Search Results (53)

The augmentation of clean energy usage is necessary to achieve Australia’s net zero emission target. New South Wales has proposed renewable energy zones (REZs) to align with this target and aims to retire coal-based energy production plants. Site selection criteria for REZs are more focused on technical and economic benefits rather than social and environmental considerations. This study aims to create a comprehensive suitability of optimal locations for renewable energy production that will minimize social disruption and maximize production rates, aligning with Sustainable Development Goal 7. To approach this gap, this study adopted a GIS-based multi-criteria evaluation method to combine understated variables such as agriculture and farmland, Aboriginal heritage, and natural conservation. Literature reviews have helped to weigh criteria based on their priority to social, economic, and environmental benefits, supporting both government targets and community concerns. This research explores the use of flexible criteria weighing in the context of a collaborative geo-design framework. This evidenced-based approach aims to assist planners in advocating for current legislation and developing strategies for coordination among private and government agencies, environmental groups, and stakeholders to minimize land-use conflicts. This study found that conducting land suitability analysis using a geo-design framework offers a collaborative strategy that can assist in mapping areas of significance for preserving community and environmental integrity. Such a collaborative approach can improve stakeholder participation in the decision-making process, with a particular focus on reaching net-zero emissions. Full article

Land utilization—a crucial resource for human survival and development—reflects the outcomes of intricate interactions between human communities and their respective environments. The Jianmen Shu Road Heritage Area presents both opportunities and challenges in terms of protection and development. Any alterations in its land use and landscape patterns directly impact the sustainable development of the regional environment and heritage sites. In this study, we considered three cities along the Jianmen Shu Road, analyzed the evolution characteristics of land use and landscape patterns from 2012 to 2022, and used the multi-criteria evaluation–cellular automata-Markov (MCE-CA-Markov) model to predict the land use and landscape patterns in 2027. The results show the following: (1) From 2012 to 2022, forest land was at its greatest extent, the growth rate of forest land increased, the loss rate of cropland increased, and impervious land continued to expand. (2) From 2012 to 2022, the degrees of fragmentation in cropland, impervious land, and grassland increased; water area had the highest connectivity; forest land had the lowest connectivity; and barren land had the highest degree of separation. The degree of fragmentation and connectivity of the landscape patterns decreased, the degree of complexity increased, and landscape diversity increased and gradually stabilized. (3) Predictions for 2022–2027 indicate that forest land, impervious land, grassland, and barren land will increase, whereas cropland and the water area will decrease. The growth rate of grassland will increase, the loss rates of cropland and water area will decrease, and the growth rates of impervious land and forest land will decrease. (4) Further predictions for 2022–2027 indicate that the density and complexity of the grassland edge will decrease, whereas the fragmentation and complexity of the remaining patches will increase. The degree of fragmentation, complexity, connectivity, and separation of landscape patterns will increase significantly, whereas landscape diversity will remain stable. This study deepens our understanding of how land use and landscape patterns change in the heritage area from a long-term perspective that involves both the past and future. Such research can provide crucial information for tourism management, heritage protection, and spatial planning in the heritage area and, thus, has important management implications for the study area and similar heritage areas in other regions. Full article

Green infrastructure (GI) is increasingly prioritised in landscape policy and planning due to its potential to benefit ecosystems and enhance wildlife conservation. However, due to the uneven distribution of protected areas (PAs) and the fragmentation of habitats more generally, multi-level policy strategies are needed to create an integrated GI network bridging national, regional and local scales. In the province of Almeria, southeastern Spain, protected areas are mainly threatened by two land use/land cover changes. On the one hand, there is the advance of intensive greenhouse agriculture, which, between 1984 and 2007, increased in surface area by more than 58%. On the other hand, there is the growth of artificial surfaces, including urban areas (+64%), construction sites (+194%) and road infrastructures (+135%). To address this challenge, we present a proposal for green infrastructure deployment in the province of Almeria. We combine Geographic Information Systems (GISs) and multi-criteria evaluation (MCE) techniques to identify and evaluate suitability for key elements to be included in GI in two key ways. First, we identify the most suitable areas to form part of the GI in order to address vulnerability to degradation and fragmentation. Second, we propose 15 ecological corridors connecting the 35 protected areas of the province that act as core areas. The proposed GI network would extend along the western coast of the province and occupy the valleys of the main rivers. The river Almanzora plays a leading role. Due to its remoteness from the coast and its climatic conditions, it has not attracted intensive greenhouse agriculture and urban development, the main drivers of the transformation and fragmentation of traditional land uses. Around 50% of the area occupied by the proposed corridors would be located in places of medium and high suitability for the movement of species between core areas. Full article

In this study, we tried to gauge the trends of localization preferences for residential buildings among young adults. The pragmatic dimension of these studies is important in the process of real estate investment, where a location can be expressed using indicators and statistical data and then, using maps, indicate preferred areas for living in a small town. The aim of our research was to examine and visualize the preferences of young people for living locations in relation to access to services. We conducted an online survey using a Likert scale to determine which services and amenities are most important for young residents. Using multi-criteria evaluation (MCE) methods and their formulas, we calculated the attractiveness coefficient of the location of residential buildings, which we propose to call the RBLAF (Residential Building’s Localization Attractiveness Factor). The results of this research are maps: qualitative–quantitative with point symbols for the structure of services and quantitative isochromatics showing the preferences of potential future investors in real estate. Full article

The present paper deals with the application of a Multi-Criteria Evaluation approach (MCE) to carry out site selection for Concentrating Solar Power plants (CSP). As this work demonstrates, multi-criteria analysis can provide a technical–scientific decision making tool capable of justifying choices in a clear and coherent manner, particularly in the renewable energy sector. The site selection for CSP is a complex topic. Although it has a significant impact on project costs, this issue has received little attention in the literature. A practical methodology based on a multi-criteria analysis is presented. Several potential sites called alternatives are compared, using a combination of Multi-Criteria Decision Making methods (MCDM) such as the Analytical Hierarchy Process (AHP), Scoring method and Benayoun and Tergny Algorithm. The relevance of this combination is examined through a case study of Algeria, a country with a high potential for CSP projects. The comparative analysis is carried out for a set of alternatives (Kenadsa, Abdala, Naâma and Hassi R’Mel). The assessment of alternatives and their ranking are discussed according to several scenarios, both for approaches used to estimate the criteria weights (AHP, weights affected in different manner) and for the two MCDM methods chosen for the present study. The methodology provides a better understanding of the site selection process for CSP, which would encourage their large-scale deployment on the green electricity market. Full article

Geographic Information System-based Multi-Criteria Evaluation (GIS-MCE) methods are designed to assist in various spatial decision-making problems using spatial data. Deriving criteria weights is an important component of GIS-MCE, typically relying on stakeholders’ opinions or mathematical methods. These approaches can be costly, time-consuming, and prone to subjectivity or bias. Therefore, the main objective of this study is to investigate the use of Machine Learning (ML) techniques to support criteria weight derivation within GIS-MCE. The proposed ML-MCE method is explored in a case study of urban development suitability analysis of the City of Kelowna, Canada. Feature importance values drawn from three ML techniques–Random Forest (RF), Extreme Gradient Boosting (XGB), and Support Vector Machine (SVM)–are used to derive criteria weights. The suitability scores obtained using the ML-MCE methodology are compared with Equal-Weights (EW) and the Analytical Hierarchy Process (AHP) approach for criteria weighting. The results indicate that ML-derived criteria weights can be used in GIS-MCE, where RF and XGB techniques provide more similar values for criteria weights than those derived from SVM. The similarities and differences are confirmed with Kappa indices obtained from comparing pairs of suitability maps. The proposed new ML-MCE methodology can support various decision-making processes in urban land-use planning. Full article

Protected areas are referred to around the world as the basis of conservation strategies. Designation of marine protected areas (MPAs) is to preserve marine biodiversity and protect species, habitats in the seas, and oceans. The simulated annealing algorithm (SAA) with other algorithms (swap iterative improvement, normal followed by two step, two step iterative improvement, and normal iterative improvement) in MARXAN conservation solutions software and the multi-criteria evaluation (MCE) method were used to locate MPAs in the Southern Caspian Sea. Then, four methods were examined for site selection that include: (1) Simulated annealing algorithm, (2) MCE with zonal land suitability (ZLS), (3) MCE with compactness and contiguity, and (4) combined method of multi-criteria evaluation with spatial constraints and a simulated annealing algorithm (improved MCE). In the MCE method, we applied different weighted scenarios to locate MPAs. The criteria for determining the desired regions of MPAs included 12 factors gathered in three groups, including: (1) Ecological criteria (distribution of fish Huso huso, Acipenser persicus, Acipenser stellatus, Rutilus frisii kutum, and Alosa braschnikowi; location of coastal protected areas, distance from coastal rivers (Coastline), distance from estuaries and deltas); (2) Physical criteria (distance from the coast, shore sensitive areas); and (3) Socio-economic criteria (distance from densely populated coastal cities, distance from industries near the coast). The results of comparing the algorithms in MARXAN 4.0.6 software showed that the simulated annealing algorithm has a better ratio of border-length/area than other algorithms. Also, the combined method of MCE (improved MCE) selects the best protection patches in terms of location, taking into account the seascape ecology metrics (e.g., patch compactness, edge density, normalized entropy, area metric for patches). Moreover, the results of the comparison of four methods for proposing MPAs based on seascape metrics showed that the combined method of MCE considers a protection network with more contiguity and compactness than the simulated annealing algorithm. The use of seascape ecology can help to preserve and create larger and denser patches in the arrangement of protective areas, because such a selection of protective areas is nature-inspired and can be more bold and appropriate in the course of conservation planning. Full article

In arid and hyper-arid areas, groundwater is a precious and rare resource. The need for water supply has grown over the past few decades as a result of population growth, urbanization, and agricultural endeavors. This research aims to locate groundwater recharge potential zones (GWPZs) using multi-criteria evaluation (MCE) in the Wadi Qena Basin, Eastern Desert of Egypt, which represents one of the most promising valleys on which the government depends for land reclamations and developments. These approaches have been used to integrate and delineate the locations of high groundwater recharge and the potential of the Quaternary aquifer in the Wadi Qena basin. After allocating weight factors to identify features in each case based on infiltration, land use/land cover, slope, geology, topology, soil, drainage density, lineament density, rainfall, flow accumulation, and flow direction, these thematic maps were combined. The results of the GIS modeling led to the division of the area’s groundwater recharge potential into five groups, ranging from very high (in the western part) to very low (in the eastern part of the basin). The zones with the best prospects for groundwater exploration turned out to be the alluvial and flood plains, with their thick strata of sand and gravel. The groundwater recharge potential map was validated using data from the field and earlier investigations. The promising recharging areas show high suitability for soil cultivation. The results overall reveal that RS and GIS methodologies offer insightful instruments for more precise assessment, planning, and monitoring of water resources in arid regions and anywhere with similar setups for groundwater prospecting and management. Full article

With the growing demand for aquatic products, aquaculture has become a prominent means of meeting this demand. However, the selection of suitable sites for aquaculture remains a key factor in the success of any aquaculture operation. While various methods exist for site selection, geographic information system (GIS)-based multi-criteria evaluation (MCE) methods have emerged as the most widely utilized approach to identifying potential aquaculture sites. Following the guidelines of the preferred reporting items for systematic reviews and meta-analyses (PRISMA), this paper presents a systematic review and meta-analysis of GIS-based MCE methods used in aquaculture sites selection. The objective of this study is to offer a comprehensive overview of existing research in this field and develop a general model for selecting sites for fish and shellfish aquaculture. The main findings indicate a growing number of studies utilizing GIS-based MCE in aquaculture site selection in recent years, with Asia being the leading continent in terms of publications in this domain. Among the journals publishing in this field, the Aquaculture journal stands out as the top publisher. Using consistent criteria across the reviewed studies, two models have been generated, each consisting of four sub-models: water quality, soil quality, infrastructure, and socioeconomic factors; and topography, environment, and physical parameters. These models can aid future researchers and assist decision-makers in identifying optimal locations for aquaculture development. Full article

Land use/cover change (LUCC) detection and modeling play an important role in global environmental change research, in particular, policy-making to mitigate climate change, support land spatial planning, and achieve sustainable development. For the time being, a couple of hybrid models, such as cellular automata–Markov (CM), logistic–cellular automata-Markov (LCM), multicriteria evaluation (MCE), and multicriteria evaluation–cellular automata–Markov (MCM), are available. However, their disadvantages lie in either dependence on expert knowledge, ignoring the constraining factors, or without consideration of driving factors. For this purpose, we proposed in this paper a new hybrid model, the logistic–multicriteria evaluation–cellular automata–Markov (LMCM) model, that uses the fully standardized logistic regression coefficients as impact weights of the driving factors to represent their importance on each land use type in order to avoid these defects but is able to better predict the future land use pattern with higher accuracy taking Hefei, China as a study area. Based on field investigation, Landsat images dated 2010, 2015, and 2020, together with digital elevation model (DEM) data, were harnessed for land use/cover (LUC) mapping using a supervised classification approach, which was achieved with high overall accuracy (AC) and reliability (AC > 95%). LUC changes in the periods 2010–2015 and 2015–2020 were hence detected using a post-classification differencing approach. Based on the LUC patterns of the study area in 2010 and 2015, the one of 2020 was simulated by the LMCM, CM, LCM, and MCM models under the same conditions and then compared with the classified LUC map of 2020. The results show that the LMCM model performs better than the other three models with a higher simulation accuracy, i.e., 1.72–5.4%, 2.14–6.63%, and 2.78–9.33% higher than the CM, LCM, and MCM models, respectively. For this reason, we used the LMCM model to simulate and predict the LUC pattern of the study area in 2025. It is expected that the results of the simulation may provide scientific support for spatial planning of territory in Hefei, and the LMCM model can be applied to other areas in China and the world for similar purposes. Full article

Land use planning is a science that specifies the optimized use of land based on ecological and socioeconomic characteristics. In many parts of Iran, the selection and management of land use (development, especially) is performed regardless of land capability, which causes disinvestment and reduces the environmental capacity. The main objective of this study is to evaluate and reform the ecological model of urban, rural, and industrial development in the study area. This study was conducted in Fasa County in the southern part of Iran, and the investigated methods included Weighted Linear Combination (WLC) or Multi-Criteria Evaluation (MCE), with two views, without limitation and with limitation, and the proposed geometric mean method through the integration of maps in GIS. The results showed that the geometric mean evaluation model (with kappa = 0.69) is the best and easiest compared to other models in the estimation of environmental capability. It should be mentioned that the lowest precision (with kappa = 0.59) between the methods was observed in the MCE method without a limiting factor, and it is clear that the limiting factor has a decisive role in assessing ecological capability and increasing accuracy. It is concluded that the proposed geometric mean method, due to the simplicity and high accuracy of the calculations, has a significant contribution to increasing efficiency and reducing the costs associated with the assessment of ecological capability. Full article

Spring water is important for human consumption, domestic use, agricultural activities, and ecotourism in the Buenavista de Cuéllar Aquifer (ABC), southern Mexico. The objective of this research was to assess the health risk from fecal coliforms, as well as the non-carcinogenic risk to human health for different age groups, by studying the oral and dermal routes. The analysis of the cartography of high-priority springs (the result of Multicriteria Evaluation (MCE)), access routes, and knowledge of the areas with high social insecurity risk enabled the selection of 20 springs to be sampled. In situ parameters were measured, major ions, fecal coliforms, and Potentially Toxic Elements (PTE). The non-carcinogenic health risk results indicated a higher risk by the oral route in children (average Hazard index (HI) value of 0.6371) and a higher risk by the dermal route in adults (average HI value of 1.2378). The highest dermal risks are in the south-southeast of the study area. On the other hand, the assessment of health risks due to fecal coliforms resulted in a medium risk for the dry season and a high risk for the rainy season. The results of this research will serve as a key reference for the management and protection of springs in order to preserve human health. Full article

As global temperatures rise, flooding and storm surges caused by extreme weather threaten people’s safety and nations’ development. Nature-based Solutions (NBS) are practical actions to support resilience to reduce flood risk and are applied in many countries. As the NBS approach mentions, small check dams made of gabion and wood can retain runoff and temporarily create detention basins to reduce the magnitude of floods and provide additional water resources. However, previous dam suitability research emphasized the criteria selection and decision method evolution, which costs time on the complex calculation and does not fit the NBS small dams. This research aims to optimize the site selection workflow of small dams in vulnerable informal settlements by utilizing Remote Sensing (RS), Geographic Information Systems (GIS), and Multi-Criteria Evaluation (MCE). Several thematic layers, such as land use, river density, building distance, vegetation cover index, slope, and elevation factors, were chosen to identify the suitable area in Mataniko catchment, Honiara. More importantly, it provides a more efficient model builder that can be replicated in ArcGIS 10.8, which contributes to visualizing scenarios of the inundation area of small dams at different heights. As a result, this study tested up to 35 potential small dams with 2.5 and 5 m wall height in the flood-prone Vara Creek and selected nine small dams with 5 m height and 15 small dams at 2.5 m as the best locations according to the volume and area. Overall, it is an efficient tool for designers to communicate with different stakeholders and applies to other developing countries facing frequent floods. Moreover, it provides a prototype and evidence of NBS action to address the flood issue. Full article

The push for urban development and the rapid increase in population have left many historic urban cores vulnerable and subject to deterioration. SDG-11 is often mentioned as the goal in UNDP regeneration, revitalization, and preservation projects regarding historic urban sites around the globe. The goal emphasizes 10 targets that are complex in nature and require closer inspection regarding their interconnectedness when being utilized in real-world scenarios. The current study explores the complexities of the decision-making process in planning urban regeneration projects concerning targets of SDG-11. The study uses a Multi-Criteria Evaluation (MCE) method to investigate how and to what significance the targeted criteria were used in planning for two UNDP urban regeneration project zones in Cyprus. These cases have a complex cultural and socio-political dynamic and pose high contextual significance for the region; therefore, many of these targets are critical in achieving more sustainable regeneration projects. The data collection was done by critically examining the projects’ documentation and conducting interviews with experts involved in the two projects. The data is controlled for internal consistency and anomalies. The study makes its case by comparing the different approaches implemented in these two projects and how effective they were in achieving SDG-11 targets. Full article

Modeling and predicting land use/cover change (LUCC) and identifying its drivers have been a focus of research over the past few decades. In order to solve the problem of land resource degradation in typical pastoral areas, reveal the temporal and spatial evolution characteristics of LUCC, and the contradiction between man and land in sustainable development, we analyze the Gurvanbulag area of Bulgan province, Mongolia, where grassland degradation is relatively serious. The LUCC data in 2000, 2010 and 2019 were obtained through interpreting human-computer interaction. On this basis, the same binary logistic regression (BLR) results were input into the multi-criteria evaluation analytic hierarchy process (MCE_AHP) of CLUE-S and CA_Markov models. The Current Trends (CT) and Ecological Protection (EP) development scenarios were used to predict the temporal and spatial evolution characteristics of LUCC in 2030 and 2040. The results show: (1) both models can effectively simulate the LUCC in 2019, and the CLUE-S model was significantly better than the CA_Markov model. (2) From 2000 to 2019, the LUCC in this region was dominated by a decrease in water and the growth of grassland and other land, indicating that the region is at the risk of land resource degradation. (3) In a multi-scenario development study, by 2030 and 2040, both models predicted that the EP development scenario is more effective in protecting the local ecological environment and it is easier to achieve the sustainability of land resources, than the CT development scenario. Combined with local policy demands and the prediction results of restraining land resource degradation, CLUE-S was significantly higher than the CA_Markov model, indicating that in typical pastoral areas, the former is more in line with the need for sustainable development of the local ecological environment than the latter. Full article