| Using a space filling curve for the management of dynamic point clouds in a relational DBMS setting. |
The code used for the thesis 'Using a space filling curve for the management of dynamic point clouds in a relational DBMS setting'.
Abstract: --------Over the last years, point cloud usage has seen a rapid growth and it is expected that this growth will become even bigger in the years to come. Apart from large-scale projects being undertaken every few years, the development of low-cost and easy-to-use devices make it now possible to perform repeated scans of the same area on a frequent basis (daily, hourly etc.). These spatio-temporal point clouds although very relevant for many applications, lack efficient management.
This repository contains the code generated as part of a thesis undertaken at TU Delft (Netherlands) and the research institute Deltares that explores ways to efficiently manage spatio-temporal point clouds. Within this a space-filling approach is followed along with two variations of space and time integration.
- Use iterator when fetching the data and not fetchall() in one go
Free software: ISC license
This package was created with Cookiecutter and the audreyr/cookiecutter-pypackage project template.