Spatial Multi-criteria Decision Analysis Research Articles

Analysis of the suitability for ecotourism in Beira Baixa region using a spatial decision support system based on a geographical information system

Ecotourism can contribute to the conservation of environmental values, as well as to the development of positive synergies between agents in the tourism sector, tourists and the local population. The growing interest in tourism offers with low environmental impact, which support the local economy, translates into a competitive advantage for low‐density territories. On the basis of this principle, the scope of the present study is intended to evaluate the potential of the existing natural and rural features in the Beira Baixa region, located in the central interior of Portugal, which can anchor the creation of sustainable tourism products. Despite the undeniable interest in carrying out studies to determine an aggregate suitability index for the development of ecotourism using spatial multicriteria decision analysis (MCDA), there are still no studies carried out in Portugal. The identification of areas suitable for the development of ecotourism, and their constraints, was carried out on the basis of the integration of nine criteria using the analytic hierarchy process (AHP) in a geographical information system (GIS) environment. The results obtained reveal that the region has high suitability for the practice of ecotourism activities, given its important natural heritage. This study was innovative as it shows the ecotourism potential based on a diversity of criteria as an aid to public administration agents with functions in planning, territorial management and management of support mechanisms for the tourist sector. The use of the landscape diversity criteria, which had not yet been tested in previous studies, proved to be important in determining the ecotourism potential of the region, together with the landscape value based in the importance of the Montado agrosystem, which supports a variety of sustainable tourist activities. The information produced in the study may be useful for the design of new policies for valuing natural resources through tourism.

Agricultural land suitability classification and crop suggestion using machine learning and spatial multicriteria decision analysis in semi-arid ecosystem

Agricultural land suitability classification and crop suggestion using machine learning and spatial multicriteria decision analysis in semi-arid ecosystem

Spatial multi-criteria decision analysis for the selection of sentinel regions in tick-borne disease surveillance

BackgroundThe implementation of cost-effective surveillance systems is essential for tracking the emerging risk of tick-borne diseases. In Canada, where Lyme disease is a growing public health concern, a national sentinel surveillance network was designed to follow the epidemiological portrait of this tick-borne disease across the country. The surveillance network consists of sentinel regions, with active drag sampling carried out annually in all regions to assess the density of Ixodes spp. ticks and prevalence of various tick-borne pathogens in the tick population. The aim of the present study was to prioritize sentinel regions by integrating different spatial criteria relevant to the surveillance goals.MethodsWe used spatially-explicit multi-criteria decision analyses (MCDA) to map priority areas for surveillance across Canada, and to evaluate different scenarios using sensitivity analyses. Results were shared with stakeholders to support their decision making for the selection of priority areas to survey during active surveillance activities.ResultsWeights attributed to criteria by decision-makers were overall consistent. Sensitivity analyses showed that the population criterion had the most impact on rankings. Thirty-seven sentinel regions were identified across Canada using this systematic and transparent approach.ConclusionThis novel application of spatial MCDA to surveillance network design favors inclusivity of nationwide partners. We propose that such an approach can support the standardized planning of spatial design of sentinel surveillance not only for vector-borne disease BDs, but more broadly for infectious disease surveillance where spatial design is an important component.

“Analysis of School Infrastructure Potential as Temporary Evacuation Centers During Emergency Disaster Conditions in Palu and Surrounding Areas”

The earthquake that occurred in Central Sulawesi province on September 28, 2018, devastated parts of Palu City, Sigi Regency, and Donggala Regency. The earthquake and tsunami caused damage to various facilities and infrastructure, resulting in a significant number of casualties. To minimize the risk of casualties during disasters, a rescue strategy is needed, one of which is providing evacuation centers in disaster-prone areas. Therefore, it is necessary to identify which areas can be proposed as temporary evacuation sites during disasters. This research aims to assess the benefits of school infrastructure by examining the suitability of school infrastructure when utilized as temporary evacuation centers. The recommended locations consider the availability of toilets, classrooms, schoolyard area, and service radius. The weighting criteria use Spatial Multi-Criteria Decision Analysis (SMCDA) with the Weighted Overlay method. The analysis is carried out using ArcGIS Pro software, and the weighting of each criterion/layer uses the Analytical Hierarchy Process (AHP) method, considering the criteria of classroom availability, schoolyard area, and service radius. The results of this study indicate that of the 72 schools reviewed, there are 24 schools with a high level of conformity, 19 schools with a moderate level of conformity and 29 schools with a low level of conformity.

Participatory mapping of local stakeholders’ perceptions of nature’s contributions to people in an intensified agricultural area in the Colombian Andes

ABSTRACT Intensification of agricultural land use in traditional Andean production landscapes has led to changes in the provision of nature’s contributions to people (NCP) that can threaten people’s wellbeing. Understanding local stakeholders’ valuation of these NCP is crucial for improving land use decisions. We implemented a spatially explicit and participatory NCP valuation method, using semi-structured interviews and participatory mapping, followed by a spatial multi-criteria decision analysis, to identify priority areas for NCP provision in a highly intensified production landscape in the Colombian Andes. We considered multiple value types, ecological, economical and sociocultural, and the points of view of different actors, orienting this towards decision-making on land use. Our results show that local actors can identify and value a wide range of NCP. However, there are also significant differences between actors. Environmentalists attached special importance to regulating NCP, while agricultural laborers focused more on agriculture-related material NCP. As we expected, tourism entrepreneurs especially valued non-material NCP related to their business experiences. Small-scale farmers tended to put more importance on regulating and non-material NCP than big farmers did. Although there was a consensus between actors as to the importance of natural ecosystems for NCP provision, agricultural actors tended to attach more importance to material NCP in areas deemed important for regulating and non-material NCP by other actors. Our main results confirm the importance of involving different stakeholders in spatial NCP valuation exercises, recognizing their different points of view to help identify possible trade-offs and synergies related to land use.

Geospatial modeling for planning an optimum and least-cost route to link three historical sites in El-Fayoum desert, Egypt

AbstractImproving the accessibility to archaeological sites in a desert is a crucial issue; it enhances the landscape value and helps in achieving sustainable tourism development. El-Fayoum Oasis and Governorate in Egypt, has a unique heterogenic environment that encompasses desert, lakes, agriculture lands, and urban areas. It is quite rich in historical heritage reflected by abundant archaeological and cultural sites, many of which fall in desert zones. A main constraint is the poor or lack of accessibility to such sites. In this study, we designed a geospatial model for planning a sustainable least cost tourist route (path) to link and develop three archaeological sites namely; Madinet Madi, Watfa city and Ummal-Barijat ruins. Spatial multicriteria decision analysis was integrated with the analytical hierarchy process (AHP) and the least cost path modules. Three cost criteria themes were created associated with economic, social and environmental costs. A cost surface and a least-cost path were created for each criterion and for each theme. The themes were combined using weighted linear combination to create four least cost scenarios for the path. Five preference criteria were used to compare the four route scenarios. Results show that the environmental scenario scored first scoring 0.69 while the economy path scores second 0.42, the equal weights path scores third 0.40 and finally the social path comes to be the last having a preference score 0.36. The method is flexible because priority can be changed and adapted according to specifications and site variances. It can be helpful for decision makers and planners in planning routes based on visual maps and priority visions.

Mapping territorial vulnerability to wildfires: A participative multi-criteria analysis

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.

Multi-criteria decision analysis for wind farm location selection in Bahir Dar City and its surroundings, Northwestern Ethiopia

While there is a consensus on the multifaceted advantages of wind farms, only a handful of developing countries harness it to the fullest potential. Among the various factors that contributed to the low development of wind farms in those countries, the dearth of methods for identifying a suitable site is the leading one. Studies conducted elsewhere on wind farm industry identifies criteria such as slope, wind speed, land use/land cover, geology, distance from electric transmission grids, roads, and settlements. However, the relative magnitude of each factor to the optimum location of the wind farm is inadequately examined. This study focuses on the combined use of geographic information systems (GIS) and spatial multi-criteria decision analysis (MCDA) for selecting the most appropriate sites for wind-farm development. Using a pairwise comparison method of the analytical hierarchical process, we computed the relative importance and weight of parameters affecting wind farm sites in a weighted overlay technique. Based on the analysis of pertinent data collected from Bahir Dar City and its surroundings, northwestern Ethiopia, we categorized the study area into five suitability classes ranging from extremely suitable to not suitable. Our result, revealed a spatial pattern of the potential sites suitable for wind farm investments that are economical, environmentally sound, and aesthetically amenable. We recommend replicating the method developed in this study in other areas of developing countries where transitioning to renewable energy sources through windfarm development is sought.

Storm Surge Risk Assessment in Coastal Communities in the Rio Grande Valley: An Application of GIS-Based Spatial Multicriteria Decision Analysis with Analytical Hierarchy Process

Kyne, D., 2023. Storm surge risk assessment in coastal communities in the Rio Grande Valley: An application of GIS-based spatial multicriteria decision analysis with analytical hierarchy process. Journal of Coastal Research, 39(3), 471–483. Charlotte (North Carolina), ISSN 0749-0208. Cameron County, which is located in the Rio Grande Valley, maintains records of storm surges associated with noticeable property damage, fatalities, and injuries. This study investigates storm surge inundation risk in Cameron County using storm surge hazard datasets from the National Oceanic and Atmospheric Administration, along with American Community Survey 2019 block group datasets. Using a GIS-based spatial multicriteria decision analysis with an analytical hierarchy process method, the study estimates that storm surge water levels could be above 6.1 m (20 ft) in category 4 and 5 hurricane events, whereas about 37% of the county's population (159,659 people) could be exposed to floodwater in the event of a category 5 hurricane. The inundation risk map shows that in the event of a category 4 or 5 hurricane, about 28 and 42%, respectively, of county's area could be exposed to a very high level of inundation risk. Because of the destructive power of such storms and their potential consequences, the findings suggest that storm surge risk should not be underestimated. All stakeholders should proactively prepare for potential storm surge events.

Where to leave fossil fuels underground? A multi-criteria analysis to identify unburnable carbon areas in the Ecuadorian Amazon region

Despite the ongoing impacts of climate change around the world, fossil fuels continue to drive the global economy. The socio-environmental impacts of oil development at the local level are widely recognized, especially in high biocultural diversity areas, highlighting the need to develop and implement effective policies that protect both biodiversity and human rights. In consideration of the estimated remaining carbon budget to limit global warming at 1.5 °C, as well as Ecuador’s past attempts at limiting carbon extraction through the Yasuni-ITT Initiative, we adopt a new framework to identify ‘unburnable carbon areas’ with the goal of eventually phasing out fossil fuels. In the Ecuadorian Amazon—one of Earth’s high-biodiversity wilderness areas and home to uncontacted indigenous populations—50 years of widespread oil production is jeopardizing tropical ecosystems. Using the Ecuadorian Amazon as a paradigmatic case study, our research explores the feasibility of implementing energy transition paths based on unburnable carbon areas through spatial multicriteria decision analysis that is based on different approaches to territory management. We modeled interactions between oil development and areas with high biocultural sensitivities using environmental, socio-cultural, and oil-related geospatial information. We found that, for all simulations, concessions that should remain unburnable are mainly located in the south-central sector of Ecuadorian Amazon, surrounding the Yasuní National Park and the intangible zone for uncontacted indigenous people, where no reserves have been identified and oil infrastructure (wells, pipelines, etc) has not been deployed. In the Northern sector, particularly along the ‘Auca’ oil road system, the eventual continuation of fossil production requires best practices to minimize environmental impacts and respect human rights. Our spatial multicriteria approach based on geographical criteria can be replicated in different place contexts to explore different scenarios for effective climate mitigation policies.

A spatial multi-criteria decision analysis framework to reveal vulnerabilities of areas to incidences of street robberies

Violence in public spaces is an aspect of society that demands analysis since this affects social and economic well-being. On setting out to explore the incidence of violence in public areas, this paper brings a multi-methodology framework to associate the exploratory analysis of data on street robberies with a geographic information system (GIS) and a multi-criteria decision analysis (MCDA) model. Our GIS-MCDA framework is based on a Dominance-based Rough Set Approach (DRSA) and induces the decision-maker to learn and understand the spatial, social, and demographic data on crime analysis. As a result, the study area was classified into levels of vulnerability. We found that the social interaction features, bus stops and street robberies are spatially and statistically associated. From the socio-demographic perspective, makeshift houses, the number of people who can read and write and the number of inhabitants were highlighted as dimensions to be considered when associated with crime. Finally, preferences in evaluation of areas of vulnerability tend to be pessimistic. Therefore, the multi-methodology framework makes a holistic analysis of such vulnerabilities and contributes to improve knowledge on urban spaces and how this informs detecting vulnerability to crime.

Potential Sites for Micro-Hydropower Station by using Spatial-MCDA

There are rural areas that still did not receive electricity supply these days. Therefore, an alternative is needed to supply electricity. One of the suitable power supply is the micro-hydropower which is a smaller scale of hydropower. It is suitable for area surrounded by river. It is also clean and green as it is a renewable resource. But, how to find the potential sites for the micro-hydropower station? This study highlighted three (3) criteria in finding the potential sites based on the literature and verified by experts which are slope, water velocity and accessibility. The potential sites can be determined by using Spatial-MCDA which combines Spatial Analysis and Multicriteria Decision Analysis (MCDA). MCDA used to weigh the criteria as they have different weightage in site selection. Spatial Analysis then used the weightage in finding the sites. To test the method, a small rural area in Sarawak, Malaysia which is Kanowit Song was chosen as it is yet to receive electricity supply though it is surrounded by small villages and small-scale vegetable plantation. The study found several potential areas that may be suitable for developing the micro-hydropower station which could supply electricity to area that did not receive one previously.

Spatial multicriteria decision analysis for Walking School Bus target development strategies

IntroductionAround the world there has been a decline in the mode share of walking to school. This is the result of many factors influencing the mode choice decisions of parents for their own journeys to work and their children's journeys to school. Walking School Bus (WSB) has been proved to be an effective strategy that can be an innovation to promote walking to school and combat the ‘vicious circle’ of chauffeuring children to school. This modal switch can thus be a key for enhancing the sustainability of our transportation system and more importantly the health of our next generation. MethodsThis paper proposes an innovative decision analysis model to identify areas for targeting WSB development. By applying spatial multicriteria decision analysis (SMCDA) to existing aggregate data on both work and school trip mode choices and relevant zonal characteristics, the proposed model can help planners and policy decision makers to identify where investments on setting up/enhancing WSBs might be most effective in enabling modal shift. We apply our SMCDA model to a case study in Bradford, UK. We highlight zones/schools within the study area where WSB programmes can be most effective to help realise the full potential of walking to school in health, environmental and social inclusion terms. ResultsSix zones in Bradford have been identified as the areas with the highest potential for the uptake of WSB schemes. These present characteristics that are favourable conditions for walking but with less than ideal current walking mode shares. They have large numbers of school aged children, lower level of work trips by car and higher parents’ availability. ConclusionsOur SMDCA method for WSB target development is highly transferable and can be applied to other cities in the UK or around the world; providing genuine applied value as an apparatus for supporting, informing and systematising the implementation of potentially successful (in engagement and usage terms) WSB schemes.

Landscape Planning Integrated Approaches to Support Post-Wildfire Restoration in Natural Protected Areas: The Vesuvius National Park Case Study

In recent decades in the Mediterranean basin there has been a considerable increase in both the number of wildfires and the extent of fire-damaged areas, resulting in ecological and socio-economic impacts. Protected areas are particularly vulnerable and many characteristics underpinning their legal protection are threatened. Several studies have been devoted to mitigating wildfire risks inside the protected areas, however often only in regard to natural heritage losses. Based on the adaptive wildfire resilience approaches, this work proposes a framework of actions that integrates natural, social and economic components. Starting from the Vesuvius National Park case study, affected by wildfires in 2017, the paper proposes a framework of action, envisaging two main phases: (i) the identification of priority intervention areas, by means of spatial multicriteria decision analysis, and (ii) damage assessment by using a monetary approach to value ecosystem services (ESs). The results identified priority areas where to concentrate economic and material resources, and estimated ecosystems damage, demonstrated ESs losses in areas adjacent to the burnt ones. This work, by integrating the relation between environmental sciences and policy, underpins a medium-long term development planning process. The aim of this work is to support landscape management and planning that includes socio-economic components such as sustainable development measures.

Geospatial analysis for fish farming across Tyrrhenian coast (Tuscany, central Italy)

Aquaculture represents an important source of food and it plays an important role in terms of contribution to economic development. Offshore farming offers considerable advantages, especially in terms of production costs (lower than those of onshore facilities) and of farmed product quality. Suitable areas for aquaculture activities are still available in Italy but are increasingly limited and the demand for new farms is high. The lack of coastal areas allocated to aquaculture and the complex regulatory and legal framework constitutes the major constraints for further development of the sector. Zoning is the process that can allow to sustainably identify and allocate suitable areas for aquaculture. Several aspects, such as effective legal framework and procedures, collection of bio-geochemical, physical and socio-economical information, are crucial for a correct aquaculture zoning process in order to identify the Allocated Zones for Aquaculture (AZAs). In the present work, a spatial multi-criteria decision analysis (SMCDA) was applied for the individuation of potentially suitable marine areas for fish farming across the southern Tyrrhenian coast of Tuscany (Italy). The spatial model was developed by collecting and processing Earth Observation (EO) data, oceanography in situ measurements, and infrastructural and environmental constraints. Excluding areas of constrains, obtained results highlight that 96% of the total investigated area is characterized by medium (62%) and high (34%) suitability. In particular, the highest suitability areas occur in the Talamone gulf and offhore the Argentario promontory at water depth between 15 and 30 m and 30 50m, respectively. Other high suitability areas occur northern of Piombino town between 30 and 100 m depth. Environmental data at higher spatial resolution are needed to improve aquaculture zoning and further process of site selection in order to ensure the sustainability of fish farming in the study area.

Spatial indicator of priority areas for the implementation of agroforestry systems: An optimization strategy for agricultural landscapes restoration

The ecological functions restoration in agricultural areas is a major challenge on a landscape scale. In the specific case of active restoration through Agroforestry Systems (AFS), the absence of a specific direction hinders ecological restoration processes, especially in regions that prefer intensive agriculture. Thus, this study aims to develop a Spatial Indicator of Priority Areas to guide Agroforestry Systems implementation in agricultural landscapes. A spatial multicriteria decision analysis (MDCA) was carried out based on environmental factors: soil, geology and slope (which determine the natural vulnerability of the land) and anthropogenic factors: land use and land cover, forest fragments, potential land use capacity and legal protected areas in rural properties (which reflects human pressure and land use suitability). Subsequently, four priority levels were classified for agroforestry interventions: (1) Low priority; (2) Average priority; (3) High priority; (4) Extreme priority. A final map was made to identify priority areas for landscape recovery in 9 cities located at the mouth of the Mogi Guaçu River Hydrographic Basin, State of São Paulo, Brazil. Considering the natural vulnerability of the land and the multifunctional aspects of the landscape, the scenarios projection allowed a consensus for forest conservation and agricultural suitability perspectives. A final combination of the explored aspects culminated in the spatial indicator, which model foresees 22,300 ha available for urgent actions for restoration, reforestation and sustainable exploitation through agroforestry systems. We emphasize the challenges in reconciling the socioeconomic and ecological functions in the agroecosystem, however, the metric provides a more inclusive and assertive management strategy for natural resources and advances towards the goal of reforestation and implementation of payment for environmental services (PES) schemes.

A three-stage geospatial multi-criteria optimization model for location identification of integrated energy service stations from macro market to micro site

With the proposal and promotion of the carbon neutrality goal, the number of new energy vehicle (NEV) in China is increasing. However, the lack of supporting infrastructure hinders the rapid development of NEV industry. Policy orientation and construction cost show that it is the most realistic initiative to deploy and build integrated energy service stations (IESS) in existing oil–gas stations. The optimal deployment location of IESS is crucial, which is the strategic decision-making issue of its sustainable development. Therefore, a three-stage geospatial multi-criteria model is proposed to solve the site optimization problem of IESS for the first time. The model realizes the quantitative analysis from macro scale (market demand) to micro scale (specific site). Firstly, various analysis elements involved in the three-stage model are identified, including economy, society, population, market, natural environment, geographical conditions, traffic elements, technical impact. Secondly, the sub-models corresponding to the three stages are described in detail: regional traffic attraction sub-model (stage 1), spatial suitability analysis sub-model (stage 2) and alternative multi-criteria decision analysis (MCDA) sub-model (stage 3). Then, taking Beijing as the layout city, an empirical study is carried out to verify the proposed model. The results show that Haidian, Chaoyang and Fengtai District in Beijing have outstanding traffic attraction, and these three districts are determined as the macro areas giving priority to the layout of IESS. The results of suitability analysis identified 13 oil–gas station sites with suitability exceeding the threshold as alternatives. The results of MCDA show that the station sites B1 and B4 in Chaoyang District and A1 and A2 in Haidian District have the highest layout priority. Finally, the results of layout planning under different decision scenarios are given in the discussion part; Sensitivity analysis and comparative analysis prove the stability and reliability of the model. This study not only provides a practical model for the location optimization of IESS, but also provides a technical reference for transportation departments and decision-makers to layout IESS in the city.

Evaluating the potential of marginal lands available for sustainable cellulosic biofuel production in Italy

The European Union aims to provide as much as one quarter of its transportation fuels via biofuels derived from renewable sources by 2030. To put this into perspective, the Italian government has recently established an ambitious goal to support the wider uptake of advanced second-generation biofuels, including cellulosic biofuels for the transportation sector. A sustainable way forward is to grow perennial biomass crops on marginal lands, however the nationwide availability of those lands for lignocellulosic feedstock production remains uncertain. We identify and evaluate the potential of marginal lands in Italy to produce sizeable amounts of biomass for sustainable cellulosic biofuel production while limiting land use conflicts and negative ecological impacts. We applied spatial multi-criteria decision analysis techniques in geographic information systems to ultimately generate spatially-explicit national land suitability and availability maps at a fine resolution (250-m). We selected a broad range of leading cellulosic biomass crops that includes poplar (Populus × canadensis Moench), willow (Salix alba Linnaeus), black locust (Robinia pseudoacacia Linnaeus), giant reed (Arundo donax Linnaeus), and vetiver grass (Chrysopogon zizanioides Linnaeus). Based on marginality criteria, our results suggest that such biomass plantations of perennial grasses and short rotation trees may produce 3.1–27.4 billion liters of cellulosic ethanol per year from 462,265 to 2,811,064 million hectares of available marginal lands. This estimated production may fulfill 7.8–69.1% of Italy's current liquid transportation fuel consumption, constrained by the requirement that each modelled location be within 70 km of a potential cellulosic biorefinery. Collectively, this study provides the cornerstone of efforts to rationally meet Italy's need for renewable fuels in a sustainable low-carbon economy future.

Delineating suitable site for settlement in potential earthquake vulnerable areas using spatial multi-criteria decision analysis in the Sukabumi regency, Indonesia

Delineating suitable site for settlement in potential earthquake vulnerable areas using spatial multi-criteria decision analysis in the Sukabumi regency, Indonesia

A comprehensive framework for assessing navigation risk and deploying maritime emergency resources in the South China Sea

Owing to increasing global maritime accidents, it is highly important to optimize the allocation of limited maritime search and rescue (SAR) resources to protect crew and ships from the catastrophic influences of marine disasters. This study proposes a comprehensive framework for assessing navigation risk and deploying maritime SAR resources. The proposed framework is based on a combination of multiple criteria decision making, geospatial techniques, and game theory. First, a composite risk index is introduced and calculated for the responsibility area of each maritime SAR base by applying spatial multi-criteria decision analysis, which represents the possibility of the occurrence of accidents in the responsibility area. Next, the deployment of SAR resources for each base is likened to the playing of a cooperative game. The risk index value is used to calculate each base's Banzhaf value. Finally, the deployment of SAR resources in all bases is determined based on the Banzhaf values of each base. The northeastern South China Sea was chosen as the area for a case study to verify the usefulness of the proposed framework. The results show that the proposed approach is feasible to plan the allocation of SAR resources and to improve navigation safety.