Application of raster-based GIS techniques in the ... - SAGE Journals

445656 2012

WMR30910.1177/0734242X12445656YildirimWaste Management & Research

Short Report

Application of raster-based GIS techniques in the siting of landfills in Trabzon Province, Turkey: a case study

Waste Management & Research 30(9) 949­–960 © The Author(s) 2012 Reprints and permission: sagepub.co.uk/journalsPermissions.nav DOI: 10.1177/0734242X12445656 wmr.sagepub.com

Volkan Yildirim

Abstract One of the most important steps in solid waste management is the selection of an appropriate landfill site. The site selection process requires the evaluation and analysis of several criteria. However, the traditional evaluation method is not sufficient for the site selection process. Geographical information system (GIS) technologies are effectively used in the process of site selection, which is a spatial problem. This article describes a raster GIS-based landfill site selection (LSS) method. This method utilizes a raster-based spatial database in which the factors affect the landfill site selection. The final product in this method is the cost surface map showing pixel-based values of the appropriate areas. Furthermore, this GIS-based LSS method was applied for the evaluation of two landfill sites in Trabzon Province in Turkey, for which the traditional evaluation method for site selection was used. The suitability values on the cost surface map of these two landfills have shown that these sites are not appropriate for a solid waste landfill. In conclusion, it was demonstrated that the method of raster GIS-based site selection gives more effective results than traditional methods. Keywords Landfill, site selection, raster, geographical information system, Trabzon

Introduction Solid waste generated from the industrial organizations and urban areas creates serious environmental problems (Seng et al., 2011). There are various methods of solid waste management, such as landfilling, thermal treatment, biological treatment, and recycling. Landfilling is the most common method for solid waste disposal used in many countries (Yesilnacar and Cetin, 2005). The first and most important step in planning a solid waste landfill is the site selection (Ramjeawon and Beerachee, 2010; Sener et al., 2011). Many environmental, economical and political factors need to be considered in the process of landfill site selection (Karadimas and Loumos, 2008; Sener et al., 2011). Rapid increases in the population and improvements in the quality of life, especially in developing countries, have aggravated the problem of solid waste generation. Therefore, municipal authorities will require huge capital investments and operational strategies for collection, transportation, and disposal of solid waste (Afroz et al., 2011; Vijay et al., 2008). Landfill sites, particularly in developing countries, pose significant environmental problems. At present, waste management systems with minimal environmental impacts, i.e., that are not harmful to human health and safety, are gaining more attention globally. However, there is no optimal system for waste management because geographic locations, characteristics of the waste, energy sources, availability of some disposal options, and size of

markets for the products derived from waste management differ widely (Mendes et al., 2004). The disposal of solid waste is a critical environmental issue in Turkey (Nas et al., 2010). Siting a landfill is a difficult task because of the increase in the quantity of municipal solid waste, a strong sense of ‘not in my back-yard’ among the public, rigid regulations, limited land resources, and the processing of a massive amount of spatial data. With increasing population, disposal problems become more difficult in urban areas. At the same time, there is a higher production of waste per unit area and a proportional decrease in the land available for waste disposal. The urban areas of Turkey encounter difficulties in waste management because of solid waste production rate, and responses from the public due to unplanned land use. The legal regulations related to solid waste and the interest various professional disciplines make further complicate the site selection process (Nas et al., 2010). Department of Geomatics Engineering, Karadeniz Technical University, Trabzon, Turkey Corresponding author: Department of Geomatics Engineering, Volkan Yildirim, Karadeniz Technical University, 61080, Trabzon, Turkey Email: [email protected]

950 The most significant step in solid waste management is the selection of an appropriate site, which is important in terms of environmental, economic, sociological, technical, and political aspects. Until now, traditional site selection methods have been used in the developing countries such as Turkey. The basic step in the traditional site selection method is the determination of appropriate sites on 1 : 25 000 scale topographical maps considering the size of the study area and the information supplied by these maps. Updates and the accuracy of these maps are consistently debated. The sites, determined manually on these maps, are evaluated by considering some significant sociological and political criteria. The main process in the traditional site selection method to find areas of suitable size and condition of the slope on 1 : 25 000 scale old topographic map. The best one is selected between these areas according to some criteria such as proximity to tourist areas and major attraction centre. However, if there is a suitable public land in the region for landfill site, these criteria can be neglected in order to avoid the cost of expropriate. However, an appropriate landfill site should have the least negative effect on the economical, sociological and environmental aspects of an area. Additionally, landfill site should respect all constraints set by the national and international legal regulations and must be accepted by the society. It is important to identify the factors that will be considered and those that will be disregarded in the decision-making process. The evaluation of the large number of conflicting factors without any decision support system and an appropriate decision-making process is not possible using the traditional methods (Higgs, 2006). Landfill site selection (LSS) is a type of land use planning that includes many spatial analyses, such as the distance between different land use zones, slope, and proximity to natural hazard thresholds, including landslides. In this context, geographical information system (GIS) software is an important decision support tool capable of operating and analysing different types of spatial data in the determination of appropriate landfill site. GIS examines the results under different conditions and considers the economic, technical, sociological and environmental conditions in the process (Chang et al., 2008; Delgado et al., 2008; Lin and Kao, 2005; Sener et al., 2011). The literature review reveals that the most advanced methodology used to automate the process of waste planning and management is the design and construction of integrated systems based on GIS environments. Concerning LSS, several models have been implemented (Karadimas and Loumos, 2008; Lin and Kao, 2005; Sener et al., 2011; Wang et al., 2009). In one of the GIS-based studies for site selection in Trabzon Province, Turkey, Ersoy and Bulut (2009), describes a spatial methodology composed of several methods, such as multicriteria analysis, that originate in different scientific fields. They determined five appropriate landfill sites and found that the Duzyurt landfill site was the most appropriate site using the analytical hierarchy process (AHP) method. They considered volumetric capacity, haul distance, cost, permeability, and population impact factors. New arrangements were made in Trabzon

Waste Management & Research 30(9) Province in Turkey, which was declared as a metropolitan city in the year 2010, and the Duzyurt landfill site, which is 25 hectares, remained as a potential development area in these borders. It was decided to keep the site close to the surface water and within the Degirmendere Basin. This basin has been discussed in many environmental protection projects, is the most important basin of Trabzon Province and has provided water to the city centre and some towns in recent years.

Materials and methods Methodology A literature review was carried out to define the factors affecting LSS and the factors that are used commonly and the ones that are used less frequently were determined. A spatial database with the appropriate standards was formed based on the factors. The influence of the factors on site selection was determined and integrated into the database as a weight value. The created spatial database was used for a case study in Trabzon Province. Essential geometric and attribute information was transferred into the database. The landfill borders of the site were determined with GPS. Unavailable data were obtained using existing data collection methods (satellite technologies, GPS). The data available from various institutions, such as the General Directorate of Rural Services, the State Hydraulic Works Region Office, Petroleum Pipeline Corporation, and the Turkish Electricity Transmission Company Region Office, for the current case study were transferred to the database using the appropriate digitizing techniques. A cost surface map of Trabzon Province in which appropriate site selection could be carried out with raster GIS technology was created by making a raster conversion of the data. Existing landfills and landfills found on the raster GIS-based model were compared (Figure 1).

Landfill site selection factors Landfill siting is a difficult, complex, tedious, and long-drawn-out process requiring the evaluation of many different criteria (Chang et al., 2008) because this decision has to combine with social, environmental, technical, and financial factors. Environmental factors are very important because the landfill may affect the biophysical environment and the ecology of the surrounding area (Kontos et al., 2005; Sumathi et al., 2008). Economic factors must be considered in the siting of landfills, including the costs associated with the acquisition, development, and operation of the site (Delgado et al., 2008; Kontos et al., 2005). Social and political opposition to landfill siting have been indicated as the greatest obstacle for successfully locating waste disposal facilities. The ‘not in my backyard’ (NIMBY) and ‘not in anyone’s backyard’(NIABY) phenomena (Chang et al., 2008; Lin and Kao, 2005; Tuzkaya et al., 2008) are becoming popular and are currently placing tremendous pressure on the decision makers involved in the selection of landfill sites (Nas et al., 2010).

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defined as an absolute barrier in one zone can be defined as a relative barrier in other zones.

Spatial database design

Figure 1.  Flowchart of methodology.

To determine the suitability of factors, factor weights, and sub-factors (Table 1), 23 scientific studies were explored. Furthermore, in the context of Turkey, the studies were examined using a model to produce more realistic results; the problems associated with the particular landfills in the current situation were also examined. In these studies, factors which were determined based on literature suitability, the degree of influence of these factors on site selection and the degree of suitability of sub-factors were also evaluated. The factors, factor weights, and sub-factors found at the end of this evaluation were discussed by experts and practitioners who have experiences in applying the LSS in Turkey using the brainstorming method. In addition, the process was discussed in detail with academics and experts who work GIS-based LSS in Trabzon, Konya, Isparta and Eskisehir. The factors, factor weights, and sub-factors used in this study were determined using three different processing steps. These determining factors may indicate differences in the landfill sites. For example, the factors such as distance to tourism facilities, climate, wind and humidity are prioritized for tourism sites, whereas the factors distance to industrial facilities and railways are important for industrial developed sites. In some cases, depending on the precision of the zones, the factors that are

Each of the factors impacting the process of LSS corresponds to the spatial dataset. These datasets are produced and stored in different formats by different institutions and particularly in developing countries such as Turkey. In some cases, datasets are produced using different methods at different scales by different institutions. Such a situation creates significant problems in the organization of spatial data. Furthermore, data collected using different methods are used in solving the daily problems of institutions but not plans for the future production of spatial data. Eventually, GIS studies remain inadequate because the spatial data are obtained in different coordinate systems and different standards (Yomralioglu, 2009). Currently, the use of spatial data at the local, national, and international levels has become a necessity. To contribute to the decision-making process, these data need to be integrated to create a framework, avoiding the loss of information in terms of time and effort. In this context, the concept of spatial data infrastructure (SDI), which is defined as the interoperability of spatial data, was developed. The enterprise of Infrastructure for Spatial Information in Europe (INSPIRE), which started its activities under the control of the European Committee in 2001, aims to play a direct role in the development of the European spatial data infrastructure. It is emphasized in the INSPIRE instructions that standards which prevent duplication in the generation of geographical data, improve data quality, and increase the effective usage of data and information must be applied. INSPIRE aims to design the standards for 34 different geographical data groups, identified as an administrative unit, topography, transportation and land cover, and aims to generate and share geographical data in accordance with this model for 27 European countries (Aydinoglu, 2009). In the study of spatial database design, the standards that are emphasized by INSPIRE in the adaptation process of the European Union for Turkey were taken into account. The site selection factors that increase the effectiveness of the created model were defined according to these standards, and the subfactors defining the difficulties in transitions of these factors were formed according to the relevant standards.

Study area Trabzon Province is situated between longitude 39° 7′ 30′′ and 40° 30′ E and latitude 40° 30′ to 41° 7′ N in the middle of the east Black Sea region of Turkey (Figure 2). The province has 17 districts and 537 villages within 4685 km2. In the city the elevation exceeded 3325 m above sea level in some regions. Generally, mountains, hills and high plateaus are part of the land within the region. The length of the coastline is 114 km. Thirty percent of the province land is highland, 60% is inclined and 25 to 30% is

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Table 1.  Factors affecting LSS

*

* *

* *

*

* *

*

* * * *

* * * *

* *

* * * * *

* *

* * *

* * *

* *

* * * * * * * * * *

*

* *

* * * * * *

* * * * * *

* * * * * * *

* * * * * * *

*

*

*

* *

* *

* *

* * * * * *

* * *

* *

* *

*

*

*

* * * * * * *

*

* * * * * * * *

* * * * * * * * *

* *

*

*

*

*

* *

* * *

* * *

* *

* * *

the coast to the south. Only 10% of the total surface area consists of plain area. The temperature usually varies between −7 and +26 °C with a yearly average of 14.6 °C. Yearly average rainfall is 830.8 mm m−2. The average wind velocity is 1.6 m s−1, and the most powerful wind is the northwest wind (Anonymous, 2010). In 2009, the population of Trabzon Province was recorded as 720 899. The annual rate of increase in population was nearly 2% in 2007–2009 (Goren and Ozdemir, 2011). Each day, approximately 200–300 tonnes of solid waste (sometimes more than 400 tonnes) is dumped into the coast-line area (88%), rivers (1.5%), and the land (10.5%) in Trabzon Province, creating serious environmental problems. The leachate

*

* *

*

*

* * *

*

* * *

*

*

*

*

* *

*

*

* * *

* * *

*

*

* * *

* * * * *

* *

* * *

Score

* * *

Wang et al. (2009)

* * *

Moeinaddini et al. (2010)

* * *

Zamorano et al. (2008)

* * * *

Yang et al. (2008)

* * *

Nas et al. (2010)

Sadek et al. (2006)

* * *

Yesilnacar and Cetin (2005)

Calijuri et al. (2004)

* * * * *

Gupta et al. (2003)

Baban et al. (1998)

* * * * *

Jarrah and Qdais (2006)

Sener et al. (2011)

* * * *

Gemitzi et al. (2007)

Chang et al. (2008)

* * * * *

Rahman et al. (2008)

* *

* *

Lin and Kao (2005)

* * * * *

* * * * * *

Karkazi et al. (2001)

* * *

* *

Akbari et al. (2008)

* * * * * *

Ersoy and Bulut (2009)

* * * * * * * * * * *

Abessi and Saeedi (2009)

* * * * * * * * * * *

Kontos et al. (2005)

Sumathi et al. (2008)

Distance to settlement area Distance to stream Distance to main roads Elevation (slope – aspect) Land use Surface water (lake, dam vb.) Distance to nearest aquifer Geology/lithology Distance to spring - well Distance to protected area Distance to nearest fault Distance to airport Population density Railways Rainfall Distance to industrial centres Distance to natural resources Distance to coastal zone Distance to power line Wind Climate Distance to pipelines Distance to sewer line Distance to irrigation channel Soil Distance to landslide areas Distance to flora and fauna Land value Land cost and ownership Administrative boundaries Distance to health centre Distance to education centre

References

Sharifi et al. (2009)

Factor name

21 21 21 19 18 17 16 16 14 13 10  9  9  8  7  6  6  5  5  5  3  3  3  3  3  2  2  2  1  1  1  1

from the uncontrolled solid waste landfill sites is rich in heavy metals and is a continual threat to sea life, humans, and environmental health. Environmental pollution originating from improper and inadequate management of solid waste landfills is common and is a serious problem for all municipalities in Trabzon Province. Thus, environmental pollution originating from open dumping is a major challenge for the future (Ersoy and Bulut 2009). Camburnu and Arakli landfill sites.  The Camburnu landfill site (CALS) (40° 54′ 32′′ E, 40° 12′ 32′′ N) in the borders of Trabzon Province is located at a distance of approximately 43 km

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Figure 2.  Study area.

from city centre and the total area is approximately 8.5 hectares. The area is situated on the highland (290–340 m above sea level), south of Camburnu Municipality and 2 km from the coast. The topographic view of the area shows a bowl-like shape with a wide cavity and the low-level part is on the north–north-east side towards the Black Sea. Gokcesu Stream, which passes through the eastern end of the area and feeds into the Black Sea, is in the drainage basin. There are three main geological formations having volcanic origin near the area. The Arakli landfill site (ALS) (40° 56′ 28′′ E, 40° 2′ 20′′ N) in the borders of Trabzon Province is located at a distance of approximately 32 km from the city centre and the total area is approximately 17.5 hectares. The north–south length of the area is approximately 600 m. The land has a mid-level slope in the south-west direction and crosses a high voltage power line. The southern part of this area borders the Kanholuk River, which is the most important river flowing through the valley and falls into the Black Sea by crossing the western part of the

proposed area. The Kanholuk River has different small streams. The drainage water from the landfill site flows into the Kanholuk River.

Factor weights for study area Different methods were used to determine the factor weights. In particular, the multi criteria decision method (MCDM) and AHP methods were actively used for the determination of factor weights. The values that are commonly used in the literature for factor and sub-factor weights were used in the study. The classification of suitability was performed on a scale of 1 to 9 (Table 2). The factors identified as an absolute barrier were symbolized as ∞. Value 1 indicates the worst and value 9 indicates the best areas. The sensitivity of the study area in weight detection and the problems in landfills used in the current situation were included in the process. For example, the areas with dense forests and soils, qualified for

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Table 2.  Factor and sub-factor weights affecting LSS Factors/sub-factors

Weights Factors/sub-factors (%)

Weights (%)

Land use Dense foresta Cultivated areas (seasonal agriculture) Agricultural areas Wetlanda Rocky areas Pasture areas Settlement areasa Other Slope  0–5°  5–10°  10–15°  15–20°  20–25°   >25°a Geology The most appropriate areas Appropriate areas Not appropriate areas Reserved areasa Stream  0–500a  500–1000  1000–2000  2000–3000   > 3000 Infrastructures (pipeline/power line/sewer line)b  0–300   > 300 Fault line/flora and faunab  0–1000*   > 1000  

15 ∞  2  1 ∞  5  6 ∞  9 10  9  7  5  3  1 ∞ 10  9  6  1 ∞ 20 ∞  1  2  6  9 – ∞  9 – ∞  9

10 ∞  1  3  4  5  6  8  9 10  9  8  6  4  2  1 20 ∞  1  5  9  5 ∞  1  2 – ∞  9 – ∞  9 – ∞  9

aAbsolute

Soil I. Class soils – excellent agriculturea II. Class soils III. Class soils IV. Class soils V. Class soils VI. Class soils VII. Class soils VIII. Class soils – non-agricultural Road  0–500  500–1000  1000–1500  1500–2000  2000–5000   > 5000 Dam – Lake  0–1000a  1000–2000  2000–3000   > 3000 Landslide Active landslide areasa Potential landslide areas Old landslide areas Railway/school/hospital/coastal line/seaport/airportb  0–500a   > 500 Natural resources (water/energy/geological)b  0–500a   > 500 Protected area/aquifers/settlement/tourismb  0–1000a   > 1000

barrier; bAbsolute barrier without weight

agriculture (the areas with a degree of land use capability classification (LUCC) of 1 and 2), were identified as absolute barriers (Table 2) (Akbari et al., 2008; Gemitzi et al., 2007; Moeinaddini et al., 2010; Nas et al., 2010; Sadek et al., 2006; Sener et al., 2011; Sumathi et al., 2008; Wang et al., 2009; Yang et al., 2008; Zamorano et al., 2008).

Data For the case study in Trabzon Province, 33 maps layers were generated. A single data image of Landsat ETM+ (Path 173; Row: 32), taken in 2002, was used to generate the land cover types. Using the image, after extracting an application area of approximately 120 km × 90 km covering administrative boundaries of Trabzon Province, other studies were carried out on this area (Reis et al., 2009).

The digital elevation model (DEM) was digitized from 1/25 000 scale standard topographic maps. The contours on these maps are drawn at 10 m intervals. The DEM of the study area was created with the ArcGIS 9.3 software. The slope map (classified in percentages) and elevation figures were generated using this DEM. The pixel dimensions of this slope map are 25 m × 25 m. In Turkey, the General Directorate of Rural Services within the Ministry of Agriculture and Rural Affairs is responsible for the production of these soil maps and related information. First, soil maps produced by this institution on a scale of 1/25 000 were digitized using a Universal Transverse Mercator (UTM) coordinate system. Then, descriptive data of LUCC were added to the database. The data for geology, lithology, fault line, stream, and surface water were derived by scanning and digitizing hard-copy maps on 1/25 000 scale geological maps with the relevant information using ArcGIS 9.3. Additionally, a road network map was

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Figure 3.  Aquifer and surface water map.

generated by digitizing the topographic maps and by comparing them to satellite images. Landslide maps were generated using the GIS technology. Education, health, airport and seaport map layers were generated using GPS-based measurements. Data for tourism, culture, and natural resources were provided by institutions in the form of hard copy maps and were digitized. Data for important aquifer areas and spring-wells were provided by State Hydraulic Works Region Office as hard copy maps and were digitized (Figure 3). Current natural gas pipelines were provided as digital copies by the Petroleum Pipeline Corporation, and power lines were digitally provided by Turkish Electricity Transmission Company Region Office. Metadata of the spatial data is shown in Table 3.

describes the suitability value of that pixel for LSS in the area on the surface (Figure 4). The high numerical value of the pixel indicated that it is an appropriate pixel for the landfill. The areas shown in grey in Figure 4 indicate the appropriate areas for landfills. Thus, in this study, as the residential units are dense along the coastline and most of the population live in coastal regions, appropriate site selection was carried out among the areas from the coast and up to 10 km to the south.

Raster-based cost surface

One of the major constraints of LSS is the need to generate a lowcost project that performs the public services in developing countries such as Turkey. The most important factors in decreasing the cost of LSS are the expropriation cost and transportation cost. The administration that keeps these factors in the forefront mostly ignores environmental and socio-economic factors. CALS was previously used as an open copper mine under the ownership of the government, which is one of the most important factors in choosing this area for the study. Additionally, the proximity of the area to the densely populated coast will decrease the transport cost, and two fault lines pass through this area. This landfill site is located in a small river basin of 545 hectares. Furthermore, this area has a population density of approximately 10 000 (Figure 5). The proximity of this area to the settlement areas is 1100 m. However, the local citizens have problems with the smell emitted from the facility into environment and the sight and sound of the

A raster data model is the most useful data format for arithmetic processes between pixels belonging to the same coverage or different coverages that have the same coordinate system. Currently, many GIS software commonly uses surface analysis, route determination, the generation of arithmetic operations between coverage and specific functions such as the most appropriate site selection due to the advantages provided by the raster data format (Yildirim, 2009). In this study, the ArcGIS 9.3 software produced by the ESRI Company was used to generate the cost surface map. In this study, the raster-based cost surface was generated using pixel-based arithmetic processes on raster data layers formed for each surface separately. The weights needed for each layer are shown in Table 2. The value of pixels on this cost surface

Results and discussion The evaluation of the Camburnu and Arakli landfill site

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Table 3.  Map layers properties (metadata) Data

Data type

Source

Scale

Road Forest Protected area Landslide Flora–fauna Tourism Boundaries Relief data Land use Aquifers Stream Geology Coast line Soil Natural resources Natural gas line Power line

Line Polygon Polygon Polygon Polygon Point Polygon Line Raster Polygon Line Polygon Line Polygon Point Line Line

Landsat, topographic maps General Directorate of Forestry Topographic maps, Ministry of Tourism General Directorate of Mine General Directorate of Forestry Topographic maps, Ministry of Tourism General Directorate of Cadastre General Command of Mapping Landsat State hydraulic works region office Landsat, General Directorate of Mine General Directorate of Mine Landsat, topographic maps General Directorate of Rural Services General Directorate of Mine Petroleum Pipeline Corporation Electricity company region office

1/25 000 1/25 000 1/25 000 1/25 000 1/25 000 1/25 000 1/25 000 1/25 000 1/25 000 1/25 000 1/25 000 1/25 000 1/25 000 1/25 000 1/100 000 1/25 000 1/25 000

garbage trucks. The social responses occurred during the initial opening stage of the facility. Therefore, CALS is not an appropriate site for solid waste disposal. ALS is located in a basin formed by two rivers. Additionally, ALS is located in the middle of the Yanbolu and Karadere aquifers, which are two important aquifers of Trabzon Province (Figure 6). This area is approximately 600 m away from settlements also approximately 285 m away from rivers. The majority of the area remains in the forest and is approximately 480 m away from the protected area of historic Zanayer Castle. This area has been declared as tourism area by the council of ministers, which is the most important problem of this area because this area was previously decided as landfill (Anonymous, 2006). This situation is proof that many constraints of the site selection process were ignored using traditional methods. Although the solid waste collection process has not started, there has been an intense social reaction.

Appropriate landfill sites for Trabzon Province Appropriate landfill sites were extracted from the area map based on the following criteria: areas with high pixel values, areas that consist of more than 20 hectares, and areas that are 10 km away from the south by considering the cost surface map. As shown in Figure 7, eight appropriate areas that satisfied these conditions were identified. New development areas of Trabzon Province, declared as a metropolitans city, and the borders around the province were arranged again in 2010, and the landfill sites are prohibited in these borders, including the settlement of Ayvali. As a result, the Derecik, Kaynarca, Pinaralti, Yokuslu, Yenice, Arsin, and Tavsanli settlements may be thought of as appropriate landfill sites (Figure 7).

Statistical evaluation In the final process of the study, four areas (Tavsanli, Kaynarca, Pinaralti and Yenice) with the highest pixel values (> 10 000) on the cost surface map among the seven different areas on the GISbased site selection model and two landfill sites used in the current situation were examined statistically. The results are shown in Table 4. The average slope of the areas on the raster GIS-based model was 13.5, and the average height was 460 m. The average slope of CALS was 15°, and the average slope of ALS was 14°. Pixel values on the cost surface map are the basic indicators in raster-based applications. In this study, the most appropriate area between the defined areas was the highest average value among the areas appropriate for landfill. The CALS which is traditionally determined and currently used as a landfill site whose average pixel value of 60 has been identified as the worst area for landfill. The Kaynarca site with an average pixel value of 10 011 was identified as the most appropriate area (Table 4). The CALS and the ALS are very close to the coast line. This situation poses a great concern for Trabzon, which is an important port city. CALS remains within the domain of Camburnu Shipyard which is one of the largest shipbuilding yards in Turkey

Conclusion This study has shown that GIS technologies provide effective results in the process of LSS. Cost surface maps generated using these technologies help by aiding the decision-making process and are fast and accurate. In particular, the features of simple modelling and the classification properties provide significant advantages in the process of site selection. Traditional methods used in developing countries could not offer effective solutions in this respect. The raster-based GIS method can be

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Figure 4.  Raster-based cost surface.

applied to different regions taking into account regional differences. In this case, factors and factor weights should be determined from a scratch. The model can easily be adapted for a user-friendly interface in which factors and factor

weights can be changed dynamically. This could be considered a future work. The accuracy, scale and update of spatial data used in the process of LSS are important. The results from this type of study

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Figure 5.  CALS evaluation.

Figure 6.  ALS evaluation.

must be controlled together with field studies. In this study, alternative landfill sites in Tavsanli, Kaynarca, Pinaralti, and Yenice were controlled by field studies. Cost surface was not identified as an appropriate area according to the values based on the distance to the fault line of the landfill site, distance to streams, distance to settlement areas, location within the basin borders for CALS, the distance of the Yanbolu and Karadere aquifers, location within the basin borders, and classification as tourism areas. When the criteria of distances to forests, health centres, and education centre were examined, these two areas were found to be inappropriate areas for landfills. It was observed in these types of studies that administrative boundaries pose significant problems. Holistic basin boundaries must be utilized instead of administrative boundaries in the study of site selection. This case is valid for the borders of

villages, towns, cities, and even countries. The landfill located in a basin may affect more towns or cities or even the country. Therefore, the solid waste management process must be performed in a holistic way without focusing on administrative borders in these types of areas, which are in different administrative boundaries. It is necessary that the appropriate places should be examined by different evaluation methods and the most appropriate areas should be determined based on the results. In this study for Trabzon Province, different administrative and political factors may need to be examined as a result of the involvement of the Trabzon & Rize Solid Waste Association (TRABRISWA). For example, the areas that are in the west of Trabzon Province may be omitted because these areas are away from Rize Province. In addition different landfill sites for Rize Province and Trabzon

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Figure 7.  Appropriate landfill sites for Trabzon Province. Table 4.  Evaluation of landfill sites found by traditional methods and the raster GIS- based method Evaluation criteria

Traditional method

Raster GIS-based method

 

CALS

ALS

Tavsanli

Kaynarca

Pinaralti

Yenice

Average pixel value on cost surface Distance to aquifers (m) Distance to settlement (m) Distance to stream (m) Distance to main road (m) Average slope (%) Distance to forest area (m) Distance to health centre (m) Distance to education centre (m) Distance to tourism area (m) Distance to protected area (m) Distance to coast line (m)

60 5977 1100 308 117 15 1100 1370 1410 1600 5720 1312

2000 743 600 285 102 14 0 1760 599 600 600 956

10027 3668 1831 1339 1146 14 2535 2180 2335 2681 15448 8614

10011 6224 2844 894 210 12 602 2621 1719 5874 9830 11890

9319 5243 1542 1033 467 11 2600 5861 1156 5006 11905 9477

8222 2898 1120 914 127 17 1200 3093 1335 4520 11791 5570

Province may be proposed. The most appropriate areas should be found by examining the criteria, such as the amount of solid waste depending on the population and storage stations For finding the best appropriate landfill sites between many alternative landfill sites some political, economic, environmental and sociological factors must be reconsidered. This process can be managed using MCDM. In this study, the best appropriate landfill site from among the many alternatives was not determined; this could be considered a limitation of this study.

Acknowledgements The author would like to thank the Geographical Information System Laboratory (GISLab - http://www.gislab.ktu.edu.tr), Karadeniz Technical University, Turkey for technical and data support.

Funding This research received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors.

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