ORIGINAL ARTICLE

Potential suitability for urban planning and industry developmentusing natural hazard maps and geological–geomorphologicalparameters

George D. Bathrellos • Kalliopi Gaki-Papanastassiou •

Hariklia D. Skilodimou • Dimitrios Papanastassiou •

Konstantinos G. Chousianitis

Received: 14 September 2010 / Accepted: 20 July 2011 / Published online: 4 August 2011

� Springer-Verlag 2011

Abstract During the planning of an urban environment,

usually only economic and social parameters are taken into

account. As a result, urban areas are susceptible to natural

disasters, which cause extensive damages in them, because

the cities or towns have been repeatedly located in vulnerable

areas. In this study, for the protection of human environment,

is proposed a unique approach of urban planning and sus-

tainable development. The study area is Trikala Prefecture

(Western Thessaly, Central Greece). An integrated evalua-

tion of the suitable areas for urban growth and light industry

development is proposed by using mainly natural hazards as

well as geological–geomorphological–geographical charac-

teristics of the study area. The used parameters were

correlated by using the analytical hierarchical process (AHP)

method and incorporated into a geographic information

system (GIS) in order to produce the corresponding suit-

ability maps. The study area is classified in five categories of

very high, high, moderate, low, and very low suitability for

urban growth and industrial development. Moreover, the

spatio-temporal changes of the urban limits are studied since

1885 for the three major towns (Trikala, Kalambaka and

Pyli) of the study area. These changes sketch out the urban

growth trend. The comparison between the urban growth

trend with the potential suitability for urban growth and

industrial development of these towns lead to discrepancies.

These can be attributed mainly to the fact that in the majority

of cases, only geographical, social, and economical factors

were used for urban development, whereas in our study,

natural hazards, geomorphological, and geographical

parameters were quantified and taken into account.

Keywords Urban geology � Land-use planning � AHP �GIS � Thessaly � Central Greece

Introduction

On a global scale, the combined forces of urbanization and

the rapidly expanding industry have been responsible for

great improvements in the quality of life over the last

150 years. Ironically, these forces now are threats for the

environment. Urban areas are widely characterized by

intense and often unregulated industrial activity, rapid and

poorly planned growth, fragmentation of natural habitats,

and degradation of surface and ground waters by a wide

range of chemical contaminants (Eyles 1997).

For the first time in history, in 2008, more than half of

the world’s human population (3.3 billion people) lived in

G. D. Bathrellos (&) � K. Gaki-Papanastassiou �H. D. Skilodimou

Department of Geography-Climatology, Faculty of Geology

and Geoenvironment, National and Kapodistrian University

of Athens, University Campus, 15784 Zografou, Athens, Greece

e-mail: gbathellos@geol.uoa.gr

K. Gaki-Papanastassiou

e-mail: gaki@geol.uoa.gr

H. D. Skilodimou

e-mail: hskilodimou@geol.uoa.gr

D. Papanastassiou � K. G. Chousianitis

Institute of Geodynamics, National Observatory of Athens,

Athens, Greece

e-mail: d.papan@gein.noa.gr

K. G. Chousianitis

e-mail: chousia@geol.uoa.gr

K. G. Chousianitis

Department of Geophysics and Geothermics,

Faculty of Geology and Geoenvironment,

National and Kapodistrian University of Athens,

University Campus, 15784 Zografou, Athens, Greece

123

Environ Earth Sci (2012) 66:537–548

DOI 10.1007/s12665-011-1263-x

urban areas. By 2030, this is expected to swell to almost 5

billion. Then, the towns and cities of the developing world

will make up 80% of urban humanity (United Nations

Population Funds 2007). The growth of towns and cities is

the engine of the world economy and generates enormous

social benefits by concentrating human creativity, but at the

same time causes most of the environmental problems

(Eyles 1997). Likewise, in Greece, more than 40% of the

national population and the greatest percent of economic

immigrants are congregating in the municipalities of the

broader Athens Area, the largest urban complex in Greece.

Almost 12% of the inhabitants of Greece live in the

municipalities of the broader Thessaloniki Area, which is

the 2nd largest Greek complex. Thus, more than 50% of the

Greek population lives in the two urban complexes of

Athens and Thessaloniki (National Statistical Service of

Greece 2009).

Urban sustainability can be influenced by a wide range

of economical, social, and environmental factors (Fedeski

and Gwilliam 2007; Thapa and Murayama 2010) such as

economic development, socioeconomic policy, population

growth, physical environment, and natural hazards (Xiao

et al. 2006; Rozos et al. 2011). However, during planning,

development, and management of an urban environment,

only the economical and social parameters are usually

taken into account. Consequently, in vulnerable locations,

such as areas presenting steep slopes and/or degraded soils,

the natural hazards that often occur, such as landslides,

earthquakes, and floods can cause extensive damage, dis-

ruption of the social and economic network and lead to the

loss of human lives and property.

In order to avoid the aforementioned effects, during the

planning and the growth of an urban environment, it is

necessary for the decision makers, engineers, planners, and

managers to take into account the physical parameters of

the urban area, as well as the susceptibility to the natural

hazards. The geology and the geomorphology of an area

are important in the assurance of sustainable land man-

agement and in the protection of human life in urban areas.

Dai et al. (2001) estimated urban land-use planning at an

urban area by means of topographic and geological

parameters, groundwater conditions, and geological haz-

ards, while Wang et al. (2008) took into consideration soil

erosion and land desertification for regional assessment of

environmental vulnerability in the Tibetan Plateau.

Multi-criteria analysis methods are decision support

tools for dealing with complex decision constellations

where technological, economical, ecological, and social

aspects have to be covered. These methods have been

repeatedly combined with geographical information sys-

tems (GIS) and are therefore suitable to optimize the land-

use planning (Marinoni 2004). According to Malczewski

(1999), the multi-criteria methods are: the simple additive

weighting, the utility function, the analytical hierarchy

process, the ideal point method, and the outranking

method. But regardless which method is being adopted,

one always comes to the point where the criteria playing a

role in the decision-making process have to be ranked and

weighted with respect to their relevance or importance,

respectively. The analytical hierarchy process (AHP) is a

weight evaluation method which, with regard to the

development of weights has already been called one of the

most promising techniques (Eastman et al. 1998; Marinoni

2004).

An integrated technique of the AHP and GIS is usually

implemented to support the assessment and the selection of

suitable areas for urban development (Bantayan and

Bishop 1998; Svoray et al. 2005; Dong et al. 2008; Tudes

and Yigiter 2010; Youssef et al. 2010) and for regional

growth (Triantakonstantis et al. 2006; Thapa and

Murayama 2008). AHP is a multi-criteria, mathematically

based technique that combines qualitative and quantitative

factors for ranking and evaluating alternative scenarios,

among which the best solution is ultimately chosen (Saaty

1977). The major concept behind the AHP is the imple-

mentation of a hierarchical representation of a decision-

making problem and the reduction of the complex problem

into pairwise comparisons. The GIS is a very useful utility

that enables the combined used of spatial multi-criteria

methods of decision making (Malczewski 1999; Chakhar

and Mousseau 2008).

In this study, the AHP and GIS techniques were

employed in the land-use decision-making procedure for

urban growth and light industrial (primary or genetic)

development, in Trikala Prefecture located in Central

Greece. The ranking of these factors was accomplished by

the implementation of AHP. The integration of the AHP in

a GIS is able to enrich decision-making methodology with

powerful visualization and mapping capabilities and

facilitate the creation of suitability maps. Moreover, the

potential urban development of the three major towns of

the study area is analyzed and compared with the derived

corresponding suitability maps.

The main scope of this study is to demonstrate the usage

of natural hazard maps and other physical parameters in

land-use planning and mainly in urban design. This con-

sideration—methodology is unique and can be used in

combination with the social-economic estimation in plan-

ners work. An effort is made to incorporate for the first

time planning parameters as natural hazard assessment

maps (earthquakes, floods, and landslides) in conjunction

with other geological and geomorphological parameters,

besides the commonly used factors. Moreover, this study is

an attempt to determinate the unsuitable areas for urban

and industrial development according to the natural

hazards.

538 Environ Earth Sci (2012) 66:537–548

123

Study area

The case study area is the Trikala Prefecture, located at the

western part of the fertile plain of Thessaly in Central

Greece. Trikala Prefecture is one of the four Prefectures of

Thessaly. The extent of the study area is 2,056 Km2 with

altitudes varying from 74 to 2,204 m above sea level. Its

major river, named Pinios (Fig. 1), flows from northwest to

southeast while the drainage network is well developed

with a significant surface run off (Migiros et al. 2011).

Its climate is mainly of Mediterranean type. The rainy

period begins on October and ends on May, while the mean

annual precipitation ranges from 671.7 to 1,633.6 mm,

depending on the altitude.

The geological formations of the studied area are crys-

talline schists, gneisses and ampibolites, semi-metamorphic

formations, crystalline limestones, conglomerates, ophio-

lites, limestones, schists-cherts, cherts, marls, flysch for-

mations, Pliocene, and Quaternary deposits, according to

the geological map of Bathrellos (2005).

The Trikala Prefecture is an appropriate case study area

because it is comprised of small urban areas, where there is

still a potentiality of interference and planning. In larger

cities, there is no such capability, apart from the peri-urban

areas. The inhabitants develop various economic activities,

such as commercial, agricultural, and touristic ones. The

total population of Trikala Prefecture was 138,047 inhab-

itants in 2001. Taking into account the population and

economic growth, the three major Prefecture towns are

Trikala (capital), Kalampaka, and Pyli. During the last

100 years, the population of these towns has at least

tripled, according to the official records, at the expense of

the smaller villages of the broader area. Specifically, the

population of the town of Trikala has increased from

14,820 inhabitants in 1889 to 48,686 in 2001. Similarly, for

the same period, the population of the town of Kalambaka

increased from 1939 to 7,392 inhabitants, while Pyli from

634 to 1,839 (National Statistical Service of Greece 2003,

2009). Regarding the industrial planning, the Trikala Pre-

fecture is also estimated as appropriate for a case study,

because there are small or medium-sized, not very pollut-

ing industrial units, making possible a planning from the

beginning or even a relocation of the current ones.

It should be noted that in the study area, land-use

planning based in natural parameters is necessary because

of the presence of one out of the UNESCO World Heritage

Sites list, which protect cultural and natural world heritage

monuments, namely the ‘‘Meteora’’, as well as several

archeological sites since the Paleolithic era (Fig. 1).

Data and methodology

Data

The used dataset for the study area is consisted of the

following:

• The corresponding topographic maps (11 sheets) of a

scale of 1:50,000, published by the Hellenic Army

Geographical Service (H.A.G.S.).

• A Digital Elevation Model (DEM), which is a repre-

sentation of the surface in raster format and was created

Fig. 1 Physicogeographical

map of the study area (Ath, Th

stands for Athens and

Thessaloniki cities,

respectively)

Environ Earth Sci (2012) 66:537–548 539

123

by digitizing the contours with 20 m intervals of the

above-mentioned topographic maps.

• The geological map on a scale of 1:50,000.

• Seismological data of the Geodynamic Institute of the

National Observatory of Athens for the time period

from 1953 until 2009.

• The town plan maps of the Trikala town for the years

1885 and 1937 on a scale of 1:5,000 (Katsogiannos

1988, 2001).

• LANDSAT 5TM/7ETM satellite images recorded on

1992 and 2005 accordingly.

• The field work data were collected for the flood hazard

of the study area.

Parameters for suitability development assessment

Several factors such as physical, social, and economic may

affect the land-use suitability in Trikala prefecture. Usu-

ally, the planners use social-economics parameters—fac-

tors in spatial planning. In the present study, it should be

noted that the selection of factors is not exhaustive and

only the physic process parameters were selected, because

of the aim of this work is to perform the usage of physic

geographical factors in planning.

Aiming for the assessment of the suitability for different

land uses in the study area, the geomorphological, geolog-

ical, and geographical parameters, in conjunction with the

major natural hazards that have affected Trikala prefecture

in the past, are taken into consideration. In order to produce

the potential suitability map for urban growth and industrial

development, the factors that incorporated in the present

study are the slope, aspect, elevation, main streams, lithol-

ogy (geomorphological–geological parameters), main road

network, main towns (geographical parameters), and natural

hazard assessment maps, namely landslide susceptibility

map, seismic and flood hazard maps. The selection of the

appropriate factors and the determination of the classes

number as well as their boundary values were based on:

(a) the literature review, (b) the discussion with researchers,

(c) the suggestions of engineers, geologists, and planners

working in the Public Services of Trikala Prefecture, and

(d) the personal experience from previous studies.

A spatial database was created by using ArcGIS 9.3

software (ESRI 2008), and the thematic layers of the

parameters were converted from vector to raster format on

a 30 9 30 m cell size.

The slope of the land surface has a crucial role in the

building activity, because steep slopes increase the cost and

conduce to erosion intensity (Rao 2005). Moreover, they

have an effect on the slope stability, increasing the land-

slide hazard (Bathrellos et al. 2009). In this study, the slope

map was derived from the Digital Elevation Model of the

study area, after the required processing. The slopes are

classified in 5 classes as follows: (1)\2�, (2) 2�–5�, (3) 5�–

8�, (4) 8�–10�, and (5) [10� (Fig. 2a).

The aspect is also taken into account because con-

structions with southern and eastern orientation are

exposed to larger amount of sunlight and heat during the

winter, compared to those with northern and western ori-

entation. The aspect map was derived from the slope map

and is classified into 4 categories, that is N 315�–45�, E

45�–135�, S 135�–225�, W 225�–315� (Fig. 2b).

Elevation is another parameter that affects urban

growth. Areas with high elevation in Greece are usually

characterized by the absence of vital infrastructure, such as

modern transportation networks. The elevation map is

derived from the Digital Elevation Model and classified

into five categories: (1)\250 m a.s.l., (2) 250 -500 m a.s.l.,

(3) 501–750 m a.s.l., (4) 751–1,200 m a.s.l., and (5)

[1,200 m a.s.l. (Fig. 2c).

Rivers are also taken into account in the present study.

They have a positive effect on urban growth because they

constitute a center of attraction and contribute in the

esthetic aspect of every city. Recreational parks are often

created nearby. On the other hand, rivers and their vicinity

are restricted areas for industrial development, because

very often industrial waste pollutes the water ecosystem

and can lead to irreversible destruction of the environment.

In the present study, the drainage network, which was

derived from the topographic maps of the study area, is

incorporated in the suitability analysis. The sixth, seventh,

and eight order streams, according to the Strahler classifi-

cation (Strahler 1964), were extracted, and the corre-

sponding spatial layer of the drainage network was

produced. Finally, a drainage buffer map was generated

and buffer zones were built around the streams of the main

drainage network at distances of 100, 200, 300, and 400 m

(Fig. 2d).

Lithology is a geological factor that affects mainly urban

development. Solid rocks are the most appropriate forma-

tions for foundation, even though they increase the cost of

infrastructure because of the required excavations. In order

to produce the lithological map, the corresponding geo-

logical map of the study area was used. The formations are

classified according their geotechnical engineering behav-

ior into three categories (Matula 1981), namely: (1) rocks

constituted of crystalline schists, gneisses and ampibolites,

semi-metamorphic formations, crystalline limestones, well-

cemented conglomerates, ophiolites, limestones, schists-

cherts, and cherts, (2) hard soils-soft rocks comprised of

marls, conglomerates with intercalations of thin-platy marly

limestones, flysch formations, lacustrine, and terrestrial

deposits of Pliocene, and (3) soils comprised of alluvial

deposits (sand, clay, silt, gravels, pebbles, etc.), talus cones,

screes, and weathering mantle (Fig. 2e).

540 Environ Earth Sci (2012) 66:537–548

123

Natural hazards comprise a crucial and very important

factor for urban development and for safe constructions in

general. In the present study, the natural hazards that are

studied and incorporated are landslides, earthquakes, and

floods. Landslides must be taken into consideration for

urban development, because the occurrence of landslides is

a regular phenomenon, especially in the mountainous part

of the study area. They can cause serious damage at sec-

tions of urban areas and at the road network. The published

landslide susceptibility map of the study area was used for

this purpose (Bathrellos et al. 2009). The used map had

been verified by active landslides. By means of this map,

we divided the study area into four zones for very high,

high, moderate, and low landslide hazard, respectively

(Fig. 2f).

The study area is characterized by low to moderate

seismicity. The National Seismic Hazard Map of Greece

(NEAK 2003) divides the area of Greece, into three seismic

zones, having maximum estimated active ground design

accelerations of 0.16, 0.24, and 0.36 g, respectively. Fol-

lowing this map, the mountainous area of the Trikala

prefecture, eastern and northern areas, is placed in the

lowest seismic zone, while the plain area belongs in the

middle one. Trying to classify in more details the seismic

hazard of the plain area, we have used the distribution of

the earthquake macroseismic intensities. These are

numerical values of a twelve-degree scale, assigned for

every place, village or town, according to the effects that

an occurred earthquake causes on people, their construc-

tions, and on the natural environment. The knowledge of

the macroseismic intensities of previous earthquakes and

the visualization of their spatial distribution in intensity

maps are of great importance for earthquake hazard studies

and are have been extensively worldwide used (Boughacha

et al. 2004; Gomez 2006; Simeonova et al. 2006; Pap-

anastassiou et al. 2008). In this work, we have mapped the

macroseismic intensities distribution across the area of

Trikala Prefecture and especially in the plain area. The

original data set consisted of 30,000 values of intensities of

151 earthquakes, located in the broader area of Greece

since 1953, as they have been routinely observed and listed

in more than 3,000 points (villages and towns) of Greece,

by the Institute of Geodynamics of the National Observa-

tory of Athens. From this data set, the intensities that have

been reported from 82 towns and villages of Trikala Pre-

fecture have been used. Values were interpolated using the

inverse distance-weighted (IDW) method and classified in

two groups according to their intensity value with \6 and

[6, and the corresponding map of macroseismic intensities

was created (Fig. 2g). Intensity values greater than 6

indicate areas where moderate to considerable damage

were reported. Following this procedure, we were able to

Fig. 2 The thematic layers of the parameters involved in the analysis.

a Slope, b aspect, c elevation, d distance from streams of the main

drainage network, e lithology, f landslide susceptibility, g earthquake

intensities, h distance from flood events, i distance from road

network, j distance from main towns

Environ Earth Sci (2012) 66:537–548 541

123

discriminate in the plain area of Trikala prefecture districts

with different seismic hazard. Comparing with the existing

National Seismic Hazard Map, the areas with intensity \6

can be compared with those of the middle zone, while

those with intensities[6 are in between the middle and the

higher zone.

It worth mentioning that flash floods are very common

in Mediterranean area and especially in Greece (Fouache

and Gaki-Papanastassiou 1997; Skilodimou et al. 2003;

Gaki-Papanastassiou et al. 2005, 2008). Concerning the

flood hazard in the study area, extensive damage and loss

of human lives have been referred in urban areas. Partic-

ularly, in the extend flood event of 1907 in the town of

Trikala, more than 100 persons were drowned and over

1,200 residences suffered serious damage. The potential

flood hazard nowadays is very low due to land reclamation

works (Migiros et al. 2011). But in the case of an extreme

flood event, e.g., with 100 years repetition, these works

could be proved insufficient. At the present time, incidents

of annual flood events are reported in specific areas. For the

purpose of this study, the flood hazard map is a preliminary

research, taking into account only the locations of previous

flood events. However, based on historical records and field

work carried out in the framework of the present study,

some not so extensive regions showed considerable flood

risk and were therefore mapped. Subsequently, a map

showing the distance from the flood affected areas was

constructed, showing buffer zones for distances 50, 100,

150, and 200 m, respectively (Fig. 2h). These distance

values were selected based on records and observation

during the field work.

In addition, intended for the development of the neces-

sary criteria for creating the suitability maps of this study,

geographical factors and particularly the main national

road network and the major towns of the study area were

taken into consideration. As a result, buffer zones were

created for 200 and 500 m distance (Fig. 2i) from the road

network and 1,000, 2,000, 3,000, and 4,000 m distance

around the major towns (Fig. 2j).

The aforementioned factors and values were used in

the suitability analysis to evaluate urban growth in the

study area. For the creation of the appropriate model to

predict the suitable areas for industrial development, the

same factors as for urban growth were used with the

following alterations. Regarding the elevation, the classes

that were distinguished were three: (1) \300 m a.s.l., (2)

300–700 m a.s.l., (3) [700 m a.s.l. Regarding the main

drainage network, the buffer zones were drawn around the

streams every 200 m, from 200 to 800 m. She buffer

zones around the major towns of the study area were

created for distances 2,000, 4,000, 6,000, and 8,000 m

around them.

Rating of the categories of the parameters

An important constraint in the evaluation is the rating of

the classes of each parameter involved in the analysis. In

the framework of the present study, the rating was con-

sistently based on a five-grade scale that as well has been

widely used by other researchers (Dai et al. 2001; Svoray

et al. 2005; Wang et al. 2008). The numerical values that

are given at each class are ranging from 0 to 4. The latter

represents the most favorable condition for urban growth

and industrial development, while the 0 value the less

favorable. It should be noted that the suggestions of the

experts working in the Public Services of Trikala Pre-

fecture and the personal experience were used to deter-

minate the assigned values for each class of the factors.

Table 1 shows the rating of the classes of each

parameter.

Weighting of the parameters

The cross-correlation and the rating of the parameters so

as to evaluate the suitability of the land for urban growth

and industrial development were achieved using the AHP

method. The AHP is a multi-criteria method that com-

bines qualitative and quantitative factors for ranking and

evaluating alternative scenarios among which the best

decision is chosen. The major concept behind the AHP is

the implementation of a hierarchical representation of a

decision-making problem and the reduction of the com-

plex problem into pair-wise comparisons. The first step in

the AHP is the computation of the pair-wise comparison

matrix, where each entry represents the relative signifi-

cance of a factor to the others. The relative importance

between two factors is measured according to a numer-

ical scale from 1 to 9. The correlation between the

numerical values and the intensity of importance is the

following: 1 = equal importance, 2 = weak or slight,

3 = moderate importance, 4 = moderate plus, 5 = strong

importance, 6 = strong plus, 7 = very strong, 8 = very,

very strong, 9 = extreme importance. Inversely, less

important variables were rated between 1 and 1/9 (Saaty

1977, 2004).

The normalized pair-wise comparison matrix is derived

by making equal to 1 the sum of the entries on each col-

umn. Finally, the objective weight of each factor was built

by averaging the entries on each row. The basic advantage

is that the AHP limits the cognitive demand on the decision

maker and provides an approach for checking the consis-

tency of the comparisons. The consistency ratio (CR) is

used in order to check inconsistency and limit the possi-

bility of random selection during the construction of the

comparison matrix and it is expressed as:

542 Environ Earth Sci (2012) 66:537–548

123

CR ¼ CI=RI

where RI is the random index which was developed by

Saaty (1977) and it is a constant which depends on the

order of the matrix and the CI is calculated by the formula:

CI ¼ k max�n=n� 1

where kmax is the largest eigenvalue of the matrix, and n is

the order of the matrix. According to Saaty (1990), for

matrices larger than 4-by-4, when CR \ 0.1 an acceptable

level of consistency has been achieved, whereas a consis-

tency ratio above 0.1 demands a reassessment of the

judgments in the matrix.

In the present study, the AHP method was applied in

order to cross-relate the parameters and to derive the

weights that were subsequently assigned to each factor

separately. A 10 9 10 matrix was primarily created, and

in its vertical and horizontal axes were set the factors

affecting urban development. A set of questionnaires with

the matrix were created. In this, the corresponsive should

decide the relative importance among the factors. The

questionnaires were allocated to five experts working in

the Public Services of Trikala Prefecture as well as to the

authors. From the questionnaires, ten separate matrix

were generated, which were further linearly combined

using average mean in order to prepare the final matrix.

After that, the rules of the AHP method were applied to

get the final weights for each factor. The weight values

and the CR are given in Table 2. The CR is equal to

0.05, which means that the matrix has an acceptable level

of consistency.

A similar procedure was applied in order to calculate the

weights of the factors affecting industrial development

(Table 3). As in the case of urban growth, the CR value

(0.06) is again satisfactorily small.

All the pair-wise comparisons, the eigenvectors, the

weights, and the consistency ratio were calculated using the

Expert Choice 11 software (ECI 2004).

The overall suitability index

The thematic layers of the parameters with their corre-

sponding weights were combined in order to calculate the

overall score index of the suitability for the two land uses.

Using the method weighted linear combination (Voogd

1983; Malczewski 1999; Marinoni 2004), factors were

combined by applying a weight to each followed by a

summation of the results to yield the suitability maps. This

method is the most frequently used technique for tackling

spatial multi-attribute decision making and is given by the

following mathematical operator:

Table 1 Rating of parameters involved in the analysis

Parameters Category Potential rating

0 1 2 3 4

Slope (�) UG [10 8–10 5–8 2–5 \2

ID [10 8–10 5–8 2–5 \2

Aspect (�) UG 315–45 225–315 45–135 135–225

Elevation (m a.s.l.) UG [1,000 750–1,000 500–750 250–500 \250

ID [700 700–300 \300

Distance from streams of main drainage network (m) UG [400 300–400 200–300 100–200 \100

ID 0–200 200–400 400–600 600–800 [800

Lithology UG Rocks Hard soils Soils

ID Rocks Hard soils Soils

Landslide susceptibility map UG Very high High Moderate Low

ID Very high High Moderate Low

Seismic intensity UG [6 \6

ID [6 \6

Distance from flood events UG \50 50–100 100–150 150–200 [200

ID \50 50–100 100–150 150–200 [200

Distance from main road network (m) UG [500 200–500 \200

ID [500 200–500 \200

Distance from main towns (m) UG [4,000 3,000–4,000 2,000–3,000 1,000–2,000 \1,000

ID \2,000 2,000–4,000 4,000–6,000 6,000–8,000 [8,000

UG urban growth, ID industrial development

Environ Earth Sci (2012) 66:537–548 543

123

S ¼Xn

i¼1

WiXi

where S is the suitability degree, n is the number of factors,

Wi is the weight of factor i and Xi is the rating of factor

i. After the application of the above-mentioned equation,

the potential suitability maps for urban growth and indus-

trial development are produced.

Processing for the urban pattern changes

Image processing and GIS techniques have been used to

accomplish the changes of urban pattern of the three major

towns of the study area. In order to record the changes of

the boundaries of the Trikala town, we initially utilized the

town plan maps for the years 1885 and 1937 on a 1:5,000

scale (Katsogiannos 1988, 2001), while for the years 1992

and 2005, we used Landsat 5TM/7ETM satellite images.

For the towns of Kalambaka and Pyli however, only

satellite imagery was used because it was not possible to

obtain town plan maps. The town plan maps were geore-

ferenced to the projection system of the topographic maps,

which was the Greek Grid and digitized using ArcGIS

capabilities. The two scenes of Landsat images were

georeferenced and geometrically corrected using ERDAS

Imagine software. Furthermore, both images were trans-

ferred in the ArcGIS environment and a data fusion image

has been produced using bands 123 (RGB) in order to map

the boundaries of urban pattern of the three towns. Over-

laying techniques have been used to identify the changes of

the urban extent of the town of Trikala for the years 1885,

1937, 1992, and 2005, while regarding Kalambaka and

Pyli, for the years 1992 and 2005.

Results and discussion

Suitability maps

The produced suitability map for urban development

(Fig. 3) was further classified, using the equal interval

method, into five classes: very low, low, moderate, high,

and very high suitability. The protected areas (Meteora and

archeological sites) were excluded from the final map as

unsuitable. Furthermore, it should be mentioned that the

used flood hazard map is a preliminary research, taking

into account only the locations of previous flood events.

Therefore, the study has some limitations, and further

research is needed for the completion of the flood hazard

assessment.

Regarding the spatial distribution of the five classes, the

areas of very high suitability for urban growth are located

mostly at the plain part of the study area. These are for each

city:

• near the town of Trikala, east, north, northwest, and

southwest of the town

• near the town of Kalampaka, south and southeast of the

town

• near the town of Pyli, east and northeast of the town

The application of the multi-parametric model, besides

the suitability assessment, allowed the evaluation of the

present urban pattern, compared to the derived urban

growth suitability. The majority of the town of Trikala was

built on areas with very high suitable conditions according

to our method. On the contrary, parts of the towns of

Kalambaka and Pyli were built on areas with moderate or

high suitable conditions.

Table 2 The parameters and the calculation of their weights for the

urban growth (F1 = slope, F2 = aspect, F3 = elevation, F4 = dis-

tance from streams of main drainage network, F5 = lithology,

F6 = landslide susceptibility, F7 = flood hazard, F8 = seismic haz-

ard, F9 = distance from main road network, F10 = distance from

main towns)

F1 F2 F3 F4 F5 F6 F7 F8 F9 F10 Weights Wi

F1 1 3 4 5 1 1 1 1/3 1 1/2 0.107

F2 1 1/2 1/2 1/4 1/4 1/4 1/4 1/3 1/2 0.031

F3 1 1 1/2 1/4 1/4 1/5 1/3 1/3 0.036

F4 1 1/3 1/4 1/4 1/5 1/2 1/3 0.035

F5 1 1/2 1/2 1/3 3 2 0.105

F6 1 1 2 3 3 0.178

F7 1 1 3 4 0.169

F8 1 2 3 0.183

F9 1 1/2 0.068

F10 1 0.087

CR = 0.05

544 Environ Earth Sci (2012) 66:537–548

123

The produced suitability map for industrial development

(Fig. 4) was classified using the same methodology into

zones of very low, low, moderate, high, and very high

suitability. The areas of very high suitability for industrial

development are also mainly located at the plain part of the

study area and are:

• between the towns of Trikala and Kalambaka

• between the towns of Trikala and Pyli along the

national road

• southeast of the town of Trikala along the national road.

Spatio-temporal changes of urban pattern

Prior to the development of the suitability maps, an

important issue of the present study was to outline the

diachronic changes of the urban boundaries. It is noted that

the existent urban pattern consists of residences as well as

some old industrial facilities, which have remained inside

the residential pattern. On the contrary, for the suitability

evaluation of the present study, the residential and the

industrial land uses were sorted out.

In general, the changes in the urban pattern define the

growth trend of a town, which is usually based on social

and economic criteria. It is important to compare the

growth trend and the changes in the boundaries of the

major towns of the study area with the suitability evalua-

tion for urban growth deduced from this study. The

boundaries of Trikala, Kalambaka, and Pyli have changed

due to the global phenomenon of urbanization. The spatio-

temporal changes of the urban pattern for these towns are

illustrated in Fig. 5.

The gradual concentration of population in the town of

Trikala and the need for new residences and infrastructure

works have led to the expansion of the town boundaries

around the old urban limits. For the time period of

1885–1937, this expansion occurred toward all directions

except for the northern tip of the town, due to the existence

of a hill. The same pattern of urban growth continued

during the subsequent periods. From 1937 until 1992, the

expansion of the town was almost quadruplicated. The

overall change of urban pattern for all the time periods

occurred mainly in a NW–SE direction and to a lesser

extent in a NE-SW direction (Fig. 5a). These directions

coincide with the axes of the two national roads, where

great commercial and industrial activity occurs. Moreover,

the existing settlements along these axes exhibit a merging

trend with the main town. The town of Kalambaka displays

a growth trend in SE direction (Fig. 5b), which also coin-

cides with the national road axis. Toward the north, urban

development cannot be implemented because of the pro-

tected area of Meteora. Lastly, town of Pyli displays a

growth trend mainly in east direction (Fig. 5c), which

again coincides with the national road.

Comparison between urban growth trend and potential

suitability for urban growth and industrial development

The growth trend that occurs in the towns of Trikala Pre-

fecture is very different from the potential suitability for

urban growth and industrial development, based mainly on

hazard maps and physical parameters. Initially, the growth

trend refers both to the residential as well as to the

industrial section because, as we stated before, industrial

facilities are found to be inside or near the major towns,

cover a relatively small area, are of low productivity, and

do not cause any major environmental trouble. However,

the suitability assessment separates areas for urban growth

from areas for industrial development.

The growth trend of the town of Trikala is circumfer-

ential of the structured areas. The potential suitability for

urban growth is, however, only toward to the west,

Table 3 The parameters and the calculation of their weights for the

industrial development (F1 = slope, F2 = elevation, F3 = distance

from streams of main drainage network, F4 = lithology,

F5 = landslide susceptibility, F6 = flood hazard, F7 = seismic haz-

ard, F8 = distance from main road network, F9 = distance from

main towns)

F1 F2 F3 F4 F5 F6 F7 F8 F9 Weights Wi

F1 1 3 5 3 1/3 1/5 1/5 1/3 1 0.079

F2 1 3 1 1/4 1/4 1/5 1/2 1/3 0.044

F3 1 1/3 1/5 1/5 1/5 1/3 1/3 0.027

F4 1 1/3 1/3 1/3 1/2 1/2 0.052

F5 1 1/2 1/3 3 2 0.159

F6 1 1 3 2 0.219

F7 1 2 2 0.229

F8 1 2 0.105

F9 1 0.086

CR = 0.06

Environ Earth Sci (2012) 66:537–548 545

123

northwest, and southeast directions. The growth trend of

the town of Kalampaka is also circumferential and in

particular mainly to the SE. The potential suitability area

for urban growth is suitable on the south and southeast

parts of the town. The growth trend of the town of Pyli is to

the east–northeast. The potential suitability area for urban

growth is also suited to the same direction.

Finally, regarding the potential suitability area for

industrial development, it has been proposed that it has to

be outside of the present residential parts of the towns. The

observed differences between the present spatial distribu-

tion of the growth trend and the potential suitability are

caused mainly because for the first case it were only used

geographical, social, and economical criteria whereas for

Fig. 3 Potential suitability for

urban growth

Fig. 4 Potential suitability for

industrial development

546 Environ Earth Sci (2012) 66:537–548

123

the latter case in the suitability assessment, greater

importance was given to hazard maps and to physical

parameters, in conjunction with geographical factors. In

conclusion, decision makers, engineers, policy makers, and

resource managers are important to employ land-use

planning, based on hazard maps in conjunction with

physical parameters and not only on social-economic fac-

tors, in order to succeed optimal development of an area

with, at the same time, preserving the environment.

Conclusions

For the first time, the potential suitability for urban growth

and industrial development of Trikala Prefecture (Thessaly,

Central Greece) is assessed, and the respective maps are

produced by using natural hazard maps and geological-

geomorphological parameters. The suitable areas for the

above-mentioned land uses are determined. In addition, the

development of the urban pattern and the spatio-temporal

changes of urban boundaries from 1885 till 2005 for the

three major towns (Trikala, Kalambaka and Pyli) of the

study area were performed. The comparison between the

urban growth trend with the potential suitability for urban

growth and industrial development of these towns lead to

discrepancies. These can be attributed mainly to the fact

that in the majority of cases, only geographical, social, and

economical factors were used for the urban development,

whereas in our study, natural hazards, geomorphological,

and geographical parameters of the study area were quan-

tified and taken into account.

The application of this methodology for land-use plan-

ning determines the potentially suitable sites that are sus-

ceptible or not in natural hazards. So a specific land use for

each area (parks, residential areas, industrial parks, etc.)

can be determined. Furthermore, it can be useful in the

verification of the present urban development trend. It is

possible to check which sites of the existed urban pattern

have been developed in vulnerable areas to natural

disasters.

Conclusively, it is demonstrated that by incorporating

these additional factors, planners, engineers, and policy

makers can enhance the results in developing suitability

evaluation studies, in order to come up with the most

beneficial use of land, along with the conservation of the

natural resources and the protection of human lives and

environment.

Acknowledgments This study was carried out with the support of

the Trikala Prefecture Public Services. Moreover, we are grateful to

Assist. Prof. Dr. Skianis G. for his assistance in the process of the

satelite imagery. The authors would like to thank the two anonymous

reviewers for their valuable and constructive comments.

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