Creating a Map of Terrain Regions for Italy
using Digital Elevation Models
Craig Allison
School of Geography & Earth Sciences, McMaster University, Hamilton, ON, Canada
1. Introduction
3. Results
(continued)
3. Results
The primary purpose of this project is to divide Italy into a
map of terrain regions using digital elevation models
(DEMs) and a fully automated approach. Automation of
traditional (manual) landform classification mapping is
appealing because it is consistent, repeatable, updatable,
and quantifiable. Terrain regions themselves are important
because they define boundary conditions for
geomorphologic, hydrologic, ecologic, and pedologic
processes [1]. Further, they impact where human activities
take place on the landscape. Italy has been chosen as the
study area because the most current effort at delineating
terrain regions [2] can be significantly improved.
Specifically, these regions were derived using coarse
resolution DEMs, highly correlated morphometric
variables, and manual qualitative techniques that are not
repeatable.
This study has four objectives:
1. To create an updated and improved landform
classification map of Italy.
2. To create a tool using Esri technology to automate the
approach so that it can be applied to other
jurisdictions.
3. To examine the impact that DEM products created
from different satellite technologies have on the
results.
4. To explore the impact that resolution has on the
resulting classified map.
2. Data and Methods
Three DEM products – ASTER (a passive along-track scanning
system with 30m resolution), SRTM (30m), and SRTM (90m)
(an active scanning system, based on radar interferometry) –
were retrieved using a combination of the U.S. Geological
Survey’s EarthExplorer tool (earthexplorer.usgs.gov/) and the
Consortium for Spatial Information (cgiar-csi.org/).
Table 2: Comparison of DEMs by % of cells per terrain region type for Italy
% of Cells in Each Terrain Region Type
Figure 2: Italian terrain regions derived from a 90m resolution SRTM Void
Filled DEM
DEM
Product
Plains
ASTER
Tablelands
Plains w/
hills or
mountains
Hills and
low
mountains
High
mountains
22.7
1.2
6.1
58.4
11.7
SRTM
(30m)
24.6
1.6
8.9
53.3
11.6
SRTM
(90m)
24.9
2.1
10.9
51.0
11.2
SRTM 30m and SRTM 90m DEM terrain region maps have
closer percentages of cells assigned to plains, plains with
hills or mountains, and hills and low mountains (i.e. 3/5
terrain region types) (Table 2). Of all five terrain region
types, the percent values (Table 2) assigned to plains and
high mountains are most similar between the three DEM
products. Therefore, the type of DEM product used for a
project matters less when you are identifying plains and
high mountains. More generally, categories at the
extremes of elevation are less affected by resolution or
the DEM product used. Projects involving plains and high
mountains should be less concerned about the specific
DEM they are using.
Figure 4: Erroneous classification results when the ASTER DEM was used
The Alps at Italy’s northern border have been classified as
“high mountains,” the Po Valley as “plains,” most of the
Apennine Mountains as “hills and low mountains,” and
most of Sicily and Sardinia as hills and low mountains.
Note that prominent features like Corno Grande (tallest
peak in the Apennines; located in central Mainland Italy)
and Mount Etna (tall volcano in eastern Sicily) have been
successfully identified as high mountains. Features like
the Po Valley in the north, Campidano plain in southwest
Sardinia, and the Tavoliere in Puglia have been nicely
extracted from the DEM as well.
The SRTM DEMs appear to classify terrain more accurately
than the ASTER DEM (Figure 4). In Piemonte, for example,
the ASTER DEM classification result indicates hills and low
mountains where there are none (just north of the
Monferrato Hills). The same is true for the southeastern
most area of Apulia. There should also be no significant
highland areas in the Po Plain (Figure 4 shows the Po Plain
in Lombardia), but there are in the ASTER DEM classification
result. SRTM DEM results did not contain these errors.
Figure 1: ASTER, SRTM (30 m), and SRTM (90 m) DEMs for Italy
The model for the landform classification was constructed
based on the work of Hammond [3], Dikau [4], Morgan & Lesh
[5], and Drescher & de Frey [6]. In the model, created in
ModelBuilder, a circular window of 1.8km radius was used to
calculate the percent of area occupied by gentle inclination
(<8% slope gradient), the relief, and the percent of the gently
sloping terrain occurring in the lower half of the local relief
[7]. One step was added to the original model that solved a
problem with the creation of NoData cells in the Alps.
Specifically, a value of 1 was added to the denominator map in
one of the divide steps. Five main types of terrain regions are
created based on merging 24 terrain types described by
Morgan & Lesh (Table 1). In total the model required 38 steps
to produce the results.
4. Conclusions
A model for automatically dividing Italy into terrain
regions has been constructed using ModelBuilder.
Results from the model show that the terrain region
classification depends more on the type of DEM used
and less on the resolution of the DEM product.
Figure 3: Model results for three different DEM products for Italy
Table 1: Assigning terrain types to terrain regions
Morgan & Lesh (2005)
Terrain Type
11, 12, 13, 14
Corresponding Terrain Region
21, 22, 23, 24
Tablelands
31, 32, 33, 34
Plains with hills or mountains
41, 42, 43, 44, 45, 51, 52, 53,
54, 55
46, 56
Hills and low mountains
Plains
High mountains
The type of DEM (i.e. ASTER vs. SRTM) appears to have a
greater influence on the classification result than does
resolution (i.e. 30m vs. 90m). More specifically, there is
visually more of a difference between the ASTER and
either SRTM map than there is between the SRTM (30m)
and SRTM (90m) maps.
5. References
[1] Drăguţ, L., & Eisank, C. (2011). Automated classification of topography from
SRTM data using object-based image analysis. Geomorphometry 2011, 7-9.
[2] Guzzetti, F., & Reichenbach, P. (1994). Towards a definition of topographic
divisions for Italy. Geomorphology, 11(1), 57-74.
[3] Hammond, E. H. (1964). Analysis of properties in land form geography: an
application to broad‐scale land form mapping. Annals of the Association of
American Geographers, 54(1), 11-19.
[4] Dikau, R. (1989). The application of a digital relief model to landform analysis
in geomorphology. In: Raper, J. (ed.) Three dimensional applications in
geographical information systems, Taylor & Francis, London, UK 51-77.
[5] Morgan, J. M., & Lesh, A. M. (2005). Developing landform maps using ESRI’S
Model-Builder. In ESRI International User Conference.
[6] Drescher, K., & de Frey, W. (2009). Landform classification using GIS. Position IT.
[7] Gallant, A. L., Brown, D. D., & Hoffer, R. M. (2005). Automated mapping of
Hammond's landforms. Geoscience and Remote Sensing Letters, IEEE, 2(4), 384-388.