Full text: International cooperation and technology transfer

244 
AUTOMATIC DEM GENERATION IN QUARRIES 
Gianfranco FORLANI 
Department of Civil Engineering - University of Parma 
Viale delle Scienze, 43100 Parma 
E-mail: forlani@parmal.eng.unipr.it 
ITALY 
Livio PINTO 
Department of Surveying (DIIAR) - Politecnico of Milan 
P.zza L. da Vinci 32, 20133 Milano 
E-mail: livio@mail.polimi.it 
ITALY 
Commission VI - Working Group 3 
KEY WORDS: Digital Elevation Models, Orthophotos, Accuracy 
ABSTRACT 
This paper reports on the application of automatic generation of DEMs in rock quarries, to figure out the excavation 
volumes by repeated surveys. Accuracies of some percentage of the volume’s estimate are acceptable, the ultimate goal 
being planning and managing the exploitation of the quarries. The aim of the investigation is therefore to check whether 
automatic DEM generation satisfy this accuracy level and what kind of restrictions should be put on flight planning, 
image resolution, scanning accuracy, additional terrain information, matching techniques to improve the performance of 
the DPW in this environment. A stereoscopic model from a 1997 flight over a quarry near Brescia has been processed 
with two different digital photogrammetric stations and the results compared to those obtained with an analytical plotter 
as well as by computing DEM errors from the left and right orthophotos of the pair. 
1. INTRODUCTION 
The automatic generation of digital elevation models 
by digital photogrammetric techniques is now several 
years old. Virtually all phogrammetric workstations 
include such modules and DEM’s are routinely 
generated in production environment. Tests on the 
accuracy of the technique as well as workshops and 
meetings on the subject, though, witness that the 
current level of sophistication of the correlation 
techniques cannot match the results of analytical 
plotters in every condition. 
Several parameters are relevant trying to asses the 
behaviour of the algorithms: image resolution, image 
texture, terrain roughness and slope, vegetation or other 
terrain superstructures (buildings, vehicles, etc.). As far 
as image resolution is concerned, empirical tests 
suggest that this parameter is almost independent of 
image scale (Baltsavias and Kaeser, 1998) (which is 
obviously kept at the smallest value for the specific 
task) and that it may be chosen in the range from 20 to 
30 micrometers with just a slight quality decay as 
resolution decreases. Using larger resolution values, 
the DEM quality becomes too poor. 
Overall DEM accuracy, defined as the RMS of the 
discrepancies between terrain heights and its 
interpolated values from the DEM, may be 
characterized by three factors (Ackermann, 1996): 
• the accuracy in elevation o z = m b h/B G p which 
depends on image scale, object to baselenght ratio 
and measurement accuracy in image space; 
• DTM grid size: interpolation errors varies with 
terrain roughness: the denser the grid the smaller 
the error, for a given terrain; 
• detection and filtering of non-terrain features 
(buildings, trees, etc.). 
The accuracy of correlation techniques is normally 
evaluated in percentage of the pixel size. Therefore, 
increasing scanning resolution may seem the 
straightforward way to improve it. In fact, 
notwithstanding storage and data handling problems, 
still severe if pixel size goes below 20 pm, empirical 
studies suggest that the current generation of 
photogrammetric scanners is affected by significant 
noise when scanning images at the maximum available 
optical resolution (below 10 pm). Perhaps more 
important than resolution is image texture: 
homogeneous regions or repetitive patterns may lead to 
wrong identification of conjugate pairs, leading to 
inaccurate results even if the terrain is not too rough. 
Steep slopes and terrain breaklines, on the other end, 
lead to strong perspective differences and occlusions 
that stereo correlation algorithms cannot cope with. As 
image scale decreases, their effect is less relevant; the 
same apply also to non-terrain features. 
At large scales, filtering out trees, buildings and so on 
is automatically performed by some systems, based on 
appropriate smoothing constraints on the curvature of 
the interpolating surface or other techniques. This 
works fine as far as these objects are isolated and there 
are no terrain breaklines in the vicinity. Forest areas 
and urban areas are still hard to deal with in large scale.
	        
Waiting...

Note to user

Dear user,

In response to current developments in the web technology used by the Goobi viewer, the software no longer supports your browser.

Please use one of the following browsers to display this page correctly.

Thank you.