Download tool for AHN2 that delivers a LAZ file with the points inside a bounding box drawn by the user. Based on Flask and Openlayers 2.

MATAHN currently requires redis (http://redis.io) and postgres (http://www.postgresql.org) with postgis and the LAStools (http://rapidlasso.com/). These need to be installed first.

The recommended way to install MATAHN is using virtualenv and pip. Assuming you have working python (2.7) installation with these utilities, run these commands:

virtualenv venv

source venv/bin/activate

pip install git+https://github.com/tudelft3d/matahn.git

Now you need to create a MATAHN configuration file for you server:

wget https://raw.githubusercontent.com/tudelft3d/matahn/master/example_matahn.cfg

mv example_matahn.cfg matahn.cfg

edit this file to match you server setup. Then create an environment variable that points to this file:

export MATAHN_SETTINGS=/path/to/matahn.cfg

A postgresql database is required with postgis extension enabled. To create the tables required for matahn run these statements from a python shell:

from matahn.database import init_db

init_db()

In directory with laz files.

• adding gound class to filtered points (optional):

las2las -i g*.laz -set_classification 2 -olaz -odix _ground

• retrieve metadata:

lasinfo -nc -nv -nmm -otxt -i *.laz

• add index (optional):

lasindex -append -i *.laz

in python shell

from matahn.tile_io import load_tiles_into_db

load_tiles_into_db('/path/to/*.laz')

Assuming both redis and postgresql are up and running. Run these commands to quickly start MATAHN:

celery -A matahn.celery_app worker

python -c 'import matahn; matahn.app.run(use_reloader=False)'

Although for production use, you should use a proper WSGI server such as gunicorn.