First look at LIDAR


This has been a very busy and intense week. Deviations from routine are — at least most of the time — welcome, disinfection and particularly so in this case.

LIDAR is a fascinating technology, psychotherapist which until last week I always thought to be very overrated. People were always presenting pretty pictures, but nothing really useful. Last Friday we had a meeting where we discussed using LIDAR, aerophotography, Quickbird and field measurements in some native forest to obtain stand level attributes and make thinning decisions. Finally a practical application!

On Monday David, Jamie and I got the text files (with x, y and z coordinates, and intensity). The files were huge, with a total of 150,000 points to describe 10 ha. I first read them with Splus and R, which clearly didn’t like much the size of the matrices. Maybe Splus 7 developer (with the new pipeline architecture) works better, but I do not have a copy yet.

At the same time, I imported the data into MayaVi (which uses VTK) using an adaptation of this Python script and producing the following visualisation to get a feeling of the site. It is easy to interact with the picture, and one can see the road and the difference between old trees and regeneration. However, it is still pretty useless.

LIDAR data in MayaVi

Trying to work with individual (non-grid) points proved to be fruitless. The size of the problem is huge, and trying to use any spatial statistics contained in the R module spatstat was hopeless. Trying to apply anything that requires a large distance matrix (150,000×150,000) is guaranteed failure.

Meanwhile, Jamie helped David to obtain crown and terrain surfaces using Kriging in SAGA.

LIDAR height surface

After transforming them in grids, and substracting them to get ‘true’ tree heights, David and I came up with a naive (slow but apparently effective) way of finding the top of the trees. After a few problems with the implementation and Simon’s help using a SQL query in Manifold, we were able to identify the tops and their respective heights. From there to a diameter/height and volume equations there is a small step.

Top of trees in small section

Now we need to move to ground truthing and thinning strategies.

PS. 2005-08-01. We are processing data from ground truthing and our work is looking even more promising.

Filed in forestry, software, statistics

There are 2 comments in this article:

  1. 14/01/2008Quantum Forest » Blog Archive » LIDAR ground truthing say:

    [...] First look at LIDAR Resucitating Quantum Forest [...]

  2. 14/01/2008Quantum Forest » Blog Archive » Ticking boxes say:

    [...] find very interesting that someone may question the time I spend working in this—particularly considering the important ramifications of this type of work—and prefers [...]

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