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Presentation of the Velas3D tool

Ravi Peters

Brett Rijnders

Michiel Degen

Why we made it?

"The handling of the points is because of the huge size not easy, and the accessibility is through the map tile system not optimal"

What did we create?

What can be done with it?

Future of this tool

What do we have?

Other Examples

Limitations/performance/scalability and reliability

The Velas3D tool is created and tested with a limited amount of tiles in the database. On this scale the tool works properly. What happens if we add all the available tiles of the Netherlands?

- More Clipping and Merging has to be done

- Far more dataspace needed

- Process will slow down

- Estimation of time will be less accurate

What's next?

Questions?

Research Question:

“Improving accessibility to and handling of AHN-2 LIDAR points in relatively large map areas”

Development in Height mapping

Goals and requirements.

User

- Access to LIDAR points easier and more intuitive

- Possibility to just select the map region of your choice and receive the points in that region

- Automatic procedure to guarantee low handling and delivery time.

- Give user more options for data format types ( xyz file, Las dem, Las zip.)

- Feedback to user about region of selection and size, selected tiles and average points on a square meter, total amount of points

Dataset - LIDAR points

With LAS you don't have to read whole file at once to know what your dataset contains

-> Computer can only open this part

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Security

Protection against MySQL injection

Look back to research question

Improvements

Whitelist of trusted email addresses

Confirmation mail

Confimation Link

Ascii format has to read all the points before you know what the file contains

Password protection

for downloadable files

Laz info

Free OpenGL LAS viewer

http://www.cs.unc.edu/~isenburg/lastools/

Compressed laz files are 10% of original file

Visualisation:

  • 3D pointcloud (in las viewer)

  • 3D landscape (triangulation)

  • 2D DEM image

20 MB laz

200 MB las

Advantage

Disadvantage

  • More download possibilities
  • Complex selections
  • Integrating Django framework
  • Introducing WFS
  • Online paying system
  • Put more tiles in database

- Wine does not work properly

- DEM tool is not bug free probably because of the first problem

- Las to laz functionality does not work properly. Probably has to do with apache permission to use Wine

- Selections in the interface can only be rectangular

- Interface is based on JavaScript quite heavily, so you need to have JavaScript enabled when using the interfaces

- The Google map has a coordinate system which is different form RD New. Even though this is dealt with transforming the tiles/selection, it introduces an inaccuracy in the selection.

  • less storage space needed
  • Reduced download size
  • Compessed format not supported by all programs (lastools can read/write from compressed format)

http://www.cs.unc.edu/~isenburg/lastools/

AHN-2 TOP10NL tiles in ASCII format

Top 10NL system

- Access to LIDAR points with Velas3D tool is more easy and intuitive

- Possibility to just select the map region of your choice and receive the points in that region

- Automatic procedure to guarantee low handling and delivery time.

- Give user more options for data format types ( xyz file, Las dem, Las zip.)

- Feedback to user about region of selection and size, selected tiles and average points on a square meter, total amount of points

AHN-2 ( Actueel hoogtebestand Nederland)

Webinterface uses

  • HTML/CSS
  • Javascript
  • KML

Goal: Collect elevation for the NL

Done With: Laser altimetry and the principles of LIDAR

Accuracy: 5 cm and minimum of 10 points per M^2

Ordening

  • Google maps
  • Shows available tiles
  • Selection tool, deals with crs projection
  • Dynamically shows tiles in current selection
  • Uses AJAX to communicate with backend

Demo

- Netherlands divided into different card tiles

- Ascii data stored in order of that tiles

Frontend

Accessibility

The LAS format is a binary format which supports storage of LIDAR data. With LAS it becomes possible to manage those large datasets.

Problem: The AHN tiles are delivered in the ascii format. When the data becomes too large (i.e. there are too many points within a tile) then it becomes impossible to open the ascii files and manage it.

- Different card tiles has to be bought separate

- Huge files delivered on DVD ( postmail)

- Delivery time More like weeks then days

-> Accessibility is far from optimal

For better handling of the ascii data points we use the LAS format:

LAS Format, what is wrong with .xyz?

Result?

Using

  • Apache/Modpython
  • Python
  • LibLAS tools
  • Client interaction using JSON
  • Executes submitted jobs
  • Does clipping and merging of LAS files
  • Monitor performance
  • Deals with security
  • Sends emails
  • Adding new tiles

Test Environment

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . LIDAR points . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

AHN-2 LAS Tiles

With DEM find direction of water flow in case of flooding

Open source

Requested data

(LAS or ASCII)

visibility analysis

  • Know areas that are visibile from a specific location
  • Area that can be reached by radar antenna
  • Light calculation
  • Flooding, evacuation plans

  • earthquake, check displacements

33,800 square kilometers

Backend

338,000,000,000 LIDAR points

classification

  • roads
  • buildings
  • forest
  • water

.xyz format

do research on beach profiles

We made a strong beginning (basic foundation), but everybody in the TU domain is welcome to add functionalities to the tool to make it more robust, efficient or more useful.

http://www.csc.noaa.gov/products/sccoasts/html/tutlid.htm

Problems

Uses MySQL

- What about the ordering of the points?

- Data (ASCII) is readable but unmanageable through the size

- Where to store and how to distribute the data?

  • Jobs
  • Tiles
  • Performance
  • Log

keep track of 'waddeneilanden' en 'waddenzee'

Construction site planning

  • know land height where you are building

Database

use it for verification

Easily determine extremes in your research area:

  • get highest/lowest point
  • get average height

Velas3d System

height distribution in a city

  • which part has high buildings?

Minor 3D Virtual Earth

B.S.Rijnders@student.tudelft.nl

R.Peters@student.tudelft.nl

M.J.M.Degen@student.tudelft.nl

Contact

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