Dynamic Flow is a qgis plugin to estimate the spatio-temporal 3D gradient flow from the point observation of the attributes values such as aggregated cell-phone mobility data. The algorithm was based on the image-processing techniques which provided a two-step 3D gradient method to extract the movement features. The first step is to estimate the initial movement pattern in each spatiotemporal grid, and then to estimate the accumulated movement pattern within a time period around a geographical grid. This method can be applied adaptively to multi-scale spatiotemporal grid data. Using geospatial visualization methods, estimated motion characteristics such as velocity and flow direction can be made intuitive and integrated with other multiscale geospatial data.

The introduction of the algorithm: Bo-Cheng Lin, Ta-Chien Chan*, 2022, “Visualizing Population Mobility from Spatio-temporally Aggregated Mobile Phone Data via a 3D Gradient Approach”, TRANSACTIONS IN GIS, https://doi.org/10.1111/tgis.13008

The tutorial data: Bergroth, C., Järv, O., Tenkanen, H., Manninen, M., Toivonen, T., 2022. A 24-hour population distribution dataset based on mobile phone data from Helsinki Metropolitan Area, Finland. Scientific Data 9, 39. https://doi.org/10.1038/s41597-021-01113-4 (https://zenodo.org/records/4726996)