ORI GIN AL PA PER

Landslide hazard and risk assessment and theirapplication in risk management and landuse planningin eastern flank of Menoreh Mountains, YogyakartaProvince, Indonesia

Danang Sri Hadmoko • Franck Lavigne • Junun Sartohadi •

Pramono Hadi • Winaryo

Received: 12 May 2008 / Accepted: 20 December 2009 / Published online: 21 January 2010� Springer Science+Business Media B.V. 2010

Abstract The Menoreh Mountains in Yogyakarta are severely affected by landslides.

Due to the high population densities, mass movements are generally damaging and fatal.

More than other Javanese mountains, the Menoreh Mountains cumulate several factors

causing landslides. Therefore, it is necessary to evaluate the ways to map landslide risk in

order to improve the risk mitigation. The objectives of this paper are to provide landslide

hazard and risk assessment that will be useful for risk prevention and landuse planning in

the Menoreh Mountains. So far, risk management has been developed by the Research

Centre for Disasters Gadjah Mada University in collaboration with the Regional Devel-

opment Planner (BAPPEDA), which carries out fundamental and applied researches. The

results of the studies have been integrated in the risk prevention and landuse planning in

order to improve the integrated landslide mitigation programme.

Keywords Landslides � Hazard � Risk mapping � GIS � Risk management �Mitigation � Menoreh Mountains � Java

1 Introduction

Like in many countries in the world, landslides have become one of the major natural risks in

Indonesia. The death toll by landslides in Java is very high, due to the high frequency of

landslide events and the high level of people’s vulnerability. During the period of

1990–2005, a thousand of landslide disasters have been reported in Java. During this period,

D. S. Hadmoko � J. SartohadiResearch Center for Disasters, Gadjah Mada University, Yogyakarta, Indonesia

D. S. Hadmoko � F. LavigneUniversite Paris 1 Pantheon Sorbonne, Paris, France

D. S. Hadmoko (&) � J. Sartohadi � P. Hadi � WinaryoFaculty of Geography, Gadjah Mada University, Sekip-Bulaksumur, Yogyakarta 55281, Indonesiae-mail: danang@gadjahmada.eduURL: http://www.hadmoko.staff.ugm.ac.id

123

Nat Hazards (2010) 54:623–642DOI 10.1007/s11069-009-9490-0

the death toll caused by landslides in Java exceeded 1,112 people and the number of people

injured reached 395 people. This vulnerability results mainly from the high density of

population and infrastructures located in the disaster prone areas. Landslide disasters also

become the major obstacle in development process because their economic losses are rel-

atively high (Guzzetti et al. 1999; Saha and Gupta 2002; Knapen et al. 2006) (Table 1).

Due to the high demand of public information related to spatial planning and envi-

ronmental protection, landslide hazard and risk assessment have become a fundamental

tool in risk management as an integral part of landuse planning in the disaster prone areas

(Gorsevski et al. 2006; Hadmoko 2007; Saldivar-Sali and Einstein 2007). Therefore,

evaluation of risks associated with landslides is an important challenge to develop proper

disaster management policies.

Varnes (1984) defined landslide hazard as the probability of occurrence of a potentially

damaging landslide within a specified period of time and within a given area. Hazard

assessments are commonly shown in maps, which display the spatial distribution or

zonation of hazard classes (Varnes 1984; Van Westen 1993). Landslide hazard zonation is

associated to the division of land in homogenous areas and their ranking according to

degrees of landslide hazard. It consists of two different aspects: assessing the terrain

susceptibility for a slope failure and determining the probability of a specific triggering

factor controlling landslides (Hadmoko 2007). Therefore, the hazard information should be

presented in a map in which the spatial information of degree of hazard is provided.

However, the temporal probability of landslide event is still difficult to be included in most

of hazard maps due to several factors: (1) absence of multi-temporal data of landslide

Table 1 Impacts of landslide disasters in Java during the period 1990–2005 to the houses, agricultural land,road and economic activities

No. Year Destruction

Housecompletelydamages

Housepartiallydamages

Agriculturearea (ha)

Road(m)

Estimatedeconomiclosses (euros)

1 2005 57 84 27 450 413,500

2 2004 68 179 169 155 650,500

3 2003 59 1354 93 235 1,816,900

4 2002 89 1119 129 607 1,772,100

5 2001 133 387 41 718 1,139,300

6 2000 182 626 1176 334 2,185,400

7 1999 120 459 89 307 1,575,900

8 1998 203 388 198 2362 1,592,200

9 1997 24 305 75 451 634,100

10 1996 131 632 58 858 1,508,800

11 1995 57 217 71 964 762,600

12 1994 125 191 266 1125,5 976,200

13 1993 88 153 221 136 736,600

14 1992 22 720 104,3 165,5 951,150

15 1991 32 264 229 345 603,700

16 1990 118 96 71 326 721 500

Total 1508 7174 3017,3 9539 18,040,450

Hadmoko (2006a, b)

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events in the hazardous area; (2) heterogeneity of the subsurface conditions; scarcity of

input data; absence or insufficient length of historical records of the triggering events

(Terlien 1996; Van Westen et al. 2005). Consequently, most of the published hazard maps

have only presented the spatial information of landslide hazard and do not provide an

estimate of ‘‘when’’ landslides occur.

Risk is defined by Einstein (1997) as ‘‘Hazard * Worth of loss’’. Hence, risk is obtained

by combining the quantified hazard or probability of failure with a quantified expression of

the consequences. Quantification of consequences requires the identification of the impacts

in terms of associated losses. Possible consequences can be listed as damage to houses, to

utilities and to roads. The spatial distribution of landslide risk may be obtained by spatial

subdivision of the area under study and multiplication of spatial landslide probability,

affected zones, landuse or spatial distribution of population or property and vulnerability

(Dai et al. 2002). This type of calculation can easily be calculated through GIS tools

(Leone and Leroi 1996; Wang et al. 2005).

Various methods have been developed and applied to landslide hazard and risk

assessment in the last 20 years (Van Westen 1993; Terlien 1996), from the simplest

method to very complex methods, using a large number of landslide parameters (Wang

et al. 2005; Hadmoko 2007; Dai et al. 2002) classified landslide hazard and risk assessment

into two methods, i.e. qualitative and quantitative assessment. The choice of these methods

is largely depending on both the desired accuracy of the outcome and the nature of the

problem and should be compatible with the quality and quantity of available data. Gen-

erally, for a large area where the quality and quantity of available data are too limited for

quantitative analysis, a qualitative risk assessment may be more applicable; while for site-

specific slopes that are amenable to conventional limit equilibrium analysis, a detailed

quantitative risk assessment should be carried out.

Semi-quantitative assessments or heuristic method of landslide hazards have been

carried out by several scientists in Indonesia. For example, Dibyosaputro (1999), Mar-

diatno (2002) and Goenadi et al. (2003) had applied relative hazards map by using com-

bination between scoring and weighting methods in Kulon Progo Area. Layers of data were

superimposed in geographic information system (GIS) to create the landslide hazard map.

Scoring and weighting value were applied to all parameters used in the analysis based on

their relative contribution to landslide hazard. Based on the relative hazard information

value, final hazard map was presented.

The key aim of this paper is to present landslide hazard and risk assessment as basic

information for risk prevention and landuse planning in the eastern flank of Menoreh

Mountains in Central Java. A vector-based GIS was used to analyse several factors,

including slope, geology, soil and landuse that play a dominant role in landslide occur-

rence. The overlay operation in GIS is mostly used in this research in order to build hazard

and risk maps. Implementation of hazard and risk maps will be presented in landslide

prevision, prevention, protection countermeasures and landuse planning (Fig. 1).

2 Description of the study area

Situated at Kulonprogo District, the eastern flank of Menoreh Mountains is located 20 km

west of Yogyakarta City (Fig. 2). The study area, which consists of five districts i.e.

Samigaluh, Kalibawang, Girimulyo, Kokap and Nanggulan, covers approximately

343 km2. Menoreh Mountains are highly and densely populated (210,448 inhabitants and

655 inhab./km2 (Hadmoko 2006a).

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Among all Indonesian provinces, Menoreh Mountains are one of the most exposed

regions to mass movements. This area is subjected to many factors favouring the occur-

rence of landslides: steep slopes; a humid climate associated with heavy rainfall;

Fig. 1 Landslide disaster risk management and landuse planning strategy

Fig. 2 Physiographic view of Mounts Menoreh, Yogyakarta Province from SRTM data

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earthquakes occurrence; human activity (mining, heavy development, agriculture). Dam-

age caused by landslides exceed hundreds of millions rupiahs (Table 1) that means tens of

thousands dollars. Moreover, local statistics and interviews carried out among local

communities living at risk underline an increasing of mass movement occurrence from the

late 1990s. For example, recurrent landslides in the Purworejo prefecture (west flank of the

Menoreh Mountains) made 56 victims since the catastrophic events of the 5th and 6th

November 2000. This example is representative of all mountainous areas in South Java.

Massive landslides affect deep slopes which has been stable for decades.

Menoreh’s climate is characterized by a humid tropical environment like others area in

Java. There are two pronounced seasons in this area: a rainy season from November to

April and a dry season from May to October. Maximum average annual rainfall calculated

in Samigaluh Station (?515 m asl) is 3107.1 mm (1973–2001), and minimum average

annual rainfall is reported in Nanggulan Station (?60 m asl) is 1563.1 mm (1973–2001).

Geomorphologically, Menoreh Mountains are dominated by three major landforms

origin, namely structural, denudational and fluvial forms, which can be subdivided into

eight landform units (Fig. 3). Denudational processes can be clearly identified in the study

area, particularly erosion and landslide processes. Very intensive denudational processes

usually occur in dryland agriculture areas on upper and middle slopes.

From a geological point of view (Fig. 4), Menoreh Mountains consist of three rock

formations, namely Nanggulan, Jonggrangan and Old Andesit Formation. The Nanggulanformation, formed between the middle Eocene and the old Oligocene (Van Bemmelen 1949),

Fig. 3 Landform map of the study area

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encompasses the oldest rocks of the Menoreh Mountains. This 300-m-thick formation is

composed of agglomerate, sandstone, limestone and clay mixed with tuffs. From the Young

Oligocene Superior to the Old Miocene, tectonic movements related to the subduction

between the Australian Plate and the Eurasian plate uplifted the mountains. This uplift is

accompanied by an intense volcanic activity built of 600-m-thick deposits called OAF (OldAndesite Formation). These deposits are composed of a thick layer of andesitic breccias

(appearing on 40% of the Menoreh) and tuffs with inserted lava flow deposits.

The Oligo-Miocene uplift caused the formation of a complex system of faults and folds,

which deformed the former deposits with sometimes much accentuated dips. Marine

deposits originated from several phases of marine invasion alternate with deposits of the

Jonggrangan and Sentolo formations on discordant breccias. These formations are defined

as olistostromes made of thick marine limestones, sandstone–limestones and mio-pliocene

marl sandstones with respective thickness of approximately 250 and 950 m. The litho-

logical variation is a major factor of instability, insofar as the lithological superposition

offers a multitude of potential slip surfaces.

Landuse system of the study area is classified into six categories (Table 2). Menoreh

Mountains are principally covered by kebun campuran (147 km2) or 43% of total area

(Regional Development Planner or BAPPEDA, unpublished data). The human settlements,

which cover about 88 km2 or 25.6% of the total area, may be located either on gentle

slopes or on very steep slope. Cut and fill, which have often been done by local people to

build their houses, aggravate slope instability.

Fig. 4 Simplified geological setting of Menoreh Mountains

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Dry fields or tegalan system (44 km2 or 12.8% of the total area) is applied by local

people to cultivate non-arable land on steeper slopes when there is no irrigation available

in this area. Rice fields or sawah area (41 km2 or 12%) is generally found on gentle slope

where the irrigation system is available. Forest areas cover the smallest part of Menoreh

Mountains (10 km2 or 2.9% of total area) due to land conversion into settlements and

agriculture area.

3 Methods

3.1 Basic assumption

The fundamental principle of landslide hazard zonation in this research is ‘the past and thepresent are keys to the future (Varnes 1984; Carrara et al. 1991; Hutchinson 1995; Wang

et al. 2005). This principle which follows from uniformitarianism implies that slope fail-

ures in the future will be more likely to occur under the conditions which led to past and

present instability (Ercanoglul et al. 2004). Hence, the future landslides will occur under

conditions and factors equal or similar to those for comparable past landslides such as

slope, geology, soil, landuse.

It is further assumed that the causative factors for the mapped landslides remain almost

constant over time. Landslide occurrence, in space or time, can be inferred from heuristic

Fig. 5 Slope steepness distribution in Eastern Part of Menoreh Mountains

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investigations, computed through the analysis of environmental information as a result of

combination of physical factors. Therefore, a territory can be zoned into hazard classes

ranked according to combination of certain factors (Guzzetti et al. 1999). In this research,

terrain susceptibility analysis to landslide has been conducted, which represents terrain

sensitivity to triggering factor such as rainfall and seismic acceleration.

3.2 Methods of obtaining the parameter maps

Five parameter maps were used in order to build landslide hazard maps, namely landform

map, slope map, geological map, soil map and landuse map. Detailed thematic data were

derived from existing topographical maps, aerial photographs and field surveys. These

Table 2 Score and weight factors used to each parameter in hazard assessment

Parameters Variables Weight Score

Landform Alluvial plain (F1), Flood plain (F2), Natural Levee (F4) 0.36 1

Colluvium-alluvial footslope (D4) 2

Footslope of structural hills (D2), Footslope of denudational hills (S2) 3

Structural hills (S1) 4

Denudational hills (D1) 5

Slope 0 \ 8% 0.36 1

8 B 15% 2

15–25% 3

25–45% 4

[45% 5

Geology Alluvium (Al) and Alluvium volcanic (Av) 0.07 1

Clastic limestone (Cl) 2

Marl (M) 3

Plutonic intrusion (Pt) 4

Non-Clastic Limestone (NCl), Andesictic Breccias (Bc), and Sandstone (Sd) 5

Soil Complex Troporthents Eutropepts Hapludalfs, Eutropepts 0.14 1

Association Pelludert Epiaquepts; Tropafluents; Association HapludalfEutropepts; Association Tropaquepts Eutropepts; Association PelludertsEutropepts; Association Hapludalfs; Troporthents; Dystropepts;Endoaquepts; Epiaquepts; Association Cromusderts Eutropepts; AssociationTropafluents Eutropepts; Hapludalfs

2

Association Hapludalfs Troporthents; Troporthents 3

Association Epiaquepts Endoaquepts 4

Complex Troporthents Eutropepts; Association; Eutropepts; Dystropepts;Complex Eutoprpts Pelluderts Troportents; Tropopsamments; AssociationEutropepts Pelluderts; Association troporthents Dystropepts; AssociationTroporthents; Pelluderts; Pelluderts

5

Landuse Forest 0.07 1

Mixed forest 2

Garden 3

Paddyfield, settlement 4

Dryland agriculture 5

Modified after PSBA-UGM (2001)

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maps were transferred into digital format in vector-based GIS by using ArcViewTM

software.

Landform map was produced based on stereo aerial photos interpretation. Landform

units are classified based on four parameters as main factors to classify landform unit i.e.

surface morphology, lithology, genesis, morphochronology and morphoarrangement. The

study area was identified into four major processes i.e. volcanic, structural, fluvial and

denudational processes. These four major processes were mapped and classify into eight

landforms unit (Fig. 3).

A triangular irregular network (TIN)-based digital elevation model (DEM) of a 1:25,000

topographical map was used to create the slope map. A TIN represents one or more

geographical layers, usually at least a surface layer, where space was partitioned into a set

of non-overlapping triangles. Attribute and geometry information was stored for the points,

lines and faces that comprise each triangle. By using the value of the each face, slope angle

can be obtained. Five slope categories were used in this analysis adopted from criteria for

landslide susceptibility assessment from Research Center for Disasters, Gadjah Mada

University (2001). These categories represent the different terrain morphology and clas-

sified according to gradients: Class I (0–8%): level to gently sloping; Class II ([8–15%):

gently sloping to undulating, Class III ([15–30%): undulating to moderately steep,

Class IV ([30–45%): moderately steep to steep, Class V ([45%): very steep (Table 2 and

Fig. 5).

Geological map (Fig. 4) was digitized from a 1:100,000 geological map (Raharjo et al.

1995). Eight geological units were mapped in Mountainous areas. These eight units of

geology were ranked into five categories of susceptibility based on the degree of weath-

ering, stability and the existence of faults. The 1:100,000 scale of geological map is used

although this scale is smaller than other parameters maps (1:25,000) due to the unavail-

ability of medium/large scale of geological map. Consequently, the smaller scale of

geological map caused the over-simplification of geological information e.g. lithology,

structure, weathering degree and rock stability. Therefore, extensive field works were

carried out in order to verify and to complete this information.

Soil map was obtained from a 1:25,000 scale map from the soil science department of

Gadjah Mada University. USDA classification was used to group the soil family. In

Menoreh Mountains, 25 soil families were identified and grouped into five categories

related to their contribution to landslide hazard based on the texture, drainage, soil

thickness and stability (Table 2).

Landuse map was used in order to rank the physical vulnerability to landslide hazard of

each landuse system. Landuse data were obtained from existing maps at 1:12,500 scales

and through the interpretation, colour aerial photographs in 1:20,000. In a 12,500 scale

map, five categories of landuse system were classified. Point data were digitized to obtain

the spatial distribution of houses. Based on the number of houses and of persons living in

each house, a risk index was created (Table 2).

3.3 Hazard assessment

Normally, a landslide hazard zonation consists of two major aspects e.g. spatial probability

of landslide occurrence which can be conducted by zoning different hazardous areas and

temporal probability which is related to the magnitude return period of the triggering event

and the occurrence of landslides (Varnes 1984). However, determining temporal proba-

bility is often not possible, due to the absence of historical landslide records that effectively

can be related with the historical records of the most important triggering events (rainfall

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and earthquakes), scarcity of input data, or the absence or insufficient length of historical

records of the triggering events (Van Westen et al. 2003). These parameters are very site

specific and can only be modelled properly using deterministic models, which require large

amount of geotechnical data. This method is sometimes unsuitable for developing coun-

tries like Indonesia due to the high budget and time required.

Therefore, an alternative method to build landslide hazard map is needed in order to

solve these problems explained previously. The semi-quantitative system can be used to

bridge between qualitative and quantitative methods by evaluating the importance of

parameters in the generation of landslide hazard maps (Van Westen et al. 2003). This

method represents only the ‘spatial extension’ of landslide hazard but the temporal

probability cannot be included. The semi-quantitative method is also widely used in

developing countries like in Baguio Region, Philippines (Saldivar-Sali and Einstein 2007),

and San Antonio del Sur, Guantanamo, Cuba (Abella and Westen (2008). This method is

useful when quantitative parameters are limited whereas qualitative data are available. The

proposed method is based on relatively simple characteristics, which can be easily assessed

on the map and checked in the field or from available records. This makes it easily

applicable in developing countries like in Indonesia.

An indirect mapping approach was applied to establish the different landslide hazard

zones using classical overlay operations by using GIS after having established maps

representing major landslide influencing factors. We built mapping unit in order to assess

landslide hazard by using five parameters mentioned previously.

Before the overlay operation, maps of landform, slope, geology, soil and landuse were

firstly prepared. Each parameter map conditioning landslide occurrence is evaluated, by

giving score and weight, and repeated to all parameter maps separately. This method was

mainly based on the experts’ knowledge and experience (Watchal and Hudak 2000; PSBA-

UGM 2001; Abella and Westen 2008). Final hazard map can be obtained by calculation of

total score through combination between adding and multiplying operation in GIS by using

the following basic formula:

LHI ¼ 0:36LANDFþ 0:36SLOPþ 0:07GEOLþ 0:14SOILþ 0:07LUð Þ ð1Þ

where LHI is landslide hazard index, LANDF is landform unit, SLOP is slope map, GEOL

is geological map, SOIL is soil map, LU is landuse map, and the number are representing

weighting factors for each parameter map. The weighting factors were calculated based on

the relative contribution of each parameter to landslide hazards (Table 2). Weighting

process was carried out by comparing the relative contribution of each factor to landslide

hazard during the extensive field investigations. The weight values were decided by team

of experts using the checklist of factors and give them a ranking. Using trial and error

method, the weight-scoring values have been re-adjusted (Panday et al. 2008). The highest

weight value of parameter map is the most important factor to landslides (Watchal and

Hudak 2000; Abella and Westen 2008). Based on the assessment, weight value of land-

form, slope, geology, soil and landuse are 0.36; 0.36; 0.07; and 0.07, respectively, with the

total weight value is 1.00. Range values between 1 and 5 systems were used to classify the

score representing importance of each parameter to landslide. Based on the maximum and

minimum total scores of all parameters and the number of rank used, hazard levels can be

classified.

Hazard map was classified into three categories e.g. high, moderate and low hazard,

based on the maximum and minimum value of the total score (Table 3), by applying the

following formula:

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Class interval ¼ Max value�min value

Number of class: ð2Þ

Hazard ratings range from 5 for the highest hazard zone to 1 for the lowest hazard zone.

Using this method, ranges are well represented by their average and values within each of

the ranges are fairly close together (Watchal and Hudak 2000).

3.4 Risk assessment

Landslide risks assessment in Menoreh Mountains had been carried out semi-quantitatively

by using risk index. Risk assessment was focused only on the number of populations

possibly threatened in each house or building mapped in the region (Table 4). In order to

calculate the density of building, we divided the number of houses by the surface of each

district (unit/km2). However, infrastructure and indirect loss induced by the disruption of

economic activities were not assessed. Legend of risk map consists of two fundamental

parameters: (1) landslide hazard index, which is displayed by hachured colour polygons

and (2) and risk index, which is presented by solid colour polygon (green, yellow and red).

4 Results

4.1 Landslide hazard map

Three hazard zones were obtained in this research (Fig. 6). Low hazard zones, which are

defined as stable and safe areas with no recognizable mass movement processes, are

usually located on flat—gentle slope (0–8%). This area is often associated with alluvial

plain, natural levee and colluvium-alluvial footslope and covered by alluvium and allu-

vium volcanic materials. The percentage of total area classified as low hazard zones is

75 km2 (22%).

The moderate hazard zones are usually associated with local evidence of shallow and

non-catastrophic landslides. Soil creep, inclined house, crack, tilted electrical pillars are the

common features identified in this zone. The damage is expected to be local and can be

prevented by relatively simple and inexpensive stabilization measures. These areas

encompass the lower and partially middle slopes of Menoreh Mountains, including

footslope of structural and denudational hills. About 180 km2 (54%) was classified as

Table 3 Hazard level classifica-tion criteria based on the totalscore

No. Interval value Hazard level

1 1–2,33 Low

2 2.34–3.67 Medium

3 3.68–5 High

Table 4 Criteria used to deter-mine the risk index

PSBA-UGM (2001)

No Persons threatened Risk index

1 No Low

2 1–10 Medium

3 [10 High

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moderate hazard zone, which is characterized by moderate—steep slope (15–30%), and

soil thickness is 2–4 m. Geologically, this zone is usually occupied by fractured weathered

rocks whereas dips are parallel with slope inclination. Landslide occurrences are relatively

high, about 10–25 landslide events occur every year.

Within the high hazard zone, a lot of catastrophic landslides, usually deep-seated

landslides, ever occurred. These areas clearly show recognizable evidence of active

landslides or reactivation in parts of the old landslide units, with some sliding currently

taking place. The percentage of total area with very high landslide susceptibility is 81 km2

(24%). Slope steepness of these areas is more than 30%, soil thickness[4 m, dips parallel

with slopes, rocks occupied by fractures, more than 25 landslides events occurring every

year. Landslide occurrence is expected to cause victims, damage infrastructure, building

and agriculture area. Building construction should be avoided in these areas or at least not

until effective mitigation measures are installed.

4.2 Landslide risk map

We defined the potential consequences of landslides, through a combination of the land-

slide hazard and a typology of damage related to landslide risk i.e. potential loss of life and

loss of property. Risk information can be classified into three levels such as high, moderate

and low. We obtained seven combinations between the risk and hazard level (Fig. 7). For

the low hazard and low risk combination, we assumed that in the low hazard zone, there is

Fig. 6 Landslide hazard map of Menoreh Mountains

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no possibility of landslide occurrence, so the risk level is considered as low although there

is more than one person living in these houses.

There are 21,254 houses including the building of public facilities such as schools,

offices and hospitals mapped in the whole study area (Fig. 8a). We found that Pengasih is

the most densely district followed by Kokap, Kalibawang, Girimulyo, Samigaluh and

Naggulan that the density reached 150, 64, 56, 47, 46 and 46 unit/km2, respectively.

Analysis of potential risk shows that the highest risk for buildings is in Girimulyo (408

units) and followed by Kokap (369 units), Samigaluh (363 units). We found only 12 units

of buildings in Pengasih and 32 units in Nanggulan, which were identified as high risk to

landslides (Fig. 8b). The calculations of total risky building in Menoreh show that 6% of

houses were identified as high risk, 55% were classified as medium risk and 39% were

classified as low risk. The majority of houses were classified to moderate risk because the

majority of houses and buildings are occupied by 1–10 people.

4.3 Implication of landslide hazard and risk map on landuse planning

The development of scientific products such as landslide hazard maps, risk maps and

reports are not effective in reducing the landslide impacts unless this information is con-

cretely applied by local (desa, kecamatan), regional (kabupaten, propinsi) and national

government organization. Public awareness and landuse planning have also been taken into

Fig. 7 Zoom of risk map in the northern part of research area with the legend showing the look up table ofhazard and risk index. Only hazard map and the number of persons living in each house were considered tocalculate risk map

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account by government and became an important aspect in landuse planning and legally

documented as a law (undang-undang), national and regional policy (peraturan pemer-intah, peraturan daerah).

Planning measures at national, regional and local level are the one of the political and

economical ways to reduce landslide losses (Lateltin et al. 2005; Stanganell 2008). It can

be accomplished by applying the landuse planning in disaster prone area based on the

spatial landslide hazard and risk information. The first priority in selecting measures

implies appropriate landuse planning for local management plan purpose such as prohi-

bition, restriction and regulation for the developments in landslide-prone areas. Therefore,

the risk information will enable decision-makers, communities and individuals to make

informed decisions on where to live, to build infrastructures or business areas.

Fig. 8 a chart showing the building density and area in six districts of Menoreh Mountains and b number ofbuildings for each risk level in six districts of Menoreh Mountains

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The Research Centre for Disasters, Gadjah Mada University (PSBA-UGM) has

developed a guideline for landuse planning and comprehensive policy for disaster man-

agement in Menoreh Mountains based on risk information. Since BAPPEDA (govern-

mental regional planner) is responsible on development planning at local and regional

levels, the result of scientific work conducted by PSBA UGM was then transferred and

implemented into political decision by BAPPEDA. This guideline was realized based on

the hazard and risk information that we have developed previously (Table 5). This sug-

gested landuse planning was introduced and comprehensively integrated with the current

spatial planning managed by BAPPEDA. The participation of local communities was also

included as important factor in the disaster mitigation programmes (PSBA-UGM 2001).

4.4 Prevention and protection countermeasures

Disaster reduction involves measures designed to avoid (prevention) or limit (mitigation

and preparedness) the adverse impact of natural hazards and related environmental and

technological disasters. A total fulfilment of prevention, with a complete removal of

hazards, is unrealistic (Stanganell 2008). Consequently, the reduction of key aspect of

vulnerability as well as more practical path should be conducted. Until now, various types

Table 5 Landuse planning guideline based on hazard information

No Hazard level Recommendation for landuse planning

1 High hazard (red zone)Area within: [30% of slope steepness, soil

thickness [4 m, dips parallel with slopes, rocksoccupied by fractures, more than 25 landslidesevents occurring every years

High possibility of people to be injured in thewhole the area both outside and inside ofbuilding. Serious destructions are possiblyoccurred to all infrastructures

a. All developments, constructions forinfrastructures, settlements and public facilitiesare prohibited

b. Evacuation planning and provisions toinhabitant must be taken to insure their safety incase of emergency, through the development ofevacuation plans

c. This area is especially used for conservationpurpose non-engineered, semi-engineered orfully engineered protection

2 Medium hazard (yellow zone)Area within: 15–30% of slope steepness, soil

thickness 2–4 m, dips parallel/semi-parallel withslopes, rocks occupied by fractures, 10–25landslides events occurring every years

Medium possibility of people to be injured in mostarea both outside and inside of building.Moderate destruction is possible depending onthe quality construction and setting

a. Building and infrastructure are allowed withseveral limitation, and conditions must berespected (e.g. limited construction density,specific requirement for buildings)

b. Evacuation planning should be taken intoaccount to anticipate people installing in the riskzone

c. With some limitation, this area is used to severalactivities (e.g. economic, agriculture), andadditional research is required to specify suitableland use, allowable levels of construction. Theconservation purpose has to be taken intoaccount in this area

3 Low hazard (green zone)Area within: \15% of slope steepness, soil

thickness \2 m, dips semi-parallel with slopes,rocks occupied by fractures, \10 landslidesevents occurring every years

Low/no damages of infrastructure are possible.People are at low risk of injury

a. All development, constructions, infrastructuresand settlement are allowed by following thegovernmental planning in this area, no specificrequirement to be addressed for buildingconstruction

b. This area usually used to agricultural,economical and productive purposes

Source: modified after PSBA-UGM (2001)

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of practical aspects of risk mitigation in order to reduce the vulnerability have been carried

out. Prevention and protection of the risks were already set up by several local authorities,

non-governmental organisations and the universities in Menoreh Mountains by using

various methods (technical and social methods).

The prevention social approach proves to be fundamental in a developing country like

Indonesia. The purpose of social risk prevention is in order to provide information to the

people in evacuation and alert system purposes. Public awareness was realised by Direc-

torate of Volcanology and Geological Hazard Mitigation for the whole area in Java dif-

fusing the poster and hazard map in regional scale. With PSBA UGM, we have also

published hazard map and risk maps in large scale (1:25,000) (Figs. 6, 7), posters and

panels and accompanied by educational action (Fig. 9).

The diffusion of scientific materials was accompanied by the technical report and user

guideline, for the operational reason that the users can interpret it easily. In addition,

disaster education for local communities has also been conducted by PSBA UGM,

BAPPEDA and local authorities in disaster mitigation. Disaster Management National

Agency is also established by government called BNPB for national level. This institution

was created in order to replace Bakornas-PBP following the launching of the Law No. 24:

2007 concerning disaster management. At provincial level, a coordinating unit, called

BPBD (Disaster Management Provincial Agency), has been established to replace

Satkorlak-PBP. Furthermore, refugee treatment units called Satlak were established at the

district level (http://www.bakornaspb.go.id/, consulted on October, 2008). The main tasks

of these institutional frameworks are to plan, to coordinate and to standardize the national

approach for disaster management. Besides, it is also important to provide a multi-hazards

assessment showing the comprehensive vulnerability and hazard area.

Various techniques of protection against landslides, traditional or modern were already

carried out by regional department of public works followed by the inhabitants. A tradi-

tional technique consists of covering soil cracks by ground coatings beaten is usually

conducted by local peoples to limit the infiltration of rain water. Another technique is

Fig. 9 Examples of landslide prevention, education and protection in Central Java; a, c, d leaflet and posterof landslide awareness; b landslide warning signs in Menoreh’s road (Photos: Hadmoko)

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improving the drainage pipes in bamboo which is introduced into the slope vulnerable to

landslides. The bioengineering technique became also alternative protection countermea-

sures which have been applied to the several slope conditions. This technique is relatively

cheaper and community-friendly which can be conducted by local peoples (Karnawati

et al. 2004). A modern technique is construction of retaining concrete walls or small gabion

(walls of unsealed blocks and retained by a net) intended to stabilize or consolidate the

slopes along principal roads.

5 Discussion

Qualitative, semi-quantitative and quantitative methods have been developed by scientists

to estimate hazard and risk level. Each technique has advantages and limitations that can be

adapted to the available data and the type of information that we need. In this research, we

used semi-quantitative method in order to quantify the qualitative parameters which are

directly influencing landslide processes.

Geomorphological maps, geological maps and soil maps have only qualitative infor-

mation about the physical features of terrain. Therefore, we have to quantify these

parameters in order to assess landslide hazards. For example, the lithological information

can be quantified by different weathering level, the existence of joints and cracks, and

bedding plane direction etc. Soil unit map can be quantified by using its parameters such as

soil depth, swelling and shrinkage parameters, permeability. The main assumptions of this

research are: (1) each factor previously mentioned has different contribution to landslide

process and (2) the future landslides will occur in the susceptible area based on the

geomorphological, geological, slope, soil and landuse condition (Guzzetti et al. 1999).

Semi-quantitative method is widely used in Indonesia to assess the hazard level for the

area that the several parameters are difficult to be obtained such as landslide occurrence,

rainfall, seismic acceleration, groundwater fluctuation Dibyosaputro (1999), Mardiatno

(2002) and Goenadi et al. (2003). By using this method, reliable maps over larger areas

with limited costs and time availability can be provided (Van Westen et al. 2005). The

current method was done during 4 months of intensive works with the budget less than

4,000 USD. Therefore, it is applicable for the developing country like Indonesia in order to

anticipate budget and time limitation. In addition, this method is relative simple compared

by the quantitative method such as deterministic model.

The Indonesian standard for landslide hazard and risk mapping is currently unavailable

at SNI (Indonesian National Standard) (http://www.idsn.or.id). However, several Indone-

sian governmental institutions have their own version to represent landslide hazard maps

(e.g. Ministry of Public Work, National Agency for Survey and Mapping (BAKOSURT-

ANAL), and Directorate of Volcanology and Geological Hazard Mitigation (DVGHM)).

BAPPEDA and PSBA UGM built their own standard through this work, in order to provide

comprehensive and simple landslide hazard and risk maps which can be used easily by

scientists and decision-makers (local and regional authorities) on risk prevention and

landuse planning. The maps are also supported by technical user guide which is clearly

understandable.

However, there are several limitations have to be taken into account for the very

detailed hazard information or for engineering purposes. Within this approach, expert

opinions are used to estimate landslide potential from data on preparatory variables. This

approach is based on the assumption that the relationships between landslide susceptibility

and the preparatory variables are known and are specified in the models (Dai et al. 2002).

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Its reliability depends largely on how well and how much the investigator understands the

geomorphological processes acting upon the terrain (Guzzetti et al. 1999). This assumption

causes several uncertainties concerning the hazard and risk level. This information is

therefore resulted from subjective assessment of experts; consequently, a scientific vali-

dation is necessary to verify the result of hazard and risk.

The resultant landslide hazard values cannot be considered as absolute values because

the parameters used were the resultant of quantification of qualitative parameters. The term

of high, moderate and low hazard could not be compared by another product resulted by

another scientist in different area because these terms would be have different meaning. In

addition, we used only the relative static parameters in hazard assessment, and the trig-

gering factors such as rainfall and seismic acceleration were not considered in this

research; consequently, the temporal probability of landslides could not be assessed.

Since this work is intended to evaluate the qualitative information concerning potential

risk and due to the limitation of budget and time availability, the detailed information

concerning types and number of properties of each sub-district cannot be provided.

However, the information provided by this work would be valuable to the local govern-

ment in order to support on decision-making concerning landuse planning. In addition,

there is no research related to landslide risk assessment conducted in the study area;

therefore, this work became a pioneer and extendable for other areas in Indonesia. Detailed

information on the properties, infrastructures such as schools, offices, mosques, churches is

recommended to be included for the future research.

In order to improve the result of heuristic methods, Hadmoko and Lavigne (2007) have

been introducing a detailed spatio-temporal analysis for preparation of landslide hazard

maps in parts of Menoreh Mountains. This method has been carried out in order to assess

the temporal probability of landslides based on the historical data of landslides, the trig-

gering factors such as intensity, duration and antecedent rainfall and to improve the current

result of hazard and risk map. It is expected that the project would be extended to other

areas, which have high susceptibility to landslide. This work would be valuable to support

the government mitigation programme as well as it will be helpful to develop a landslide

hazard and risk assessment model for the area.

As pointed out in the previous section that the important efforts have been applied for

the assessment and management of landslide hazards such as risk prevention, public

awareness and protection by several institutions e.g. governmental, educational and non-

governmental organizations. Mitigation efforts i.e. hazard and risk mapping, scientific

researches, prevention and protection countermeasures have been applied. Landuse plan-

ning guideline based on landslide risk information has also been developed in district

levels is among the tools for landslide risk management.

However, many landslides are still occurring, triggering a considerable number of

destruction and victims. This phenomenon is probably caused by several constraints in

disaster mitigation programme. An integrated and multi-sectoral approach to risk man-

agement is currently still limited. Until now, many difficulties are still involved from

conceptual and practical aspects, including scientific barriers, administrative/bureaucratic

structures and the risk comprehensions to the society. This problem should be taken into

account as an important aspect to be considered as next action towards improved inte-

gration of landslide risk management and planning actions in landslide disaster prone area.

In addition, there is no sustainability of disaster education for local people. Hazard edu-

cation should be conducted regularly in order to build the better perception and under-

standing for local people regarding to landslide hazard and risk.

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6 Conclusion

Landslide disasters became a serious problem in Java particularly in Menoreh Mountains

as a result of physical–natural factors (e.g. high of rainfall intensity, domination of

mountainous area, intensive weathering processes). In addition, high demand of land due to

the rapid increase of population might aggravate the vulnerability. This phenomenon has

encouraged scientists to build landslide hazard and risk map in order to assess the most

hazardous area to landslides. Such maps are useful to provide the information for landslide

disaster mitigation programme. These hazard and risk assessments are followed by the

diffusion of scientific materials in order to educate the local peoples and to build their

perception to landslide risk. Several efforts were also being conducted in disaster miti-

gation through formal and non-formal education. However, there are still many constrains

have to be solved in order to obtain the better result. Therefore, an efficient management on

landslide risk, the coordination between regions, departments concerned, universities,

research centres, non-governmental organisations and local peoples in landslide-prone

would be helpful in order to obtain the better risk management. This coordination and

communication would minimize the wasting budget, man power, time allocation and miss-

communication of decisions taken in future.

Acknowledgments The authors thankful to the governmental regional planner (BAPPEDA) of Kulon-progo district, Yogyakarta Special Province, who had supported this work, as well as the Laboratoire deGeographie Physique, UMR 8591 CNRS, France, and the French Embassy in Indonesia. We acknowledgeResearch Centre for Disasters, Gadjah Mada University (PSBA UGM), for all the service and help duringthe field work and data processing, as well as the Directorate Volcanology and Geological Hazard Miti-gation, who provided the landslide data in Java.

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