International Archives of Photogrammetry and Remote 
automate the process of identifying individual tree position, 
species and height for forest ecology studies. 
7 ACKNOWLEDGMENTS 
We thank the National Science and Engineering Research 
Council of Canada for funding the project. Our gratitude also 
goes to Lasermap ImagePlus (Boisbriand, QC, Canada) for 
providing the laser survey at a significantly discounted price, 
GENEQ (Ville d'Anjou, QC, Canada) for their very competent 
and timely help with GPS technology and methods, and ER- 
Mapper for its grant of image processing software. Finally, we 
wish to thank Patrick Dupuis and Christian Lavoix of UQAM 
for their very professional work as field assistants and GPS/GIS 
wizards. 
REFERENCES 
Flood, M., and Gutelius, B., 1997. Commercial implications of 
topographic terrain mapping using Scanning Airborne Laser 
Radar, Photogramm. Remote Sens., 63, pp. 327-366. 
   
Sensing, Vol. 32, Part 3W14, La Jolla, CA, 9-11 Nov. 1999 
Lefsky, M., Harding, D., Cohen, W.B., Parker G. and Shugart 
H.H., 1999. Surface lidar remote sensing of basal area and 
biomass in deciduous forests of eastern Maryland, USA, 
Rem. Sens. Env., 67, pp. 83-98. 
Naesset, E., 1997, Determination of mean tree height of forest 
stands using airborne lidar scanner data, ISPRS J. 
Photogramm. Remote Sens., 52, pp. 49-56. 
Nelson, R., Oderwald, R., and Gregoire, T., 1997. Separating 
the ground and airborne laser sampling phases to estimate 
tropical forest basal area, volume, and biomass, Rem. Sens. 
Env., 60, pp. 311-326. 
Ritchie, J.J., Evans, D.L., Jacobs, D., Everitt, J.H., and Weltz, 
M.A., 1993. Measuring canopy structure with an airborne 
las altimeter. Trans. ASAE, 36, pp. 1235-1238. 
Weltz, M.A., Ritchie, J.C., and Fox, H.D., 1994. Comparison 
of laser and field measurements of vegetation height and 
canopy cover. Water Resour. Res., 30, pp. 1311-1319. 
  
  
   
      
   
   
   
    
  
     
     
   
       
     
  
Laser survey characteristics 
Survey carried out by Lasermap Image Plus, 
Boisbriand, Canada 
Contact name : Pierre Bélanger 
WWW site : www.lasermap.com 
Flight characteristics 
Date of survey: June 28" 1998 
Plane: Piper Navajo 
Flight altitude for vegetation and ground: 700 m 
Flight speed for vegetation and ground: 65 m/s 
Area covered by the survey : approx : 8 km? 
Flight line width : 0.25 km 
Number of flight lines for vegetation and ground: 10 
Number of passes for vegetation: 2 
Number of passes for ground : 1 
Flight time for each pass: 80 minutes 
  
Laser characteristics 
Laser sensor: Optec's ALTM1020 built in 1995 
Impulse frequency: 4000 Hz, scan frequency: 16 Hz 
Power: 140 microjoules 
Laser wavelength: 1047 nm 
Ground spot size: 0.19 m 
Scan mode: zig-zag 
Maximum scan angle from nadir : 10 degrees 
Approximate X,Y,Z accuracy: +/- 15 cm 
Average hit density for vegetation: 1 hit/n? 
Average hit density for ground: 1 hit/2.5 m? 
Vegetation/ground separation : Optec's ALTM 
Positioning system characteristics 
Plane Trimble 4000 SSI kinematic GPS frequency: 1 Hz 
GPS base: Trimble 4000 SSE on a geodetic point 
Inertial system: Litton 
  
  
  
  
  
  
  
Table 1 — Scanning laser altimetry survey characteristics 
  
      
    
   
Flight date: September 27, 1997 
Flight time: 11h00 - 13h00 
Sun elevation: 37 - 39 degrees 
Flight altitude: 1890 m 
Spatial resolution: 50 cm 
  
Spectral bands (3 x 8 bits): 
- green = 520 nm - 600 nm 
- red = 630 nm - 690 nm 
- infrared = 760 nm - 900 nm 
  
  
   
   
      
Table 2 - Multispectral digital video survey characteristics 
International 
ROADS 
KEY WORDS: Digital | 
ABSTRACT 
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semi-automatically deline 
paper, emphasis is laid oi 
DTM actually representi 
detected by applying st: 
continuous) break lines. 
break line detection, a ne 
be interactively selected t 
candidate regions can be 
data and the rectified gi 
improvement of classific: 
paper the algorithms invo 
KURZFASSUNG 
Durch die Möglichkeit, ' 
möglich, vóllig neue Met 
für die Verwaltung solche 
Gebäuden aus Laserscan 
tatsächliche Erdoberfläch 
Verwendung von Standar 
sind, um „gute“ (lange. 
kantenverstärkenden Filt 
Geländemodell abgeleitet 
werden können. Weiters 
verbessert werden. Kandi 
pulse-“ Daten und des 
Klassifizierung von Diffe: 
wobei das Hauptproblem 
werden die Algorithmen : 
Tests vorgestellt. 
1.1 Motivation 
The intensive utilisation 
cultivation. Especially the 
usually very time-consu