Journal of Geographic Information System, 2010, 2, 163-168
doi:10.4236/jgis.2010.23023 Published Online July 2010 (
Copyright © 2010 SciRes. JGIS
Contribution of Topographically Explicit Descriptors of
Landscape Measures for Application in the Vector
Data Environment
Jomaa Ihab1, Auda Yves2
1Remote Sensing Center-National Council for Scientific Research, Riad El Solh, Beirut, Lebanon
2LMTG, CNRS - Université Paul Sabatier - Observatoire Midi-Pyrénées, Avenue Edouard Belin, Toulouse, France
Received February 23, 2010; revised March 27, 2010; accepted April 5, 2010
Digital terrain models (DTMs) are not commonly used to integrate for landscape spatial analysis. Two di-
mensional patch-corridor-matrix models are prototypes in landscape spatial ecology analysis. Previous stud-
ies have motivated ecologists to integrate terrain models in landscape analysis through 1) adjusting areas and
distance calculations prior computing landscape indices; 2) designing new indices to capture topography and
3) searching the possible relationship between topographic characteristics and vegetation patterns. This study
presents new indices called Relative number of Topographic Faces (RTF) and Simplicity of topographic
Faces (STF) that can be easily computed in a GIS environment, capturing topographical features of land-
scapes. Digital terrain model was first prepared and topographic units were extracted and installed in com-
puting the suggested indices. Mountainous and rugged topography in Lebanon was chosen on a forested
landscape for the purpose of this study. The indices were useful in monitoring changes of topographic fea-
tures on patch and landscape level. Both indices are ecologically useful if integrated in landscape pattern
analysis, especially in areas of rugged terrains.
Keywords: Landscape Indices, Topography, Forest, Digital Terrain Model, Patch, Lebanon
1. Introduction
Ecological concern was about quantifying patterns in the
spatial heterogeneity of landscapes [1]. Although lands-
cape indices capture important aspects of landscape pat-
terns, one of the main engines of patterning remains poo-
rly or uninstalled into the spatial analysis of landscapes
[2-7]. Topographically neutral landscapes remain the ba-
ckbone of landscape pattern analysis, especially when
two dimensional patch-corridor-matrix models are inte-
grated into friendly and easy to use packages of land-
scape analysis.
Although, ecologists know well the effect of topograp-
hy on patterns and processes, trials are still rare to inte-
grate topographical characteristics in a landscape spatial
analytical approach. Previous proposals on introducing
topography to landscape indices include 1) correcting
surface areas and distances prior to landscape metric
computation, 2) designing new indices that could relate
vegetation pattern with topographical characteristics, and
3) use of statistical models relating topography with
vegetation patterns. New indices will continue to derive
which causes ecologists to face long list metrics [8]. New
emerged topographically related landscape metrics are
therefore, under prediction, since without topographical
analysis and relation to metrics in certain areas will ind-
uce misleading final interpretation. Studies still urge
scientists for further topographical insertions within met-
ric computations and/or development of simple approa-
ches that could be readily implemented into familiar sof-
tware packages with regard to ecologists [9,10].
Landscape ecology has started with oversimplification
in conceptualizing and analyzing landscapes as mosaic of
discrete patches [11,12]. Nowadays, it is being directed
toward the utilization of surface metrics together with
patch metrics for quantifying landscape patterns [13].
Surface metrics are to be used for continuous representa-
tion of spatial heterogeneity but unlike patch metrics
they are less accessible for direct computation to the
hand of landscape ecologists. A simple easy to use to-
pography related indices remains as a priority.
Copyright © 2010 SciRes. JGIS
Developing landscape indices requires deep investiga-
tions with trials in order to eliminate redundancy of infor-
mation [14,15]. Ecological indicators also need to cap-
ture the complexities of the ecosystem yet remain simple
enough to be easily and routinely monitored [16]. The
concept of landscape ecology does not provide well de-
veloped and easy to apply methodology for analyzing
pattern and dynamics in landscapes with rugged topog-
Topography results variation in community structure,
composition and succession pathways [17,18] and influ-
ences the frequency, spread, extent, and distribution of
natural disturbances [19,20]. Ecosystem dynamics also
demonstrated interactions with topography [21]. Relation
of topography in forming landscape pattern has not well
understood yet.
Topographical analysis is consequently needed for the
completion of relating pattern to processes. Accomplish-
ing this concern, a first step is providing ecologists quan-
tifiable topographical information in an easy approach.
The present study introduces two landscape indices that
account for topography on patch and landscape level of
ecological hierarchy. Rugged topography of forest land-
scapes in Lebanon was chosen for applying such indices.
2. Materials and Methods
2.1. Study Area
Situated on the eastern coast of the Mediterranean Sea,
Lebanon occupies the junction between Europe, Asia and
Africa, with a surface area of 10,452 km2 and it is char-
acterized by four main geomorphological units: narrow
Coastal Plain and two mountain chains (Mount Lebanon
and Anti Lebanon) separated by a fertile and relatively
elevated plateau at an elevation of 700 to 1100 m named
Bekaa Plain (Figure 1). The geomorphological units are
Figure 1. Major geomorphological units of Lebanon (top); East-west cross-section across Lebanon (below).
Copyright © 2010 SciRes. JGIS
oriented from northeast to southwest. The two mountain
chains are almost of rugged topography due to the dom-
inant hard carbonate rocks, and the occupy about 70% of
the total Lebanese territory.
2.2. Preparatory Phase
First, the Triangulated Irregular Network (TIN) of the ent-
ire landscape was performed. A TIN is a vector-based
representation of physical land surface resulted from the
three dimensional coordinates (x, y and z). It is con-
structed of nodes that are arranged in a network of non-
overlapping triangles. The points of a TIN are distributed
based on algorithm that uses locations where most nec-
essary to an accurate representation of the terrain. A TIN
comprises a triangular network of vertices connected by
edges to form a triangular tessellation. Points of triangles
are widened in a lower density when terrains have little
variations in heights. Conversely, density of points incre-
ases in terrains of intense topographic variations. Constr-
uction of a TIN requires elevation data of the terrain as
points or adapted from contour lines. A TIN is typically
based on a Delaunay triangulation that entails points cap-
turing changes in surface forms. Unlike unique sized grid
cells, triangles of variable dimensions in a TIN are able
to reflect large complexity of relief, providing slope gra-
dient and aspect.
TIN GIS layer was prepared for Lebanon using 50 m
equidistance contour lines in the GIS system, using the
software ArcGIS 9.2. Forest maps of 1965 [22,23] were
overlapped digitally onto the TIN vector layer where
topography of each forest patch of both periods was ob-
tained. The geographic space of a patch with triangles
(faces or tiles of the TIN) of slope gradients and aspects
was dissolved or generalized into contiguous non-over-
lapping triangles that were first derived from the detailed
triangulation of the TIN. For the purpose of this study,
triangles of slope gradient were chosen.
2.3. Relative Number of Topographic Faces
Relative number of Topographic Faces (RTF) is one of
the suggested new indices that fits within the descriptive
modeling of landscape patterns. RTF captures topograp-
hical characteristics of vegetation patterns (forest patches)
at the level of individual TIN tiles. It is based on com-
puting the number of topographic faces in a forest patch
relative to its surface area with a landscape as follows:
)( 2
where Number of topographic faces is the total variation
of landform within a forest patch and Area is the spatial
extent of the same forest patch in square kilometer.
RTF was computed using GIS facilities of relating
each forest patch to other attributable data that were de-
rived from the TIN layer. The number of TIN faces was
obtained for each forest patch after overlapping proce-
dures. A one-to-one link was set between GIS tables that
hold data about patches surface areas and their number of
topographic faces. This database link has enabled the
calculation of RTF.
2.4. Topographic Faces Degree of Simplicity
The relative number of topographic faces will reflect one
side of a patch topographic feature. The RTF could not
perceive the percent area of each topo-face within a pat-
ch, which will not completely reflect the topographic
characteristics of landscapes. The simplicity of topog-
raphic faces (STF) is an added developed index in this
study that accounts for percent area of each topo-face
within a patch or landscape. STF was computed at the
landscape level through the following equation:
where hpp is the highest percent of area of a topo-face
for each patch within the landscape; and N is the total nu-
mber of patches. STF will oscillate between 0 and 100%.
Higher STF values is the result of a landscape with larger
topo-faces within patches, i.e. topographically more ho-
mogeneous landscape. Two patches of similar size and
equal RTF would probably have completely different
STF, which lead us to clearly understand their degree of
topographic complexity.
2.5. Application of the Developed Indices
Figure 2 illustrates the different steps followed in the
computation of the indices “RTF and STF”, starting from
contour lines to creation of TIN layer and overlapping
forest maps.
Each of the obtained triangles in a forest patch repre-
sents a slope gradient and aspect. Within a forest patch,
two neighboring triangles of the same slope characterist-
ics were dissolved in a unified larger triangle. Joined
triangles or faces have equal slope gradient. These faces
were counted within each forest patch.
For the purpose of this work, forest maps of 1965 and
1998 for Lebanon were chosen. Changes in RTF were in-
vestigated between different forest patches of both years
that explain the trend of forest dynamics, i.e., whether
forest patches are moving toward either complex or sim-
ple topography.
3. Results
The Relative number of Topographic Faces (RTF) dem-
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onstrated sensitivity for variations in patch size and to-
pographic complexity. The total number of topographic
faces increases with increasing patch size (Figure 3(a)).
In Lebanon, it appeared that the increasing trend of topo-
faces number is even faster than patch size increase. To-
pographically complex mountains are what causing such
phenomenon; knowing the fact that mountains of Leba-
non have intensive rugged topography [24]. In moun-
tainous terrain, forest patches will accumulate topo-faces
in accentuated manner as they increase in size. This fact
required normalization of RTF to patch size (surface area)
in order to buffer out the effect of patch-size-topo-faces
relation (Figure 3(b)).
The largest patch of the 1965 forest map with an area
of 68.6 sqkm has its RTF of 41. This means for each 1 sqkm
of an area for this particular patch, 41 facets or topog-
raphic faces existed. The topographic complexity or RTF
for another patch, half size of the previous one, was 95.
The smallest patch size (0.26 sqkm) has RTF of 148.
Another example, two patches of almost similar size
(0.53 sqkm) have largely different RTF which are 311
and 18. The complexity of the topographic features of a
geographic location affects the RTF value of a patch.
RTF reflected the degree of ruggedness or topographic
complexity of a forest patch.
Figure 2. Steps followed to obtain topographic faces of for-
est patches for the computation of the proposed indices. (a)
contour lines of 50 m equidistance; (b) preparation of the
TIN; (c) Forest patches; (d) topographic faces within each
forest patch.
Figure 3. (a) The number of topographic faces with relation
to patch area; (b) Relative number of Topographic Faces
(RTF) after area normalization.
In addition to the path-based computation of RTF, this
index could be computed on landscape level. In 1965, the
topographic complexity of the forest patches, entire land-
scape, was 106, i.e., the mean RTF. The mean RTF
demonstrated an important increase, reaching more than
double the previous value, i.e. 264, in the year 1998. The
lowest RTF that characterizes forest of 1965 was 9 and
its maximum value was 311 (Figure 4). These values
have changed to set between 2 and 688 in 1998. Forests
have moved toward geographic locations that are chara-
cterized by more topographic complexity. Mean forest
patch size has decreased from 1.4 sqkm in 1965 to 0.2 sqkm
in 1998, i.e., the size of the forest patches decreased by
about 75% for both periods. Forests have moved or re-
mained limited in unreachable geographical locations
from point of view geomorphology, i.e., moved toward
topographically complex places. The simplicity of topog-
raphic faces (STF) on landscape level has changed from
32% in 1965 to 12% in 1998. The largest topographic
face within a forest patch has decreased by 20% in the
entire landscape. This landscape decrease in STF means
that each forest patch is being divided into smaller areas
of topo-faces.
On patch level, 1965 forests demonstrated a maximum
STF of 83% that decreased to 54% in 1998. This largest
STF was limited between 20 and 40% of slope gradient
Copyright © 2010 SciRes. JGIS
Figure 4. Two different forest patches showing minimum and maximum RTF of 1965 map.
in 1965 and between 27% and 44% of slope gradient in
4. Discussions and Conclusions
Metrics are still challenging for their ecological applica-
tions relating pattern to process. This study gives an insi-
ght about how to integrate topography into pattern analy-
sis at the landscape or patch level. New landscape indic-
es were proposed that could be computed in GIS system
with automated method. Both indices account directly
for topographic characteristics of a patch or landscape.
They are designed to assess topographic variation, follo-
wing detailed topographic segmentation of area through
the triangulated irregular network (TIN). Analysis could
undergo on any level of subdividing topographic units or
faces. Also, a topographic face could remain in the poss-
ible smallest subdivision generated through TIN compu-
tation or generalization of faces also could be practiced
depending on the study purpose. Detailed information of
slope gradient or aspect was provided in TIN layer of
GIS. The user has to decide whether to establish the anal-
ysis on the basis of slope gradient or aspect or on both
divisions. Our example uses forests of Lebanon that are
characterized by their mountainous habitat. In such rug-
ged mountains, topography play prominent role in pat-
terning the landscape. While landscape indices alone do
not account for topographic characteristics of an area, the
indices ‘RTF and STF’, as presented here, integrate topo-
graphy in a simple manner without the need to pass into
complicated transformation of grid computation sugges-
ted in previous studies [9]. Through, the computation of
RTF and STF, forest patches are separated into different
ranges of topographic complexity. Different landscapes
could also be analyzed for variations topographic chara-
cteristics. The developed indices could also investigate
changes of topography through different time periods. In
Lebanon, forest patches demonstrated more topographi-
cal complexity when comparing forest maps of 1965 and
1998. During this period, such increase in topographic
complexity was accompanied with patch size decrease.
Some forest patches have moved towards less topograp-
hically complex areas while others forest residues remain-
ned in rugged areas. RTF has doubled with 20% decrease
in STF and 75% decrease in patch size. This reveals the
importance and explains what valuable information
could be obtained of computing RTF and STF together
with other landscape indices. Previous studies were sati-
sfied in monitoring changes of landscape spatial pattern-
ing through the computation of landscape indices that
have no relation to topography although the landscapes
were mostly of mountainous characteristics. Many land-
scape indices have limited or no/undiscovered relation to
processes. It is therefore, recommended to work on land-
scape indices basis that are more creditable to answer
changes in processes. Processes are largely connected to
topography as well as its changes [6]. The presented in-
dices are easy to apply in a GIS system. Their automa-
tion is also possible through their future implementation
in a landscape spatial analysis software package.
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