gis-based land suitability analysis integrating multi-criteria evaluation for the allocation of...

ORIGINAL ARTICLE

GIS-based land suitability analysis integrating multi-criteriaevaluation for the allocation of potential pollution sources

Ingrida Bagdanaviciut _e • Jurijus Valiunas

Received: 1 September 2011 / Accepted: 23 July 2012 / Published online: 12 August 2012

� Springer-Verlag 2012

Abstract The geological environment has been heavily

polluted by chemical substances over the past few decades.

Pollution sources located on the earth’s surface or under-

ground have affected the quality of the environment. A

significant amount of impact could be reduced if the allo-

cation of potential pollution sources was based on an

evaluation of environmental conditions. The main objec-

tive of this study was to develop a methodology for the

allocation of potential pollution sources by employing GIS

and multi-criteria evaluation techniques. This methodology

was applied to a study area located in the eastern part of

Lithuania. A GIS-based land suitability analysis was per-

formed after identifying 16 factors concerning the geo-

logical and socio-economic environment, which were

important for environmental protection, land use and spa-

tial planning. The environmental and socio-economic fac-

tors were divided into eliminating and limiting criteria.

Criteria maps based on the selected factors were compiled.

Areas delineated by eliminating criteria were identified as

unsuitable for development (according to national legisla-

tion). Limiting criteria were evaluated according to the

suitability level, which were determined in this study

considering the principles of sustainable development. The

relative importance of each criterion was assessed utilising

the Analytical Hierarchy Process (AHP). A land suitability

index (LSI) was calculated and the final result of the land

suitability analysis was summarized in three suitability

maps (environmental, socio-economic and composite).

Four suitability classes (unsuitable, least, moderately and

most suitable) for the allocation of potential pollution

sources in the study area were used, and the nine most

suitable candidate sites were selected according to the

proposed methodology.

Keywords Geological environment � Potential pollution

sources � Land suitability analysis � Multi-criteria

evaluation � AHP � GIS

Introduction

The geological environment, as an integral part of the

biosphere, has a direct impact on the human living envi-

ronment. On the other hand, the geological environment is

significantly affected by human activity. The geological

environment (soil, surface water and groundwater) has

been heavily polluted by chemical substances over the past

few decades (Juodkazis et al. 1998). Pollution sources

located on the earth’s surface or underground have affected

the quality of the environment, particularly the ground-

water, which is the main water supply source in Lithuania.

A significant amount of impact could be reduced if the

allocation of potential pollution sources was based on an

evaluation of the environmental conditions. An evaluation

of the geological environment typically considers the

principles of environmental protection and land use, which

are integrated into the concept of sustainable development

(WCED 1987; NSSD 2003). Sustainability principles are

important for the regulation of human activity, optimal use

of geological resources and the reduction of environmental

I. Bagdanaviciut _e (&)

Coastal Research and Planning Institute, Klaip _eda University,

H. Manto 84, 92294 Klaip _eda, Lithuania

e-mail: [email protected]; [email protected]

I. Bagdanaviciut _e � J. Valiunas

Institute of Geology and Geography, Nature Research Centre,

Sevcenkos 13, 03223 Vilnius, Lithuania

e-mail: [email protected]

123

Environ Earth Sci (2013) 68:1797–1812

DOI 10.1007/s12665-012-1869-7

impact. The application of sustainability principles requires

defining favourable and limiting factors concerning the

geological environment along with the development of

approaches for the evaluation and integration of complex

geological information into the land-use planning process.

The main objective of this study was to develop a

methodology of environmental evaluation for the alloca-

tion of potential pollution sources (permanent or tempo-

rary) employing GIS and multi-criteria evaluation

techniques and to also apply it to a study area located in the

eastern part of Lithuania.

The sources of environmental pollution are analysed in

terms of economic activity (industry, agriculture), the

accumulation of pollutants (landfills, repositories, farms)

and the type of pollutants (industrial, building materials)

(Juodkazis et al. 1998). In this study, pollution sources

were treated as the accumulation of pollutants (liquid and

solid waste landfills, repositories, farms, etc.). The largest

and most risky pollution sources are liquid and solid waste

landfills. Their negative impact on the environment has

been well investigated and described (Diliunas et al. 2004)

and is regulated by national and EU legislation (MERL

2000; Council Directive on the Landfill of Waste (99/31/

EC)).

During the past few decades, most of environmental

data were arranged in a map form that makes GIS one of

the best analytical tools to analyse environmental infor-

mation (Weerakoon 2002). Land suitability analysis

advanced by McHarg (1969) has, over the past 40 years,

become accepted as one of the most comprehensive

approaches in land use planning. Its basic purpose is to

determine the suitability of a given area for a particular

use (Murphy 2005). Multi-criteria Decision Making

(MCDM) methods were introduced to extend GIS ana-

lysing capabilities since MCDM methods are capable of

dealing with heterogeneous criteria that are both qualita-

tive and quantitative in nature (Jankowski 1995;

Malczewski 1999, 2004). MCDM integrated with GIS is

widely used for land suitability analysis (Siddiqui et al.

1996; Weerakoon 2002; Kontos et al. 2005; Simsek et al.

2006; Sener et al. 2006, 2010; Lamelas et al. 2007;

Delgado et al. 2008).

The present study describes environmental evaluation

methodology that was developed for the allocation of

potential pollution sources employing GIS-based land

suitability analysis and multi-criteria evaluation. Initially,

EU and national legislation regulating the establishment of

potential pollution sources (landfills) was analysed. GIS

was employed for data acquisition and analysis. GIS-based

land suitability analysis was performed after setting the

specific factors of the geological and socio-economic

environment which were important for environmental

protection, including land use and spatial planning.

Selected environmental and socio-economic factors were

divided into eliminating and limiting criteria. An area

delineated by eliminating criteria was identified as

unsuitable for development (according to national legisla-

tion and practical guidelines). Limiting criteria were eval-

uated according to the suitability conditions and their

scoring, which were determined considering the principles

of sustainable development. The relative importance of

selected factors was estimated using the Analytical Hier-

archy Process (AHP). The final result of the land suitability

analysis was compiled in three suitability maps for the

allocation of potential pollution sources in the study region.

Environmental and socio-economic factors were evaluated

separately using two different scenarios based either on

environmental or socio-economic factors. A final overall

suitability map for the allocation of the potential pollution

sources was compiled combining the output maps of the

two scenarios.

Study area

The methodology of the environmental evaluation was

applied to the Ignalina municipality located in the eastern

part of Lithuania (Fig. 1). The municipality has an area of

1,496 km2, the lowest population density in Lithuania

(13.4 inhabitants per sq.km) and a relatively high forestry

level (32.2 % of the total municipality area).

From a geological-tectonic point of view, the Ignalina

municipality is situated at a juncture of the Baltic Synec-

lise, Masurian-Belorussian anteclise and the Latvian saddle

(Valiunas et al. 2000). The crystalline basement and sedi-

mentary rock cover are faulted. The area is underlain by

Quaternary deposits of 90–120 m in average thickness,

ranging from 70 m in the south to 250 m along the buried

valleys. The system of Quaternary sediments has accu-

mulated large resources of fresh groundwater which are

widely used for the water supply. Surface sediments and

the relief of the study area were formed by glaciers and

their meltwaters. Glacial (till, sandy loam) and glacioflu-

vial (various grained sand with gravel) sediments are

predominant and widespread.

The groundwater resources extracted from the

Quaternary aquifers are the most widely used for both

centralized and individual water supplies in the study

area. Two centralized water supply well fields are located

in municipality area; the third one—Visaginas wellfield—

is located outside the municipality border, but its pro-

tection zone extends to the northern part of the munici-

pality. The predominant depth of the shallow groundwater

varies from 2 to 4 m, and is most often used for indi-

vidual water supply. Quaternary aquifers lying at different

depths (10–100 m) are mostly exploitable. Some

1798 Environ Earth Sci (2013) 68:1797–1812

123

individual wells in the central, north-western and western

parts of the study area are exploiting the Upper Devonian

terrigeneous aquifer.

According to the database of pollution sources of Lith-

uania (Sugalskien _e and Kanopien _e 2002) 224 pollution

sources were inventoried in the study area and classified

into three main groups: cattle breeding objects (86),

accumulation of pollutants (77, incl. 22 landfills) and

industrial objects (61). Since the landfills did not meet the

legal requirements of EU and national legislation, they

were closed during the past few years and waste is cur-

rently being transported outside the municipality.

Materials and methods

In this study, we use land suitability analysis integrating

GIS and MCDM methods to determine the optimum site

location for potential pollution sources. The aim of the land

suitability analysis is to determine the optimum site loca-

tion for certain types of activities while minimizing the

negative impact on the environment (Murphy 2005).

The methodology consists of the following steps:

1. Identification of factors having a significant effect on

land suitability for potential pollution sources and

development of a GIS database which includes spatial

information on the identified factors.

2. Reclassification of initial data to compile criteria maps

for further land suitability analysis.

3. Determination of a suitability level and scoring scale

based on principles of sustainable development and the

evaluation of criteria suitability.

4. Application of an analytic hierarchy process (AHP)

method for the assessment of the relative importance

(weights) of the criteria and sub-criteria.

5. Application of a simple additive weighting (SAW)

method for estimation of the land suitability index

(LSI).

6. Evaluation of land suitability according to environ-

mental and socio-economic criteria. Reclassification of

the LSI into land suitability classes and their repre-

sentation on land suitability maps.

7. Selection and evaluation of alternative sites.

The land suitability approach developed and used in this

study is demonstrated in the workflow scheme (Fig. 2).

Only those environmental and socio-economic factors

which were directly or indirectly related to the considered

economic activity were selected during the factor identifi-

cation process. Maplnfo 6.5 and ArcGIS 9.2 software were

used for data collection, conversion and analysis. Sixteen

Fig. 1 Location map of the study area

Environ Earth Sci (2013) 68:1797–1812 1799

123

input data layers were collected, representing information

on the geology, hydrogeology, hydrology and morphology

of the study area, as well as the social and economic

aspects of the considered activity, and were all integrated

into the GIS-based land suitability analysis. Data reclassi-

fication and objects’ buffering were performed to compile

the criteria maps.

The land suitability analysis required environmental and

socio-economic factors to be divided into eliminating and

limiting criteria. An area defined by eliminating criteria

was recognized as unsuitable for development according

to national legislation. Consequently, eliminating criteria

were excluded from further multi-criteria evaluation pro-

cess. An additional suitability evaluation was carried out on

the limiting criteria since their components had different

impacts on the natural environment. Each criteria map was

evaluated according to the suitability scale as determined in

respect to the land use being considered.

Multi-criteria evaluation has been performed employ-

ing EXPERT CHOICE software based on the AHP (Saaty

1980, 1996). AHP was applied to derive the relative

weights for a set of criteria and was based on three

principles: decomposition, comparative judgment and the

synthesis of priorities. The decomposition principle

requires a decision problem to be decomposed into a

hierarchy that captures the essential elements of a deci-

sion problem. By breaking down the problem into levels,

the decision maker can focus on smaller sets of decisions.

The principle of comparative judgment requires the

assessment of pairwise comparison presented in a ratio

matrix. The weights of the criteria were determined by

normalizing the eigenvector associated with the maximum

eigenvalue of the reciprocal ratio matrix (Malczewski

1999). The method employs an underlying scale with

values from 1 to 9 to rate the relative preferences of two

criteria (Table 1).

The AHP method includes a consistency ratio (CR)

index which indicates consistency of the judgments:

CR ¼ CI

RIð1Þ

where RI is random consistency index and CI the

consistency index defined as follows:

CI ¼ kmax � n

n� 1ð2Þ

where kmax is the maximum eigenvalue of the matrix and

n the number of compared elements.

Consistency ratio index values C0.10 indicate an ade-

quate evaluation of criteria and acceptable results, whereas

CR index \0.10 denotes the inconsistent judgment of a

matrix (Saaty 1980). In cases of inconsistency, the original

values in the pairwise comparison matrix have to be

revised. AHP comparative weights were integrated into

criteria maps as additional attribute data.

The SAW method was used to estimate the LSI

according to the following formula:

Vi ¼Xn

j¼1

wj � vij ð3Þ

where Vi is the suitability index for a given area i; wj is the

weight of criterion j; vij is the suitability score of area

i under criterion j and n is the total number of criteria.

Three suitability maps were compiled as the final output

of the land suitability analysis.

Fig. 2 Workflow of the land suitability analysis


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Results

Suitability conditions were determined and scoring per-

formed for the evaluation of factors’ suitability according

to the principles listed in Table 2. Environmental and

socio-economic factors were evaluated according to the

proposed suitability conditions and ranked by suitability

scores to compile two suitability maps. Environmental

factors were classified into the four following groups:

geological, hydrological/hydrogeological, morphological

and nature conservation (Table 3).

Geological criteria comprise two sub-criteria: top

soil vulnerability to pollution and surface sediments

permeability.

Top soil pollution potential. Soil composition deter-

mines the soil pollution potential to chemical pollution.

Higher amounts of clay particles in the soil increase

accumulation of heavy metals (Pb, Cd, Sn, etc.), which in

turn may have a negative impact on the environment.

According to the Lithuanian hygiene standard (MHRL

2003) sand/sandy loam were defined as soil of low pollu-

tion potential, whereas heavy loam/light clay and heavy

clay were defined as soils of moderate and high pollution

potential, respectively. A soil map (scale 1:300,000)

(Juodis and Jasinskas 1998) of the study area was reclas-

sified into three soil pollution potential classes (Fig. 3a)

determined by the Lithuanian hygiene standard (MHRL

2003) and evaluated according to the suitability scale

(Table 3). Soils of low pollution potential (clay particles

\30 %) were considered to be the most suitable for

potential pollution source location, while soils of high

pollution potential (clay particles[65 %) were considered

to be the least suitable.

Surface sediments permeability. The vulnerability of the

groundwater depends on the presence of a geological barrier

which can control the vertical movement of pollutants to the

groundwater level. The main requirement for a geological

barrier is low permeability (Dorhofer and Siebert 1997),

which depends on the genesis and lithological character of

the uppermost Quaternary deposits. The quaternary sedi-

ments of the study area (map scale 1: 50,000, Valiunas et al.

2000) were reclassified into four groups according to the

relative permeability described by hydraulic conductivity

(Holman et al. 2000) (Table 3; Fig. 3b). According to the

results published in different studies (Dobkevicius et al.

1995; Baltrunas et al. 1998; Holman et al. 2000), gravel and

gravelly sand are characterized by a very high permeability

(hydraulic conductivity [400 cm/day), whereas various

sand, silt/peat and glacial till/clay are defined by high

(100–400 cm/day), moderate (1–100 cm/day) and low

permeability (\1 cm/day), respectively. Various sands of

high and very high permeability were assessed as the least

suitable for the allocation of potential pollution sources,

while silt, till and clay of moderate and low permeability

were assumed to be the most suitable.

Hydrological/hydrogeological criteria comprise three

sub-criteria: shallow groundwater vulnerability, ground-

water sources and surface water protection.

Table 1 Scale for pairwise comparisons (Saaty 1980)

Intensity of importance Definition

1 Equal importance

2 Equal to moderate importance

3 Moderate importance

4 Moderate to strong importance

5 Strong importance

6 Strong to very strong importance

7 Very strong importance

8 Very to extreme importance

9 Extreme importance

Table 2 Suitability conditions and scoring of the environmental and socio-economic factors

Suitability

level

Suitability

score (vij)

Evaluation criteria

Environmental protection Economic Social

Most

suitable

2 No impact on the natural

environment

Natural resources are directly used for their

intended function and do not require

investments

No impact on the human living

environment and human health

Moderately

suitable

1 Slight impact on the natural

environment

Natural conditions require little investments

for the intended functions

Slight impact on the human

living environment and human

health

Least

suitable

-2 Significant impact the on

natural environment

Require large investments to assimilate the

area for the intended function and neutralize

the negative impact on the environment

Significant impact on the human

living environment and human

health

Unsuitable 0 Considerable impact on the

natural environment;

economic activity is not

recommended

Considerable economic losses is possible Considerable impact on the

human living environment;

health issues and risks for

humans


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Shallow groundwater vulnerability depends on the litho-

logical composition of the vadose zone and groundwater

depth. According to the methodology of a groundwater vul-

nerability assessment approved by a Geological survey of

Lithuania (Kanopien_e and Marcinkevicius 1995), the vul-

nerability of shallow groundwater is characterized by the time

of moisture migration to the groundwater level. A shallow

groundwater vulnerability map (scale 1:200,000) was reclas-

sified into three vulnerability classes according to the migra-

tion time of pollutants to the groundwater table (Kanopien_e

et al. 2004) (Table 3; Fig. 3c). Since shallow groundwater is

not protected from surface pollution throughout the entire

territory of Lithuania, only conditional categories of vulner-

ability are defined. A suitability classification of the migration

time of pollutants is provided in Table 3.

Protection of groundwater sources. Potential pollution

sources should not be located in approved wellfield pro-

tection zones and must not be adjacent to any groundwater

source, such as springs or groundwater wells since the

protection of exploited resources is essential for the pro-

tection of groundwater (GRL 2012). Two approved well-

field protection zones were considered as eliminating

criteria for the allocation of potential pollution sources

according to the legal requirements (Table 3; Fig. 3d).

Nevertheless, the Visaginas wellfield is located outside the

study area, but its protection zone extends to the northern

part of the municipality and was therefore taken into

consideration.

Protection of surface water The allocation of potential

pollution sources is prohibited in the buffer zones of lakes

Table 3 Environmental criteria integrated in the land suitability analysis and its suitability evaluation

Criteria Sub-criteria Component Attribute Suitability

conditions

Suitability

score (vij)

Environmental Geological

Top soil pollution

potential

High Mid-heavy clay, heavy clay LS -2

Moderate Mid-heavy loam, heavy loam, light clay MS 1

Low Sand, sandy loam, sandy light loam S 2

Surface sediments

permeability

Very high Gravel, sand and gravel, Holocene aeolian

sand and Pleistocene alluvial sand

LS -2

High Sand (except those identified above) LS -2

Moderate Silt, peat and Weichselian till S 2

Low Central Glacial till and glaciolacustrine clay S 2

Hydrological/hydrogeological

Shallow groundwater

vulnerability

Very high Migration time of pollutants to groundwater

table:

0–1 years

LS -2

High 1–2 years MS 1

Moderate 2–5 years S 2

5–7 years S 2

7–10 years S 2

Groundwater sources

protection

Wellfield protection

zones

E –

Surface water protection Lakes protection zone Distance to lake \500 m, 200 m E –

Rivers protection zone Distance to river \150 m E –

Morphologic

Slope gradient Flat \1 % S 2

Flat to gentle 1–2 % S 2

Gentle to moderate 2–5 % MS 1

Moderate to steep 5–10 % LS -2

Steep [10 % U 0

Conservation

Protected area Reserves, national and regional parks, Natura 2000 areas E –

Land use Forest E –

E eliminating, U unsuitable, LS least suitable, MS moderately suitable, S most suitable


123

Fig. 3 a Top soil vulnerability, b surface sediment permeability, c shallow groundwater vulnerability, d surface water and wellfield protection

zones, e slope gradient, f conservation


123

and rivers in order to avoid the penetration of pollutants.

Surface water bodies were derived from a topographic map

(1:10,000) and buffer zones were generated in a derivative

map (Table 3; Fig. 3d). The size of protection zones is

regulated by national legislation (MERL 2007) so buffer

zones with a size of 200 and 500 m were delineated for

lakes up to 200 ha, and for lakes larger than 200 ha,

respectively. The distances of 200 and 100 m were fixed

for the buffer zones of rivers having more than 50 km and

less than 50 km in length, respectively. The protection

zones of water bodies were assessed as eliminating criteria.

Morphological criteria were defined by slope gradient

to reflect slope erodibility. A digital elevation model

(DEM) was prepared employing ArcGIS 3D Analyst the

Triangular Irregular Network (TIN) on the basis of a

topographical map (1: 50,000). A slope map was derived

from the DEM of the study area and classified into five

classes based on slope erodibility potential (Table 3;

Fig. 3d). Flat to gentle slopes (0–2 %) were identified as

the most suitable areas for landfill location. Weakly

undulating plains and slopes of limited erosion potential

(2–5 %) were identified as moderately suitable. Steep

slopes occurring in the hilly relief and characterized by

high erodibility potential ([10 %) were classified as

unsuitable.

Conservation criteria included protected areas (nature

reserves, national and regional parks, Natura 2000 sites)

and all types of forest which were considered as elimi-

nating criteria and excluded the area from further assess-

ment according to legal requirements (GRL 2012)

(Table 3; Fig. 3d).

Socio-economic criteria included components related to

the quality of the human living environment (e.g. resi-

dential and recreational areas) and possible economic costs

(e.g. investments needed for area development and infra-

structure) (Table 4).

Geotechnical properties of sediments. The suitability of

the geological environment for engineering constructions

in Lithuania mainly depends on the distribution of fine- and

coarse-grained sediments and their physical–mechanical

properties (Buceviciut _e et al. 1995, 2004). The most

important parameter for the classification of sediments

considering their strength is the deformation module

(E) for biogenic soils and conic resistance (q) for cohesive

and non-cohesive soils. According to a summarized engi-

neering geology map of Lithuania, soils considering their

strength parameters were categorised into several classes:

biogenic viscous soils, highly compressible (E B 2 MPa);

cohesive soils, soft (q \ 1 MPa); firm (1–3), stiff (3–5) and

very stiff ([5); non-cohesive soils, soft (q B 2 MPa); firm

(2–6), stiff (6–10) and very stiff ([10). Quaternary sedi-

ments (map scale 1: 50, 000, Valiunas et al. 2000) were

classified into five classes according to the strength

parameter of soil and their suitability conditions for the

allocation of potential pollution sources were assessed

(Table 4; Fig 4a). Highly compressible organogenic soils

are unsuitable for any engineering construction. Stiff and

very stiff soils, being the best basement for engineering

construction, were recognized as the most suitable for the

location of pollution sources.

Protection of mineral resources All the deposits of

mineral resources are grouped according to the classifica-

tion of solid mineral resources of Lithuania (LGSME 1999)

by three criteria: extent of geological exploration, possi-

bilities of resource utilization and the economic value of a

resource. The protection status of mineral resources is

based on the extent of geological exploration, i.e. mineral

resources explored in detail, explored in general or prog-

nostic (detected or supposed). Explored deposits of mineral

resources were defined as eliminating criteria due to pro-

hibited engineering constructions in these areas (GRL

2012). Deposits and prognostic areas of mineral resources

were derived from a map of mineral deposits (map scale 1:

50,000, Valiunas et al. 2000) (Fig. 4b). Construction is not

recommended in the prognostic areas of mineral deposits

since these areas may be prospected, explored and prepared

for exploitation in the future. The prognostic areas of

mineral deposits were evaluated as the least suitable for the

allocation of potential pollution sources (Table 4).

Wind exposure was considered because potential pollu-

tion sources (landfills, farms) should not be exposed to

wind because of the odour effect, but it is not based on

legal restriction. According to long-term data, west and

southwest winds prevail (wind frequency 40 %) in the

study area (Lithuanian Hydrometeorological Service,

unpublished data). A wind exposure map (Fig. 4c) was

derived from the DEM. Zones exposed to west and

southwest winds and flat areas exposed to any wind

direction were given the lowest suitability score. Zones

exposed to winds from the northeast and north winds

(average wind frequency about 7 %) have been recognized

as the most suitable, while other zones were classified as

being moderately suitable (Table 4).

Accessibility to pollution sources was considered in the

context of waste transportation and response to an accident.

The pollution sources should be located at a place where it

can be reached by roads under all weather conditions. Three

zones having different distances from roads were selected

according to recommendations (MERL 2000), but it is not

strictly defined. Zones at a distance of 200 m from roads

were evaluated as the most suitable and distances of more

than 500 m were recognized as the least suitable for the

location of potential pollution sources (Table 4; Fig. 4d).

Land use Limitation of the distance from pollution

sources to residential homes depends on their hazardous-

ness and varies from 10 to 1,500 m (GRL 2012). For


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example, landfills of solid municipal waste cannot be

located closer than 500 m to a residential home and pro-

tection zones with corresponding buffers were generated

around the residential homes or settlements (Fig. 4e).

Protective zones and recreational areas were considered as

eliminating criteria following legal requirements (Table 4).

An AHP method was employed to calculate the relative

importance (weights) of criteria and sub-criteria. The

analytical hierarchical model developed in this study only

included the limiting sub-criteria (Fig. 5). The comparative

judgment in the AHP relied on a pairwise comparison

matrix, where each factor was rated against every other

factor using a scale of relative importance (1–9) proposed

by Saaty (1980) (Table 1). In the first level of the hierar-

chy, environmental and socio-economic criteria were rated.

The equal importance of environmental and socio-eco-

nomic criteria was assumed and equal weights (0.5) were

assigned. At the level of sub-criteria, environmental and

socio-economic criteria were evaluated separately to

determine local weights (wl) for each class (Table 5).

Pairwise comparison matrix was filled by importance val-

ues for each pair of sub-criteria. As an example, suppose

that sediments permeability (SP) is moderately preferred

over the soil vulnerability (SV) criteria, a score of 3. Since

comparison matrix is reciprocal, if criterion SP receives a

score of 3 relative to criterion SV, criterion SV should

receive a score of 1/3 when compared with criterion SP.

The same logic was used to complete the environmental

and socio-economic matrixes of pairwise comparisons.

Finally, sub-criteria weights obtained from the matrixes

were multiplied by criteria weights to obtain the global

weights (wg) of the hierarchy. Since the consistency ratio in

this study did not exceeded 0.1, the matrix was accepted as

consistent.

Since the main aim in locating a pollution source is

containment of the pollution, an understanding of the

geological composition and behaviour of the ground and

surface water of the study area is required (Dorhofer and

Siebert 1997; Proske et al. 2005). The sub-criteria of

groundwater vulnerability and surface sediment perme-

ability were assessed as criteria of major importance for

groundwater protection. Slope gradient, while being an

important limiting criterion in hilly areas possessed a minor

importance in the slightly hilly terrain of the study area.

The protection of mineral resources (controlled by national

legislation) was important from an economic viewpoint

Table 4 Socio-economic criteria integrated in the land suitability analysis and its suitability evaluation

Criteria Sub-criteria Component Attribute Suitability

conditions

Suitability

score (vij)

Socio-

economic

Economic

Geotechnical

properties

of soils

High

compressibility

Biogenical deposits U 0

Soft Alluvial, lacustrine organic sand, slope wash deposits LS -2

Firm Lacustrine clay and silt, morainic loam and sandy loam

(gt III bl), eolian and lacustrine various grained sand

MS 1

Stiff Morainic loam and sandy loam (gt III gr), alluvial fine

grained and silty sands, limnoglacial, fliuvioglacial

various grained sand

S 2

Very stiff Central Glacial till, alluvial coarse and medium coarse

sand, limnoglacial, fliuvioglacial gravel and gravely

sand

S 2

Protection of

mineral

resources

Prospected and explored mineral deposits E –

Prognostic areas of mineral deposits LS -2

Accessibility Roads Distance to road 0–200 m S 2

Distance to road 200–500 m MS 1

Distance to road [500 m LS -2

Social

Wind exposure Aspect Flat, W, SW LS -2

NW, E, SE, S MS 1

NE, N S 2

Land use Residential area Distance to settlements \500 m E –

Recreational area – E –

E eliminating, U unsuitable, LS least suitable, MS moderately suitable, S most suitable


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Fig. 4 a Geotechnical properties of soils, b mineral deposits, c wind exposure, d accessibility, e land use


123

and was consequently assessed as a criterion of major

importance in the socio-economic class.

Comparative AHP weights were integrated into the

criteria maps as additional attribute data. Data analysis was

performed by combining environmental and socio-eco-

nomic criteria maps using Boolean logic—arithmetical

overlay. Using this operation, new spatial data and new

topology were created in the output layer. A LSI was

estimated employing the SAW method according to the

formula (3).

Land delineated by environmental and socio-economic

eliminating criteria was removed from the final suitability

maps. All polygons indicated by the LSI were classified

into four qualitative suitability classes: unsuitable, the

least, moderately and the most suitable. Polygons having a

LSI of 0 were recognized as unsuitable. The rest of the LSI

values ranged from -1 to 1 and were divided into 3 equal

intervals to obtain three suitability classes (Table 6). Two

land suitability maps for the allocation of potential pollu-

tion sources were compiled according to environmental

(Fig. 6a) and socio-economic scenarios (Fig. 6b).

In the environmental scenario, protected areas, forests,

surface waters and wellfield protection zones were recog-

nized as eliminating criteria for the allocation of pollution

sources according to the legal restrictions. Eliminated

zones were widespread in the western part of the study area

due to the high number of protected areas and extensive

forest and in the northern part due to the appearance of a

wellfield protection zone. Legally restricted zones elimi-

nated 68 % of the total municipality area. Unsuitable areas

covered approximately 1 % and coincided with area of

steep slopes ([10 %). Suitable land distribution coincided

Fig. 5 Analytical hierarchy model for the allocation of pollution sources and overall weights of the environmental and socio-economic criteria

Table 5 Comparison matrix and the significance weighting of the environmental and socio-economic criteria

Environmental wl = 0.5 SV SP GV SG Local weights (wl) Global weights (wg)

Soil vulnerability (SV) 1 1/3 1/3 3 0.156 0.078

Sediments permeability (SP) 3 1 1 4 0.377 0.188

Groundwater vulnerability (GV) 3 1 1 5 0.395 0.197

Slope gradient (SG) 1/3 1/4 1/5 1 0.073 0.037

Socio-economic wl = 0.5 GP MR WE A Local weights (wl) Global weights (wg)

Geotechnical properties (GP) 1 1/3 3 3 0.244 0.122

Mineral resources (MR) 3 1 6 5 0.573 0.286

Wind exposure (WE) 1/3 1/6 1 1 0.089 0.045

Accessibility (A) 1/3 1/5 1 1 0.094 0.047

CR = 0.03

CR = 0.01

Table 6 Classification of the

study area according to

suitability level

Suitability level Land suitability

index (LSI)

Area (%) Land suitability

index (LSI)

Area (%)

Environmental

criteria

Socio-economic

criteria (%)

Overall

criteria

Eliminating – 68 72 – 95.5

Unsuitable 0 1 4 0 0.8

Least suitable -1 to (-0.33) 5 1 -2 to (-0.67) 0.2

Moderate suitable -0.33 to 0.34 15 21 -0.67 to 0.66 2.5

Most suitable 0.34–1 11 2 0.66–2 1


123

Fig. 6 Land suitability map for the allocation of potential pollution sources in the study area based on a environmental criteria, b socio-

economic criteria


123

with low-permeability sediments where the migration time

of pollutants is more than 1 year (Table 6; Fig. 6a).

Prospected mineral deposits, along with residential and

recreational areas, were assessed as eliminating criteria in

the socio-economic scenario. Eliminated areas were evenly

distributed in the study area due to the widespread resi-

dential areas. Legally restricted zones covered 72 % of the

total municipality area (Table 6). Biogenical sediments

were assessed as unsuitable due to their poor geotechnical

properties and covered more than 4 % of the study area.

Suitable areas were mainly distributed in the central part of

the municipality and coincided with stiff and very stiff soil

distribution (Fig. 6b).

The final overall suitability map integrated the envi-

ronmental and socio-economic scenario maps (Fig. 7). The

two maps were overlaid and the LSI values of both maps

were added. Approximately 8,000 polygons with different

LSI values, ranging from -2 to 2, were obtained after

processing the data. The final LSI values and correspond-

ing polygons were classified into four suitability classes

(Table 6). An additional 27 % of area was removed

from the environmental suitability map considering the

eliminating socio-economic criteria. Nevertheless, distance

to a residential area can be reduced depending on the type

of pollution sources, and the total area delineated by the

eliminating socio-economic criteria can be considerably

reduced. Approximately 90 % of the total municipality

area in the composite land suitability map was defined by

eliminating criteria. Suitable areas were concentrated in the

central part of the municipality, and only 3 % of the total

area was defined as suitable and could be recommended for

further investigation to allocate potential pollution sources

in the analysed municipality.

Nine parcels of land with an area larger than 0.2 km2

were selected as the most suitable for the allocation of

potential pollution sources (Table 7; Fig. 7). Each land

parcel was an aggregation of tiny polygons (from 172 to 48

each), with different LSI values. To determine the most

suitable sites, an average LSIavg was estimated for each

parcel. According to the LSI result the most suitable are

site 6 (1.018), site 3 (0.990) and site 5 (0.956), but site 3

has the largest area in comparing with others, what makes

it more suitable for the allocation of the large pollution

sources.

Fig. 7 Composite land suitability map for the allocation of potential pollution sources in the study area


123

Discussions and conclusions

The principles of sustainable development confront land

use planners with two apparently contradictory objectives:

environmental conservation and economic development

(Van Lier 1998). The present study describes specific

methodology which relied on GIS-based land suitability

analysis integrating multi-criteria evaluation. A methodol-

ogy was developed for spatial land planning purposes

based on the main principle of sustainable development

regarding environmental protection and sustainable use.

The methodology developed was applied performing land

suitability analysis for the allocation of potential pollution

sources on a case study area.

The principles and methods for the development of land

suitability maps and data interpretation differ substantially

between countries and researchers. A wide range of factors

can be taken into account when searching for suitable sites

for the allocation of pollution sources (Proske et al. 2005).

In this study, the selected factors were classified into two

groups (environmental and socio-economic) to develop two

land suitability scenarios. Evaluation of the geological

environment was based on two assumptions: first, only

those geological factors which are directly or indirectly

related to a particular human economic activity were

evaluated; and second, an evaluation of the geological

environment was based on existing data. This allowed an

optimisation of the volume of information analysed and

simplified the assessment procedure for the time and work

required for evaluation. In this study, the protection of

mineral resources, shallow groundwater vulnerability,

surface sediment permeability and geotechnical properties

were considered as factors of major importance. Classifi-

cation of the criteria into eliminating and limiting helped

to distinguish the data required for the land suitability

analysis. Eliminating criteria were defined according to

the national legislation and excluded areas from the

multi-criteria analysis and final suitability maps. Limiting

criteria were integrated into the multi-criteria assessment

and its suitability was evaluated using four suitability

levels (0, unsuitable; -2, least suitable; 1, moderately

suitable; and 2, most suitable). The applied suitability scale

was considered sufficient for the land suitability analysis at

a regional scale, whereas the other authors used more

explicit scales composed of five (Delgado et al. 2008) or

even ten (Kontos et al. 2005) suitability levels. Negative

values for the ‘‘least suitable’’ and zero for ‘‘unsuitable’’

categories, applied in this study, contradict traditional

ranking logic. Nevertheless, such a suitability scoring is

recommended (Land Suitability Analysis User Guide for

ArcView 3.x and ArcGis 9.x 2005) to product zero values

to the final LSI results, what could assist clearly identify

unsuitable areas. The final LSI values (excluding 0,

unsuitable) vary from -1.3 to 1.4. This assessment

revealed that none of the land parcel was ‘‘most suitable’’

or ‘‘least suitable’’ under all eight evaluation criteria. The

highest and the lowest LSI values obtained areas where at

least six criteria were evaluated as most suitable (2) and

least suitable (-2), respectively. Such situation, when each

land parcel has contradicted characteristic, occurs fre-

quently in the land suitability assessment. As example,

highly permeable gravelly sand assessed as least suitable in

point of groundwater vulnerability, on the other hand is the

most suitable from a geotechnical viewpoint. Therefore,

relative weights are integrated to reduce this inconsistency;

consequently, the final suitability map was more affected

by the criteria with highest weights.

The AHP method makes the decision-making process

clear and transparent and also facilitates controlling this

process. A user with AHP assessment knowledge can

adjust the relative importance of the selected criteria. The

integration of the GIS and AHP methods is highly appro-

priate and relevant in solving tasks in spatial land planning

and environmental protection. This method reflects the

expert’s opinion on the pending problem since the relative

evaluation used in the AHP is based on expert judgment.

An increase in the number of experts involved may

decrease the level of subjectivity in comparisons of the

criteria. Additionally, alternative multi-criteria decision

making methods (WSM, TOPSIS) could be applied for

comparison of the final results.

The geological environment determines the suitability of

a territory for a particular economic activity. However, the

more strictly the particular economic activity is regulated,

the less the relative impact of the geological conditions to

the final outcome. In summarizing the case study results,

more than 95 % of the municipality area which was in

some degree suitable for development, according to geo-

logical conditions, was eliminated by the restrictions of

national legislation. Social criteria such as residential zones

Table 7 The most suitable sites selected for the allocation of

potential pollution sources

Selected

site

Site area

(km2)

Average land

suitability index (LSIavg)

Site 1 0.59 0.905

Site 2 1.06 0.798

Site 3 1.04 0.990

Site 4 0.33 0.873

Site 5 0.61 0.956

Site 6 0.22 1.018

Site 7 0.45 0.896

Site 8 0.34 0.941

Site 9 0.51 0.850


123

eliminated 70 % of the analysed area. The area influenced

by social eliminating criteria may potentially increase in

municipalities with a higher population density, where

distribution of residential homes is more extensive, but on

the other hand, if population is concentrated in towns the

amount of the eliminating area could be even less. Socio-

economic criteria should be revised in each particular case

according to legal requirements and considering the type

and size of the pollution sources.

The accuracy and detail of the geological data collected

on the final land suitability maps were determined by the

scale and quality of the data used for the map compilation

(Proske et al. 2005). Criteria maps at a scale of 1: 50,000

were considered as appropriate for a land suitability anal-

ysis at the municipality scale. Criteria maps of different

scales were analysed in this study due to the lack of geo-

logical data at the desirable scale and consequently could

result in a lower accuracy of the final suitability maps.

Land suitability mapping can only be used as an initial step

in spatial planning, since actual suitability can only be

judged on the basis of a detailed investigation (Dorhofer

and Siebert 1997; Proske et al. 2005).

The proposed methodology can be applied for the entire

territory of Lithuania to fulfil environmental protection

tasks to minimize pollution effects: site selection for

landfills, temporary storage of waste or objects potentially

related to groundwater and soil pollution. Additionally, the

methodology developed could be applied for an assessment

of the hazardousness of already existing pollution sources.

Classified and assessed environmental criteria could be

applied in land suitability analyses in areas with similar

geological composition and hydrogeological conditions.

Additional criteria could be added or removed from the

suitability analysis as required. The methodology devel-

oped for the evaluation of a geological environment using

GIS and the multi-criteria decision-making method as well

as workflow designed in this study could be useful in

numerous spatial planning problems related to different

land usage (e.g. recreational, industrial). The compilation

of suitability maps possessing land suitability information

are a good example of the integration of complex geolog-

ical information into spatial planning process.

Acknowledgments This study was the subject of a Ph.D. thesis

prepared at the Institute of Geology and Geography and partially

supported by the State Studies Foundation of Lithuania. The authors

are grateful to Dr. Darius Daunys and two reviewers for their valuable

comments, which considerably improved the manuscript.

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