Full text: International cooperation and technology transfer

236 
DEM’S COMPARISON FOR THE EVALUATION OF LANDSLIDE VOLUME 
M. Fiani, S. Troisi 
1st. di Geodesia, Topografia e Idrografia - Universitary Naval Institute of Naples (Italy) 
Commission VI, Working Group 3 
KEY WORDS: DEM, algorithms’ comparison, different input data, volume evaluation. 
ABSTRACT 
Evaluation of the amount of material displaced has been a problem came out on the occasion of the landslides that 
struck some countries of region Campania on May 1998. 
Landslide volume has been obtained as difference between the Digital Elevation Model derived from the survey carried 
out on the ground and that one derived from maps of the same zone preceding the event. 
Several methods can be applied for the creation of the model and the results are strongly influenced by the choice of the 
algorithm used. In this work some different interpolators have been tested in order to generate the DEMs of the surfaces 
with regard to three of the abovesaid landslides. The evaluation of the volume has been carried out by means of the 
comparison of the two “best” DEMs. 
1. INTRODUCTION 
On the occasion of the landslides occurred in Campania 
on May’98, the “Protezione Civile” Department 
organised a series of researches useful for a complete 
knowledge of the territory. 
The topographical research-unity involved in works had 
also the task to provide some information on the volume 
of the displaced mud. Such volume can be obtained by 
means of the difference between the Digital Elevation 
Model (DEM) achievable from the survey made on the 
ground after the event and the other one concerning the 
situation of the same zone before the landslide. 
Different techniques and methodologies were adopted for 
the survey because of the different morphology of the 
ground: kinematic and differential GPS, total stations 
both classic and special, such as the one called MDL, that 
supplies the distance even without the use of reflecting 
prism. 
The ground surveys, to a scale of 1:1000-1:2000, have 
been performed as from some vertices belonging to a 
GPS frame network which also include four vertices of 
the IGM95 national network. By means of such vertices, 
known in the different geodetical system, the co-ordinates 
of the surveyed points has been transformed in the 
National cartographic system Gauss-Boaga. 
In the same cartographic system have been acquired the 
co-ordinates of the contour lines with equidistance equal 
to 25 m from the elements of the “Cassa del 
Mezzogiorno” cartography at scale 1:5000, produced in 
1974 (we shall subsequently use the acronym CdM). 
The acquisition of such co-ordinates passes through a 
procedure of semiautomatic digitization of the contour 
lines coming from the cartography in raster form, 
previously geo-referenced to mean of a similar 
transformation. 
The contour line points yield a Digital Elevation Model 
that can be compared with the one derived from the 
survey, provided that both have the same step and size. 
The software of elaboration of the DEMs used for the 
experimentation is the Surfer, of the American House 
“Golden Software”, version 6.04 of 1996. It is a software 
that elaborates numerical data (typically co-ordinates of 
points in the space) furnishing models of surface on 
square grid. It foresees the most common modality of 
data interpolation. 
The tests have been carried out on three landslides, called 
SA20, SA30 and SA60. 
2. USED INTERPOLATION’S ALGORITHMS 
The gridding methods included with Surfer can be 
divided into two general categories: exact interpolators 
and smoothing interpolators. Some exact interpolators 
can incorporate a smoothing factor that causes them to 
become smoothing interpolators. 
Exact interpolators honour data points exactly when the 
data point coincides with the grid node being 
interpolated. Even when using exact interpolators it is 
possible that the grid file does not exactly honour the data 
if points do not coincide with the grid nodes. 
In the next the griddings algorithms used for the tests are 
described; the abbreviate word used sometimes in the 
next is written between brackets. 
1. Inverse Distance to a Power (I.D.) 
It is a weighted average interpolator, and can be either an 
exact or a smoothing interpolator. 
The power parameter controls how the weighting factors 
drop off as distance from a grid node increases. The 
weight given to a particular data point when calculating a 
grid node is proportional to the inverse of the distance to 
the specified power of the observation from the grid 
node. When calculating a grid node, the assigned weights 
are fractions, and the sum of all the weights is equal to 1. 
When an observation is coincident with a grid node, the 
observation is given a weight of essentially 1, and all 
other observations are given a weight of almost 0. In 
other words, the grid node is assigned the value of the
	        
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