Full text: Proceedings, XXth congress (Part 2)

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International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol XXXV, Part B2. Istanbul 2004 
  
= workflow management 
« Storage resource management 
= quality control 
= documentation and report generation 
= simultaneous multi-user and network capabilities 
= flexible process scheduler for running time-consuming 
tasks automatically during suitable periods 
The user meets a consistent, easy-to-use interface, including 
* graphical project organizer, process scheduler, and 
workflow monitor 
" fast and flexible data viewer giving visual access to the 
data in a variety of display modes in multiple synchronized 
windows and with efficient display control mechanisms, 
* intuitive and efficient data editor with instant visual 
feedback for interactive operations 
=» comprehensive online help features on several levels. 
LasTools is able to manage, process, and visualize 3D-point, 
vector, 2D-raster, and volume data simultaneously. Therefore, it 
is ready to handle the output of advanced lidar systems 
recording echo waveforms. An open data interface architecture 
allows LasTools to be easily expanded with additional 
processing capabilities in the future, as well as giving third- 
party developers and users with special requirements access for 
customized applications. 
Within the scope of this paper, we will focus on two aspects of 
LasTools in more detail: project management and classification. 
2. PROJECT AND DATA MANAGEMENT 
2.1 Project Organization and Data Management 
A project in LasTools is organized as one or several regions, 
each of which contains one or more blocks. Blocks are 
considered elementary coherent survey areas. Data is acquired 
in flights (between one takeoff and landing) collecting one or 
more /racks of data that may cover a single or multiple blocks. 
While flights and tracks result from sequential data acquisition 
and thus represent the temporal structure of a project, regions 
and blocks reflect its spatial organization. A flight will usually 
be done with a single lidar sensor and one set of calibration 
values. A block may, however, contain data from several flights 
with different sensors and calibration sets. LasTools maintains a 
database that relates flights, tracks, blocks, and regions with the 
relevant sensor descriptions and calibration data sets. 
  
Project 
   
  
- Subblock | 
| 
Tile | 
  
  
  
  
  
Figure 1. Project layout 
Regions and blocks are defined by their perimeters (outline 
polygons) that are imported when a project is created. During 
import of track data (or its creation in the process of 
geocoding), outline polygons of tracks are generated to allow 
casy access to track-related information at later processing 
stages when data of multiple tracks has been merged. 
File Header 
Coordinate Header 
  
    
Point Coordinate Layer 
    
  
Data Pyramid 
Point Density 
Elevation 
Height Difference 
Point Coordinates 
returns 1 
returns n 
  
      
     
  
  
  
  
Timestamp Layer Timestamps 
Track ID Layer Track ID Header 
Track IDs 
Point Class Header 
Point Classes 
Point Class Layer 
| 
! 
1 
1 
! 
I 
I 
I 
1 
I 
1 
I 
I 
! 
Intensity Layer Intensity Header 
1; Intensity Data Pyramid 
Intensity Values 
! 
Surface Color Layer Surface Color Header 
!__Color Data Pyramid 
; Color Values 
I 
| 
1 
! 
1 
I 
I 
1 
! 
I 
I 
Waveform Data 
Layer 
Waveform Header 
Waveform Base Data 
Endpoint coordinates, vectors, 
waveform data array indexes 
Waveform Arrays 
Figure 2. Subblock file layout 
The geocoded lidar measurement points are held and organized 
in blocks. Blocks are subdivided into square subblocks for 
manageable file sizes (subblocks are the storage units) which 
themselves are divided into tiles for rapid location-based access. 
Subblock files hold in a meta-data structure basic lidar data 
(point coordinates) and attribute information (time stamps, track 
identifier, return signal intensity, surface point color, point 
class, etc.) in multiple segments or layers. The sequence of data 
in all layers is identical allowing the relevant information of 
any point to be accessed directly and rapidly by indexing from 
the layer start while maintaining a fully bi-directional 
relationship between coordinates and attribute values on the 
level of single measurements. This organization also makes it 
easy to include additional attributes without having to change 
the basic file structure and access mechanisms. 
For example, the inclusion of digitized waveform data from the 
advanced lidar systems is easily accomplished as an additional 
layer of data. For each laser measurement, a variable-length 
array of waveform samples plus azimuth and incidence angle 
values of the beam direction and the coordinate of the last 
sample is appended to the subblock files. While file sizes 
increase substantially by including waveform data, the layered 
organization of the files does not require the entire file to be 
read for performing geometric operations, so processing speed 
is not compromised. 
To further speed up data access and display at coarser levels, 
each subblock contains aggregated surface height, height 
 
	        
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