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Nat. Hazards Earth Syst. Sci., 10, 2539–2546, 2010
www.nat-hazards-earth-syst-sci.net/10/2539/2010/
doi:10.5194/nhess-10-2539-2010
© Author(s) 2010. CC Attribution 3.0 License.
Natural Hazards
and Earth
System Sciences
Remote landslide mapping using a laser rangefinder binocular
and GPS
M. Santangelo1, M. Cardinali1, M. Rossi1, A. C. Mondini1,2, and F. Guzzetti1
1CNR IRPI, via Madonna Alta 126, 06128 Perugia, Italy
2Dipartimento di Scienze della Terra, Universit`
a degli Studi di Perugia, Piazza dell’Universit`
a, 06123 Perugia, Italy
Received: 24 May 2010 – Revised: 13 August 2010 – Accepted: 15 November 2010 – Published: 9 December 2010
Abstract. We tested a high-quality laser rangefinder
binocular coupled with a GPS receiver connected to a
Tablet PC running dedicated software to help recognize
and map in the field recent rainfall-induced landslides.
The system was tested in the period between March and
April 2010, in the Monte Castello di Vibio area, Umbria,
Central Italy. To test the equipment, we measured thirteen
slope failures that were mapped previously during a visual
reconnaissance field campaign conducted in February and
March 2010. For reference, four slope failures were also
mapped by walking the GPS receiver along the landslide
perimeter. Comparison of the different mappings revealed
that the geographical information obtained remotely for
each landslide by the rangefinder binocular and GPS was
comparable to the information obtained by walking the
GPS around the landslide perimeter, and was superior to
the information obtained through the visual reconnaissance
mapping. Although our tests were not exhaustive, we
maintain that the system is effective to map recent rainfall
induced landslides in the field, and we foresee the possibility
of using the same (or similar) system to map landslides, and
other geomorphological features, in other areas.
1 Introduction
Preparing reliable landslide inventory maps is key to several
types of geomorphological investigations, and to determine
landslide hazards and risk. Landslides can be recognized
and mapped at different geographical scales using a number
of techniques (Guzzetti et al., 2000), including: (i) direct
Correspondence to: M. Santangelo
(michele.santangelo@irpi.cnr.it)
field mapping (Brunsden, 1985; Ardizzone et al., 2007),
(ii) interpretation of stereoscopic aerial photographs (Rib
and Liang, 1978; Turner and Schuster, 1996), (iii) surface
and sub-surface monitoring (Petley, 1984; Franklin, 1984),
(iv) systematic analysis of chronicles and archive informa-
tion (Reichenbach et al., 1998), and (v) by exploiting a
variety of air- and space-borne remote sensing technologies
(Mantovani et al., 1996; K¨
a¨
ab, 2002; McKean and Roering,
2003; Cheng et al., 2004; Catani et al., 2005; Metternicht et
al., 2005; Singhroy, 2005; Ardizzone et al., 2007).
Regardless of the adopted technique, detecting and
mapping landslides is a difficult, time-consuming, and error
prone task (Roth, 1983; Carrara et al., 1992; Guzzetti et al.,
2000; Galli et al., 2008). Any technology that can facilitate
the recognition and mapping of landslides, that can reduce
the time or cost for the production of a landslide inventory
map, or that can improve the accuracy and quality of a
landslide map, should be considered and tested.
In this work, we present the results of an experiment aimed
at testing a modern technology for the regional mapping
of landslides in the field. More precisely, the experiment
was intended to perform a preliminary evaluation of the
possibility of using a rangefinder binocular coupled with
a GPS receiver to help map recent landslides in the field,
remotely. If successful, the technology may represent an
aid for the rapid production of reconnaissance inventory
maps over large areas. The scope of the experiment was
not to perform a systematic comparison of the considered
technology with consolidated methods and technologies
for the production of landslide inventory maps over large
areas (Guzzetti et al., 2000; Malamud et al., 2004; Galli
et al., 2008), including the visual interpretation of aerial
photographs or satellite imagery aided by field surveys (Rib
and Liang, 1978; Wieczorek, 1984; Galli et al., 2008).
Published by Copernicus Publications on behalf of the European Geosciences Union.
2540 M. Santangelo et al.: Landslide mapping using laser binocular and GPS
Fig. 1. Instruments used. (A) Vectronix VECTOR IV rangefinder
binocular. (B) Leica Geosystems ATX1230 GG GPS/GLONAS
receiver. (C) Xplore Technologies iX104C4 Rugged Tablet PC with
ESRI’s ArcGIS release 9.3.1 and Leica Mobilematrix on ArcGIS
release 3.1 software.
The experiment was conducted in the period from March
to April 2010 in the Monte Castello di Vibio area, Umbria,
Central Italy, a hilly area of about 21km2where landslides
are abundant. Sedimentary rocks, Tertiary to recent in age,
crop out in the area, including fluvial deposits along the
valley bottoms, continental gravel, sand and clay, and layered
sandstone and marl.
2 Instrumentation
The instrumentation used for the experiment consisted of
(Fig. 1): (i) a Vectronix VECTOR IV binocular with
7×magnification optics, a high performance 1500nm laser
distance meter with a 6km operational range, a digital
magnetic compass, and a digital clinometer (Table 1),
(ii) a Leica Geosystems ATX1230 GG GPS/GLONAS
double frequency receiver, and (iii) an Xplore Technologies
iX104C4 Rugged Tablet PC running Windows XP, ESRI’s
ArcGIS release 9.3.1, and Leica Mobilematrix on ArcGIS
release 3.1 software. For improved performance and
simplicity of use, the binocular was mounted on a tripod. The
total weight of the system is about 8.7 kg, including 3.5 kg for
the tripod, 2.4kg for the Tablet PC, 1.7kg for the binocular,
and 1.1kg for the GPS receiver.
The GPS receiver obtains three-dimensional (latitude,
longitude, and elevation) geographical coordinates of the
point where the rangefinder binocular is installed (the
viewpoint). Via wireless technology, information on the
position of the viewpoint is sent to the binocular. Using this
information, and data captured by the laser distance meter,
the digital compass, and the clinometer, the rangefinder
binocular obtains three-dimensional geographical coordi-
Table 1. Main technical data for the Vectronix VECTOR IV
rangefinder binocular. One mil is equal to 1/6400 of 360◦. Source:
Vectronix AG (2008).
Field of view 6.75◦, 120 mil
Range capability 6000 m
Minimal distance 5 m
Accuracy (1σ) 50m–2000 m ±2m
Accuracy (1σ ) < 50 m and >2000m ±3m
Magnification 7×
Azimuth accuracy (1σ)±0.3◦,±5mil
Inclination accuracy (1σ)±0.2◦,±3mil
Weight 1.68kg
nates of distant points remotely. The binocular is wired to
the Tablet PC for real-time data acquisition and geographical
feature editing. To obtain a geographical representation of a
distant landslide, the operator aims the rangefinder binocular
to the landslide, and measures points along the landslide
perimeter. In the GIS, the individual points are transformed
into a polygon to represent the landslide.
3 Experimental setting
The experiment was conducted in three steps. First, thirteen
landslides caused by prolonged rainfall in the period from
January to March 2010, in the Monte Castello di Vibio
area were recognized and mapped in the field during a
regional reconnaissance campaign (Fig. 2). These were
all the landslides visible from roads in the ∼21km2study
area. For mapping the landslides, we used the methodology
adopted in a nearby area by Ardizzone et al. (2007) to
map similar rainfall-induced landslides occurred in the
winter of 2004. Four geomorphologists (in two teams)
drove and walked systematically along the roads in the
study area. The teams stopped where single or multiple
landslides were identified, and at scenery points to check
individual and multiple slopes, and to take single or pseudo-
stereoscopic photographs of each landslide or group of
landslides. In the field, the geomorphologists prepared
a preliminary map of the landslides using 1:10000 scale
base maps. Individual landslides were placed on the
map visually, using the geomorphological and topographic
information available on site. The two teams checked
and photographed some of the landslides repeatedly. The
cartographic and photographic information obtained in the
field by the different geomorphologists was used in the
laboratory to map visually the individual slope failures
on 1:10000 scale ortho-photographic base maps. Where
information from multiple sources was available for the same
landslide, the information was merged heuristically to obtain
a single representation of the landslide.
Nat. Hazards Earth Syst. Sci., 10, 2539–2546, 2010 www.nat-hazards-earth-syst-sci.net/10/2539/2010/
M. Santangelo et al.: Landslide mapping using laser binocular and GPS 2541
N
0 0.5 1 km
©2010 Google - Map data ©2010 Tele Atlas
4748697 N
280127 E
4748697 N
285742 E
4744866 N
285742 E
4744866 N
280127 E
Figure 2
1
2
3
4
5
6
7
8
9
AB
C
D
Fig. 2. Landslide event inventory map for the Monte Castello di Vibio area, Umbria, Central Italy. Red dots show the location of 13 landslides
mapped through the visual reconnaissance survey and using the rangefinder binocular and GPS. Blue triangles show location of four
viewpoints, and dashed lines identify fields of view. Numbers (1–9) identify landslides mapped through the reconnaissance survey and
using the rangefinder binocular. Letters (A–D) identify slope failures mapped also by walking the GPS receiver along the landslide perimeter
(see Fig. 3). Source of base maps: © 2010 Google – Map data, and © 2010 Tele Atlas.
The rainfall-induced landslides were shallow soil slides,
shallow compound slide-earth flows, and translational slides,
ranging in area from AL=218m2to AL=7706 m2(mean
AL=2174m2, standard deviation, σ,AL=1993 m2),
for a total landslide area AL=28267 m2. The visual
reconnaissance survey was conducted on 9 February and
on 18 March 2010, and required a total of nine hours of
fieldwork, and five additional hours of a GIS expert in the
laboratory for mapping, editing and final feature correction.
Based on these figures, we estimate that the average time
required for the visual mapping a single (typical) landslide
ranged between 30min and one hour (average 45 min).
Next, the same landslides were mapped using the
rangefinder binocular and GPS system. The same team
of four geomorphologists that performed the visual recon-
naissance mapping executed the remote mapping operating
from viewpoints located at distances ranging from ∼250m
to ∼3km to the landslides. Due to the local perspective
and the terrain morphology, only eleven landslides were
mapped individually. Two landslides (n. 8 and n. 9 in Fig. 2)
were recognized as a combined feature using the rangefinder
binocular, and mapped as a single landslide. To investigate
biases (or errors) introduced by different operators, two or
three geomorphologists mapped some of the same landslides
repeatedly. The repeated measurements were performed in a
period of time not exceeding 30min, i.e. in the same (or very
similar) lighting and visual conditions. Remote mapping of
the individual landslides in the field using the rangefinder
binocular and GPS was conducted on 17 March and 1 April
2010. The time required for mapping a single landslide in
the field (from identification to completion of the mapping)
ranged from 5 to 15min (average 7 minutes). The mapping
time depended on the size and complexity of the slope
failure, the appearance and local visibility of the landslide,
and on the number of landslides visible (hence, that could be
mapped) from the same viewpoint. In addition to the time
in the field, in the laboratory data transfer and editing of the
geographical and thematic information in the GIS required
an average of 2 to 5min per landslide, including automatic
smoothing of the line representing the landslide boundary,
for improved cartographic appearance. Line smoothing was
necessary because use of the relatively limited number of
points measured with the rangefinder binocular and GPS
would have resulted in an unrealistic, angular appearance
of the individual landslides. The mapped landslides ranged
in area from AL=77m2to AL=4678 m2(mean AL=
1978m2,σ AL=1565 m2), for a total landslide area AL=
23965 m2, 15.2% less than in the visual reconnaissance
mapping.
Lastly, to obtain an accurate (“reference”) geographical
representation of the position and geometry of a subset
of the slope failures, geomorphologists walked the GPS
receiver along the perimeter of four landslides (A, B, C, D
in Fig. 2). For this operation, the GPS captured geographical
coordinates every meter, a spatial sampling frequency higher
than the one used to measure points along the landslide
perimeter with the rangefinder binocular. No correction was
applied to the GPS signal, and the expected planimetric error
for the individual GPS measurements was ±5m, or less. In
the walk along the perimeter of a slope failure, we included
the crown area and the deposit of the landslide. In places,
it was not straightforward (or unequivocal) to identify the
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2542 M. Santangelo et al.: Landslide mapping using laser binocular and GPS
local boundary of the landslide, particularly along the sides
of the slope failure, where topography was hummocky, and
where the vegetation was tall. In these places, the ability
of the geomorphologist to follow the landslide boundary
was hampered by the reduced visibility of the slope failure,
a consequence of the local perspective, of the size of the
landslide, and of the fact that the landslide boundary was
locally indistinct. The geographical coordinates of the
individual landslides were automatically superimposed in
the GIS on the geographical information obtained using the
rangefinder binocular. Direct mapping of the landslides using
the GPS receiver was performed on 1 April 2010. The time
to walk around a single landslide varied from 30min to 1h,
depending on the size of the landslide and the complexity of
the terrain.
4 Results
We now compare the landslide maps produced using the
different mapping methods. For the purpose, we assume
that the maps obtained by walking the GPS receiver
along the landslide perimeter are the most accurate and
reliable representations of the individual slope failures. The
assumption is justified considering that: (i) with local
exceptions, the recognition of recent, fresh landslides is
relatively simple from a distance, and (ii) the error associated
with the individual GPS measurements (±5m) is lower
than the error made by mapping a landslide visually in the
reconnaissance mapping, and lower than the error associated
to the measurements obtained by the rangefinder binocular,
which include GPS measurements.
In Fig. 3 we compare the maps of four landslides obtained:
(i) through visual reconnaissance mapping and interpretation
of digital photographs taken in the field, (ii) using the
rangefinder binocular and GPS, and (iii) by walking the GPS
receiver along the perimeter of the individual landslides.
Pictures in the left-hand column of Fig. 3 (3.1–3.4) portray
digital photographs of the slope failures taken in the field at
distances ranging from several hundreds to a few thousands
meters. In the photographs, the dotted yellow lines were
added to outline the location and shape of the landslides.
Images in the second column of Fig. 3 (3.5–3.8) portray the
mapping of the four landslides obtained by walking the GPS
receiver along the perimeter of the slope failures (light blue
dots). For the individual landslides, the mapping obtained
by the GPS was considered an accurate representation of the
slope failure, and taken as reference for comparison with the
other mappings. Images in the third column of Fig. 3 (3.9–
3.12) show the result of the field-based visual reconnaissance
mapping (violet lines) with the reference mapping obtained
by walking the GPS receiver along the landslide perimeter
(light blue dots). Lastly, Fig. 3.13–3.16 portray the mapping
obtained using the rangefinder binocular and GPS, compared
to the mapping obtained by walking the GPS receiver along
the perimeter of the slope failures. In the later images,
the yellow points along the dashed lines show the raw data
captured in the field, and the continuous red lines show the
adjusted representations of the landslide perimeters obtained
by smoothing of the raw data in the GIS. Light blue dots
show points captured walking the GPS receiver along the
landslide perimeter.
Inspection of Fig. 3 reveals that there is good agreement
between the slope failures mapped using the rangefinder
binocular and GPS, and the same failures mapped by walking
the GPS receiver along the landslide perimeter. Further,
the cartographic representation of the individual landslides
obtained by the rangefinder binocular and GPS is similar
(Fig. 3.15), better (Fig. 3.14 and 3.16), or significantly
better (Fig. 3.13) than the mapping obtained with the
reconnaissance survey. In particular, Fig. 3.13 shows that the
location and size of the landslide in the visual reconnaissance
inventory (Fig. 3.9) were incorrect, probably due to the
difficulty in locating the landslide visually from a distance on
the available base map. Similarly, image 12 in Fig. 3 shows
that the landslide mapped during the visual reconnaissance
survey is smaller, of different shape, and in a slightly
different position than the same landslide mapped using the
rangefinder binocular (Fig. 3.16) and the GPS (Fig. 3.8).
In an attempt to quantify the degree of similarity
(or discrepancy) between the different mappings, we
determined the error index E(Carrara et al., 1992), and the
corresponding matching index M(Galli et al., 2008), for
the individual landslides. For the purpose, we used Eqs. (1)
and (2):
E=(AL1 ∪AL2)−(AL1 ∩AL2)
(AL1 ∪AL2),0≤E≤1 (1)
M=1−E, 0≤M≤1 (2)
where, AL1 and AL2 are the areas of a single landslide
measured by two separate mappings, and ∪and ∩are the
geographical union and intersection of the two landslides,
obtained in the GIS. From Eqs. (1) and (2), if two mappings
show a landslide of exactly the same shape and size in the
same geographical location (a rare condition), matching is
perfect (M=1) and cartographic error is nil (E=0). On
the contrary, where two mappings disagree totally (e.g.,
Figs. 3.9, 3.13), error is largest (E=1) and cartographic
matching is nil (M=0). Table 2 lists the results for the
thirteen mapped landslides.
Analysis of the indices reveals that the mismatch
Ebetween the mapping obtained using the rangefinder
binocular and the mapping obtained by walking the
GPS along the landslide perimeter is reduced (min= 0.17,
max= 0.29, mean= 0.19, σ=0.06), when compared to the
mismatch measured between the mapping obtained with the
rangefinder binocular and the visual reconnaissance mapping
(min= 0.37, max=1, mean = 0.65, σ=0.22). This confirms
that maps obtained using the rangefinder binocular are simi-
lar to the (“reference”) maps obtained by walking the GPS
Nat. Hazards Earth Syst. Sci., 10, 2539–2546, 2010 www.nat-hazards-earth-syst-sci.net/10/2539/2010/
M. Santangelo et al.: Landslide mapping using laser binocular and GPS 2543
GPS mapping Rangefinder binocular
vs. GPS mapping
Reconnaissance mapping
vs. GPS mapping
Field photograph
(1)(13)
(5)
(2)(14)
(6)
(3)(15)
(7)
(4)(16)
(8)
N
Landslide ALandslide BLandslide CLandslide D
0 50 100 m25
Figure 3
(9)
(10)
(11)
(12)
Fig. 3. Comparison of landslide maps prepared for four landslides in the Monte Castello di Vibio area, Umbria, Central Italy. From left to
right, columns show: (i) photographs taken in the field to help the visual reconnaissance mapping (dotted yellow lines added to outline the
landslides), (ii) maps obtained by walking the GPS receiver along the perimeter of the individual landslides, (iii) maps portraying the result
of the visual reconnaissance mapping (violet lines) and mapping obtained by walking the GPS receiver along the landslide perimeter (light
blue dots), (iv) maps obtained using the rangefinder binocular and GPS (yellow dashed lines show raw data obtained in the field, and red
lines show smoothed landslide boundaries for improved cartographic appearance) and mapping obtained by walking the GPS receiver along
the landslide perimeter (light blue dots).
along the landslide perimeter, and significantly dissimilar
to the visual reconnaissance mapping. Further, analysis of
the error indices indicates that the mismatch between the
mapping obtained using the rangefinder binocular and that
obtained by walking the GPS along the landslide perimeter
is significantly less than the mismatch measured by Carrara
et al. (1992), Ardizzone et al. (2002), and Galli et al. (2008),
who compared landslide maps prepared through the visual
interpretation of stereoscopic aerial photographs.
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2544 M. Santangelo et al.: Landslide mapping using laser binocular and GPS
Landslide ALandslide B Landslide B
(1)(3)
(2)
Figure 4
0 50 100 m25
N
Fig. 4. Comparison of maps prepared for two landslides in the Monte Castello di Vibio area, Umbria, Central Italy. (1) Two mappings
prepared by the same operator using the rangefinder binocular and GPS from a distance of ∼2.5 km (orange), and from a distance of ∼250m
(violet). (2) Mappings performed by two operators (yellow and red lines) using the rangefinder binocular from a distance of ∼2.5km.
(3) Mappings obtained by three operators (yellow, red, and pink lines) using the rangefinder binocular and GPS from a distance of ∼250 m.
In all maps, light blue dots show data obtained by walking the GPS receiver along the landslide perimeter.
Table 2. Landslide cartographic errors. E(error index) computed
using Eq. (1), M(matching index) computed using Eq. (2). For
landslide codes see (Fig. 2). BIN, mapping obtained using the
rangefinder binocular; VRS, mapping obtained through visual
reconnaissance survey; GPS mapping obtained by walking the GPS
receiver along the landslide perimeter.
Landslide BIN vs. VRS BIN vs. GPS
code E M E M
A 1.00 0.00 0.17 0.83
B 0.71 0.29 0.16 0.84
C 0.45 0.55 0.15 0.85
D 0.54 0.46 0.29 0.71
1 0.77 0.23
2 0.93 0.07
3 0.95 0.05
4 0.49 0.51
5 0.56 0.44
6 0.48 0.52
7 0.37 0.63
8, 9 0.59 0.41
We next compare mappings of two landslides obtained
using the rangefinder binocular from different measuring
distances, and by different operators (Fig. 4). Figure 4.1
shows two representations of the same landslide (B, in
Fig. 2) obtained by the same operator using the rangefinder
binocular positioned at two distances from the slope failure:
(i) about 250m (violet line), and (ii) about 2500 m (orange
line). The two representations of the same landslide are
similar, and in agreement with the “reference” mapping
obtained by GPS (light blue dots). The measurements of
the area of the landslide confirm the degree of matching:
(i) AL=2189m2for GPS, (ii) AL=2083 m2for binocular
and GPS positioned at 250m distance (4.8% difference),
and (iii) AL=1976m2for binocular and GPS positioned
at 2500m distance (9.6% difference). Further, in Fig. 4.1
points laying on the orange and violet lines are at a maximum
distance of 8m, and most of them within a distance of 4 m,
from the boundary of the landslide obtained by walking the
GPS along the landslide perimeter (light blue dots).
Figure 4.2 shows two representations of the same landslide
(A, in Fig. 2) obtained by two separate investigators (red
and yellow lines) that used the rangefinder binocular from
the same surveying distance of about 2500m. Similarly,
Fig. 4.3 shows three mappings of the same landslide (B,
in Fig. 2) obtained by different operators (red, yellow,
and blue lines) that used the binocular and GPS to
measure the landslide from a distance of about 250m.
Comparison of the measurements confirms the accuracy
of the mappings obtained by different operators using the
rangefinder binocular. We take this as an indication that the
equipment tested can be used to map landslides consistently
(i.e., accurately) in the field. Considering both maps, points
laying on the orange, violet and red lines are at a maximum
distance of 10m, and most of them within a distance of
5m, from the boundary of the landslides obtained by GPS
(light blue dots). For the two landslides, the measured
areas are also similar. For Fig. 4.2, AL=1878 m2for GPS,
AL=1789m2(red line, 4.7% difference), and AL=1718 m2
(yellow line, 5.2% difference). For Fig. 4.2, AL=2189 m2
for GPS, AL=2083m2(red line, 4.8% difference), AL=
2204m2(yellow line, 0.7% difference), and AL=2027 m2
(violet line, 7.4% difference).
Nat. Hazards Earth Syst. Sci., 10, 2539–2546, 2010 www.nat-hazards-earth-syst-sci.net/10/2539/2010/
M. Santangelo et al.: Landslide mapping using laser binocular and GPS 2545
5 Discussion
Despite local problems related to the difficulty in determin-
ing the “exact” position and extent of a landslide in the
field, the mapping of the landslide obtained by taking the
GPS receiver along the perimeter of the individual slope
failure was undoubtedly the most accurate. This procedure
is resource intensive and clearly impractical to map slope
failures in a large area, where landslides are numerous,
or in difficult, hazardous, or inaccessible terrain. Use
of the rangefinder binocular and GPS allowed capturing
information on the geographical location, size, and shape
of the landslides in the field, remotely. For the purpose
of preparing regional, landslide event-inventory maps at
1:10000 scale (or smaller), the quality of the landslide
information obtained remotely was comparable to the quality
of the similar information obtained by walking the GPS
receiver along the landslide perimeter, and was locally
superior to much superior to the information obtained
through the reconnaissance mapping (Fig. 3).
We now discuss general advantages and main limitations
of the remote mapping using the rangefinder binocular and
GPS receiver, compared to the visual reconnaissance field
mapping.
In a field-based reconnaissance mapping, landslides are
identified visually. To locate and map the individual slope
failures, the geomorphologist relies on a base map, which
almost invariably pre-dates the landslides. This can result in
local errors (Figs. 3.4 and 3.13), where landslides are difficult
to locate visually, or where the base map does not show
clear or sufficient topographical (morphological) information
to place and map the landslides, e.g., where the pre-failure
topography does not show signs of the post-failure geometry
of the landslide. Use of the rangefinder binocular and
GPS solves the problem, allowing for an accurate (within
the nominal accuracy of the instruments) location of the
individual landslides. The remote mapping may result in
landslide maps that are in local contrast with the topography
shown on the base map. Where this is a problem, post-
processing of the landslide information in the GIS can reduce
the mismatch.
The remote mapping requires less time, skills, and
resources than the visual reconnaissance mapping to map the
same landslides. First, accurate geographical information
is obtained digitally and stored directly in the GIS. This
reduces the post-processing effort, which is a considerable
part of the reconnaissance mapping procedure. Second,
the operator performing the mapping needs “only” to be
able to recognize the landslide in the field, and to trace
the landslide perimeter with the rangefinder binocular. This
is simpler than the reconnaissance mapping that requires
that the geomorphologist reads and understands the local
topography shown on the base map.
Despite the clear advantages, landslide mapping using the
rangefinder binocular has limitations. First, only landslides
that can be clearly seen from viewpoints, and that are at
distances within the operational range of the laser rangefinder
(6km, for the Vectronix VECTOR IV), can be measured
successfully. As an example, landslides numbered 8 and 9
in Fig. 2 could not be resolved individually, and were –
erroneously – mapped as a single landslide. This is evidence
that the technology will not replace the interpretation of
aerial or satellite images, completely. Also, the GPS signal
must be available at the surveying points, for the system to
work. The equipment may not work always and everywhere,
and for all landslides. As an example, the system may not
work in forested terrain or in foggy areas. We conclude that
use of the system will not guarantee the completeness of the
inventory (Malamud et al., 2004; Galli et al., 2008).
Second, the system requires power to work (for the Tablet
PC, the GPS receiver, and the binocular). In our test, use of
the system was limited only by the run time of the battery
of the Tablet PC (∼4 h with a single battery). The system
is not heavy (<10kg) or bulky (Fig. 1), and can be easily
transported and used by a single person. However, the system
was most effective when operated with the support of a
vehicle, which allowed for: (i) recharging the batteries of the
Tablet PC, extending the operational period of the system,
(ii) maintaining the GPS system connected throughout the
field work, and (iii) keeping the binocular mounted on the
tripod, reducing the time required to set up the system at each
measuring point.
Third, the system is expensive to buy. In Italy, the
total cost for the instruments and the software used in the
experiment ranges between 18 000 C to 35000 C, depending
chiefly on the cost of the GIS software license. The hardware
that we have tested requires proprietary GIS software.
Should the hardware use open-source or free GIS software,
the cost of the system could be reduced substantially.
We stress that our experiment, and the analysis of the
results, were based on a limited number of landslides
(13 slope failures), all of the same type. We acknowledge
that this limits the validity of our work. The rangefinder
binocular was tested on landslides triggered by a single
rainfall period in one geographical area characterized by a
specific morphological and geological setting. This also
limits the force of our conclusions. More efforts are
required to test the technology with different landslide types,
and in diversified geomorphological and environmental
settings. Lastly, new tests are needed to compare the
mapping performed using the rangefinder binocular with
maps obtained adopting consolidated methods for the
production of regional landslide inventories, chiefly the
visual interpretation of aerial photographs (Rib and Liang,
1978; Wieczorek, 1984; Galli et al., 2008).
www.nat-hazards-earth-syst-sci.net/10/2539/2010/ Nat. Hazards Earth Syst. Sci., 10, 2539–2546, 2010
2546 M. Santangelo et al.: Landslide mapping using laser binocular and GPS
6 Conclusions
We have tested a system composed of a high-quality laser
rangefinder binocular, coupled with a GPS receiver, and
connected to a Tablet PC running GIS and dedicated
software, to help recognize and map recent rainfall-induced
landslides in the field, remotely. The experiment was suc-
cessful, and demonstrated that the technology is effective to
prepare accurate landslide event-inventory maps (Malamud
et al., 2004) at 1:10 000scale, or smaller. Despite a few
limitations, and the need for more extensive tests, including
a comparison with established methods for the production
of regional inventories (Rib and Liang, 1978; Wieczorek,
1984; Galli et al., 2008), we foresee the possibility of
using the equipment systematically to map similar and
different landslides remotely in other geographical areas and
morphological settings. We further expect that the system,
or other systems based on instruments with similar technical
characteristics, will contribute substantially to the production
of new accurate and reliable landslide event-inventory maps,
particularly where post-event aerial photography or very high
resolution satellite images are not available. This will have a
positive feedback for geomorphological studies, and hazard
and risk evaluations (Guzzetti et al., 2000).
Acknowledgements. We are grateful to the Regione dell’Umbria,
Direzione Ambiente Territorio e Infrastrutture, that provided the
technical equipment used for the experiment and funding for the
study. MR and MS were supported by grants of the Italian national
Department for Civil Protection. ACM was supported by a grant of
the ASI MORFEO project.
Disclaimer In this work, use of copyright, brand, logo and trade
names is for descriptive and identification purposes only, and does
not imply an endorsement from the authors or their institutions.
Edited by: O. Katz
Reviewed by: two anonymous referees
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