PySTPrism: Tools for voxel-based space-time prisms

Abstract The observed movements of humans and animals are realizations of complex spatiotemporal processes. Recent advances in location-aware technologies have rendered trajectory data ubiquitous. Examining the sequenced, instantaneous locations found in movement trajectory data for information reconstructing the location or state of the mover between observed points comprises a primary focus in Time Geography and related disciplines. The PySTPrism toolbox introduced in this paper provides a straightforward and open-source implementation of the Probabilistic Space Time Prism, in addition to related tools from Time Geography. PySTPrism is implemented in Python using the ArcPy module in ArcGIS Pro Desktop.

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