10 users.
The dataset can support a wide range of research applications, from transportation planning and disaster response to socioeconomic analysis and tourism studies in low- and middle-income country contexts, where mobile data-driven insights are particularly valuable. Researchers are encouraged to combine the dataset with complementary sources, such as demographic surveys, geospatial data, and environmental indicators, to gain deeper, more contextualized insights.
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