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Welcome to the AHN2_Kadaster wiki!

Goal

The basic goal is to use the kadaster data to classify all points in AHN2 and AHN3 into, e.g. road, water, building, other. The Challenge here is to filter the point cloud data through the polygons provided in the Kadaster files as efficiently as possible to avoid excessive computational times. After a previous conversation with you and Jisk I had gathered that there is experience at the center in doing this, e.g. by use of indexing and a database. As we hadn’t started on this in the context of eEcoLiDAR yet, but it is high on the to-do list, it crossed my mind when Elena asked whether there might be a way eEcoLiDAR could benefit from the sprint. I have the Kadaster data downloaded and/or will make sure to have it before the sprint, and the AHN data is also present, as you well know. My naïve guess was that at the very least setting up the infrastructure to process the data could be achieved during the sprint if someone with expertise in this regard were on the team. After that it would only be a question of running it on the VMs. Beyond advancing the project, it would also result in a AHN data sets with highly accurate point classifications which could be published by NLeSC as a resource, facilitating further open use of the AHN data sets.

Extra info

The instructions for mounting the eecolidar-webdav can be found in the above repository https://github.com/eEcoLiDAR/miscellaneous/tree/lidar_tilling/utils

Previous NLeSC Knowledge (Should be very relevant)

http://knowledge.esciencecenter.nl/content/pcdms_usage_guide.pdf

eEcoLiDAR Github

https://github.com/eEcoLiDAR/ and in particular https://github.com/eEcoLiDAR/miscellaneous/tree/lidar_tilling

Databases

PostgreSQL

Main page

https://www.postgresql.org

Resources/tutorial

https://www.postgresql.org/docs/ https://www.postgresql.org/docs/online-resources/

PostGIS

Main web page

https://postgis.net

Intro/tutorial

https://postgis.net/workshops/postgis-intro/

Pointcloud data and tools

Point cloud visualisation

CloudCompare https://www.cloudcompare.org

Fugroviewer

https://www.fugro.com/about-fugro/our-expertise/technology/fugroviewer

Geospatial data visualisation

QGIS 3

https://www.qgis.org/en/site/

Pointcloud data format(s)

LAS/LAZ

Format definiition https://www.asprs.org/wp-content/uploads/2010/12/LAS_1_4_r13.pdf

Tools

LAStools

https://rapidlasso.com

PDAL

https://pdal.io/index.html https://pdal.io/stages/filters.overlay.html

NL Kadaster data

https://www.pdok.nl/introductie?articleid=1976855

AHN2 data

https://www.pdok.nl/introductie?articleid=1948857 This data resides on the surf hosted webdav server as detailed in the eEcoLiDAR GitHub