Agricultural land suitability analysis (ALSA) for crop production is one of the key tools for ensuring sustainable agriculture and for attaining the current global food security goal in line with the ...Sustainability Development Goals (SDGs) of United Nations. Although some review studies addressed land suitability, few of them specifically focused on land suitability analysis for agriculture. Furthermore, previous reviews have not reflected on the impact of climate change on future land suitability and how this can be addressed or integrated into ALSA methods. In the context of global environmental changes and sustainable agriculture debate, we showed from the current review that ALSA is a worldwide land use planning approach. We reported from the reviewed articles 69 frequently used factors in ALSA. These factors were further categorized in climatic conditions (16), nutrients and favorable soils (34 of soil and landscape), water availability in the root zone (8 for hydrology and irrigation) and socio-economic and technical requirements (11). Also, in getting a complete view of crop’s ecosystems and factors that can explain and improve yield, inherent local socio-economic factors should be considered. We showed that this aspect has been often omitted in most of the ALSA modeling with only 38% of the total reviewed article using socio-economic factors. Also, only 30% of the studies included uncertainty and sensitivity analysis in their modeling process. We found limited inclusions of climate change in the application of the ALSA. We emphasize that incorporating current and future climate change projections in ALSA is the way forward for sustainable or optimum agriculture and food security. To this end, qualitative and quantitative approaches must be integrated into a unique ALSA system (Hybrid Land Evaluation System - HLES) to improve the land evaluation approach.
•Methods used in agricultural land suitability analysis (ALSA) strengths and limitations•Uncertainty and sensitivity analysis inclusion in ALSA modeling process•Climate change analysis inclusion in ALSA task•Frequently used predictors in ALSA modeling including biophysical, socioeconomic and management practices
The use of wind turbines can help progress towards economic and technological development, lower rates of fossil fuel consumption, decreased greenhouse emissions, and reduced side-effects of climate ...change. A successful mechanism for developing renewable energy worldwide is the guaranteed purchase of electricity generated from renewable energy sources. Accordingly, this study aims to integrate Geographic Information System-based Multi-criteria Evaluation (GIS-MCE) models with economic frameworks to estimate the optimal purchasing price for electricity produced by wind turbines. A total of 13 criteria maps were used and integrated using Ordered Weighted Averaging (OWA) as a type of MCE model. The criteria were initially normalized based on the minimum, and maximum values and weights were assigned to each criterion, using the Best-Worst method. The OWA model identified optimal site locations at various decision risk levels. The economic efficiency of wind turbines and the potential purchasing price of electricity from turbines were also assessed in terms of Net Present Value (NPV). The results show that Ardabil and Southern Khorasan provinces had the most significant areas in the very-suitable class for wind turbine installation (small/large scale). The purchasing prices for wind-generated electricity ranged from 0.047 to 0.182 US$ for large wind farms and 0.074 to 0.384 US$ for small wind plants. The highest electricity produced from large wind farms was found in Maragheh.
•This paper presents a GIS-MCE model to assess the suitability of locations for wind power plants.•It shows a GIS-MCE-based economic model for price estimation of wind energy generated electricity.•The study integrates expert weights, criteria maps, and risk degrees in the price estimation model.
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•The first LUC risk changes data of China was generated with a resolution of 100 m.•The highest LUCs conversion frequency was from no conflict to moderate one (35 %).•LUCs conversion ...frequency of big cities are generally stable and positive.•Tourism development in ecologically fragile regions may aggravate LUCs.
Under the background of rapid urbanization, a series of urgent problems have emerged in China, such as tightening resource constraints and intensifying land use conflicts (LUCs). Based on the perspective of agricultural production – residents’ life – ecological security, this study took China as the study area, applied the multi-criteria evaluation analysis method to diagnose the LUC type based on spatial statistics, coupling relationship matrix, comprehensive conflict index, and spatial autocorrelation model, then divided the LUC risk changes into seven patterns, and analyzed their spatial evolution characteristics. The results demonstrated that the scale of competition for scarce land between agriculture, construction, and ecology increased by 3.4 % over the last 20-year period. High conflict zone was mainly located in the eastern plains, which was also the main distribution zone of agriculture-construction conflict, while the agriculture-ecology conflict zone was mainly located in the west. Over time, LUC risk grade changed in 14.3 % of the study area, with the largest area of transitions from no conflict to moderate conflict (34.78 %). High intensification zone coincided almost entirely with ecologically fragile regions of the Midwest, underscoring the critical importance of LUC perspectives in ecological conservation. We provided a new perspective for the study of LUC changes and a scientific reference for realizing sustainable land use management in China and other regions.
•Twelve different internally finned absorbers are examined in the LS-2 PTC.•The thermal enhancement and the pressure drop are the main calculated parameters.•Four evaluation criteria are used for ...determining the optimum fin geometry.•The fin with 10mm length and 2mm thickness is found to be the optimum case.•The optimum fin presents 0.82% thermal efficiency enhancement compared to smooth case.
Among the solar concentrating technologies, parabolic trough collector (PTC) is the most mature and cost-effective technology for medium and high-temperature levels (150–400°C). This paper investigates the utilization of internally finned absorbers in LS-2 PTC module for various operating conditions. Twelve different longitudinal fins are tested and compared with the smooth case. The analysis is performed with SolidWorks Flow Simulation, using a validated model by literature results. Generally, it is proved that both greater length and thickness lead to higher thermal enhancement and to higher pressure losses. Various methods are presented for evaluating together the thermal efficiency or Nusselt number enhancement versus the increase in pressure drop or in the friction factor. Taking into consideration four different criteria, the absorber with 10mm fin length and 2mm fin thickness is found to be the overall optimum case. For this case, the thermal efficiency is enhanced about 0.82%, the Nusselt number increase 65.8%, while the friction factor and the pressure losses are about the double compared to the smooth case.
•Develop a method to identify priority areas for green infrastructure.•The method applied in Ghent and reveals new site for future green infrastructure.•The Method can be deployed for other cities.
...Urban surface water floods pose growing threats in urban areas, which cause not only massive physical water disturbance, but also loss of human lives, destruction of social and economic infrastructures and disorder of society. The number and scale of flood damage in urban areas will continue to increase in the next several decades due to global trend in urbanization and climate change. Despite the extensive construction of grey infrastructures, many cities in the world remain vulnerable to surface water flooding, especially during the extremely weather events. Since the 1990s, green infrastructure has developed as an alternative and sustainable approach to mitigate flood hazard in urban areas. Despite the great effectiveness of urban green infrastructures in alleviating storm water runoff, there is comparatively little research for planners and designers to determine an appropriate strategy for green infrastructure planning. To address this gap, we propose a GIS-based multi-criteria evaluation method to identify the priority areas to site green infrastructure, based on five criteria: 1) storm-water runoff mitigation; 2) social flood vulnerable group protection; 3) flood sensitive area road infrastructures protection; 4) flood sensitive area buildings protection and 5) environmental justice. The weights of the five criteria are defined by the Analytic Hierarchy Process. We focus particularly on mitigating urban surface water flooding risk and demonstrate how the method can be applied using a case study of Ghent.
Several factors contribute to on-going challenges of spatial planning and urban policy in megacities, including rapid population shifts, less organized urban areas, and a lack of data with which to ...monitor urban growth and land use change. To support Mumbai's sustainable development, this research was conducted to examine past urban land use changes on the basis of remote sensing data collected between 1973 and 2010. An integrated Markov Chains–Cellular Automata (MC–CA) urban growth model was implemented to predict the city's expansion for the years 2020–2030. To consider the factors affecting urban growth, the MC–CA model was also connected to multi-criteria evaluation to generate transition probability maps. The results of the multi-temporal change detection show that the highest urban growth rates, 142% occurred between 1973 and 1990. In contrast, the growth rates decreased to 40% between 1990 and 2001 and decreased to 38% between 2001 and 2010. The areas most affected by this degradation were open land and croplands. The MC–CA model predicts that this trend will continue in the future. Compared to the reference year, 2010, increases in built-up areas of 26% by 2020 and 12% by 2030 are forecast. Strong evidence is provided for complex future urban growth, characterized by a mixture of growth patterns. The most pronounced of these is urban expansion toward the north along the main traffic infrastructure, linking the two currently non-affiliated main settlement ribbons. Additionally, urban infill developments are expected to emerge in the eastern areas, and these developments are expected to increase urban pressure.
► Mumbai has been undergoing exceptionally dynamic land cover changes. ► Land use mapping and simulation is used to predict urban extent in 2020 and 2030. ► Urbanization continues and coincides with the transportation systems. ► Apart from in-fill developments, the emergence of new urban nuclei is forecasted.
•Propose an optimization and evaluation integrated framework.•Establish a Mixed Integer Non-linear Programming optimal planning model.•Conduct multi-objective optimization by Ɛ-constraint ...method.•Identify Pareto-optimal solution through three decision making methods.•An Analytic Hierarchy Process and Gray Relation Analysis combined evaluation.
This study proposes an integrated framework for planning distributed energy system with addressing the multi-objective optimization and multi-criteria evaluation issues simultaneously. The framework can be decomposed into two stages. At the optimization stage, the system design and dispatch are optimized considering multiple objectives by Ɛ-constraint method. Three decision making approaches are applied to identify the Pareto optimal solution. At the evaluation stage, a combined Analytic Hierarchy Process and Gray Relation Analysis method is proposed to evaluate and rank various optimal solutions when different objectives and cases are considered. Two stages of work are integrated by introducing the baseline conditions. As an illustrative example, an optimal planning model for a solar-assisted Solid Oxide Fuel Cell distributed energy system is proposed by Mixed Integer Non-linear Programming approach firstly. Then, the system is applied to different cases considering two types of buildings located in three climate zones. The obtained optimal solutions are further evaluated by the proposed multi-criteria evaluation method. Therefore, the overall optimal system design and dispatch strategy, as well as the best demonstration site can be identified comprehensively considering multiple objectives. In general, the results have verified the effectiveness of the proposed framework.
•Healthcare waste disposal management is a challenge faced by healthcare providers.•Waste disposal location planning is a difficult task due to complexities in the evaluation process.•We propose a ...new best-worst method with interval rough numbers for location decisions.•A new interval rough numbers Dombi-Bonferroni method is used to process imprecise data.•A case study is presented to demonstrate the applicability and exhibit the efficacy of the method.
Healthcare waste disposal management is one of the biggest day-to-day challenges faced by healthcare providers and urban municipalities. Poor management of healthcare waste can cause serious problems for healthcare workers, patients, and the general public. Healthcare providers and urban planners usually struggle with the action of locating an appropriate waste disposal center in a municipal area. Healthcare waste disposal location planning is a difficult task due to complexities inherent in the evaluation of alternative locations according to multiple and often competing criteria. We propose a new best-worst method with interval rough numbers (IRN) for healthcare waste disposal location decisions. A new IRN Dombi-Bonferroni (IRNDBM) means the operator is also introduced to process the rough data because of the unavailability of precise information. A case study at a private hospital in Madrid is presented to demonstrate the applicability and exhibit the efficacy of the proposed multi-criteria evaluation method.
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