Processing lidar and UAV point clouds in GRASS GIS (workshop at FOSS4G Boston 2017)

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Abstract: GRASS GIS offers, besides other things, numerous analytical tools for point clouds, terrain, and remote sensing. In this hands-on workshop we will explore the tools in GRASS GIS for processing point clouds obtained by lidar or through processing of UAV imagery. We will start with a brief and focused introduction into GRASS GIS graphical user interface (GUI) and we will continue with short introduction to GRASS GIS Python interface. Participants will then decide if they will use GUI, command line, Python, or online Jupyter Notebook for the rest of the workshop. We will explore the properties of the point cloud, interpolate surfaces, and perform advanced terrain analyses to detect landforms and artifacts. We will go through several terrain 2D and 3D visualization techniques to get more information out of the data and finish with vegetation analysis.

Requirements: This workshop is accessible to beginners, but some basic knowledge of lidar processing or GIS is helpful for a smooth experience.

Authors: Vaclav Petras, Anna Petrasova, and Helena Mitasova from North Carolina State University

Preparation

Software

GRASS GIS 7.2 compiled with libLAS is needed (e.g. r.in.lidar should work).

OSGeo-Live

All needed software is included.

Ubuntu

Install GRASS GIS from packages:

sudo add-apt-repository ppa:ubuntugis/ubuntugis-unstable
sudo apt-get update
sudo apt-get install grass

Linux

For other Linux distributions other then Ubuntu, please try to find GRASS GIS in their package managers.

MS Windows

Download the standalone GRASS GIS binaries from grass.osgeo.org.

Mac OS

Install GRASS GIS using Homebrew osgeo4mac:

brew tap osgeo/osgeo4mac
brew install grass7

Note that currently (summer 2017) r.in.lidar is often not accessible on Mac OS, use r.in.ascii in combination with libLAS or PDAL command line tools to achieve the same. Note also that the 3D view may not be accessible.

Data

Basic introduction to graphical user interface

Basic introduction to Python interface

Decide if to use GUI, command line, Python, or online Jupyter Notebook

Binning of the point cloud

Interpolation

Terrain analysis

Visualization, profiles and statistics

Vegetation analysis

3D visualization

3D visualization of DSM with orthophoto draped over

We can explore our study area in 3D view (use image on the right if clarification is needed for below steps):

  1. Add raster dsm and uncheck or remove any other layers. Any layer in Layer Manager is interpreted as surface in 3D view.
  2. Switch to 3D view (in the right corner of Map Display).
  3. Adjust the view (perspective, height).
  4. In Data tab, set Fine mode resolution to 1 and set ortho as the color of the surface (the orthophoto is draped over the DSM).
  5. Go back to View tab and explore the different view directions using the green puck.
  6. Go again to Data tab and change color to viewshed raster computed in the previous steps.
  7. Go to Appearance tab and change the light conditions (lower the light height, change directions).
  8. When finished, switch back to 2D view.

See also