Landslide inventory map of the upper Sinni River valley,

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Landslide inventory map of the upperSinni River valley, Southern ItalyMichele Santangeloab, Dario Gioiac, Mauro Cardinalia, FaustoGuzzettia & Marcello Schiattarellad

a Istituto di Ricerca per la Protezione Idrogeologa, ConsiglioNazionale delle Ricerche, Perugia, Italyb Dipartimento di Scienze della Terra, Università degli Studi diPerugia, Piazza dell'Università, Perugia, Italyc Istituto per i Beni Archeologici e Monumentali, ConsiglioNazionale delle Ricerche, Tito Scalo, Italyd Dipartimento di Scienze, Università degli Studi della Basilicata,Potenza, ItalyPublished online: 28 Aug 2014.

To cite this article: Michele Santangelo, Dario Gioia, Mauro Cardinali, Fausto Guzzetti & MarcelloSchiattarella (2014): Landslide inventory map of the upper Sinni River valley, Southern Italy, Journalof Maps, DOI: 10.1080/17445647.2014.949313

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SCIENCE

Landslide inventory map of the upper Sinni River valley, Southern Italy†

Michele Santangeloa,b∗, Dario Gioiac, Mauro Cardinalia, Fausto Guzzettia andMarcello Schiattarellad

aIstituto di Ricerca per la Protezione Idrogeologa, Consiglio Nazionale delle Ricerche, Perugia, Italy;bDipartimento di Scienze della Terra, Universita degli Studi di Perugia, Piazza dell’Universita, Perugia,Italy; cIstituto per i Beni Archeologici e Monumentali, Consiglio Nazionale delle Ricerche, Tito Scalo,Italy; dDipartimento di Scienze, Universita degli Studi della Basilicata, Potenza, Italy

(Received 23 January 2014; resubmitted 10 July 2014; accepted 24 July 2014)

In this paper, we present a geomorphological landslide inventory map for an intermountaincatchment in the southern Italian Apennines. The study area is seismically active, and it ischaracterized by high uplift rates produced by Quaternary tectonics. A total of 531landslides of different types, relative age, and sizes, including some kilometer-scale relictlandslides were mapped through the visual interpretation of 1:33,000-scale stereoscopicaerial photographs, and dedicated field surveys. Analysis of the inventory map revealed thatrecent landslides consist chiefly of reactivations of older landslides, and of the newlandslides formed in pre-existing landslide deposits, triggered primarily by intense rainfallevents, or prolonged rainfall periods. We expect that the inventory will be used for theevaluation of landslide susceptibility and hazard in the area, and to investigate the long-termgeomorphological evolution of a portion of the southern Apennines.

Keywords: aerial photo-interpretation; landslide inventory map; upper Sinni River valley

1. Introduction

Landslide inventory maps document the extent and types of mass movements in an area (Guzzettiet al., 2012). Prepared at a range of scales, landslide inventory maps can cover areas ranging from asingle slope to a large region (e.g., Cardinali, Antonini, Reichenbach, & Guzzetti, 2001), andexamples exist of inventories compiled for an entire state (Cardinali, Guzzetti, & Brabb, 1990),nation (e.g., Trigila, Iadanza, & Spizzichino, 2010), or continent (Van Den Eeckhaut & Hervas,2012). Inventory maps can be prepared using traditional methods and new techniques (Guzzettiet al., 2012). Traditional methods include field survey and the visual interpretation of stereoscopicaerial photographs (see e.g., Brunsden, 1993; Brardinoni, Slaymaker, & Hassan, 2003), and the col-lection of historical information on landslides and their consequences (e.g., Schuster, 1996). Newtechniques include the visual, semi-automatic, or automatic analysis of LiDAR-derived and opticalsatellite images (see e.g., Mondini et al., 2011; Van Den Eeckhaut, Kerle, Poesen, & Hervas, 2012;Razak, Santangelo, Van Westen, Straatsma, & de Jong, 2013). Other innovative techniques and data

# 2014 Michele Santangelo

†The research was conducted here∗Correspondending author. Email: [email protected]

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used for landslide mapping, include the use of synthetic aperture radar (SAR) data to map largelandslides (Czuchlewsky, Weissel, & Kim, 2003; Singhroy, Mattar, & Gray, 1998), and as ancil-lary data to help geomorphologists characterize and monitor landslides (Farina, Colombo,Fumagalli, Marks, & Moretti, 2006; Singhroy & Molch, 2004). Landslide maps are important(i) to document the effect of a single landslide triggering event (i.e., landslide event inventory,Bucknam, et al., 2001; Chigira, Wu, Inokuchi, & Wang, 2010; Gorum et al., 2011; Harp &Jibson, 1995 among others), (ii) to collect information for the definition of landslide suscepti-bility, hazard, vulnerability, and risk (e.g., Balteanu, Chendesb, Simaa, & Enciua, 2010, vanWesten, van Asch, & Soeters, 2006), (iii) to investigate morphogenetic processes in landscapesdominated by slope wasting phenomena (e.g., Hovius, Stark, & Allen, 1997), (iv) to determinelandslide statistics (e.g., Malamud, Turcotte, Guzzetti, & Reichenbach, 2004), and (v) forerosion and ecological studies (e.g., Fiorucci et al., 2011).

In Italy, despite the presence of a comprehensive national landslide inventory, at 1:25,000scale (Trigila et al., 2010), the need exists for accurate, large-scale (1:10,000 scale, or larger) land-slide inventory maps. In this paper, we present a geomorphological landslide inventory map(Main Map) for an area in the upper Sinni River valley, southern Italy, where landslides of differ-ent types and sizes are abundant.

2. Geological setting

The study area extends for 120 km2 in the northern sector of the Calabria-Lucania border, to the Nof Mt. Pollino and the Monti di Lauria ridges (Figure 1). The Sinni River drains the area, where

Figure 1. Location and geologic overview of the southern Apennines (modified from Gioia & Schiattarella,2006). Red line shows the border of the study area.

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elevation ranges from 502 to 1873 m, and landscape is characterized by medium-to-high relief. Inthe area, the Liguridi and Sicilidi sedimentary units (Bonardi et al., 1988) crop out along a narrowbelt parallel to the main Apennines range (ISPRA, 2011). The Mt. Alpi ridge, composed ofshallow-water Mesozoic sediments of the Apulia platform, dominates the northern part of thearea. In the study area, the Liguridi units, consisting of Jurassic to Oligocene sediments, and ofMiocene siliciclastic units partially affected by low-grade metamorphism (Invernizzi et al.,2008), represent the uppermost part of the southern Apennines fold-and-thrust belt. Rocks per-taining to the metamorphic basement crop out locally. In the Miocene, the sediments in thestudy area were piled in an accretionary wedge emplaced by the subduction of the Ligurianoceanic lithosphere under the Apulian continental margin (Gioia and Schiattarella, 2006; Schiat-tarella, 1998). In the Quaternary, the fold-and-thrust belt was cut by left-lateral, strike-slip andextensional faults (Schiattarella, 1998). As a result, the Mt. Alpi ridge and the surroundingareas were affected by intense exhumation and high uplift rates (Capolongo, Dall’arche, & Pen-netta, 2008; Corrado, Invernizzi, & Mazzoli, 2002; Di Leo, Schiattarella, Cuadros, & Cullers,2005; Gioia and Schiattarella, 2006). Regional uplift and recent fault activity are responsiblefor rapid incision of the drainage network, and for abundant slope wasting processes, includingseveral landslides (Santangelo, Gioia, Cardinali, Guzzetti, & Schiattarella, 2013).

3. Method

We prepared the geomorphological landslide inventory map (Guzzetti et al., 2012) through thesystematic, visual interpretation of a single set of black-and-white stereoscopic aerial photographsacquired in 1991, at a nominal scale of 1:33,000, aided by field surveys conducted in March 2009to check the results of the photo-interpretation. Interpretation of the aerial photographs was per-formed first by a single interpreter [MS] using (i) a Galileo SFG 2/D stereoscope, with 1× and 6×zoom capabilities, and (ii) an improved Galileo Siscam Falcon ZII stereoscope, with a 1.5× to13.5× continuous zoom, for more detailed analyses. A second interpreter [MC] reviewed the pre-liminary landslide mapping using a Galileo SFG 3/B stereoscope, with 1.25× and 4× zoomcapability.

To prepare the inventory, a legend for the landslide map was developed based upon the scaleof the aerial photographs, the extent of the study area, and the purpose of the investigation. Thelegend classifies the landslides based on the type and relative age of the landslides. Adopting asimplified version of the classification of the landslide types proposed by Cruden and Varnes(1996), landslides were classified as: (i) slide, (ii) complex/composite, (iii) earth flow, (iv) rockfall and topple, and (v) debris flow (Main Map). Two classes of estimated landslide relativeage were considered, including: (i) old (i.e., dormant young and dormant mature (Keaton andDeGraff, 1996)), and (ii) very old (i.e., relict, or dormant old (Keaton & DeGraff, 1996)) land-slides. Landslide relative age was estimated heuristically, considering the appearance of the land-slides on the aerial photographs (e.g., the presence or absence of a vegetation cover, of fluvialactivity and erosion processes, including other landslides), and examining the morphologicaland geometric relationships of the landslide, or portions of the landslides, with other landslidesand other geomorphological features. Very old landslides are large to very large, and are charac-terized by dismantled or partially eroded landforms. The landslide deposit is affected locally byreactivations, and small catchments may have developed in the crown area. Old landslides aresmaller in size, better preserved, and less dismantled than the very old failures. Younger reactiva-tions can be present in the deposit of old landslides.

The first interpreter [MS] performed field checks driving and walking along main and second-ary roads and trails to (i) validate the information collected during the aerial photo interpretation(API), and (ii) prepare a landslide event inventory map of slope failures triggered by intense

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rainfall and prolonged rainfall periods between November 2008 and March 2009 (2009 eventinventory, Figure 2). For the first purpose, the interpreter used a printed copy of the 1:10,000-scale topographic base map with the landslide information drawn on it during the API. Fieldchecks were conducted on all the locations where the API provided ambiguous information onlandslide boundary position, or on landslide classification and relative age. For the preparationof the landslide event inventory map, the interpreter collected information for the full extent ofthe study area, using the same 10,000-scale printed base map. The event inventory map reportsinformation on all the slope failures showing morphological features of event landslides, suchas disrupted vegetation, sharp escarpment edges, undrained depressions and hummockytopography.

During the preliminary mapping and review process, the interpreters drew the landslide andancillary geomorphological information on transparent overlays on the aerial photographs. Suc-cessively, the landslide information was transferred visually from the aerial photographs to adigital version on a 1:10,000-scale topographic base map. Finally, a geographical database wascompiled in a geographic information system (GIS) to store and organize the landslide infor-mation. Single landslides are classified based on the landslide type, and three separate layersare used to separate landslides of different relative age.

4. Results

The landslide inventory map shows 531 landslides, with an average density of 4.4 landslides persquare kilometer. The inventory shows 317 complex/compound failures, 115 earthflows, 54slides, 40 debris flows, and 5 rock falls (Table 1). The mapped landslides range in size fromAL ¼ 4.0 × 102 m2 to AL ¼ 4.0 × 106m2, for a total landslide area ALT ¼ 4.43 × 107 m2,37.4% of the study area. The figure is significantly larger than the proportion of landslides inother areas in the Apennines (e.g., Guzzetti et al., 2008), and demonstrates the importance of land-slides as a mass-wasting process in the study area.

Visual inspection of the landslide map reveals high spatial persistence of slope failures ofdifferent generations inside pre-existing (older) landslides. Local relief and geological settingcontrol the type and spatial distribution of the landslides. Debris flows cluster at the toe of thewestern slope of Mt. Alpi, where relative relief is greatest. Complex/composite failures aremost abundant where clay-rich layers are associated with hard metamorphic and sedimentaryrocks. Slides and earthflows have formed primarily where stiff clay and marls crop out. Large,very old deep-seated landslides are controlled by the spatial arrangement of stratigraphic and tec-tonic discontinuities; a typical condition for the development of deep-seated landslides in theApennines (Guzzetti, Cardinali, & Reichenbach, 1996, Guzzetti et al., 2008, 2012; Conforti,Robustelli, Muto, & Critelli, 2011).

Table 1. Descriptive statistics for landslides mapped on inventory map prepared for the upper Sinni Rivervalley.

Landslide type N (#) Amin (km2) Amax (km2) Aavg (km2) Atot (km2)

Complex/Composite 317 3.76 × 1023 4.05 × 100 2.89 × 1021 3.76 × 101

Earthflow 115 4.02 × 1024 8.4 × 1021 3.75 × 1022 4.32 × 100

Slide 54 1.10 × 1022 2.11 × 100 2.74 × 1021 1.48 × 101

Debris flow 40 4.53 × 1024 2.52 × 1021 1.88 × 1022 7.51 × 1021

Rock fall 5 1.8 × 1022 4.03 × 1022 2.72 × 1022 1.36 × 1021

Total (all landslides) 531 4.02 × 1024 4.05 × 100 1.08 × 1021 5.76 × 101

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Figure 2. (A) Sketch of the landslide inventory map. Landslides are classified according to their relativeage. (B) Box plot comparison for landslide areas within the ‘Very old’, ‘Old’, and ‘2009 landslide event’classes. Color coding of the box plots is the same as the sketch map in (A). Box plot of the entire inventoryis shown for reference.

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Figure 2 summarizes information on the estimated relative age of the mapped landslides.Inspection of the box-plot reveals that the median (50th percentile) of the area of the very-oldlandslides is larger than the maximum area of the old landslides. We interpret this result as an evi-dence for the incompleteness of the old landslides, some of which have been removed by erosion,other landslides, and human activity. Figure 3 shows the distribution of terrain slope and elevationinside and outside the mapped landslides in the study area. Landslides form primarily whereterrain slope is in the range between 108 and 288, with about 50% of the terrain in this sloperange affected by landslides (Figure 3(a)). Landslides are most abundant between 800 and1000 m of elevation, and cover about 50% of the area with elevation in the range from 600 to

Figure 3. Histograms showing the percentage of area covered by landslide-free area (black bars) andlandslides (gray bars) within each slope (A) and elevation (B) class.

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1000 m (Figure 3(b)), where soft rocks (clays pertaining to the Liguridi Units, and marls and clayspertaining to the Lagonegro Units) crop out. Landslides are less abundant at elevations higherthan 1,000 m, where hard rocks (Mesozoic limestones, and rocks pertaining to the metamorphicbasement) crop out. In this elevation range, the most widespread landslides are of the rock fall anddebris flow type.

Whilst visual interpretation of stereoscopic aerial photographs and geomorphological fieldmapping are traditional methods for detecting and mapping landslides (Brunsden, 1993; Guzzettiet al., 2012), they are not error free. Therefore, landslide inventories produced by both of thesemethods have limitations that must be considered when consulting such maps (Galli, Ardizzone,Cardinali, Guzzetti, & Reichenbach, 2008; Guzzetti et al., 2012; Santangelo, Cardinali, Rossi,Mondini, & Guzzetti, 2010). Visual interpretation of stereoscopic aerial photographs can resultin mapping errors due e.g., to the complexity of the terrain and the landslides in the studyarea, to the ability and the experience of the interpreters, and to the tools and techniques usedto transfer landslide information from the aerial photographs to the topographic base maps,and to store the information in a digital format (Guzzetti et al., 2012). Mapping errors are pro-duced by the different scales of the aerial photographs and the base map, the distortion of a land-slide in the stereoscopic model, caused by the vertical exaggeration and the conical projection ofthe aerial photographs, and by differences in the topography shown in the aerial photographs andthe base maps (Ardizzone, Cardinali, Galli, Guzzetti, & Reichenbach, 2007, Santangelo et al.,2014).

Field mapping of event landslides (i.e., landslides triggered by a single triggering event) isalso problematic. Errors are caused primarily by the fact that the landslides are identified andmapped visually using base maps that pre-date the event landslides, and may not show sufficientmorphological information to place the landslides accurately (Santangelo et al., 2010).

Despite possible mapping errors, which are inherent to any landslide inventory map (Guzzettiet al., 2012; Santangelo et al., 2010, 2013), we maintain that our inventory was prepared adoptinga rigorous legend, contributing to reducing potential inconsistencies in the interpretation of theaerial photographs and the classification of the mapped landslides. Further, two interpreters per-formed the mapping of most of the landslides. This contributed to reducing the subjectivityinherent in landslide mapping (Guzzetti et al., 2012).

Finally, we stress that the landslide inventory map was produced interpreting 1:33,000-scalestereoscopic aerial photographs and transferring the landslide information to 1:10,000-scale topo-graphic base maps. The landslide inventory map should be viewed and used at 1:10,000 scale, orat a smaller scale. Use of the landslide information shown in the inventory map for studies andapplications that require greater cartographic detail or accuracy is not recommended.

5. Conclusions

In this paper, we present a geomorphological landslide inventory map for an area of 120 km2 inthe upper Sinni River valley, southern Apennines, Italy. We produced the landslide inventory mapthrough the visual interpretation of 1:33,000-scale stereoscopic aerial photographs, aided by fieldsurveys performed to check the interpretation of the aerial photographs. The landslide map shows531 landslides of different types, for a total landslide area ALT ¼ 4.43 × 107 m2, 37.4% of thestudy area. About 30% of all the mapped landslides were located inside or in the vicinity ofpre-existing (i.e., older) slope failures, confirming that the spatial distribution of the recent land-slides is influenced by the presence of older landslides. In the study area, the landslide types, dis-tribution, and pattern are controlled by the local lithological and structural settings. We expect thatthe new landslide inventory map will be used for the evaluation of landslide susceptibility and

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hazard in the study area, and for quantitative geomorphological analyses aimed at understandingthe long-term geomorphological evolution of a portion of the southern Apennines.

SoftwareEsri ArcGIS 9.2 was used to digitize the landslide information collected during the field surveys and toperform the spatial analyses.

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Van Den Eeckhaut, M., Kerle, N., Poesen, J., & Hervas, J. (2012). Identification of vegetated landslides usingonly a Lidar-based terrain model and derivatives in an object-oriented environment. Proceedings of the4th GEOBIA, May 7–9, 2012 - Rio de Janeiro - Brazil. p.211.

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850

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700

650

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600

650

700

750

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850

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550

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800

750

700

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600

650

600

550

1050

1000

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900

850

800

750

700

750

700

650

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950.0

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260000015° 55’ 12’’

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40°

9’ 1

6’’

4444

000

16° 4’ 23’’

40°

1’ 5

9’’

LANDSLIDE INVENTORY MAP FOR THE UPPER SINNI RIVER VALLEY, SOUTHERN ITALYMICHELE SANTANGELO (1,2)*, DARIO GIOIA (3), MAURO CARDINALI (1), FAUSTO GUZZETTI (1), MARCELLO SCHIATTARELLA (4)

(1) Istituto di Ricerca per la Protezione Idrogeologa, Consiglio Nazionale delle Ricerche, via Madonna Alta 126, I-06128 Perugia, Italy(2) Dipartimento di Scienze della Terra, Università degli Studi di Perugia, Piazza dell’Università, I-06123 Perugia, Italy

(3) Istituto per i Beni Archeologici e Monumentali, Consiglio Nazionale delle Ricerche, C.da S. Loja, I-85050 Tito Scalo (PZ), Italy(4) Dipartimento di Scienze, Università degli Studi della Basilicata, via dell’Ateneo Lucano, I-85100 Potenza, Italy

(*) Corresponding Author: M. Santangelo ([email protected])

Boundary of Study area

Lake

A

B

Slide – The source is arched and concave upward, with cracks and vertical escarpments. The deposit exhibits a distinct hummocky topography, with depressions, back-tilted slopes and ridges. (A) Source area. (B) Deposit.

A

B

Complex/Composite – Large to very large failures, mostly slide-earth flows and other failures with two or more types of movement in the same failure. The deposit is long and narrow, with a hummocky topography. (A) Source area. (B) Deposit.

Alluvial deposit

A

B

Earth flow – Small to large, elongated failures with a distinct hummocky morphology and a lobate convex deposit. (A) Source area. (B) Deposit.

Debris flow – Failure that originates from steep slopes, travels along the drainage network and deposits along the channels or on the fans at the mouth of the channels. The material involved consists of soil, debris and broken rock, fine to very coarse in size. Source, travel and depositional areas were mapped sepa-rately, but they may be useful to separate. (A) Source area. (B) Transport zone. (C) Deposit.

A

B

Rock fall and Topple – Failure of single or multiple elements of rock or debris from cliffs and escarpments. The source area is vertical to sub-vertical. The deposit is characterised by irregular rock blocks and debris of different sizes. (A) Source area. (B) Deposit.

LEGEND

A

B

C

Datum: Monte Mario, Projection: Transverse Mercator, eastern zone

EPSG: 3004

Topographic map based on the Carta Tecnica Regionale of the Regione Basilicata

At intended printing scale of 1:25,000

The landslide inventory covers 120 km2 of mountain-ous terrain in the Upper Sinni River Basin, Southern Italy. The map was prepared through the systematic visual interpretation of black and white stereoscopic aerial photographs, flown in 1991 at 1:33,000 scale. Field surveys were performed to check the landslide information obtained from the aerial photographs.

Analysis of the morphological and photographical signature of each landslide in the aerial photographs and in the field allowed classifying the single slope failures in five classes, using a simplified version of the classification proposed by Cruden and Varnes (1996). The map shows 531 landslides, for a total landslide area of 44.9 km2, 37.4% of the study area.

N

0 1 2 3km

0.5

© Journal of Maps, 2014