Introduction

The problem of solid waste constitutes one of the most contemporary environmental issues that threaten humans and the quality of ecosystems globally (Özkan et al. 2019; Bilgilioglu et al. 2021; Ahire et al. 2022). For the last two decades, economic and social developments have led to an increase in human requirements for services and goods, consequently, leading to a rise in the quantities of solid waste (Abdullah-Al-Mahbub et al. 2022; Babiker et al. 2005; Mohsenizadeh et al. 2020). The sensitivity of the solid waste problem grows as a result of poor management practices, acceleration in population growth, urban expansion, land use change, unplanned agricultural and social development, low technology, and low societal awareness (Khaliq et al. 2022; Aguilar et al. 2018; Kazuva and Zhang 2019).

Solid waste management is considered one of the difficult challenges facing local decision-makers and planners in developing countries (Yang et al. 2014; Orhan et al. 2020). This challenge requires the formulation of vital policies aimed at building a sustainable and effective environmental management system (Cheng and Urpelainen 2015; Bilgilioglu et al. 2021; Ahire et al. 2022). The concept of solid waste management can be defined as the process of waste disposal in the best method that promotes environmental and population health while supporting the local population, especially those affected by the existing solid waste sites (Balaban and Birdoğan 2010; Kazuva et al. 2021). However, the absence of solid waste management methods can cause serious environmental consequences (Kazuva and Zhang 2019; Tulun et al. 2021; Eghtesadifard et al. 2020).

Despite the presence of a number of methods and techniques that assist in reducing the amount of solid waste, including its recycling, transfer, and recovery, they hardly make the disposal foolproof (Kazuva et al. 2021). In this connection, organized storage of solid waste may be mentioned as among the most important means used globally to manage solid waste (Rahimi et al. 2020; Eghtesadifard et al. 2020). Determining the optimal sites for landfilling, however, is considered one of the critical environmental measures worldwide by decision makers in the framework of solid waste management within the comprehensive design of sustainable economic infrastructure (Bilgilioglu et al. 2021; Tulun et al. 2021). The best selection of these sites requires a comprehensive survey of all relevant physical, human, economic, health, and geographical criteria (Karasan et al. 2019; Kazuva et al. 2021; Ahire et al. 2022). Moreover, the traditional methods of selecting optimal landfill sites involve complex and long-term procedures with high costs. Multi-criteria decision-making is considered one of the most important modern tools used in choosing the most appropriate spatial options that can be exercised to bury household waste within the framework of urban, environmental, and regional planning procedures (Kareem et al. 2021). Furthermore, multi-criteria decision-based spatial appropriateness mapping in a geographic information system (GIS) environment determines the spatial dimensions of the distribution of optimal landfill areas. (Güler and Yomralıoğlu 2017; Orhan et al. 2020).

The integration of analytical hierarchy process (AHP) with GIS provides the best multi-criteria decision-building platform selecting the potential landfill site suitability. Previous literature has provided constructive results through that integration, including Aley and Chouf, Lebanon (Kamel and Hasan 2018); Sulaimaniyah Governorate, Iraq (Alkaradaghi et al. 2019); Aksaray, Turkey (Bilgilioğlu and Bilgilioğlu 2017); Dar es Salaam, Tanzania (Kazuva et al. 2021); Sicily, Italy (Randazzo et al. 2018); Sharjah, United Arab Emirates (Al-Ruzouq et al. 2018); Lahore, Pakistan (Asif et al. 2020); State of West Bengal, India (Ali et al. 2021); Savar upazila, Bangladesh (Islam et al. 2020); the Béni Mellal-Khouribga region of Morocco (Barakat et al. 2017); Paraiba do Sul river basin, Brazil (Senkiio et al. 2022); Songkhla, Thailand (Kamdar et al. 2019); Egyptian Suez Canal Corridor, Egypt (Monsef and Smith); and Gondar, Ethiopia (Sisay et al. 2021).

Syria generally lacks proper management of solid waste due to a rapid population growth and structural transformation in lifestyles, especially as the consequences of the current war (Rahmoun et al. 2016; Saghir 2019; Noufal et al. 2021; Khaddour 2021). Tartous governorate suffers from the accumulation of tons of solid waste in 10 random landfill sites, which led to the deterioration of the environment with a severe negative impact on various agricultural, economic, social, and cultural aspects oflifestyles (Noufal et al. 2020). Safita has seventeen main landfill sites, in addition to dozens of random landfill sites. These landfills collected waste in order to disposing presses in several methods, including burial, burning, and dumping.

During the period of war in Syria (since 2012), Safita area received thousands of displaced people from the war zones inside Syria. This massive inflation in the population of the area led to serious environmental consequences, including the accumulation of thousands of waste tons, especially in places of settlement and human activity, roads, rivers, and lakes. Based on the field surveys carried out, there is an urgent need to suggest suitable sites for landfilling as a critical part of formulating effective solid waste management policies for the Safita region. In this study, the optimal sites for landfills are suggested based on the integration between the AHP method and remote sensing data in a GIS platform. The outputs of this study include values of high importance to decision-makers and local planners in creating policies for managing the problem of solid waste in light of the consequences of the current war.

Material and methods

Study zone description (Safita area)

Safita is one of the six administrative regions in western Syria, including Tartous, Al-Draikish, Sheikhbadr, Al-Qadmous, Baniyas, in the Tartous governorate on the eastern coast of the Mediterranean. Study area lies between 35.8–36.1○ E longitude and 34.41–35.3○N latitude (Fig. 1), with an area of 335 km2 and a population of 22,145 (Abdo 2018). Study area is characterized by mountainous-hilly terrain with an elevation of 1120 m a.m.s.l. Safita is classified under the mountainous Mediterranean climate: the Csa and Csb patterns (Köppen climate classification), where the average annual temperature reaches 15.7 °C with a relative humidity of 68.4% (Mohammed et al. 2020). The rainy period extends for about eight months, from September to April, with the annual precipitation rate reaching to 1247 mm (Abdo 2020). Safita is one of the most important areas in Tartous governorate, which is characterized by economic activities such as agriculture and tourism. Moreover, Safita is part of the first agricultural stability zone in Syria (Abdo 2018). Olives and citrus are the most important agricultural crops.

Fig. 1
figure 1

Location of the study area: a—location for the Syrian governorates, b—location on the DEM, c—Landsat 8 OLI true image of the study area

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Data used, processing and preparation

In order to map the spatial suitability of landfills, a set of multi-source data, especially remote sensing data, was relied on, as shown in the Table 1. However, data was entered and processed in a GIS environment using spatial analysis tools: Resample, Resize, Euclidean Distance, Interpolation, Tabulation, Conversion, Raster Calculator, and Reclassification tools at a resolution of 30 m. The considered criteria map layers were prepared and produced according to the spatial raster grid data format at a resolution of 30 m. Figure 2 shows the flow chart that represents the methodological framework used in this study. The digital elevation model (DEM) was used to derive the elevation, slope, and drainage layer maps. Slope degree layers were prepared using surface analysis tools in in the ArcGIS software. The drainage layer also was derived using the hydrological analysis tools, by applying the steps: fill, flow direction, flow accumulation, con, and streams. The spatial distribution of permeability values was mapped through the process of digitizing and converting to the Raster formula. A comprehensive spatial evaluation process was conducted for the faults, settlements, drainages , water supplies, lakes, roads, tourist centers, archaeological centers, and religious centers criteria using the Euclidean distance analysis (Eq.1) (Gonçalves et al. 2014).

Table 1 Thematic layers of factors used and sources of data
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Fig. 2
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Flowchart of methodology used in this study

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$$d\left(p, q\right)=\sqrt{\sum\nolimits_{i=1}^{n}{({q}_{i}-{p}_{i})}^{2}}$$
(1)

\(p, q\): two points in Euclidean n-space, \({q}_{i}-{p}_{i}\): Euclidean vectors, starting from the origin of the space (initial point),\(n\): n-space. Land use/land cover (LULC) map was created based on the analysis of Landsat 8 OLI Image using the maximum likelihood classifier supervised classification algorithm. The quality of the LULC classification was verified experimentally by using the method of comparison between the LULC layer and a set of randomly distributed reference points (Al Shogoor et al. 2022). In this regard, an error matrix was built, which is the basis for the accuracy evaluation process, as well as the kappa coefficient was used. The classification accuracy and kappa coefficient were 88% and 84.7%, respectively. Referring to a map of settlements, it was exported from LULC layer.

Exclusion assessment

The process of sanitary municipal landfill site selection is a necessity for sustainable spatial development in any region. Thus, the classification of criteria involved in the modeling process must be accurately determined through the evaluation of exclusion. In this study, new landfill site selection in the study area were identified based on several methodological justifications in the evaluation of exclusion, including the regulations of the Ministry of Local Administration and Environment in Syria, expert opinions, and a review of the relevant literature. Table 2 refers to exclusion, threshold values, and references utilized in the current investigation.

Table 2 Exclusion, threshold values, and references utilized in the current investigation
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Considered criteria

The determination of the criteria for spatial suitability is one of the most important and complex procedures, especially in a sensitive issue such as choosing the optimal sites for landfills. To this end, twelve experts (ecologists, geologists, geomorphologists, land use planners, and waste management practitioners) were surveyed with the aim of accurate identification of AHP criteria. Furthermore, a systematic survey of the relevant literature was conducted for the criteria used in mapping the spatial suitability of landfills, as shown in Table 3. Based on the expert opinions, the previous literature, the field study, and the specificity of the study area, thirteen factors were identified for modeling the spatial suitability of landfills establishment.

Table 3 Literature review of several parameters for landfill site selection using AHP
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Elevation

Elevation is at the forefront of the topographical parameters in the selection process for optimal landfill sites. The relevant literature indicates that areas with high elevation values are not suitable for sustainable landfill construction due to high waste transportation costs, extreme climatic characteristics, and insufficient management. (Alkaradaghi et al. 2019). Moreover, areas with low elevation are considered unsuitable for landfills due to proximity to water sources and drainage constraints (Bilgilioglu et al. 2021). Thus, landfills should be established in areas with moderate elevation values to avoid related problems. In this study, the elevation layer map was categorized into five classes: <200, 200–400, 400–600, 600–800, and >800 m as Fig. 4a illustrates.

Slope

Slope is among the critical terrain factors that must be taken into account in the construction of sustainable landfill sites. Steep slopes cause an increase in landfill construction and maintenance costs, a high potential for soil and water pollution due to increased movement of slope materials, and an increase in transportation costs (Babiker et al. 2005). Therefore, areas with slope values greater than 30 degrees are considered unsuitable for the establishment of landfills, as indicated by the previous literature (Dereli and Tercan 2021; Chabuk et al. 2017). The study area is characterized by high sensitivity to landslides due to several factors, especially severe slopes (Abdo 2018). In the current assessment, the slope degree map were categorized into five classes (Fig. 4b): <5°, 5–10°, 10–15°, 15–20°, and >20°.

Permeability

The hydrological permeability factor determines the susceptibility to soil and groundwater contamination by landfill output of highly toxic liquids. Thus, areas with low hydrological permeability should be selected in order to reduce hydrogeological pollution (Tulun et al. 2021). Geological investigations indicate that the study area consists of mainly Mesosoic (Jurassic and Cretaceous), Cenosoic (Neogene volcanic), and Quaternary (Holocene) formations (Fig. 3). According to several geological studies carried out in the Syrian coast, the Jurassic and Holocene formations are characterized by high permeability, followed by the Cretaceous formations. In this regard, basaltic neogene formations are described as having low permeability due to clay (Ponikarov 1966). The Quaternary formations were identified as unsuitable sites for landfill construction (sand and gravel) in contrast to the Tertiary volcanic formations with impermeable lithology (clay). However, Fig. 4c shows the spatial distribution of hydrological permeability according to three classes: permeable, impermeable, and semi-permeable.

Fig. 3
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Geological units in this study

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Fig. 4
figure 4figure 4figure 4

Layers factors: a elevation, b slope degree, c permeability, d proximity to faults, e distance to settlement, f LULC, g distance to drainage, h distance to water supplies, i distance to lakes, j distance to road, k distance from tourist centers, l distance from archaeological centers, m distance from religious centers

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Distance to faults (DF)

Fractured zones provide a critical indicator of the potential for landfill output into groundwater (Barakat et al. 2017). Moreover, geomorphological hazards increase in areas near faults that can cause irreversible environmental hazards. Thus, the areas near the faults are not suitable for the establishment of landfills. The study area is characterized by the density of faults as a result of tectonic complexity due to the influence of the huge African-Asian fault. The fault layer was derived on the basis of the geological maps 1/50000 (the maps of Safita and Tartous) issued by the General Corporation of Geology in Lattakia Governorate. Moreover, the fault layer was supported by data derived from the studies carried out by the General Authority for Remote Sensing—Lattakia Governorate. In the current analysis, the distance to faults in the study area was classified into four categories, including 100 < m, 100–200 m, 200–300 m, 300–400 m, and < 400 m, as Fig. 4d shows.

Distance to settlement (DS)

The establishment of landfills near settlement areas leads to catastrophic environmental and health consequences for the population, including the spread of diseases, emission of unpleasant odours, noise pollution, distortion of the aesthetics of the place, and the devaluation of the property (Rahimi et al. 2020). For these reasons, the criterion of distance from settlements is one of the decisive human criteria in the process of establishing landfills. In the current assessment, the distance to settlements was divided into five categories: <100, 100–200, 200–300, 300–400, and >400 m, as Fig. 4e shows.

Land use/land cover (LULC)

The integrated management of LULC reduces the negative environmental and social consequences of establishing landfills (Bilgilioğlu and Bilgilioğlu 2017). In addition, the LULC is one of the critical criteria for the mitigation of the land degradation susceptibility (Rahmat et al. 2017). In this regard, the establishment of landfill sites on lands with high biological values is an illegal issue. Unfortunately, LULC planning in the context of spatial management is almost missing in the study area (Abdo et al. 2022; Chaaban et al. 2022). Agricultural land, bare ground, forest, grass, scrub/shrub, settlement, and water are the types of LULC in study area, as Fig. 4f depicts.

Distance to drainage

The distance to drainage network is one of the most important hydrological criteria included in the modeling of land suitability for landfills. The output of landfills can enter the rivers, causing severe pollution to humans and the environment. Moreover, the sensitivity of this criterion is increased in humid and semi-humid environments that are characterized by high precipitation intensities and the density of the drainage network, as is the case in the study area (Mohammed et al. 2021). In the current analysis, the distance to o drainages was divided into five classes: 100 < m, 100–200 m, 200–300 m, 300–400 m, and < 400 m, as Fig. 4g shows.

Distance to water supplies

The spatial distribution of water supplies is a pivotal consideration when constructing landfills. In the study area, drinking water is secured through a group of wells that are scattered around. It is important to consider this distribution when establishing landfills in the context of continuous maintenance of surface water quality. Figure 4h classifies the distance to water supplies into five classes: 100 < m, 100–200 m, 200–300 m, 300–400 m, and < 400 m.

Distance to lakes

Lakes represent an important basis for the sustainability of humans, agricultural development, and wildlife conservation. Maintaining the quality of water bodies, including lakes and dams, is one of the most important criteria for sustainable environmental planning (Pasalari et al. 2019). However, continuous water surfaces are among the most polluted environmental components. The criterion of distance to lakes is decisive in the study area due to the presence of Al-Basel lake, which is the largest one in Tartuse Governorate. In the current assessment, the distance to lakes was divided into five classes: 100 < m, 100–200 m, 200–300 m, 300–400 m, and < 400 m, as Fig. 4i illustrates.

Distance to road

The distance to roads constitutes one of the most substantial economic criteria for choosing potential sites for the construction of landfills. Despite the financial ease of transporting waste owing to the proximity of the landfill site to the main road network, it distorts the general aesthetic appearance (Aksoy and San 2019). Thus, a balance must be struck between costs and the beauty of the landscape when planning the construction of landfills. At the present evaluation, the distance to road was divided into five classes: 100 < m, 100–200 m, 200–300 m, 300–400 m, and < 400 m, as Fig. 4j shows.

Distance from tourist centers

Tourism activity is considered one of the most important aspect of economic life in the study area. The proximity of landfills to tourist centers distorts the aesthetics of the urban environment, which leads to hitting one of the most important sources of local income. Thus, due consideration should be given to existing tourism infrastructure when constructing landfills (Ding et al. 2018). In this study, the distance from tourist centers was divided into five classes: 100 < m, 100–200 m, 200–300 m, 300–400 m, and < 400 m, as Fig. 4k shows.

Distance from archaeological centers

Preservation of archaeological sites is among the essential criteria that must be taken into account when planning the establishment of landfills (Chabuk et al. 2017). The study area possesses a cultural and historical heritage represented by many archaeological sites. Also, these sites support tourism activity in the study area. In this study, the distance from archaeological centers was divided into five classes: 100 < m, 100–200 m, 200–300 m, 300–400 m, and < 400 m, as Fig. 4l shows.

Distance from religious centers

The study area is characterized by rich religious heritage as it houses some important Christian and Islamic religious centers. These centers are places of great spiritual sanctity, and it should be borne in mind when conducting environmental and urban planning processes. Achieving distance to religious centers is one of the most important considerations when establishing landfills. In this study, the distance from religious centers was divided into five classes: 100 < m, 100–200 m, 200–300 m, 300–400 m, and < 400 m, as Fig. 4m shows.

Analytical hierarchy process

Analytical hierarchy process (AHP) is a well-known multi-criteria decision-making method evolved by Saaty in 1980 (Saaty 1980; Halder et al. 2022; Islam et al. 2020). In this method, criteria are ordered in a hierarchal approach targeting the quantification of relative preferences in a given set of alternatives on a ratio scale (Asfaw et al. 2022; Asif et al. 2020; Islam et al. 2020; Abdo 2022). In addition, a lot of scholars have reported the importance of analytical hierarchy process implementation in land suitability for landfills (Kamdar et al. 2019).

In order to produce a logical conclusion on the significance of chosen criteria, a decision matrix was constructed utilizing the analytic hierarchy process (AHP) by considering the expert views on the impact of each factor on the construction of potential landfill sites (Abdelouhed et al. 2022; L. Kareem et al. 2021; Manguri and Hamza 2022). This pairwise comparison matrix is composed in which aii = 1 and aij = 1/ai. The importance coefficients of the ranking criteria and the sub-criteria are computed utilizing the right eigenvector calculated from the maximum absolute eigenvalue (λmax, 1, 2). The estimating values of all the criteria are normalized to 1.

  • Step 1: Principal eigenvalue (λ) was calculated by the eigenvector technique (Kumar and Krishna 2018) which is expressed by the equation below (Eq. 2).

    $${\lambda }_{max}=\frac{1}{n}\sum\nolimits_{wi}^{n}\frac{\left(AW\right)i}{w}$$
    (2)

  • Step 2: Pairwise comparison matrix was built (Eq. 3) (Saaty 1980)

    $$AW=\left(\begin{array}{ccc}a11& a12& \begin{array}{ccc}.& .& . \end{array} a1n\\ a21& a22& \begin{array}{ccc}.& .& .\end{array} a2n\\ \begin{array}{c}a31\\ \begin{array}{c}.\\ .\\ .\end{array}\\ an1\end{array}& \begin{array}{c}a32\\ \begin{array}{c}.\\ .\\ .\end{array}\\ an2\end{array}& \begin{array}{c}\begin{array}{ccc}.& .& .\end{array} a3n\\ \begin{array}{c}.\\ .\\ .\end{array}\\ \begin{array}{ccc}.& .& .\end{array} ann\end{array}\end{array}\right)\times \left({w}_{\mathrm{1,2},3\dots .n}\right)$$
    (3)

    where \(W\) is the corresponding eigenvector of \({\lambda }_{\mathrm{max}}\) and wi (i = 1, 2, 3,..., n) is the weight value for ranking. The rank of each pairwise comparison was specified from Saaty’s pairwise scale to put the relative significance to the selected criteria taken for land suitability for landfills. The scale ranges from 1 to 9 point scale as proposed and developed by Saaty (1980) (Table 4).

  • Step 3: The consistency of the decision matrix should be tested with the computation of the consistency index (CI) which is expressed by the below equation (Eq. 4) (Saaty 1980).

    $$CI=\frac{{\lambda }_{\mathrm{max}}-n}{n-1}$$
    (4)

    where \(CI\) is the consistency index, \({\lambda }_{\mathrm{max}}\) is the maximum or principal eigenvalue of the decision matrix, and n is the order of the matrix.

  • Step 4: The consistency ratio (\(CR\)) coefficient is computed based on the approach suggested by Saaty (1980). The CR coefficient should be less than “0.1,” representing the total consistency of the pairwise comparison matrix. If the consistency ratio exceeds “0.1,” the matrix of the decision will be considered “inconsistent” and the matrix has to be evaluated again. Simultaneously, the value of the consistency ratio is totally equaled to “0” or ranging from 0 to 0.09 will be accepted only as consistent. The consistency ratio (\(CR\)), however, is expressed by the equation below (Eq. 5) (Saaty 1980).

    $$CR=\frac{CI}{RI}$$
    (5)

    where \(CR\) is the consistency ratio, \(CI\) is the consistency index, and \(RI\) is the random index, whereas RI has been adopted according to Table 5.

Table 4 The random inconsistency value
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Table 5 The random inconsistency value
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Mapping the spatial suitability of landfill

The multi-criteria suitability map of landfills is a spatial dimensionless outcome that supports predicting the acceptable land sectors for sustainable sanitary municipal landfill sites in a specific area. In the current assessment, the weight overlay analysis in GIS platform method has been implemented to map the spatial suitability of landfills as follows (Eq. 6) (Abdelouhed et al. 2022)

$$S=\sum\nolimits_{t=1}^{m}\sum\nolimits_{f=1}^{n}({W}_{t}+{X}_{f})$$
(6)

where \({W}_{t}\) represents the normalized weight of the t thematic layer, \({X}_{f}\) represents the rank value of each class with respect to the f layer, m represents the total number of thematic layers, and n represents the total number of classes in the thematic layer. In this context, weights specified to the different thematic layers and derivation of the normalized weights using AHP are shown in Tables 5 and 6. The multi-criteria suitability map of landfills evaluating all the criteria in an integrated layer is computed utilizing Eq. 7

$$\begin{array}{c}{LM= {El}_{wi}\times {El}_{r}+SL}_{wi}\times {SL}_{r}+{PE}_{wi}\times {PE}_{r}+{DF}_{wi}\times {DF}_{r}+{DS}_{wi}\times {DS}_{r}+\\ {{LULC}_{wi}\times {LULC}_{r}+DD}_{wi}\times {DD}_{r}+{DW}_{wi}\times {DW}_{r}+{DL}_{wi}\times {DL}_{r}+{DR}_{wi}\times {DR}_{r}+{DT}_{wi}\times {DT}_{r}+ {DA}_{wi}\times {DA}_{r}+{DG}_{wi}\times {DG}_{r}\end{array}$$
(7)

where \({El}_{wi}\) represents the weight index of elevation criteria and \({El}_{r}\) is the rank of elevation criteria; \({SL}_{wi}\) represents the weight index of slope criteria and \({SL}_{r}\) is the rank of slope criteria; \({PE}_{wi}\) represents the weight index of permeability criteria and \({PE}_{r}\) is the rank of permeability criteria; \({DF}_{wi}\) represents the weight index of distance to faults criteria and \({DF}_{r}\) is the rank of distance to faults criteria; \({DS}_{wi}\) represents the weight index of distance to settlement criteria and \({DS}_{r}\) is the rank of distance to settlement criteria; \({LULC}_{wi}\) represents the weight index of LULC criteria and \({LULC}_{r}\) is the rank of LULC criteria; \({DD}_{wi}\) represents the weight index of distance to drainage criteria and \({DD}_{r}\) is the rank of distance to drainage criteria; \({DW}_{wi}\) represents the weight index of proximity of distance to water supplies criteria and \({DW}_{r}\) is the rank of distance to water supplies criteria; \({DL}_{wi}\) represents the weight index of distance to lakes criteria and \({DL}_{r}\) is the rank of proximity of distance to lakes criteria; \({DR}_{wi}\) represents the weight index of distance to road criteria and \({DR}_{r}\) is the rank of proximity of distance to road criteria;\({DT}_{wi}\) represents the weight index of distance from tourist centers criteria and \({DT}_{r}\) is the rank of proximity of distance from tourist centers criteria;\({DA}_{wi}\) represents the weight index of distance from archaeological centers criteria and \({DA}_{r}\) is the rank of proximity of distance from archaeological centers criteria; \({DG}_{wi}\) represents the weight index of distance from archaeological centers criteria and \({DG}_{r}\) is the rank of proximity of distance from archaeological centers criteria.

Table 6 Pairwise comparison matrix by AHP
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Validation

The process of accuracy evaluating of the final output of spatial modeling is a critical complementary procedure contributes in providing a reliable output that allows optimal use of the results of this study (Mohsin et al. 2022). The area under curve-receiver operating characteristic (AUC-ROC) was used in order to assess the accuracy of the final map of sanitary municipal landfill site selection in study area. To this end, several fieldworks were carried out in cooperation with the mayors across the study area to identify 100 sites, with 50 suitable sites and 50 unsuitable sites of landfills.

Result and discussion

The integration between spatial multi-criteria technology and GIS provided a reliable tool for developing a map of spatial suitability for optimal landfill sites. In this study, thirteen criteria, including geological, topographical, geomorphological, hydrological, and structural criteria, were used in selecting process the optimal sites for sustainable landfills. The selected criteria contribute to providing a correct spatial decision that helps in managing the problem of landfill sites in the context of reducing their negative effects on humans and the environment in the study area.

The AHP approach was based on evaluating the quantitative importance of the criteria involved in the spatial fit process to identify potential new landfill sites. At this stage, the importance of the criteria was compared by developing a pairwise comparison matrix according to the Saaty scale of 1 to 9. In this context, the opinions of 11 experts were based on the weighting of the criteria used. The consistency of this weighting performed in AHP approach was tested by CR index calculation. The value of CR is 0.061 (CR < 0.1), meaning that the criteria can be considered consistent and acceptable for modeling and classification in reliable spatial decision making. Final weights were assigned to all maps of the criteria layers used in the GIS environment (Fig. 5, Tables 7 and 8), and then, a spatial suitability map was produced.

Fig. 5
figure 5

Final weight ratio of sub-criteria based on AHP

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Table 7 Normalized pairwise comparison matrix and computation of criterion weightage
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Table 8 Weights of the criteria and scores of the sub-criteria
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Figure 6a shows the final output of the multi-criteria spatial modeling process for the potential landfill locations according to five suitability levels, i.e. unsuitable (83.28%), less suitable (8.49%), moderately suitable (4.49%), highly suitable (2.57%), and very highly suitable (0.72%) (Table 9). According to the current result, it was found that more than 80% of the study area is not suitable for establishing new landfill sites. It may be mentioned here that, this area is characterized by high environmental sensitivity, and consists mainly of forest masses and built-up lands; therefore, it is an area for forest conservation and urban and tourism development (Khodaparast et al. 2018; Bilgilioglu et al. 2021). Also, these areas are characterized by steep slopes measuring more than 50 degrees in some locations. Many ecologists indicate that slope enhances the risk of landfills, especially in humid areas (Şener et al. 2010; Pasalari et al. 2019; Barzehkar et al. 2019). The slope increases the runoff causing a greater spatial distribution of the landfill liquids. In sum, the establishment of landfills in these areas will inevitably lead to catastrophic environmental consequences for various vital sectors in study area.

Fig. 6
figure 6

Final outputs of landfilling suitability modeling: a suitability degrees map for the landfill sites, b candidate sites for landfilling according to AHP

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Table 9 Tabulate areas of landfills suitability degrees
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Simultaneously, it was found that only 0.72% of the study area is suitable for establishing new sustainable landfills. In this connection, Figure 6b shows the proposed sites for the establishment of landfills. The distribution of the proposed landfill sites, however, ensures the spatial balance between the distribution of population and settlements. It can be seen that the largest candidate sites for the establishment of new landfills were concentrated in the southern and southwestern regions. The proposed sites also provide important spatial horizons for achieving sustainable environmental conservation of natural resources in the study area with environmentally safe urbanization. Furthermore, it can be seen a spatial incompatibility between the existing dumps and the proposed ones. This indicates the environmental risk caused by the current landfills in destroying the local environment.

Figure 7 shows the spatial distribution of 100 landfill sites, including 50 suitable sites and 50 unfavorable sites. These sites, however, were used to assess the quality of the final map using ROC/AUC method. The AUC value of 88.01% indicates that the final map of the proposed landfill sites in this study is characterized by high accuracy (accuracy greater than 85%) according to Mohsin et al.’s (2022) study (Fig. 8). Thus, this final map can be used in the process of developing new landfill sites with environmental sustainability.

Fig. 7
figure 7

Determining suitable and unsuitable landfill locations

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Fig. 8
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AUC/ROC accuracy assessment of the final map

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Despite the strict criteria presented in exclusion analysis based on national and methodological justifications in landfill site selection, it is important to note the great flexibility that characterizes the rigid integration of GIS and computers. In this regard, making any improvements or additions to these criteria based on the abundance of data will produce other final spatial outputs that have greater credibility and reliability.

In this regard, the national criteria adopted in this analysis are compatible with the regulations of the countries neighbouring Syria, especially if the national population growth is compared with the neighbouring countries. In this regard, many studies have been conducted based on strict environmental regulations similar to the Syrian environmental regulations, including in Turkey (Azem et al. 2021), Iraq (Manguri and Hamza 2022), Jordan (Alsarayreh and Alsarayreh 2021), and Lebanon (Kamel and Hasan 2018). Moreover, some regions of the neighboring countries are witnessing a demographic growth similar to the study area. In those regions, the integration of GIS and the MCDM was relied upon in selecting the best sites for landfills, such as Aley and Chouf, Lebanon (Kamel and Hasan 2018) and Al-Naja city, Iraq (Kareem et al. 2021).

Despite the catastrophic health consequences induced by the landfills in the western region of Syria, mitigation of this problem is still absent from the list of priorities of the local administrative authorities (Nasser and Ahmad 2019; Noufal et al. 2021). During the last three decades, the rapid population growth and urbanization acceleration have led to an increase in the generation of solid waste which explains the massive spread of random landfills. This spread was not limited to the huge landfill for each administrative area in the study area, but almost every village has its own landfill. These landfills have negative impacts on the environmental quality, including soil degradation, pollution of water resources, population health, and distortion of the landscape. Incidentally, tourism is considered one of the most important sources of earnings in the study area due to the presence of some favorable factors including a moderate climate, the density of the river network, a dense forest cover, and the historical ruins. Consequently, the proliferation of landfills is a negatively impacts for the local economy and welfare. Similar observations can be reported by Chabuk et al. (2017) and Tercan et al. (2020) studies.

During the decade of war in Syria, the study area was among ones that received tens of thousands of displaced people from the places of hostilities inside Syria. The sudden and massive inflation in the population has caused an increase in the generation of solid waste, thus implying complete inability of the environmental authorities to manage the increase. In this study, a computerized hierarchical system incorporating a robust quantitative integration between AHP and GIS environment enabled the selection of sustainable landfill sites. The approach applied in this study helps in providing the basis for managing the pollution caused by random sites of landfills in the study area in the post-war environmental rehabilitation stage.

Conclusion

The spread of random landfills possesses catastrophic environmental consequences on public health and environmental quality. Despite the great complexity, choosing the optimal sites for landfills is one of the best urgent solutions applied globally. This selection process requires an understanding of many different criteria including physical, socio-economic, and technical ones. The robust integration of GIS and MCDM provides a creative platform which helps in proposing sustainable sites for landfills. In this study, the sustainable sites for sanitary landfills were determined through the integration of AHP and GIS techniques in the Safita area (western Syria). The study area, however, suffers from the indiscriminate spread of landfills, especially during the war period, which witnessed massive internal refugee waves. Based on national standards, previous literature, expert opinions, and the specificity of the study area, thirteen evaluation criteria were identified and used in the spatial suitability modeling process. These criteria are: elevation, slope, permeability, distance to faults, distance to settlement, land use/land cover, distance to drainage, distance to water supplies, distance to lakes, distance to road, distance from tourist centers, distance from archaeological centers, and distance from religious centers. A map of proposed sustainable landfills was generated and categorized using Natural Breaks into five classes: unsuitable (83.28%), less suitable (8.49%), moderately suitable (4.49%), highly suitable (2.57%), and very highly suitable (0.72%). The AUC value of this map, further, reached to 88.01%. The outputs of this paper provide high-value spatial insights into the problems of Safita area for local decision-makers and environmental planners. These insights will help manage the risk of random landfills in the post-war period in Syria.