7th Workshop on Forest Fire Management - EARSeL, European ...

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I - PRE-FIRE PLANNING AND MANAGEMENT
2 - Methods
There are two different types of ALS: (i) conventional scanners based on
discrete echo and (ii) full-waveform scanners. The conventional or discrete
echo scanners detect a representative trigger signal for each laser beam,
whereas the full-waveform (FW) laser scanning systems permit one to digitize
the complete waveform of each backscattered pulse. FW ALS data
allows us to have more control in the interpretation process of the physical
measurements, this enables the extraction of additional information
about the structure and the physical backscattering characteristics of the
illuminated surfaces. The FW ALS sensor can effectively penetrate vegetation
canopies and therefore it allows us to identify and better classify the
understory.
3 - Data analysis
The ALS survey was operated by GEOCART on the 26 th April 2007 and carried
out using a RIEGL Airborne Laser Scanner LMS-Q560 mounted on an
helicopter. The average point density value of the dataset is about 30
points/m2. The accuracy is 25 cm in xy and 10 cm in z.
Usually, laser scanning products can be classified by: (i) height; (ii) intensity;
(iii) RGB colours if an ortophoto is available; (iv) echo width. Herein,
we will focus on the elaboration we performed using both height, obtained
from the 3D point clouds, and ortophoto acquired at the same time as ALS
survey. Due to its ability to pass between plants or tree branches, ALS is
suited to assess both canopy and understory, but it is necessary to process
the ALS point cloud using appropriate numerical filters. For the case study
the elaborations were performed using a commercial software TerraScan
(Terrasolid, www.terrasolid.fi), which represents a high standard for the
laser data processing. TerraScan classification is based on a parametric
approach and develops according to an orderly sequence of stages decided
by an operator. In this case study, the classification of laser data was performed
using a strategy based on a set of “filtrations of the filtrate”.
Appropriate criteria for the classification and filtering were set to gradually
refine the intermediate results in order to obtain fuel height identification
and the discrimination between canopy and understory. The workflow
can be summarized as follows:
- Classify low point;
- Classify ground;
- Classify points below surface;
- Classify points by class;
- Classify points by height from ground for different heights;
- Classify isolated points;
- Shape identification and load computation.