Identifying optimal sites for vertical farms: a GIS-based multi-criteria analysis

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.

This study presents a Geographic Information System-based (GIS-based) multi-criteria decision analysis for avalanche risk mapping using the Analytical Hierarchy Process (AHP) method in Van province of Turkey. Essential parameters for avalanche occurrence such as slope, elevation, aspect, curvature, and land cover are used in this study. Shuttle Radar Topography Mission (SRTM) digital elevation model (DEM) is used to generate slope, elevation, aspect, and curvature layers; Corine Land Cover data is used as a land cover map, and Landsat 8 OLI satellite imagery was used to extract snow-covered areas. The GIS-based multi-criteria analysis was used to assess the areas’ risk susceptibility; thus, 29% of the study area is classified as having a very low risk, 46% low risk, 18% moderate risk, 5% high risk, and 2% very high risk. The resulting avalanche risk map will create a clear view of the riskiest areas. It can be useful for taking emergency measures in the area and artificially trigger avalanches before they naturally start to form.

Society today is enjoying an unprecedented level of human mobility but is also confronting environmental degradation resulting from fossil fuel consumption and greenhouse gas emissions. The electrification of bus transit systems is recognized as one of the practical solutions to mitigate air pollution and other externalities of increased mobility. However, the implementation of an e-bus system requires the purchase of e-buses and the development of charging infrastructure. To reduce costs and maximize benefits, it is crucial to develop an integrated strategy during the planning stage. This study applies a GIS-based multi-criteria decision analysis approach to determine the candidate bus routes to convert from diesel-powered to electric-driven. This framework appraises not only the characteristics of bus routes but also the possibility of deploying charging infrastructures in bus terminals. Fourteen common criteria are used to evaluate the main considerations of bus electrification, including economic, environmental, and social benefits and costs. The analytic hierarchy process and the technique of order preference similarity to the ideal solution are employed to determine the criteria weights and the route ranking, respectively. The bus network of Twin Cities, MN, U.S., is used as a study case to present the proposed approach. Sensitivity analysis is included to identify the overall top 10 bus routes. The result shows that this method can use widely available open data to select top candidate routes that meet multiple criteria.

The climate crisis is rapidly provoking water scarcity in several areas of the planet, where an exponential growth of the seawater desalination industry is expected. In this context, multiple efforts are currently under development to reduce potential impacts and promote the sustainability of this industry. The selection of a suitable site for a desalination plant is critical to ensure operational continuity and the environmental sustainability of its processes, optimizing the plant’s productive performance and thus safeguarding water security for final users. In this study, we apply a GIS-based Multi-Criteria Analysis (GIS-MCA) approach to explore and assess potential areas suitable for the construction and operation of desalination plants in Chile. Different environmental, social, and technical criteria were evaluated and weighted by expert criteria using the Analytic Hierarchy Process (AHP) methodology. From a total of 114,450 km2 analyzed, only 4.54% of the territory was classified as highly suitable, demonstrating the scarcity of space available to meet the growth expectations for the industry. These results suggest that GIS-based analysis provides a practical solution to determine suitable areas for developing desalination plants, highlighting the need to define priority areas for the sustainable development of the desalination industry in Chile with the required capacity to reach the national water security goals for the following decades.

Liberia is marked by poor and insufficient hydrogeological data due to limited studies coupled with years of civil instability. Although Montserrado County has abundant water resources, lack of adequate knowledge of the available water resources has led to unsustainable groundwater utilization as well as investment losses from drilling unsuccessful boreholes. This research therefore aims at blending remote sensing with GIS-based multicriteria analysis to delineate suitable groundwater potential zones. Remote sensing and conventional data were used to construct a groundwater potential zone (GWPZ) map by integrating lineament and drainage densities, geology, slope and elevation, soil, annual rainfall, land use land cover, and the normalized difference vegetation index (NDVI) maps of the study area. The Analytic Hierarchy Process (AHP) was used in assigning weights to each thematic map, according to its influence on groundwater accumulation, for their integration. The results reveal that slope, lineament density, drainage density, geology, and land use land cover are parameters with the most influence (about 68%) on groundwater recharge within the area. The result also shows that about 10 %, 25 %, 30 %, 25 %, and 10 % of Montserrado County has very high, high, moderate, low zone, and very low groundwater potential zones, respectively. The study, therefore, provides very useful information that may guide the development and management of the groundwater resources within the study area.

Unplanned and haphazard built-up growth due to immense pressure of population is a common problem for maximum cities of developing countries which paves to create urban sprawl by capturing spacious areas of natural environment. For this, selection of suitable places for built-up development by maintaining ecological balance has become inevitable part for proper urban planning. Siliguri planning area, which has witnessed a tremendous growth in built-up features after the 1990, has been chosen for this work to find out best places for future built-up development with minimum effects on different natural features and also calculates the amount of different types of suitability which will be transferred from different land use and land cover categories in near future which is a novelty of this work. The work has been executed through GIS-based multi-criteria analysis, and a total of nine criteria have been taken to locate best places for built-up development. Analytic hierarchy process or AHP has been used to calculate weights of each criterion by using pair wise comparison matrix. Final site suitability map has been prepared with four different classes: high suitable, moderate suitable, less suitable and restricted area and the percentage of land is high in moderate suitable category that is 52.33% which covers the intermediary portion, mainly wastelands and agricultural land of the study area with higher facility of accessibility. Results from this work would be helpful for the planners, stakeholders, policy makers by identifying best locations for the intensive developmental projects in near future.

Satellite remote sensing and GIS-based multi-criteria analysis for the assessment of groundwater potentiality in fractured limestone aquifer: Case study of Maknassy Basin, central Tunisia

GIS-based multi-criteria analysis for potential wastewater aquifer recharge sites

A decision support approach for the selection and implementation of water harvesting techniques in arid and semi-arid regions

Application of GIS-based multi-criteria analysis for site selection of aquifer recharge with reclaimed water

GIS-based Multi-Criteria Decision Analysis is a well-known decision support tool that can be used in a wide variety of contexts. It is particularly useful for territorial planning in situations where several actors with different, and sometimes contradictory, point of views have to take a decision regarding land use development. While the impact of the weights used to represent the relative importance of criteria has been widely studied in the recent literature, the impact of the order weights used to combine the criteria have rarely been investigated. This paper presents a spatial sensitivity analysis to assess the impact of order weights determination in GIS-based Multi-Criteria Analysis by Ordered Weighted Averaging. We propose a methodology based on an efficient exploration of the decision-strategy space defined by the level of risk and trade-off in the decision process. We illustrate our approach with a land use planning process in the South of France. The objective is to find suitable areas for urban development while preserving green areas and their associated ecosystem services. The ecosystem service approach has indeed the potential to widen the scope of traditional landscape-ecological planning by including ecosystem-based benefits, including social and economic benefits, green infrastructures and biophysical parameters in urban and territorial planning. We show that in this particular case the decision-strategy space can be divided into four clusters. Each of them is associated with a map summarizing the average spatial suitability distribution used to identify potential areas for urban development. We also demonstrate the pertinence of a spatial variance within-cluster analysis to disentangle the relationship between risk and trade-off values. At the end, we perform a site suitability ranking analysis to assess the relationship between the four detected clusters.

Urban green spaces play a vital role in enhancing the well-being of communities and mitigating environmental challenges such as air pollution and global warming. Despite their importance, effective models to allocate these green spaces are often overlooked, particularly in developing countries. This study utilises GIS-based Multi-Criteria Analysis and the Analytical Hierarchy Process to recommend optimal locations for green space interventions in Lilongwe City, Malawi, based on nine factors: population density, proximity to roads, slope, Digital Elevation Model (DEM), Normalized Difference Vegetative Index (NDVI), land cover, existing green space, proximity to water bodies, and nitrogen dioxide concentration. The results show that 0.57% (23,776 hectares) of Lilongwe city is highly suitable while 14.50% (604,596 hectares) is unsuitable for green space interventions, where population density was the most determining factor. The suitability varied across the city, with highly suitable areas predominantly located in the southern part. The study highlights the importance of informed decision-making in urban green space planning, setting a standard for equitable access to green spaces and sustainable urban development.

GIS-based multi-criteria analysis of breeding habitats for recolonising species: New Zealand sea lions

The study utilizes a GIS-Based Multi-Criteria Analysis to evaluate the viability of solar, wind, and biomass energy in Iraq, focusing on enhancing the nation's energy independence and meeting international climate objectives. Detailed spatial analysis revealed specific zones suited for the efficient installation of energy power plants. Zones with an energy surplus factor of less than 0.2 are deemed not viable for development, whereas regions with factors less than 0.4 are ideal for harnessing solar, wind, and biomass resources. Furthermore, zones with surplus factors greater than 0.6 are highly recommended for energy projects. Notably, the results show that strategic development of these zones can cater to between 45 % and 68 % of the country total energy demand, potentially reducing the CO2 footprint by 0.5. Moreover, with an increase in the construction threshold, the CO2 reduction potential has shown a decrease to 1.29E+08 tones, particularly evident in areas with rigorous construction standards. A plateau in reduction figures is observed once the construction threshold surpasses 3.5, stabilizing between 2.5E+07 tones. As the threshold exceeds 5, a further stabilization is noted, consistently around 2.17E+07 tones, persisting even when the threshold approaches 8. The outcomes underscores the critical role of strategic zoning in maximizing renewable energy potential, highlighting pathways for the country to achieve energy self-sufficiency and make significant strides in climate goals.

To investigate the optimal cultivation conditions for cassava cultivar (TMS98/0505) in Nigeria, we employed agro-ecological zoning to delineate the cultivated lands. Using GIS-based multi-criteria analysis, we researched the influence of some meteorological and soil parameters on the clone cultivation. From the multiple-parameter climato-edaphic zoning map, an average yield of 26 t ha−1 was estimated. The dry Rainforest and southern Guinea Savanna account for 80% of the favorable zones. However, with irrigation, the cultivar would yield optimally in the northern marginal zones. Further, the significant climatic parameters are sunshine hour (t = 3.292, α = 0.0064) and rainfall (t = 2.100, α = 0.0575). Thus, the potentials of a location for cassava cultivation in Nigeria largely depend on the soil conditions, sunshine hour, and rainfall. Generally, the cassava yield correlates strongly (+0.88) with the suitability map. Considering future climate variability based on the annual rainfall data, we projected an average annual rainfall range of 565–3,193 mm between 2070 and 2099. Likewise, the projected range of daily temperature for 2046–2100 is 24.57–31.94 °C. Consequently, with currently allotted farmlands, Nigeria can double her current cassava production through soil fertility enhancement and irrigation.