Massive Point Clouds for eSciences

Using point clouds to their full potential

Image: Fugro

We are witnessing an increased significance of point clouds for societal and scientific applications, such as in smart cities, 3D urban modeling, flood modeling, dike monitoring, forest mapping, and digital object preservation in history and art. Modern Big Data acquisition technologies, such as laser scanning from airborne, mobile, or static platforms, dense image matching from photos, or multi-beam echo-sounding, have the potential to generate point clouds with billions (or even trillions) of elevation/depth points. One example is the height map of the Netherlands (the  AHN2 dataset), which consists of no less than 640.000.000.000 height values.

The main problem with these point clouds is that they are simply too big (several terabytes) to be handled efficiently by common ICT infrastructures. At this moment researchers are unable to use this point cloud Big Data to its full potential because of a lack of tools for data management, dissemination, processing, and visualization.

Within this project several novel and innovative eScience techniques will be developed. Our work will also result in proposals for new standards to the Open Geospatial Consortium (OGC) and/or the International Organisation for Standardisation/Technical Committee 211:

Enjoy our AHN2-webviewer at http://ahn2.pointclouds.nl/

The goal is a scalable (more data and users without architectural change) and generic solution: keep all current standard object-relational database management system (DBMS) and integrate with existing spatial vector and raster data functionality. Core support for point cloud data types in the DBMS is needed, besides the existing vector and raster data types. Furthermore, a new and specific web-services protocol for point cloud data is investigated, supporting progressive transfer based on multi-resolution. Based on user requirements analysis a point cloud benchmark is specified. Oracle, PostgreSQL, MonetDB and file based solutions are analyzed and compared. After identifying weaknesses in existing DBMSs, R&D activities will be conducted in order to realize improved solutions, in close cooperation with the various DBMS developers. The non-academic partners in this project (Rijkswaterstaat, Fugro and Oracle) will deliver their services and expertise and provide access to data and software (development).

Participating organisations

Delft University of Technology
Fugro
Netherlands eScience Center
Environment & Sustainability
Environment & Sustainability
Oracle
MonetDB Solutions
Rijkswaterstaat

Impact

  • 1.
    Author(s): Giuseppe Patanè, Michela Spagnuolo
    Published in 2016

Output

Team

PvO
Peter van Oosterom
Principle Investigator
Delft University of Technology
Oscar Martinez Rubi
Oscar Martinez Rubi
Romulo Gonçalves
Romulo Gonçalves
TT
Theo Tijssen
Co-applicant
TU Delft
Elena Ranguelova
Elena Ranguelova
eScience Coordinator
Netherlands eScience Center

Related projects

MobyLe - Motion by Learning

Estimating Motion of Objects on Earth from Space

Updated 2 months ago
In progress

nD-PointCloud

continuous level representation for spatio-temporal phenomena in Open Point Cloud Maps

Updated 14 months ago
Finished

CHEOPS

Verified construction of correct and optimised parallel software

Updated 22 months ago
Finished

Enhance Your Research Alliance (EYRA) Benchmark Platform

Supporting researchers to easily set-up benchmarks

Updated 18 months ago
Finished

SecConNet Smart

Smart, secure container networks for trusted big data sharing

Updated 22 months ago
Finished

PROCESS

Providing computing solutions for exascale challenges

Updated 22 months ago
Finished

eEcoLiDAR

eScience infrastructure for ecological applications of LiDAR point clouds

Updated 22 months ago
Finished

Triple-A 2

Accelerating astronomical applications 2

Updated 22 months ago
Finished

Big Data Analytics in the Geo-Spatial Domain

Empowering geo-spatial analytics with database technology

Updated 18 months ago
Finished

Mapping the Via Appia in 3D

Developing a 4D geographic information system for archaeological purposes

Updated 19 months ago
Finished

Related software

AHN2 pointcloud viewer

AH

A web application able to visualize the AHN2 point cloud data of the Netherlands.

Updated 12 months ago
24 3

AHN point cloud viewer web service

AH

A web service to serve large point cloud data efficiently using octrees.

Updated 27 months ago
1 2

Massive PotreeConverter

MA

Use parallel processing to quickly convert large point cloud data sets to the format used by the Potree viewer.

Updated 27 months ago
1 3

PattyAnalytics

PA

Library for aligning and scaling one point cloud to an other.

Updated 27 months ago
9