Spatial Multi-criteria Analysis Research Articles

Spatial Multi-Criteria Analysis and Least-Cost Path on The Highway Route Planning: A Case Study of Bawen – Yogyakarta Highway, Indonesia

Infrastructure planning ideally not only considers the geotechnical aspects and physical conditions of the infrastructure development location but also must be able to support regional development. One kind of spatial analysis technique which has capabilities to integrate various regional characteristics associated with its suitability for a particular use is spatial multi-criteria analysis. By using Bawen-Yogyakarta Toll Road Plan as a case study, this research is intended to apply route planning that takes into account regional characteristics, through the involvement of Spatial Multi-Criteria Analysis, Analytic Hierarchy Process, and Least Cost Path analysis. The analysis results then compared with the government preferred route to see its advantages and disadvantages. The results show that the generated route from the analysis has several advantages over the government preferred route, while also having some shortcomings. The advantages of route analysis results compared to government preference routes include: better able to avoid earthquake and landslide-prone areas, better support to the preservation of protected areas, has more areas with flat to gentle topography, and have smaller additional construction cost as the consequences of intersection with existing roads, rivers and railways, In terms of affected land-use, generated route also has minimum negative impacts on the sustainability of agricultural land in the study area. The shortcomings of the analysis result are: not yet able to avoid flood and volcanic eruptions-prone areas as well as government’s preferences route, higher land acquisition cost estimation, and less support for industrial and tourism activities in the research area. Improvement of analysis methods, data, and cost assessment strategy is needed to obtain better results and more appropriate modeling and analysis, in order to support regional infrastructure planning and development.

Recreation vs conservation in Natura 2000 sites: a spatial multicriteria approach analysis

Because of its high naturalness and biodiversity, Natura 2000 network (N2K) is becoming increasingly important for recreational opportunity, providing benefits in terms of physical and mental health through outdoor experiences. Nature-based tourism (NBT) is tourism based on the natural attractions of an area: the greater the recreation opportunities, the greater the attractiveness to people. N2K sites are suitable places to favour the development of the NBT, as N2K is not a system of strict nature reserves from which all human activities would be excluded. The approach to conservation and sustainable use of N2K areas is much wider, largely centred on people working with nature rather than against it. To do this, a balance between nature-based tourism development and ecological protection should be reached. In this work, we propose the application of spatial multicriteria analysis, in order to analyse multiple conflicting dimensions interacting over time, considering in particular both criteria related to NBT development and ecological protection. The aim of the work was to analyse the opportunities of Nature-based tourism development in N2K in Umbria, one of the Regions of central Italy, which consists of 102 sites. In particular, the work considered the conditions of biodiversity conservation, flora and fauna, as well as the leisure opportunities provided by the sites and the pressure produced by human activities on them. A spatial multicriteria analysis has been carried out to understand the potentiality of the N2K at territorial level. In particular, the proposed methodology would like to support decision makers in the identification of N2K sites in which NBT activities could be improved and developed, in a balanced way according to biodiversity conservation. Results show, according to preferences set by three different kinds of experts, that only a small bunch of N2K sites could be suitable for an increase of the NBT.

Dry port location optimization to foster sustainable regional development

A saturação das zonas de influência portuária acentua impactos ambientais e conflitos socioespaciais, demandando alternativas logísticas. O porto seco possibilita a descentralização de atividades aduaneiras, de manuseio e armazenagem, mitigando parte dos problemas, além de estimular a economia na região onde é inserido. Dessa forma, a sua localização é crucial para a eficiência dos sistemas logísticos de importação e exportação. O objetivo deste trabalho foi avaliar a distribuição espacial dos portos secos em Minas Gerais e identificar os melhores locais para uma nova instalação. A metodologia agregou dois métodos reconhecidos de definição locacional: a Análise Multicritério Espacial e o Problema de Localização-Alocação. O primeiro, em consonância com as práticas mais atuais no planejamento de transporte, integrou critérios sociais, ambientais e técnicos. O segundo, adotou o resultado da análise multicritério como demanda ponderada e aplicou uma meta heurística para solução do problema de otimização. Os resultados evidenciam a disparidade regional e a deficiência de infraestruturas logísticas no norte de Minas. Todos os cenários apontam a região de Montes Claros como candidata à instalação de um porto seco. A possibilidade de conciliar sociedade, ambiente e economia no planejamento de infraestrutura foi demonstrada.

Terrorism vulnerability assessment in Java Island: a spatial multi-criteria analysis approach

Terrorism is one of the Indonesia’s national security threat. The attack mostly happens in Java Island, attracted by the dense population, also because the island is a center for economic and governance. The spatial pattern of terrorism attack shows correlations with the spatial density of the targeted attack. Therefore, this study assesses the spatial vulnerability of Java Island using a spatial multi-criteria analysis (SMCA). The main attributes analyzed were the density of the past terrorist attack, arrested area, police/military facility, government facility, business center, densely populated area, and church, determine that in the case of a terrorist attack is strongly affected by the attraction of the area.

Waste to Land (W2L): A novel tool to show and predict the spatial effect of applying biosolids on the environment

There is a complex relationship between land-use, the environment, food production and quality. Regulatory and non-regulatory interventions, such as application of biosolids to agricultural land, are often undertaken at a field- or farm- level and the aggregated effects across farms and regions are difficult to understand, predict, and communicate to others both spatially and temporally. The aim of this paper was to introduce Waste to Land (W2L). W2L is a novel, holistic tool that combines spatial data analysis methods, multi-criteria analysis, and numerical models to detect areas for optimum biosolids application and to predict the spatial effect of applying biosolids to land. A robust framework was developed first to chart the effects of applied biosolids on the environment and, potentially, on the human food chain. Selecting cadmium as a prototype contaminant, a conceptual model was designed as the basis to define the workflow for the tool. Using the open-source, statistical language R and freely available data, the operation and outputs from the tool were demonstrated at a national scale in Scotland, UK. The results provided fresh intelligence on the ability of the Scottish Landbank to receive biosolids and on the spatial effect of landspreading biosolids, to facilitate the exchange of information between stakeholders, and to enable decision-making in a context of spreading biosolids on farmland.

Coastal Flooding Risk Assessment Using a GIS-Based Spatial Multi-Criteria Decision Analysis Approach

Coastal areas are expected to be at a higher risk of flooding when climate change-induced sea-level rise (SLR) is combined with episodic rises in sea level. Flood susceptibility mapping (FSM), mostly based on statistical and machine learning methods, has been widely employed to mitigate flood risk; however, they neglect exposure and vulnerability assessment as the key components of flood risk. Flood risk assessment is often conducted by quantitative methods (e.g., probabilistic). Such assessment uses analytical and empirical techniques to construct the physical vulnerability curves of elements at risk, but the role of people’s capacity, depending on social vulnerability, remains limited. To address this gap, this study developed a semiquantitative method, based on the spatial multi-criteria decision analysis (SMCDA). The model combines two representative concentration pathway (RCP) scenarios: RCP 2.6 and RCP 8.5, and factors triggering coastal flooding in Bandar Abbas, Iran. It also employs an analytical hierarchy process (AHP) model to weight indicators of hazard, exposure, and social vulnerability components. Under the most extreme flooding scenario, 14.8% of flooded areas were identified as high and very high risk, mostly located in eastern, western, and partly in the middle of the City. The results of this study can be employed by decision-makers to apply appropriate risk reduction strategies in high-risk flooding zones.

A GIS-BASED MULTI-CRITERIA ANALYSIS ON CROPLAND SUITABILITY IN BORNUUR SOUM, MONGOLIA

Abstract. Agriculture is one of the most critical sectors of the Mongolian economy. In Mongolia, land degradation is increasing in the cropland region, especially in a cultivated area. The country has challenges to identify new croplands with sufficient capacity for cultivation, especially for local decision-makers. GIS applications tremendously help science in making land assessments. This study was carried out in Bornuur soum, Mongolia. The goal of this study to estimate that best suitable area for supporting crop production in Bornuur soum, using a GIS-based multi-criteria analysis (MCA) and remote sensing. GIS-based multi-criteria analysis (MCA) has been widely used in land suitability analyses in many countries. In this research, the GIS-based spatial MCA among the Analytical Hierarchy Process (AHP) method has employed. The approach was enhanced for each criterion which as soil, topography and vegetation. The opinions of agronomist experts and a literature review helped in identifying criteria (soil data, topography, water and vegetation data) that are necessary to determine areas suitable for crops. The detailed cropland suitability maps indicate that 46.12 % is highly suitable for cropland, 34.68 % is moderate suitable, 13.64 % is marginal suitable and 5.56 % is not suitable. The MCA and AHP tools play an essential role in the multi-criteria analysis. Therefore, the results of these methods allow us to estimate an appropriate area for cultivation in Bornuur soum, Tuv province. The crop suitability method implies significant decisions on different levels and the result will be used for cropland management plan to make a decision. It is an integral role in agricultural management and land evaluation. Future research should further develop this method by including socio-economic (potential citizens for agriculture, current crop growth, water resource, etc.) and environmental variables (rainfall, vegetation types, permafrost distribution, etc.) to obtain specific results. However, it could be also be applied for a single crop type (mainly barley, wheat and potato) in Mongolia.

A Decision Process for Optimizing Multi-Hazard Shelter Location Using Global Data

Mitigating the effects of natural hazards through infrastructure planning requires integration of diverse types of information from a range of fields, including engineering, geography, social science, and geology. Challenges in data availability and previously siloed data have hindered the ability to obtain the information necessary to support decision making for disaster risk management. This is particularly challenging for areas susceptible to multiple types of natural hazards, especially in low-income communities that lack the resources for data collection. The data revolution is altering this landscape, due to the increased availability of remotely sensed data and global data repositories. This work seeks to leverage these advancements to develop a framework using open global datasets for identifying optimal locations for disaster relief shelters. The goal of this study is to empower low-income regions and make resilience more equitable by providing a multi-hazard shelter planning framework that is accessible to all decision-makers. The tool described integrates spatial multi-criteria decision analysis methods with a network analysis procedure to inform decisions regarding disaster shelter planning and siting.

The reintroduction of Castor fiber in Piedmont (Italy): An integrated SWOT-spatial multicriteria based approach for the analysis of suitability scenarios

The Castor fiber or Eurasian beaver can change its habitat by building dams and creating ponds. For this reason, Castor fiber is known as an “ecosystem engineer” for aquatic and riparian environments. Despite its ecological importance, at the beginning of the 20th century the population was reduced to only 1200 beavers in Europe and Asia, due to uncontrolled hunting. Recently, some reintroductions and translocations have partly re-established the population. In Italy, however, the beaver disappeared in the 16th century and no action has been taken despite the recommendation of the Council of Europe to perform a feasibility study.This research evaluates beaver reintroduction and identifies suitable areas in Italy and, in particular, in the Piedmont region. In order to achieve this, a SWOT analysis combined with a Spatial Multicriteria Analysis was performed. Firstly, the zoological and ethological aspects concerning this rodent were studied, as well as the historical reasons that led to its disappearance in Italy and near extinction in Eurasia. Secondly, Strengths, Weaknesses, Opportunities and Threats (SWOT) of the territory were identified for beaver reintroduction. The SWOT analysis was implemented, as the starting point for the spatial multicriteria analysis. Thirdly, the Multicriteria Spatial Decision Support System (MC-SDSS) was structured into two criteria, i.e. Potentials and Criticalities, representing the spatialization of strengths and weaknesses. The final result of the MC-SDSS is a map showing suitable areas for beaver reintroduction in Piedmont. This map is the weighted sum of the maps of criticalities and potentialities, performed through a set of GIS operations and weighted through a pairwise comparison of criteria by experts.The analysis was conducted for the Piedmont region, but the integrated approach and the set of criteria can also be applied in other regions. Moreover, this mixed-method approach takes into account the characteristics necessary for the choice of suitable beaver habitats and also includes economic and social aspects. Therefore, it is an improvement on the Habitat Suitability Index (HIS), generally used in reintroductions. The aspects considered in the analysis are fundamental for the future development of a shared action plan, which considers both technical and social motivations and acts for the long-term on a wide area.

Modeling predictive suitability to determine potential areas for establishing wind power plants in Sri Lanka

Many of renewable energy sources significantly contributing for fulfill increasing energy demand while reducing greenhouse gas emissions in all around the world. Among various source of renewable energy source, wind energy has been identified as one of the main potential, economically viable and environment friendly energy sources particular in Sri Lanka. Due to the geographical position of Sri Lanka, it has a good condition for wind energy exploitation. However, the optimal sites for install wind power plants are specific, because wind potential is dependent on the several geographical factors. This study introduced geospatial approaches to determine potential areas for wind power plants. For that, five decision factors; Elevation, Wind density, Land use, restricted area, Proximity to road network were extracted from the existing Geodatabases were used and their relative weights were estimated by applying Spatial Multi-Criteria Analysis methods in GIS environment. Results mainly concluded that, Sri Lanka has sufficient wind power potential in 13,130 km2 (20%) of the land extent to maximize the renewable energy contribution in the national power supply. In addition, most of the potential areas were found in the sparsely populated coastal belt of the country. The proposed model has precious wind power predictive capacity. Hence, developed model could be used to estimate the wind power capacity in predicted areas. It is recommended to install wind power plants in possible areas to achieve more than half of the renewable energy target for 2030 by through wing power plants to generate electricity.

Geospatial Tools for Suitable Assessment of Small Holder Irrigation Water, towards Increased Food Production and Poverty Eradicationin Nigeria: A Case of Jos East LGA. Plateau State

Irrigation is very crucial for sustaining global food security and poverty reduction, especially during off season food production in developing countries. Plateau state in recent years is exploring extensive irrigation schemes to meet up overwhelming national demands of exotic temperate crops and vegetables. The local farmers relyon seasonal streams and abandoned mine ponds for irrigating their crops, but water in these sources are exhausted easily, leading to increased yield losses. This research explores geoinformation methods to map, select and quantify suitable areas to site reservoirs for sustainable Small Holder Irrigation in Jos East LGA of Plateau state as a case study. Spatial Multi Criteria Analysis (SMCA) and other quantitative tools were employed for the spatial modeling and subsequent analysis. The results revealed that 11 sites are highly suitable in Jos East. Volumetric analysis was carried out to estimate potential water collection capabilities of these reservoirs, and the water prospect is estimated between ~172,660 m3 to ~13,929,275 m3, this was based on the calculated depth, and surface area of the prospective reservoirs. Subsequently, this model can be replicated in other parts of Plateau state, Nigeria and Africa with similar environmental, climatic conditions and water demands. We propose small reservoirs with simple engineering techniques to serve poor local communities in developing countries, which can alleviate poverty and enhance sustainable agricultural production. The initiative is in line with FAO’s and World Bank’s programs and recommendations, and which can promote pragmatic solutions and guide project allocations in line with Sustainable Development Goals (SDGs).

Multi-criteria spatial screening and uncertainty analysis applied to direct-use geothermal projects

ABSTRACT The focus of this work is general methods for prioritization or screening of project sites based on the favorability of multiple spatial criteria. We present a threshold-based transformation of each underlying spatial favorability factor into a continuous scale with a common favorability interpretation across all criteria. We compare several methods of computing site favorability and propagating uncertainty from the data to the favorability metrics. Including uncertainty allows decision makers to determine if seeming differences among sites are significant. We address uncertainty using Taylor series approximations and analytical distributions, which are compared to computationally intensive Monte Carlo simulations. Our methods are applied to siting direct-use geothermal energy projects in the Appalachian Basin, where our knowledge about any particular site is limited, yet sufficient data exist to estimate favorability. We consider four factors that contribute to site favorability: the thermal resource described by the depth to 80°C rock, natural reservoir productivity described by rock permeability and thickness, potential for induced seismicity, and the estimated cost of surface infrastructure for heat distribution. Those factors are combined in three ways. We develop favorability uncertainty propagation and sensitivity analysis methods. All methods are general and can be applied to other multi-criteria spatial screening problems.

A geospatial model for allocating potential urban–industrial zones in a desert: Case study Matrouh, Egypt

Planning for new urban–industrial communities in deserts is a main objective of the Egyptian government. Allocation of such communities should comply with both environmental protection and sustainable consumption of resources. The current study explores such approach, through mapping potential zones for new urban–industrial communities in Matrouh Governorate, Western Desert, Egypt. A spatial multidisciplinary approach has been adopted to facilitate zoning based on satellite data, spatial decision support systems and a geospatial model. Landsat 8, Shuttle Radar Topography Mission in addition to several thematic maps were input for the geospatial model. Three sub-models were created for three themes (visions), two of which were created using spatial multicriteria analysis (land resources and infrastructures), and the third sub-model, namely environmental protection, was created using a binary model. The analytical hierarchy process method was applied to assign relative weights for the resources theme, while the rank-sum method was used for the infrastructure theme. The three sub-models were aggregated to produce the suitability index for three zoning visions. Such index was classified and the highest three suitability values in each suitability index were extracted being the most optimum zones. Such zones are found in the northeastern part of the study area. The most optimum zones amounted to 23,863 km2, 47,707 km2 and 25,474 km2; equivalent to 14.8%, 29.7% and 15.9% for the first, second and third visions, respectively. The resultant maps can be used in site selection, allocation, decisions and for planning new urban communities.

A spatial multi-criteria analysis approach for planning and management of community-scale desalination plants

The rapid deterioration of the groundwater quality in the Gaza Strip-Palestine has increased reliance on community-scale brackish-water desalination plants (CBDPs). However, the escalating numbers of CBDPs is associated with poor operation practices and exhibit various adverse impacts, while the existing regulatory framework of this sector is still lacking the necessary tools for identifying and mitigating these impacts. The current study employed a GIS-based Multi-criteria Analysis (MCA) approach to plan and manage the existing and proposed CBDPs in Gaza Strip, Palestine. The criteria account for the various possible effects including: level of chloride and nitrate in the groundwater, variation in the water-table depth, population density, potential production capacity of CBDPs and operation hours, distance to the pumping wells, sea shoreline, and point-source contamination sites. The results showed that the locations of around 53% of the existing CBDPs are unsuitable; and the CBDPs exhibit potential risks to the environment. The study revealed that 65% of the total area of Gaza Strip would be unsuitable for CBDPs operating in a capacity above the current average. This highlights the significance of regulating the operational conditions of the existing CBDPs according to their geographical location and considering different alternatives of supply-demand schemes.

Landslide susceptibility mapping for the Black Sea Region with spatial fuzzy multi-criteria decision analysis under semi-humid and humid terrestrial ecosystems

Landslide, which is a process experienced not only at the local and catchment scales but also the regional and national scales, adversely affects the natural environment, including the flora and fauna, and the socio-economic well-being of human communities. The main aim of the present study was to generate a landslide susceptibility mapping model for the semi-humid and humid terrestrial ecosystems of the Black Sea Region. The modelling was done by using a spatial multi-criterion analysis (SMCA) method based on the integration of fuzzy environment and geographical information system (GIS) techniques and also the use of the AHP approach by incorporating 9 environmental indicators and 27 sub-indicators. In order to allocate a weighting value for each indicator, the fuzzy-AHP approach was applied to determine efficiently sensitive levels of importance for the indicator. In addition, precipitation climatology was included in detail with respect to the temporal and spatial distribution of rainfall in the study area. It was determined that approximately 33% of the research area includes high or very high susceptibility to landslide, whereas about 37% of the research area is in the low or very low susceptibility classes. Most highly or very highly susceptibility areas were located in the western and central Black Sea regions. In conclusion, this study provides an alternative perspective a useful alternative method for landslide susceptibility mapping through the incorporation of fuzzy sets through AHP in conjunction with the Buckley approach in modelling.

The suitability level of bike-sharing station in Yogyakarta using SMCA technique

Yogyakarta is experiencing the increasing number of population (1,13%) from 2014 to 2017 that influences the rising number of motorized vehicles. Besides, it is also led by the easiness to access vehicles ownership in Yogyakarta. In 2017, Yogyakarta ranked fourth as the most congested city in Indonesia that indicates the importance of changing the transportation mode from private vehicles to public transportation. Through the mission of Yogyakarta to strengthen urban planning and environmental sustainability, it is necessary to implement green transportation along with transport demand management to reduce the disadvantages of road congestion in the city. Hence, bike-sharing system can be an option that provides new alternative mobility. However, the important thing to manage bike-sharing systems is the optimal location of bike-sharing station. In Yogyakarta, there is already a bike-sharing systems but only in 12 stations. This research aims to identify the best location for siting bike-sharing station based on spatial analysis using Analytical Hierarchy Process (AHP) and Spatial Multi-Criteria Analysis (SMCA). According to the analysis, the urban core of Yogyakarta and its surrounding are the most suitable location for bike-sharing station.

The politics of multifunctional green infrastructure planning in New York City

Cities are expanding green infrastructure and presenting it as a panacea for social and environmental challenges, but the reality is more complex and inherently political. We need to advance our understanding of these politics, which I divide into the politics of green infrastructure performance and planning. I use New York City as a case study to begin unpacking these politics of planning. New York City's green infrastructure program focuses on water quality, but aims to provide other sustainability benefits. How are potential benefits prioritized, factored into planning, and what are the implications of these decisions? I examine these questions by combining spatial analyses, survey, and interview data. I survey local stakeholders about the relative importance of six benefits of green infrastructure (managing stormwater, reducing social vulnerability, increasing access to green space, improving air quality, mitigating the urban heat island effect, and increasing landscape connectivity). Second, I use spatial multi-criteria analysis to identify priority neighborhoods for green infrastructure based on those criteria. I examine tradeoffs and synergies between criteria and compare modeled priorities with existing green infrastructure locations. Interviews with key decision-makers provide a deeper understanding of planning processes. Results illustrate why spatial planning represents a critical challenge for green infrastructure planning.

Spatial patterns and environmental risks of ringnet fishing along the Kenyan coast

Ringnet fishing began in the early 20th century and is practised worldwide, mainly to target nearshore pelagic species. The method was introduced to Kenya’s coastal waters by migrant fishers from Tanzania. However, the impacts of this fishing gear remain poorly assessed. We assessed the spatial distribution of ringnet fishing effort and its possible effects on ecosystem components, such as coral reefs, marine megafauna and marine protected areas, on the south coast of Kenya. We tracked 89 ringnet fishing trips made from December 2015 to January 2016 and used spatial multicriteria analysis to determine hotspots of possible environmental risks. The results showed that habitat type and bathymetric profile influenced the spatial distribution of ringnet fishing effort. Mixed seagrass and coral habitats had the highest concentration of the effort. Most of the habitats in the study area were moderately exposed to the impacts of the ringnet fishery. The study identifies high-risk areas that require spatial measures to minimise possible environmental risks of the gear both to habitats and to endangered sea turtles.

A multi-criteria spatial analysis using GIS to evaluate potential sites for a new border gate on Turkey's Syria frontier

After the internal disturbance in Syria in 2011, many Syrian refugees migrated to Turkey progressively, and the Turkish Government provided humanitarian aid to people in Syria. These incidents caused a huge amount of density on current border gates. Also, increasing potential terrorist attacks and growing frontier infringements also create a need for a new border gate on Turkey's Syria frontier. Thus, a four-step hybrid solution approach is developed for this problem. This approach starts with determination of selection criteria; then, the spatial database of these criteria is created by using a geographical information system. In the third step, the DEMATEL technique is applied to assign importance levels to the criteria. Lastly, MULTIMOORA technique is used to rank the potential sites. The results indicate that, recommended potential sites are more suitable than current border gates. This paper can serve as a scientific-base while selecting the optimal site for border gates. [Received: 8 February 2019; Revised: 1 July 2019; Accepted: 7 August 2019]

A multi-criteria spatial analysis using GIS to evaluate potential sites for a new border gate on Turkey's Syria frontier

A multi-criteria spatial analysis using GIS to evaluate potential sites for a new border gate on Turkey's Syria frontier