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Abstract In arid climates, conventional water resources are severely limited and stressed in the face of rapid population growth and future climate change. So, it is necessary to find alternative non-conventional water resources for use in drought situations. Additionally, the non-conventional water resources in these areas are not sufficient to meet future water demand. Therefore, non-conventional water resources can be adopted as a strategic reserve to bridge the gap between water supply and demand in case of emergency and drought events. These resources might include rainwater harvesting, treated wastewater, and desalinated seawater. Managed aquifer recharge (MAR) can be applied to store these resources in the hydrogeological system using Geo information System—Multi Criteria Decision Analysis (GIS-MCDA) approach for determining the suitable MAR location for storage. North-west Kingdom of Saudi Arabia area was chosen for this study because it is extremely arid, has high potential for social and economic development, and it has newly constructed non-conventional water infrastructures distributed throughout the area including water desalination plants, Tertiary Sewage Effluent (TSE) waste water plants, and flash-flood storage dams. To identify the suitable MAR site location and structure, different data related to aquifer hydrogeology, surface hydrology, hydrometeorology, and water quality were applied. Then, GIS-MCDA holistic approach was applied with aid of ordered weighting average (OWA) technique. Finally, two maps were created to show the MAR location and structure type. Potential map indicates that ~ 18.85% of the area is suitable for MAR installations. About 0.17% of the total area exhibited very high potential, where infiltration ponds can be applied, 1.86% had high potential for construction of check dams with diversion channels, and 16.82% had moderate potential for installation of recharge wells. Additionally, 56 MAR structures were proposed and a map showing their locations has been created. Thus, results indicated that the study area is promising for MAR installation. These maps could aid the decision makers to propose a sustainable development plan for the future water resources of the area.

In arid climates, conventional water resources are severely limited and stressed in the face of rapid population growth and future climate change. So, it is necessary to find alternative non-conventional water resources for use in drought situations. Additionally, the non-conventional water resources in these areas are not sufficient to meet future water demand. Therefore, non-conventional water resources can be adopted as a strategic reserve to bridge the gap between water supply and demand in case of emergency and drought events. These resources might include rainwater harvesting, treated wastewater, and desalinated seawater. Managed aquifer recharge (MAR) can be applied to store these resources in the hydrogeological system using Geo information System—Multi Criteria Decision Analysis (GIS-MCDA) approach for determining the suitable MAR location for storage. North-west Kingdom of Saudi Arabia area was chosen for this study because it is extremely arid, has high potential for social and economic development, and it has newly constructed non-conventional water infrastructures distributed throughout the area including water desalination plants, Tertiary Sewage Effluent (TSE) waste water plants, and flash-flood storage dams. To identify the suitable MAR site location and structure, different data related to aquifer hydrogeology, surface hydrology, hydrometeorology, and water quality were applied. Then, GIS-MCDA holistic approach was applied with aid of ordered weighting average (OWA) technique. Finally, two maps were created to show the MAR location and structure type. Potential map indicates that ~ 18.85% of the area is suitable for MAR installations. About 0.17% of the total area exhibited very high potential, where infiltration ponds can be applied, 1.86% had high potential for construction of check dams with diversion channels, and 16.82% had moderate potential for installation of recharge wells. Additionally, 56 MAR structures were proposed and a map showing their locations has been created. Thus, results indicated that the study area is promising for MAR installation. These maps could aid the decision makers to propose a sustainable development plan for the future water resources of the area. [ABSTRACT FROM AUTHOR]

The combination of accelerated urbanization and tourism-related activities, along with frequent coastal flooding, has generated pressure on the coastline of the Republic of Croatia (RH). In this paper, an integrated coastal vulnerability model (ICVI) for coastal flooding was developed. The ICVI was generated using a GIS multicriteria approach and derived from two sub-indices: the physical vulnerability index (CVIN) and the socio-economic vulnerability index (CVIS). In total, 30 criteria were used in the derivation of the ICVI, with twelve contributing to CVIS and eighteen to CVIN. The ICVI model is represented as a line divided into smaller segments, each segment indicating ICVI vulnerability levels ranging from 1 (very low) to 5 (very high). The accuracy of CVIN was evaluated using 159 geocoded coastal flood locations obtained from various websites and the official register of Hrvatske Vode flood events from 2008 to 2023. More than 80% of geocoded flood locations are situated in areas with very high (5) or high (4) CVIN. Furthermore, out of 32 settlements with officially registered flood events, 90.6% of them are located in areas with very high or high ICVI. Since all data used in the ICVI derivation were acquired from open-source databases and a user-friendly GIS-MCDA toolbox was utilized, this paper presents a cost-effective approach to modeling integrated coastal vulnerability. This model can guide decision-makers and provide them with new insights for implementing an effective integrated coastal zone management strategy.

Groundwater in the Nabogo Basin is threatened by increasing domestic and irrigation demands during the dry season, owing to climate change and overexploitation. Managed aquifer recharge (MAR) has therefore been proposed as a water management technique to augment groundwater resources. However, the success of MAR schemes depends on the selection of sites with suitable surface and subsurface properties to enhance the recharge rates. Thus, this study created spatial maps of the slope, drainage density, land use/cover, soil texture, transmissivity, groundwater depth, and aquifer thickness in the basin to create a suitability map. Analytical hierarchy process (AHP) with and without Monte Carlo (MC) simulation was used to create weights for each criterion based on seven expert opinions to assess their performance in dealing with uncertainties. The spatial maps and weights were then integrated to create a MAR suitability map. The results showed similar mean weights for AHP- and MC-aided simulations. However, MC-aided simulations narrowed the confidence interval and reduced the standard deviation of the AHP weights by 50–89%, thereby reducing the uncertainty and sensitivity of the weights. Furthermore, the suitability map showed that 38.8% (1124 km2), 39.2% (1136 km2), and 22% (637 km2) of the basin was suitable, less suitable, and unsuitable, respectively, for MAR applications. A receiver operating curve (ROC) value of 77.8% from the validation process indicated good model performance. This proves the effectiveness of MC simulations in reducing errors and uncertainty in the AHP. Therefore, it is a useful tool for mapping MAR suitability. [ABSTRACT FROM AUTHOR]

Across Europe marginalization has been highlighted as an object of important political concern. In the area of Central Europe and the Balkans, the problem of marginalization has not been sufficiently researched. This particularly applies to the Bosnia and Herzegovina (BiH). Using the GIS multicriteria decision analysis a composite index of geographical marginalization (GMAR) was created. Marginalization is analyzed as a multidimensional concept using the 4 groups with a total of 40 criteria. Spatial patterns were detected from extremely marginalized to extremely non-marginalized regions. The GMAR indicates the existence of regional disparities in BiH. The high degree of marginalization, especially those in the border sector, alerts the implementation of the demarginalization measures. [ABSTRACT FROM AUTHOR]

Godavari basin, a rain-fed and the second largest river basin in India has witnessed numerous extreme events of droughts and floods in recent decades, having major implications on the water resource situation of the basin. The present study is an attempt to assess the near-future water stress zones of the basin by analysing seven variables under GIS-based multi-criteria decision analysis (GIS-MCDA): dryness intensity (DI), dry-episodes frequency (DF), wet-episodes frequency (WF), annual rainfall trend (RfT), dry days trend (DD), population growth rate (PGR) and groundwater fluctuation rate (GWR). The weight of the variables was assigned by analytical hierarchical process (AHP), and water stress regions were identified using weighted linear combination (WLC) under GIS-MCDA. DI, DF and WF for the last three decades of this basin were calculated using the 9-month Standardised Precipitation Evapotranspiration Index (SPEI-9). Mann–Kendall's test and Sen’s slope were used to examine the dry and wet trends in SPEI-9 and estimate the groundwater fluctuation rate. The analysis shows that if the current trends of the seven climatic, hydrologic and demographic variables persist, then the interior districts of the basin will be prone to high water stress risk in the near future. This study has identified the districts that need urgent structural and non-structural changes in the current water resource management practices to sustain the future climate change challenges. Highlights: Examined the frequency and intensity of dry and wet episodes between 1990 and 2019 of the Godavari basin at the sub-basin level using Standardised Precipitation Evapotranspiration Index (SPEI–9 months). Mann–Kendall’s test shows that Manjra and Pranhita register strong dryness trend during most of the months of a year. The maximum decline (> 10 cm bgl y–1) of groundwater is recorded in Upper Godavari, Middle Godavari, Manjra and parts of Wardah and Pranhita. GIS-MCDA-based water stress risk assessment found that the interior districts of the basin are more prone to high water stress in near future. Identified the districts that need urgent structural and non-structural changes in the current water resource management practices. [ABSTRACT FROM AUTHOR]

Infiltration models and impervious surface models have gained significant attention in recent years as crucial tools in urban and environmental planning, to assess the extent of land-surface changes and their impacts on hydrological processes. These models are important for understanding the hydrological dynamics and ecological impacts of urbanization and for the improvement of sustainable land-use planning and stormwater-management strategies. Due to the fact that many authors partially or entirely overlook the significance of the infiltration process in geographic information system (GIS) analyses, there is currently no universally accepted method for creating an infiltration model that is suitable for GIS multicriteria decision analysis (GIS-MCDA). This research paper presents an innovative approach to modeling the infiltration-efficiency index (IEI) for GIS analysis, with a focus on achieving high-quality results. The proposed methodology integrates very-high-resolution (VHR) remote-sensing data, GIS-MCDA, and statistical methods. The methodology was tested and demonstrated on a small sub-catchment in Metković, Croatia. The study developed a VHR IEI model from six specific criteria that produced values between 0 and 0.71. The model revealed that 14.89% of the research area is covered by impervious surfaces. This percentage is relatively favorable when compared to urban areas globally. The majority of the research area (62.79%) has good infiltration efficiency. These areas are predominantly characterized by agricultural land use, encompassing orchards, tangerines, olive groves, vineyards, and a diverse range of low-lying and high vegetation on flat terrain. The IEI model can provide input spatial data for high-resolution GIS analysis of hydrological processes. This model will aid decision-makers in stormwater-management, flood-risk assessment, land-use planning, and the design of green infrastructure. By utilizing the information derived from this study, policymakers can make informed decisions to mitigate flooding risks and promote sustainable urban development. [ABSTRACT FROM AUTHOR]

Site selection and allocation of manufacturing and processing facilities are essential to sustainable economic productivity of a given product while preserving soil, the environment, and biodiversity. An essential criterion when evaluating various approaches to model land suitability for pistachio processing facilities is their adaptability to accommodate diverse perspectives and circumstances of managers and decision makers. Incorporating the concept of risk into the decision-making process stands as a significant research gap in modeling land suitability for pistachio processing facilities. This study presents a scenario-based multi-criteria decision-making system for modeling the land suitability of pistachio processing facilities. The model was implemented based on a stakeholder analysis as well as inclusion of a set of influential criteria and restrictions for an Iranian case study, which is among the top three producers. The weight of each criterion was determined based on the best-worst method (BWM) after the stakeholder analysis. Then, the ordered weighted averaging (OWA) model was used to prepare maps of spatial potential for building a pistachio processing factory in different decision-making scenarios, including very pessimistic, pessimistic, intermediate, optimistic, and very optimistic attitudes. Finally, the sensitivity analysis of very-high- and high-potential regions to changes in the weight of the effective criteria was evaluated and proved that the most important criteria were proximity to pistachio orchards, proximity to residential areas, proximity to the road network, and proximity to industrial areas. Overall, 327 km2 of the study area was classified as restricted, meaning that they are not suitable locations for pistachio processing. The average estimated potential values based on the proposed model for very pessimistic, pessimistic, intermediate, optimistic, and very optimistic scenarios were 0.19, 0.47, 0.63, 0.78, and 0.97, respectively. The very-high-potential class covered 0, 0.41, 8.25, 39.64, and 99.78 percent of the study area based on these scenarios, respectively. The area of suitable regions for investment decreased by increasing risk aversion in decision making. The model was more sensitive to changes in the weights of proximity to residential areas, proximity to pistachio orchards, and proximity to transportation hubs. The proposed approach and the achieved findings could be of broader use to respective stakeholders and investors. Given the suitability of arid regions for planting pistachio and its relatively high profitability, the local authorities and decision makers can promote further expansion of the orchards, which can lead to better welfare of farmers and reducing rural-urban migration in the region. [ABSTRACT FROM AUTHOR]

Chennai, the capital city of Tamil Nadu in India, has experienced several instances of severe flooding over the past two decades, primarily attributed to persistent heavy rainfall. Accurate mapping of flood-prone regions in the basin is crucial for the comprehensive flood risk management. This study used the GIS-MCDA model, a multi-criteria decision analysis (MCDA) model that incorporated geographic information system (GIS) technology to support decision making processes. Remote sensing, GIS, and analytical hierarchy technique (AHP) were used to identify flood-prone zones and to determine the weights of various factors affecting flood risk, such as rainfall, distance to river, elevation, slope, land use/land cover, drainage density, soil type, and lithology. Four groups (zones) were identified by the flood susceptibility map including high, medium, low, and very low. These zones occupied 16.41%, 67.33%, 16.18%, and 0.08% of the area, respectively. Historical flood events in the study area coincided with the flood risk classification and flood vulnerability map. Regions situated close to rivers, characterized by low elevation, slope, and high runoff density were found to be more susceptible to flooding. The flood susceptibility map generated by the GIS-MCDA accurately described the flood-prone regions in the study area. [ABSTRACT FROM AUTHOR]

This study presents a simple framework methodology for selecting the most appropriate locations for managed aquifer recharge (MAR). The proposed approach is applicable to aquifers that are located in coastal or mountainous areas and are used either for agricultural or industrial (e.g., mining) activities. A characteristic case study for the identification of the areas that are the most suitable for aquifer recharge using a GIS multi-criteria decision analysis (GIS-MCDA) method by means of MAR type spreading methods is the Geropotamos basin, Crete, Greece. Criteria combining a high relevance and high data availability, and providing unique information, were selected to assess the suitability of aquifer recharge in the basin. The criteria applied to evaluate the sites’ suitability for MAR spreading methods are hydrogeology, slope, land use, rainfall, groundwater level, soil texture and distance to source water. This study uses the ‘Pairwise comparison’ to assign criteria weights, as part of the Analytic Hierarchy Process (AHP), and examines four different scenarios. In all four scenarios, downstream areas, and close to the river Geropotamos, coincide as the most appropriate for aquifer recharge. HIGHLIGHTS aquifer recharge.; multi-criteria decision analysis (GIS-MCDA) method.; to identify suitable sites for implementing an MAR (Managed Aquifer Recharge) type spreading method.; This study uses the ‘Pairwise comparison’ to assign criteria weights.; Analytic Hierarchy Process (AHP).;

Montenegro has different influences on the weather and climate; in general, according to Köppen's classification, there are two climate zones: warm temperate (C) and cold temperate (D). The aim of this study is to determine the susceptibility to wildfires in the Montenegrin coastal municipality of Budva and the northern municipality of Rožaje, which are located in different climatic conditions, using multicriteria GIS decision analysis (GIS-MCDA). Nine natural and anthropogenic criteria were used for the analysis. Open geospatial data were used as input data for all criteria. The assignment of weighting coefficients for the criteria in relation to wildfire susceptibility importance was based on the Analytic Hierarchy Process (AHP) and Fuzzy Analytic Hierarchy Process (F-AHP) procedures. The results for the AHP and F-AHP models were obtained using the Weighted Linear Combination (WLC) method. According to the AHP model, the very high and high category covers 80.93% of the total area in Budva and 80.65% in Rožaje. According to the F-AHP model, the very high and high category occupies 80.71% of the total area in Budva and 82.30% in Rožaje. The validation shows that the models of GIS-MCDA perform fair in both climatic zones. The proposed models, especially in the absence of geospatial data, can be a strategic and operational advantage in the development of plans and strategies for protection against wildfires. [ABSTRACT FROM AUTHOR]

Protected natural areas of Kazakhstan, particularly national parks, occupy a unique role in developing ecological tourism. One way to ensure biodiversity conservation, environmental preservation, and regional sustainability is through promoting ecotourism in national parks. For the "Altynemel" National Park, ecotourism should be regarded as a priority type of tourism. The article considers the essential technologies and principles of implementation of ecological tourism in the National Park "Altynemel". Identified and justified the uniqueness of this protected area—the equal value of natural and cultural heritage on its territory. We revealed the problems and constraints of ecotourism development in the national park and offered the ways of their solution. The article is written based on field research materials, methods of a local population survey, interviews, and focus group discussions. In this article, 201 representative families were interviewed using questions on a 5-point Likert scale, including 159 residents of the village of Basshi and 42 residents of the village of Nurym. The results show that the overall assessment of sustainability is mild in the two communities. As a result, we claim that sustainable development in the "Altynemel" National Park is far from perfect. Sustainable development in the "Altynemel" National Park could be better. In particular, tourism development's positive economic and political impact has yet to be apparent. [ABSTRACT FROM AUTHOR]

The latest Indonesian Electricity Supply Business Plan (RUPTL 2021-2030) confirms Indonesia’s commitment to renewable energy. The government projects electricity generation of 40.6 GW in 2023 and is committed to involving renewable energy, which constitutes 38% of the total electricity generation capacity. Using simple regression analysis, the projected renewable energy capacity requirement is 47 GW, some of which can be met by building solar PV as a power plant. The main obstacle to achieving this goal is securing private investment, which requires identifying optimal locations where protected and conservation areas are not threatened. GIS-based Multi-Criteria Decision Analysis (MCDA) techniques are used in this research to evaluate various constraints. A commonly used method in this framework is AHP (Analytic Hierarchy Process), which uses pairwise comparisons to assign weights based on significance in a hierarchy of objectives. Criteria for determining locations for solar PV development using spatial analysis include prohibited areas, including forest areas and protected habitats, rice fields and peatlands; surface radiance, slope, temperature at 2m; and proximity to highways and power grids. Since the surface radiance spatial data obtained possess missing data, inverse distance weighting (IDW) is utilised to overcome this issue due to its simplicity and fast computation. The location determination process resulted in an estimated 43 solar power plant locations strategically located across all islands in Indonesia to help meet national energy needs.

Climate-related hazards such as sand and dust storms (SDS) have various impacts on human health, socio-economy, environment, and agroecosystems. Iran has been severely affected by domestic and external SDS during the last two decades. Considering the fragile economy of Iran's rural areas and the strong dependence of livelihood on agroecosystems, SDS cause serious damage to human communities. Therefore, there is an urgent need to conduct a vulnerability assessment for developing SDS risk mitigation plans. In this study, various components of SDS vulnerability were formulated through a geographic information system (GIS)-based integrated assessment approach using composite indicators. By implementing a GIS multiple-criteria decision analysis (GIS-MCDA) model using socioeconomic and remote sensing data, a map of rural vulnerability to SDS was produced. Our results show that about 37% of Iran's rural areas have experienced high and very high levels of vulnerability to SDS. Rural areas in the southeast and south of Iran, especially Sistan and Baluchestan and Hormozgan provinces are more vulnerable to SDS. The findings of this study provide a basis for developing SDS disaster risk-reduction plans and enabling the authorities to prioritize SDS mitigation policies at the provincial administrative scale in Iran. [ABSTRACT FROM AUTHOR]

This study presents a simple framework methodology for selecting the most appropriate locations for managed aquifer recharge (MAR). The proposed approach is applicable to aquifers that are located in coastal or mountainous areas and are used either for agricultural or industrial (e.g., mining) activities. A characteristic case study for the identification of the areas that are the most suitable for aquifer recharge using a GIS multi-criteria decision analysis (GIS-MCDA) method by means of MAR type spreading methods is the Geropotamos basin, Crete, Greece. Criteria combining a high relevance and high data availability, and providing unique information, were selected to assess the suitability of aquifer recharge in the basin. The criteria applied to evaluate the sites' suitability for MAR spreading methods are hydrogeology, slope, land use, rainfall, groundwater level, soil texture and distance to source water. This study uses the 'Pairwise comparison' to assign criteria weights, as part of the Analytic Hierarchy Process (AHP), and examines four different scenarios. In all four scenarios, downstream areas, and close to the river Geropotamos, coincide as the most appropriate for aquifer recharge. [ABSTRACT FROM AUTHOR]

• An objective hierarchy framework for BGI planning is co-developed with stakeholders. • Value-focused thinking was used to align the framework with stakeholders' values. • Value scales for objective attributes are elicited to assess BGI site performance. • The framework and the approach can be transferable for use in other cities. Strategic planning approaches are essential for addressing the complex and multi-dimensional challenges in selecting blue-green infrastructure (BGI) location. The development of planning support systems (PSS) for BGI siting often lacks a value-based approach with early stakeholder engagement. In this study, we used value-focused thinking (VFT) to adapt and develop a BGI planning support framework to the Canadian urban context, moving towards an objective-driven framework. We provide a hierarchical objectives framework for BGI planning in urban areas, aligned with stakeholder values, with three-level information: higher-level objectives, lower-level objectives and measurable spatial attributes. To assess site performance across these attributes, value scales elicitation was conducted with 17 experts. The engagement of 37 stakeholders in co-creating and validating our objectives set helped identify common concerns and refine our framework, focusing on the most relevant objectives for stakeholders. The VFT approach and the resulting framework can be easily transferred to other cities in Quebec (Canada), but also to other urban contexts looking to optimize BGI site selection to maximize benefits across the multiple functions of BGI and opportunities arising from the urban context. [ABSTRACT FROM AUTHOR]

Montenegro has different influences on the weather and climate; in general, according to Köppen’s classification, there are two climate zones: warm temperate (C) and cold temperate (D). The aim of this study is to determine the susceptibility to wildfires in the Montenegrin coastal municipality of Budva and the northern municipality of Rožaje, which are located in different climatic conditions, using multicriteria GIS decision analysis (GIS-MCDA). Nine natural and anthropogenic criteria were used for the analysis. Open geospatial data were used as input data for all criteria. The assignment of weighting coefficients for the criteria in relation to wildfire susceptibility importance was based on the Analytic Hierarchy Process (AHP) and Fuzzy Analytic Hierarchy Process (F-AHP) procedures. The results for the AHP and F-AHP models were obtained using the Weighted Linear Combination (WLC) method. According to the AHP model, the very high and high category covers 80.93% of the total area in Budva and 80.65% in Rožaje. According to the F-AHP model, the very high and high category occupies 80.71% of the total area in Budva and 82.30% in Rožaje. The validation shows that the models of GIS-MCDA perform fair in both climatic zones. The proposed models, especially in the absence of geospatial data, can be a strategic and operational advantage in the development of plans and strategies for protection against wildfires.

Suitability mapping for managed aquifer recharge is recently gaining more attention because of its potential in producing comprehensive maps easily interpreted and used by policy makers. In front of the divers existing methodologies, an adapted approach for the arid and semi-arid conditions of Tunisia was developed to generate a managed aquifer recharge (MAR) suitability and feasibility maps within a participatory approach with stakeholders. A Geographical Information Systems coupled with multi-criteria decision analysis (GIS-MCDA) was applied to establish the suitability and feasibility of MAR in Enfidha plain, NE of Tunisia. Selected criterions were spatialized under GIS thematic layers, and they were standardized based on literature and experts' opinions regarding their importance in MAR implementation. Weights of each criterion were determined using analytic hierarchy process (AHP). Intrinsic suitability map was obtained using weighted linear combination (WLC) by the mean of ArcGIS software and via the INOWAS (innovative web-based decision support system for water sustainability under a changing climate) platform. It shows that more than 80% of the total plain area is intrinsically suitable and highly suitable for MAR. MAR feasibility map was established by overlaying intrinsic suitability, recharge water availability, and water demand maps of the region. It reveals that almost the fifth of the plain has high MAR feasibility potential. A decision support system (DSS) web-portal, namely, INOWAS, was finally used as an effective tool to store, share, and establish the MAR suitability maps with the concerned stakeholders. [ABSTRACT FROM AUTHOR]

Multicriteria route planning is a crucial transportation planning issue under the field of GIS-based multicriteria decision analysis (GIS-MCDA) with broad applications. A searching algorithm is proposed to solve the multicriteria route planning problem with spatial urban information and constraints such an existing transit network in operation, certain vertices to be visited in the path, total number of vertices been visited, and length or range for the path. Evaluation of two in-operation mass-transit systems from Chicago and Tainan show that our method can retrieve solutions in a Pareto-optimal sense over comparative methods between profit under queried constraints (the expected passenger flow to be maximized, referring to the social welfare for the public) and cost for construction as well as maintenance (the cost of route to be minimized, referring to the sustainability for the government) with reasonable runtime over comparative methods. [ABSTRACT FROM AUTHOR]

Ecotourism is a major tourism dimension that has received significant attention in recent years. It is widely known that the tourism industry, and in particular ecotourism, makes a significant contribution to sustainable development. In this context, the West Azerbaijan province is one of most important tourist destinations in Iran for attracting tourists interested in nature. The main purpose of this study was to analyze and map the potential for sustainable ecotourism development. The research methodology was developed based on GIS multi-criteria decision analysis (GIS-MCDA) techniques, using 28 spatial indicators. For this purpose, areas with the potential for attracting tourists were identified and the effective factors for increasing and decreasing tourism development activities were evaluated by GIS analysis. The method used as a multi-criteria spatial decision-making technique is based on the network analysis process and its combination with fuzzy logic is very effective for increasing the accuracy of the model and obtaining more realistic results. According to the results of this study, West Azerbaijan, due to its potential, including some areas unknown to tourists and even tourism planners, could be introduced as a nature tourism hub in the northwest of the country. The detailed tourism sustainability map obtained, at the scale of 1/25,000, could be used as a basis for regional planning and sustainable ecotourism development. In this context, the results could also be critical for tourism companies, agencies and local stakeholders and organizations for various applications, such as investment and development of tourism hospitality facilities and infrastructure in high potential areas. The research can also be considered as progressive in tourism research and supports future research on the selection of beneficial criteria and the application of efficient methods for tourism sustainability assessment and mapping. [ABSTRACT FROM AUTHOR]

Grains play a significant role in meeting the nutritional needs of the increasing world population. Consequently, the need for new studies on agricultural production and land suitability assessments has increased. The present paper aims to perform agricultural land suitability assessment to evaluate agricultural productivity in Tekirdağ province to determine precise productive agricultural areas. This study combines a variety of datasets to develop a dynamic model using GIS-based multi-criteria decision analysis for land suitability assessment and agricultural productivity. The datasets used in this study are supported by terrestrial samples and processed with spatial technologies. The results of the study indicate that the agricultural potential of the provincial lands is quite high. It reveals that 65.7% of province lands are suitable for agricultural production. Of the remaining lands, 20.3% is marginally suitable while only 8% of the land is unsuitable for agricultural production. In the northwestern part, suitable land for agricultural productivity is higher compared to other parts of the study area. This part also corresponds to the areas where industrial activities are marginal. The results also imply that agricultural activities in grain production areas must be reconsidered and replanned according to the new classification of land suitability assessment. In this respect, our study suggests that the policymakers and the government should take necessary steps to ensure the protection and sustainability of agricultural lands while planning for the industrial and settlement development in grain production areas. [ABSTRACT FROM AUTHOR]

Abstract Recent years have shown a significant increase in the occurrence of floods globally, with an impact on habitation and different sectors of the economy. This, in turn, necessitates the use of different flood mitigation strategies, wherein flood vulnerability assessment plays a significant role. The proposed work presents a methodology that combines vulnerability under physical-environmental and socio-economic domains to assess the overall flood vulnerability at the local self-government level. The methodology was illustrated to the case of Aluva municipality, located on the banks of River Periyar, in Kerala state, India. The spatial variation of hazard inducing factors and population statistics were analysed using Geographic Information System (GIS) tools. The machine learning algorithm, Random Forest, which uses hazard inducing factors as input was implemented for the evaluation of physical-environmental vulnerability. The social vulnerability of the region was analysed using the GIS Multi-criteria decision analysis approach (MCDA), with criteria weights to incorporate the interests of different stakeholders. The critical combinations of the two domains of vulnerability in the assessment of the vulnerability to flood, to have efficient flood management in local self-government was demonstrated in this study and can be made use of for any flood event.

Climate-related hazards such as sand and dust storms (SDS) have various impacts on human health, socio-economy, environment, and agroecosystems. Iran has been severely affected by domestic and external SDS during the last two decades. Considering the fragile economy of Iran’s rural areas and the strong dependence of livelihood on agroecosystems, SDS cause serious damage to human communities. Therefore, there is an urgent need to conduct a vulnerability assessment for developing SDS risk mitigation plans. In this study, various components of SDS vulnerability were formulated through a geographic information system (GIS)-based integrated assessment approach using composite indicators. By implementing a GIS multiple-criteria decision analysis (GIS-MCDA) model using socioeconomic and remote sensing data, a map of rural vulnerability to SDS was produced. Our results show that about 37% of Iran’s rural areas have experienced high and very high levels of vulnerability to SDS. Rural areas in the southeast and south of Iran, especially Sistan and Baluchestan and Hormozgan provinces are more vulnerable to SDS. The findings of this study provide a basis for developing SDS disaster risk-reduction plans and enabling the authorities to prioritize SDS mitigation policies at the provincial administrative scale in Iran.

The fishing bycatch of the loggerhead sea turtle (Caretta caretta) epitomizes the challenges of designing fisheries management strategies to protect highly migratory, endangered species. We present here the case of turtle bycatch in the Gulf of Ulloa, Mexico, in which conservation advocacy groups requested the United States Government to apply the legal provisions for preventing fishing bycatch of protected living marine resources (PLMR). Because these provisions implied the possibility of trade sanctions, the Mexican government had to devise policies equivalent to those imposed on the United States’ fleet. While conservation advocacy groups claimed that the effect of fishing bycatch was proven, the federal fisheries agency disregarded the facts for political reasons. Evidently, there was a need for a practical approach to address this highly contested policy-making problem characterized by limited data, deep uncertainties, and urgency for results. Our goal here is to present the implementation of an exploratory modeling rationale to tackle this sort of complex socio-ecological technological problem. We focused on identifying the bycatch level at which the environmental authorities would be compelled by law to act in protecting the loggerheads. We combined ecological risk analysis and area-oriented multiple-use framework to evaluate a wide range of plausible scenarios consistent with the available data. Results identified the bycatch level that indicated a potential critical transition to a low resilience state of the loggerhead population, and the proper multiple-use management scheme. Our findings were used to formulate regulations aimed to set a bycatch cap and a refuge area for the loggerhead population in the region.

The North-South highway is a central axis of the Algerian road network. This major project is expected to enhance the socio-economic development of Algeria. However, its first section is implemented within a complex region with very contrasted landscapes marked by mass movements. In the present work, we conducted a mass movement susceptibility assessment on the first section of the road infrastructure using a Multi-Criteria Decision Analysis approach. Various data from different sources were processed in a GIS environment, and nine landslide and rockfall conditioning factors were considered: Lithology, Slope, Daily Temperature Amplitude, Rainfall, Lineament Density, NDVI, Relative Relief, Drainage Density, and Distance to Streams. Each of the conditioning factors was selected, reclassified, and ranked according to its influence on each mass movement type. Two popular GIS-MCDA methods, namely AHP and WLC, were used to weight the influence and combine the selected factors and construct the landslide and rockfall assessment models. Then, landslide and rockfall susceptibility indices were calculated and used to produce mass movement susceptibility maps of the study area. Finally, a spatial analysis was performed to assess the highway section's susceptibility to the two mass movements. The results show that 22.49% and 12.44% of the road section are highly susceptible to landslide and rockfall hazards, respectively. Finally, the combination of the resulting map with the road chainage enabled the delineation of segments highly susceptible to landslide and rockfall hazards by kilometric points. [ABSTRACT FROM AUTHOR]

Multicriteria route planning is a crucial transportation planning issue under the field of GIS-based multicriteria decision analysis (GIS-MCDA) with broad applications. A searching algorithm is proposed to solve the multicriteria route planning problem with spatial urban information and constraints such an existing transit network in operation, certain vertices to be visited in the path, total number of vertices been visited, and length or range for the path. Evaluation of two in-operation mass-transit systems from Chicago and Tainan show that our method can retrieve solutions in a Pareto-optimal sense over comparative methods between profit under queried constraints (the expected passenger flow to be maximized, referring to the social welfare for the public) and cost for construction as well as maintenance (the cost of route to be minimized, referring to the sustainability for the government) with reasonable runtime over comparative methods.

Recent years have shown a significant increase in the occurrence of floods globally, with an impact on habitation and different sectors of the economy. This, in turn, necessitates the use of different flood mitigation strategies, wherein flood vulnerability assessment plays a significant role. The proposed work presents a methodology that combines vulnerability under physical-environmental and socio-economic domains to assess the overall flood vulnerability at the local self-government level. The methodology was illustrated to the case of Aluva municipality, located on the banks of River Periyar, in Kerala state, India. The spatial variation of hazard inducing factors and population statistics were analysed using Geographic Information System (GIS) tools. The machine learning algorithm, Random Forest, which uses hazard inducing factors as input was implemented for the evaluation of physical-environmental vulnerability. The social vulnerability of the region was analysed using the GIS Multi-criteria decision analysis approach (MCDA), with criteria weights to incorporate the interests of different stakeholders. The critical combinations of the two domains of vulnerability in the assessment of the vulnerability to flood, to have efficient flood management in local self-government was demonstrated in this study and can be made use of for any flood event. [ABSTRACT FROM AUTHOR]

This research investigates the efficiency of combining the Analytical Network Process (ANP) and fuzzy logic for developing a fire risk map. Major factors influencing the occurrence of forest fires were identified from the literature. The importance of each factor was determined by an ANP ranking procedure, which yielded the criteria weights, while fuzzy logic was employed for assessing the weights of the subcriteria. Then, GIS-based aggregation functions were employed to produce a fire risk map. In order to validate the results, forest fire locations were identified using field data, satellite images, and national reports. This validation revealed a very high accuracy of 0.819 for the fuzzy ANP model. The results will serve as guidelines for researchers and scientists by introducing new and robust MCDA methods. In general, the mentioned Hybrid method can be applied to early warning, fire suppression resources planning, and allocation work in the study area. [ABSTRACT FROM AUTHOR]

The site selection for Low Impact Development (LID) practices is a significant process. It affects the effectiveness of LID in controlling stormwater surface runoff, volume, flow rate, and infiltration. This research paper presents a comprehensive review of various methods used for LID site selection. It starts by introducing different methods and tools. Three main methods: index-based methods, GIS-based multi-criteria decision analysis (MCDA), and multi-criteria models and tools, are discussed in detail. A comparative analysis of these methods is then conducted based on ten different criteria. These criteria include the number of variables, data properties, the scale of analysis, benefits maximization approach, multi-attribute decision analysis, user-friendliness, community and stakeholder participation, and the validation methods. This comparison reveals limitations in each method. These include inadequate data availability and quality, lack of evaluation methods, comprehensive assessment criteria and spatial explicitness. These challenges underscore the need for future research to prioritize spatial clarity, broaden criteria, improve data quality through standardization, incorporate field visits and remote sensing for robust results, integrate big data, and develop web-based, open-source tools for enhanced accessibility. These key strategies provide valuable insights for advancing LID site selection methods. • Reviews key LID site selection methods. • Comparative analysis based on multiple factors. • Highlights method limitations, prompting further research in LID site selection. • Recommends improvements and new methods to address research gaps. [ABSTRACT FROM AUTHOR]

Spatio-temporal fluctuation of climatic variables with the terrain characteristics and their inter-relationship is a priority for predicting flash-flood-induced landslide hazards over the fragile Himalayas. The present study addressed this anxiety by assimilating satellite data products and auxiliary datasets in the Bhagirathi River basin of the Indian Himalayas. Snow Covered Area (SCA) is a critical indicator of the ecosystem that influenced the flash flood along different terrain features such as Altitude, Hill-Gradient, and Aspect. GIS-based multi-criteria decision analysis (GIS-MCDA) technique is used to analyze the possible landslide zones and flood extent along the river basin, and MODIS Terra (MOD10A2) data products derived annual SCA is 4278 km2 for the year 2021, the analysis of geospatial maps at 25° intervals of Altitude, hill-gradient, and Aspect. The SCA distribution reveals that apart from the Altitude, the Aspect of the hill gradient significantly impacts snow accumulation. Hill-Gradient, ranging from 13.06 to 19.52, occupies 24.7% of the total area, and 45.3 to 51.83 are found without snow. The highest variation of SCA is along the Western direction (9.19%), followed by North-East (8.79%), while the least (3.78%) variance is in the Southwest direction. Additionally, it was found that many bridges, roads, and other properties are under threat in this study area, even with a moderate flash flood. Findings from this study provide the spatiotemporal status of SCA in various geological stress conditions during the last decades and probable landslide zones. This will be a preliminary pathway to policymakers in rehabilitation and early evacuation of human lives due to flash flood occurrence. [Display omitted] • Spatio-temporal pattern of SCA estimated along the terrain characteristics. • Climate change induced flash-flood influencing socioeconomic development. • The landslide susceptibility analysis through GIS-MCDA distressed high-risk zones. • This study may provide a pathway to policymakers in hazardous conditions. [ABSTRACT FROM AUTHOR]

Distributed green stormwater management infrastructure is increasingly applied worldwide to counter the negative impacts of urbanisation and climate change, while providing a range of benefits related to ecosystem services. They are known as Water Sensitive Urban Design (WSUD) in Australia, Nature Based Solutions (NBS) in Europe, Low Impact Development (LID) in the USA, and Sponge City systems in China. Urban planning for WSUD has been ad-hoc, lacking strategy and resulting in sub-optimal outcomes. The purpose of this study is to help improve strategic WSUD planning and placement through the development of a Planning Support System. This paper presents the development of Spatial Suitability ANalysis TOol (SSANTO), a rapid GIS-based Multi-Criteria Decision Analysis tool using a flexible mix of techniques to map suitability for WSUD assets across urban areas. SSANTO applies a novel WSUD suitability framework, which conceptualises spatial suitability for WSUD implementation from two perspectives: 'Needs' and 'Opportunities' for WSUD. It combines biophysical as well as socio-economic, planning and governance criteria ('Opportunities') with criteria relating to ecosystem services ('Needs'). Testing SSANTO through comparing its results to work done by a WSUD consultancy successfully verified its algorithms and demonstrated its capability to reflect and potentially enhance the outcomes of planning processes. Manual GIS based suitability analysis is time and resource intensive. Through its rapid suitability analysis, SSANTO facilitates iterative spatial analysis for exploration of scenarios and stakeholder preferences. It thus facilitates collaborative planning and deeper understanding of the relationship between diverse and complex urban contexts and urban planning outcomes for WSUD. Unlabelled Image • Current WSUD planning is ad-hoc, causing sub-optimal functioning of systems and uncapitalized potential benefits; • We developed a spatial suitability model (SSANTO) to inform placement of WSUD, assessing opportunities and needs; • Besides biophysical, socio-economic and planning aspects, SSANTO brings knowledge from ecosystem services into WSUD planning; • SSANTO facilitates sophisticated Geo-Information Science-based Multi-Criteria Decision Analysis; • Testing of SSANTO shows its usefulness to robust WSUD planning/implementation; • SSANTO enables deep stakeholder engagement with urban planning focussing on opportunities and needs of WSUD. [ABSTRACT FROM AUTHOR]

Finding an appropriate vacant lot to buy is one of the most important land marketing problems in Tehran, Iran. Typically, the land selection and purchase processes in Tehran city are based on face-to-face meetings. Despite the face-to-face land sale and purchase strategies, a few online geo-marketing or real-estate websites have been developed. However, these geo-marketing real-estate web services have two main limitations. The services have focused on simple searches and selections from a set of predefined land parcels according to some basic criteria, such as land price, area etc. They do not consider spatially explicit criteria and spatial analyses relevant to a land selection process (e.g. proximity to transportation stations). The services are lacking a proper scientific foundation for spatial multi-criteria selection of land parcels. Moreover, the alternative land parcels are dynamically created by new sellers. However, the services are hard-coded based on a set of predefined land parcels and fail to support evaluation of the parcels added by new owners. To overcome these limitations, the study proposes a geo-marketing decision support system by integrating geographic information system (GIS) and multi-criteria decision analysis (MCDA) techniques into the web platform. The GIS-based MCDA tools provide appropriate analytical approaches and platforms to support decision makers/people in spatial decision-making processes based on individual values and interests. The paper demonstrates the implementation of a geo-marketing decision support system for land selection and purchase processes in district no. 22 of Tehran. [ABSTRACT FROM AUTHOR]

The main objective of this research is to model the uncertainty associated with GIS-based multi-criteria decision analysis (MCDA) for crop suitability assessment. To achieve this goal, an integrated approach using GIS-MCDA in association with Monte Carlo simulation (MCS) and global sensitivity analysis (GSA) were applied for Saffron suitability mapping in East-Azerbaijan Province in Iran. The results of this study indicated that integration of MCDA with MCS and GSA could improve modeling precision by reducing data variance. Results indicated that applying the MCS method using the local training data leads to computing the spatial correlation between criteria weights and characteristics of the study area. Results of the GSA method also allow us to obtain the priority of criteria and identify the most important criteria and the variability of outputs under uncertainty conditions for model inputs. The findings showed that, commonly used primary zoning methods, without considering the interaction effects of variables, had significant errors and uncertainty in the output of MCDA-based suitability models, which should be minimized by the advanced complementarity of sensitivity and uncertainty analysis. [ABSTRACT FROM AUTHOR]

Wind power plays a pivotal role in China's endeavor to achieve its ambitious emissions reduction targets. However, the current research on wind energy potential lacks standardization, making it arduous to compare wind potential across different regions and match energy supply and demand accurately. To address this issue, this study developed a geographically-constrained multi-criteria decision analysis (GIS-MCDA) model to estimate China's wind energy potential at a resolution of 1 km2. The GIS-MCDA model is reconstructed from a geospatial perspective using 11 finely-grained metric indicators, significantly improving the accuracy of estimates. Moreover, this study proposes a research paradigm for wind energy potential that can serve as a reference for other countries and regions. The results demonstrate that China possesses a wind energy development potential of 4.6 TW at a height of 100 m, including 4.1 TW of onshore wind power potential and 0.5 TW of offshore potential. The abundant resources can assist China in achieving its zero-carbon emissions goal. However, the abundant wind energy resources in the "Three North" region of China do not match the current electricity demand. Conversely, the southeast coastal region presents significant potential for offshore wind power, heralding a new opportunity for wind power development. By depicting the deployment potential of wind power, this study provides more precise estimates, establishes a research paradigm for wind energy potential, enhances researchers' comprehension of wind energy development, and provides a replicable, scalable, and quantifiable wind energy potential measurement platform for effective planning of renewable energy. • A GIS-MCDA model is reconstructed using 11 finely-grained metric indicators. • Precise wind energy evaluation at kilometer-level granularity with high spatial and temporal resolution. • A systematic research paradigm for quantifying wind energy potential that is promotable, replicable, and referenceable. • China has the potential to develop 4.6 TW of wind energy at 100 m, including 4.1 TW onshore and 0.5 TW offshore. [ABSTRACT FROM AUTHOR]

Abstract The Web-based Multicriteria Spatial Decision Support Systems (MC-SDSS) enhance the collaborative/participatory spatial decision making by providing the relevant GIS-based MCDA (Multicriteria Decision Analysis) tools for active participation/collaboration. Typically, regular/novice decision makers need to acquire knowledge from expert decision makers in a participatory decision making process. Over the last decade or so, significant research efforts have been made to use Web-based GIS-MCDA tools for collaborative spatial decision making. However, these efforts as the collaborative decision making tools lack a knowledge sharing mechanism or framework that allow for exchange and sharing of decision knowledge between decision makers (decision makers' agents). In the case of providing knowledge sharing capabilities by these tools, exchange of decision knowledge relies on decision makers' common sense to manually interpret the meanings of each other's knowledge and use the right ones. To address these limitations, this study proposes an ontology-based multi-agents approach for knowledge sharing in a collaborative MC-SDSS. The decision makers' agents committed to the ontology can interoperate and exchange decision knowledge with intended and unambiguous meanings. Highlights • This paper facilitates knowledge sharing in collaborative spatial decision analyses. • The study uses an ontology-based multi-agents approach for knowledge sharing. • The similarity between the knowledge elements is assessed based on lexical and contextual information. [ABSTRACT FROM AUTHOR]

Land reform is identified as a key tool in fostering development in South Africa. Twenty years after the advent of democracy in South Africa, the land question remains a critical issue for policy makers. Several frameworks have been put in place by the government to identify land that is strategically located for land reform. However, many of these frameworks are not well aligned and not objective in defining strategically located land for land reform and often lead to unsustainable land use management practices. This has hampered the government’s land reform initiative in promoting agricultural land reform and food security. Accordingly, there is a need to develop a decision support tool that facilitates the identification of strategically located land for land reform. This study proposes the use of geographic information systems (GIS) and multi-criteria decision analysis (MCDA) to develop a strategically located land index (SLLI) to identify land suitable for agricultural land reform. Participatory workshops and the group analytical hierarchy process were utilised to identify and weigh criteria used in computing the SLLI. The results indicate that land that is suitable for agricultural land reform is scarce, and there are also competing needs on the highly suitable land for agriculture. The study demonstrates that GIS and MCDA are invaluable tools in facilitating evidence-based decision-making for land reform and sustainable land use management practices. The SLLI is not the panacea to land identification; there is also need to appreciate the contested nature of land in South Africa. [ABSTRACT FROM AUTHOR]

Cycling has been recognized as one of the solutions to urban transportation challenges. In 2013, Singapore has announced the National Cycling Plan to significantly increase the cycling infrastructure and promote cycling across the entire country by 2030. Given Singapore's land constraints, planning the most effective cycling network is critical. Moreover, there has been growing pressure to incorporate public participation in planning decisions. In order to achieve ideal planning outcomes and greater transparency in planning, multiple criteria and the perspectives of different stakeholders need to be considered. This paper proposes a Geographical Information System-based multi-criteria decision analysis (GIS-MCDA) framework for the support of cycling paths planning in Singapore. It is positioned to address the lacuna in the literature that is dominated by western-centric case studies and a fixation on only infrastructural and objective factors in the planning of cycling paths. The proposed cycling paths planning support framework will be implemented in Woodlands Planning Area (WPA). The primary research questions are about where to build cycling paths in WPA and whether/how the cycling paths to be built will change based on different stakeholders' preferences. The cycling paths planning support framework is able to incorporate different stakeholders' preferences into various scenarios, hence can improve the engagement between stakeholders and contribute to greater transparency in Singapore's cycling paths planning. The limitations and further applications of the framework is also discussed. [ABSTRACT FROM AUTHOR]

Tackling fuel poverty has become an increasingly important issue on many European countries’ political agendas. Consequently, national governments, local authorities and NGOs have established policies and programmes to reduce the fuel poverty vulnerability of households. However, evaluations of such policies and programmes show that they barely reach those who are most in need. The reasons for this failure are diverse and include fuel poverty measurement metrics, local scale data availability and policy design. This raises the question of how fuel poor homes can be more effectively identified and targeted to ensure that limited local and national budgets are used to benefit those who most need help. Area-based approaches, which pinpoint spatial units highly affected by fuel poverty due to their specific characteristics, offer an opportunity for creating more tailored policies and programmes. In this study, the author developed a GIS-MCDA (Multi-Criteria Decision Analysis), using an AHP (Analytical Hierarchy Process) and applied the approach to the German city of Oberhausen. The overall issue of fuel poverty was broken down into three vulnerability dimensions (heating burden, socio-economic and building vulnerability), the relative importance of fuel poverty criteria and the dimensions were evaluated by experts, and an overall Fuel Poverty Index was created to assess the relative fuel poverty vulnerability of 168 urban neighbourhoods. The analysis offers insights into the spatial pattern of fuel poverty within a city and thus provides an opportunity to channel efforts towards households in those neighbourhoods most in need. It also demonstrates that a trade-off between ecological and social targets should be considered in the development of future policies for tackling fuel poverty. [ABSTRACT FROM AUTHOR]

• Analytical Hierarchy Process proves a flexible method to assess vulnerability and risk. • Risk experience, wildland-urban interface and tree traits drive vulnerability. • Considering socio-economic drivers and several assets broadens the analysis. • Stakeholders confirmed the relevance of participative assessments using MCDA. • We identify vulnerable locations not yet subject to hazard. The Mediterranean region is routinely affected by forest fires, with adverse consequences on ecological, infrastructural, and socioeconomic assets. In a context of climate change, it is crucial for fire prevention and suppression to be able to identify locations where assets are most at risk, due to environmental, physical or socio-economic reasons. Besides, this knowledge needs to be developed together with operational services and field experts to ensure their application. So far, fire risk research has largely focused on fire behavior, effects, and model simulation. In this article, we show how the concept of vulnerability can provide a flexible and relevant framework for assessing fire risk and be evaluated using a spatial multicriteria decision analysis method (MCDA) - the Analytical Hierarchy Process (AHP)- based on both quantitative data and expert judgment gathered through a participative approach. We focus on South-Eastern France, a region characterized by high economic and environmental stakes and heavily affected by wildfires. We develop a series of spatialized indicators using ecological, land-use and sociodemographic data which we aggregate to produce vulnerability maps for three categories of assets: population, ecosystems and infrastructures. An ex-post workshop was organized with field experts to put both the approach and results into discussion. Results reveal significant differences in indicators' perceived contributions to risk and vulnerability and enable appraising the contribution of sociodemographic factors, often overlooked in the literature. We also reveal differences in spatial patterns across both vulnerability subcomponents and exposed assets, helping identify primary and secondary vulnerability hotspots and underlying drivers. Consideration of multiple subcomponents of risk and vulnerability may help local decision makers prioritize how and where measures should be implemented, while the use of MCDA favors experience and knowledge sharing and among stakeholders while providing a basis of discussion. [ABSTRACT FROM AUTHOR]

Identifying proper location of a biomass facility is a critical issue due to biomass materials characteristic geographically spread. This paper presents a GIS-MCDA approach with WLC and sensitivity analysis to optimize suitable areas of a biomass facility. The approach can be used to solve renewable energy planning problems in sustainable environment context. The results’ analysis with 16 criteria concludes the most suitable locations close to agricultural and forestal areas, 8.64% of the Spanish case study region. Therefore, the results denote that the approach proposed could be used for decision-makings for renewable energy management policy in various governmental and industrial sectors. [ABSTRACT FROM AUTHOR]

Spatial planning for green stormwater treatment technologies, known as Water Sensitive Urban Design (WSUD), is a ‘wicked’ problem which can greatly benefit from the application of Planning Support Systems (PSS). Our review of currently existing WSUD-PSS shows that WSUD is approached from three perspectives: hydrological, urban planning and water governance. As a form of best (urban) planning practice, WSUD requires PSS that regard these technologies as an integral part of the urban form. We argue that suitability of location for WSUD has two sides: ‘WSUD needs a place’ and ‘a place needs WSUD’. No framework or PSS exists that frames WSUD from both sides of suitability. We propose such a suitability framework, building on evidence from literature. Our review found no comprehensive tool or strategy incorporating all relevant factors for suitability analysis. Our proposed framework addresses this gap, and serves as the basis for rigorous WSUD-PSS. [ABSTRACT FROM AUTHOR]