Efficient trajectory data handling
This talk presents MovingPandas, a new Python library for dealing with movement data.
Movement data analysis is a high-interest topic in many different scientific domains. Even though Python is the scripting language of choice for many analysts, there is no Python library available so far that would enable researchers and practitioners to interact with and analyze movement data efficiently. MovingPandas development is based on an analysis of state-of-the-art conceptual frameworks and existing implementations (in PostGIS, Hermes, and the R package trajectories). We describe how MovingPandas avoids limitations of SimpleFeature based movement data models commonly used in the GIS (geographic information systems) world. Finally, we present the current state of the MovingPandas implementation and demonstrate its use in stand-alone Python scripts, as well as within the context of the desktop GIS application QGIS. This work represents the first steps towards a general-purpose Python library that enables researchers and practitioners in the GIS field and beyond to handle and analyze movement data more efficiently.