GIS Multi-Criteria Analysis by Ordered Weighted Averaging (OWA): Toward an Integrated Citrus Management Strategy

Siting MPAs for multiple protecting purposes by co-consideration of ecological importance and anthropogenic impacts

The global marine ecosystem has been significantly altered by the combined effects of multiple anthropogenic impacts. Systematic planning of marine protected areas (MPAs) is of paramount importance in alleviating conflicts between humans and the sea. Existing approaches, however, merely integrate both ecological and anthropogenic factors for multiple conservation purposes. By combining the three main anthropogenic impact factors with two main ecological importance factors, this study used a GIS-based AHP-OWA method to identify different levels of priority protection for MPAs in Zhejiang, China. Our results proved that: 1) the multi-objective MPA siting issues can be addressed by the GIS-based AHP-OWA method through scenario simulation; 2) the best locations for MPAs are in the northeast, central, and southern marine areas of Zhejiang; 3) considering the trade-off degree, spatial conservation efficiency, and spatial heterogeneity, an optimized MPA siting scheme can be developed for decision-makers. The proposed MPA siting method and case study may provide an effective technical reference for solving regional marine spatial planning (MSP) issues in the future.

Fuzzy-based models' performance on qualitative and quantitative land suitability evaluation for cotton cultivation in Sarayan County, South Khorasan Province, Iran

Using appropriate models in the land use planning process will help increase the accuracy and precision of decisions made by designers. The aim of this study was to investigate and compare fuzzy-based models (fuzzy set theory, fuzzy-AHP, and fuzzy-ANP) to evaluate the suitability of cotton cultivation in Sarayan region (located in eastern Iran). Twenty-eight land units were selected. Weighted arithmetic means of characteristics were performed in representative soil profiles of each unit. Landform-related characteristics were directly entered into the land suitability evaluation modeling. The land index was calculated using three selective qualitative land suitability model guidelines. Qualitative and quantitative land suitability was estimated. The validity of models was determined by r², RMSE, GMER, and MAPE indicators between predicted and actual production. Soil texture, pH, calcium carbonate equivalent, drainage, organic matter, salinity and sodicity, slope, and gypsum are the most important, respectively. Also, the fuzzy-ANP method is more efficient than other models due to its higher r² (0.98) and lower RMSE (4.31) and MAPE (0.56) and GMER (0.99) closer to 1. The value of cotton production using fuzzy, fuzzy-AHP, and fuzzy-ANP methods was calculated as 1085 to 4235, 1235 to 4318, and 1391 to 4452 tons per hectare, respectively. The high efficiency of the fuzzy-ANP model is due to the characteristics of the lands used in the evaluation process that are not independent of each other and this model considers them. Examining these models in different weather conditions and combining with the other computational intelligence methods in future experiments are recommended.

A Spatial Decision Support Approach for Flood Vulnerability Analysis in Urban Areas: A Case Study of Tehran

Preparedness against floods in a hazard management perspective plays a major role in the pre-event phase. Hence, assessing urban vulnerability and resilience towards floods for different risk scenarios is a prerequisite for urban planners and decision makers. Therefore, the main objective of this study is to propose the design and implementation of a spatial decision support tool for mapping flood vulnerability in the metropolis of Tehran under different risk scenarios. Several factors reflecting topographical and hydrological characteristics, demographics, vegetation, land use, and urban features were considered, and their weights were determined using expert opinions and the fuzzy analytic hierarchy process (FAHP) method. Thereafter, a vulnerability map for different risk scenarios was prepared using the ordered weighted averaging (OWA) method. Based on our findings from the vulnerability analysis of the case study, it was concluded that in the optimistic scenario (ORness = 1), more than 36% of Tehran’s metropolis area was marked with very high vulnerability, and in the pessimistic scenario (ORness = 0), it was less than 1%was marked with very high vulnerability. The sensitivity analysis of our results confirmed that the validity of the model’s outcomes in different scenarios, i.e., high reliability of the model’s outcomes. The methodical approach, choice of data, and the presented results and discussions can be exploited by a wide range of stakeholders, e.g., urban planners, decision makers, and hydrologists, to better plan and build resilience against floods.

Application of Multi-Criteria Decision-Making Analysis to Rural Spatial Sustainability Evaluation: A Systematic Review

The rational allocation of spatial resources is an important factor to ensure the sustainable development of rural areas, and effective pre-emptive spatial evaluation is the prerequisite for identifying the predicament of rural resource allocation. Multi-criteria decision-making analysis has advantages in solving multi-attribute and multi-objective decision-making problems, and has been used in sustainability evaluation research in various disciplines in recent years. Previous studies have proved the value of spatial evaluation using multi-criteria decision analysis in guiding rural incremental development and inventory updates, but systematic reviews of the previous literature from a multidisciplinary perspective and studies of the implementation steps of the evaluation framework are lacking. In the current paper, the research is reviewed from the two levels of quantitative statistics and research content, and through vertical and horizontal comparisons based on three common operating procedures: standard formulation, weight distribution, and ranking and verification. Through the results, the application status and characteristics of the MCDA method in related research are determined, and five research foci in the future are proposed.

Agricultural land suitability assessment for agricultural productivity based on GIS modeling and multi-criteria decision analysis: the case of Tekirdağ province

Grains play a significant role in meeting the nutritional needs of the increasing world population. Consequently, the need for new studies on agricultural production and land suitability assessments has increased. The present paper aims to perform agricultural land suitability assessment to evaluate agricultural productivity in Tekirdağ province to determine precise productive agricultural areas. This study combines a variety of datasets to develop a dynamic model using GIS-based multi-criteria decision analysis for land suitability assessment and agricultural productivity. The datasets used in this study are supported by terrestrial samples and processed with spatial technologies. The results of the study indicate that the agricultural potential of the provincial lands is quite high. It reveals that 65.7% of province lands are suitable for agricultural production. Of the remaining lands, 20.3% is marginally suitable while only 8% of the land is unsuitable for agricultural production. In the northwestern part, suitable land for agricultural productivity is higher compared to other parts of the study area. This part also corresponds to the areas where industrial activities are marginal. The results also imply that agricultural activities in grain production areas must be reconsidered and replanned according to the new classification of land suitability assessment. In this respect, our study suggests that the policymakers and the government should take necessary steps to ensure the protection and sustainability of agricultural lands while planning for the industrial and settlement development in grain production areas.

Prospects and Constraints of Sustainable Marketing Mix Development for Poland’s High-Energy Consumer Goods

The research examined awareness, prospects and constraints of sustainable marketing mix development (SMD) from the perspective of Poland’s high-energy consumer goods (HECG), i.e., confectionery products, as an example of the Polish food industry. A questionnaire survey was designed for this purpose. The purpose of the survey questions was to evaluate selected areas of SMD; thus, a reference value ratio was proposed. An original approach to pairwise comparisons technique was applied to rank the value of each survey to provide an intensity measure for each examined area, i.e., a non-heuristic approach with verifiable accuracy and reliability. It was found that a high level of awareness among respondents exists in relation to SMD. Considering all aspects of constraints intensity for SMD, it could be concluded that SMD for Poland’s HECG is at a quite high level. However, considering all aspects of prospects intensity for SMD, this evaluation supported the conclusion that its level for Poland’s HECG is moderate only. It was also found that prices of sustainable products constitute the highest ranked determinant of SMD. Considering these research findings regarding awareness, limitations and perspectives for the development of a sustainable marketing mix in the enterprises operating in Poland’s HECG sector, it can be concluded that there are many more problems and difficulties in implementing sustainable marketing mix programs than there are prospects for the development of this concept.

Visitation Rate Analysis of Geoheritage Features from Earth Science Education Perspective Using Automated Landform Classification and Crowdsourcing: A Geoeducation Capacity Map of the Auckland Volcanic Field, New Zealand

The increase in geoheritage studies has secured recognition globally regarding the importance of abiotic natural features. Prominent in geoheritage screening practices follows a multicriteria assessment framework; however, the complexity of interest in values often causes decision making to overlook geoeducation, one of the primary facets of geosystem services. Auckland volcanic field in New Zealand stretches through the whole area of metropolitan Auckland, which helps preserve volcanic cones and their cultural heritage around its central business district (CBD). They are important sites for developing tourist activities. Geoeducation is becoming a significant factor for tourists and others visiting geomorphological features, but it cannot be achieved without sound planning. This paper investigates the use of big data (FlickR), Geopreservation Inventory, and Geographic Information System for identifying geoeducation capacity of tourist attractions. Through landform classification using the Topographic Position Index and integrated with geological and the inventory data, the underpromoted important geoeducation sites can be mapped and added to the spatial database Auckland Council uses for urban planning. The use of the Geoeducation Capacity Map can help resolve conflicts between the multiple objectives that a bicultural, metropolitan city council need to tackle in the planning of upgrading open spaces while battling of growing demand for land.

The Identification and Classification of Arid Zones through Multicriteria Evaluation and Geographic Information Systems—Case Study: Arid Regions of Northwest Mexico

Arid and semiarid regions are geographic units that cover approximately 43% of the earth’s surface worldwide, and conditions of extreme drought and reduced vegetation cover predominate in these regions. In Mexico, arid and semiarid ecosystems cover more than half of the territory, with desertification, mainly caused by anthropogenic activities and climatic events, as the main problem in these regions. The present research aimed to assess, identify, and classify arid and semiarid zones by employing a methodology based on multicriteria evaluation analysis (MCA) using the weighted linear combination (WLC) technique and geographic information systems (GIS) in the hydrological administrative regions (HARs) of the North Pacific, Northwest, and Baja California Peninsula, located in Northwest Mexico. Data related to aridity, desertification, degradation, and drought were investigated, and the main factors involved in the aridity process, such as surface temperature, soil humidity, precipitation, slopes, orientations, the normalized difference vegetation index (NDVI), and evapotranspiration, were obtained. For the standardization of factors, a fuzzy inference system was used. The weight of each factor was then determined with the analytical hierarchy process (AHP). To delimit arid regions, the classification of arid zones proposed by the United Nations Environment Program (UNEP) was used, and the result was an aridity suitability map. To validate the results, the sensitivity analysis method was applied. Quantitative and geospatial aridity indicators were obtained at the administrative hydrological level and by state. The main results indicated that semiarid and dry subhumid zones predominated, representing 40% and 43% of the surface of the study area, respectively, while arid regions represented 17%, and humid regions represented less than 1%. In addition, of the states for which 100% of the surface lay in the study area, it was observed that Baja California and Baja California Sur had the largest arid and semiarid zones, while subhumid regions predominated in Sonora and Sinaloa.

A Numerical Comparison of the Sensitivity of the Geometric Mean Method, Eigenvalue Method, and Best–Worst Method

In this paper, we compare three methods for deriving a priority vector in the theoretical framework of pairwise comparisons—the Geometric Mean Method (GMM), Eigenvalue Method (EVM) and Best–Worst Method (BWM)—with respect to two features: sensitivity and order violation. As the research method, we apply One-Factor-At-a-Time (OFAT) sensitivity analysis via Monte Carlo simulations; the number of compared objects ranges from 3 to 8, and the comparison scale coincides with Saaty’s fundamental scale from 1 to 9 with reciprocals. Our findings suggest that the BWM is, on average, significantly more sensitive statistically (and thus less robust) and more susceptible to order violation than the GMM and EVM for every examined matrix (vector) size, even after adjustment for the different numbers of pairwise comparisons required by each method. On the other hand, differences in sensitivity and order violation between the GMM and EMM were found to be mostly statistically insignificant.

A New Integrated Approach for Municipal Landfill Siting Based on Urban Physical Growth Prediction: A Case Study Mashhad Metropolis in Iran

Due to irregular and uncontrolled expansion of cities in developing countries, currently operational landfill sites cannot be used in the long-term, as people will be living in proximity to these sites and be exposed to unhygienic circumstances. Hence, this study aims at proposing an integrated approach for determining suitable locations for landfills while considering their physical expansion. The proposed approach utilizes the fuzzy analytical hierarchy process (FAHP) to weigh the sets of identified landfill location criteria. Furthermore, the weighted linear combination (WLC) approach was applied for the elicitation of the proper primary locations. Finally, the support vector machine (SVM) and cellular automation-based Markov chain method were used to predict urban growth. To demonstrate the applicability of the developed approach, it was applied to a case study, namely the city of Mashhad in Iran, where suitable sites for landfills were identified considering the urban growth in different geographical directions for this city by 2048. The proposed approach could be of use for policymakers, urban planners, and other decision-makers to minimize uncertainty arising from long-term resource allocation.

Optimization of the Weighted Linear Combination Method for Agricultural Land Suitability Evaluation Considering Current Land Use and Regional Differences

This study was aimed at optimizing the weighted linear combination method (WLC) for agricultural land suitability evaluation (ALSE) through indicator selection, weight determination, and classification of overall suitability scores in Handan, China. Handan is a representative research area with distinct agricultural advantages and regional differences in land use, where the expansion of construction land has led to a rapid decrease of agricultural land in recent years. Natural factors (topography, climate, soil conditions, and vegetation cover) and socioeconomic factors (land use and spatial accessibility) were selected to establish a more comprehensive evaluation system. The index weight was calculated by the mutual information between index suitability and current land use. The consistency index was used to identify the boundary value dividing the overall suitability score into a suitable category and unsuitable category in each sub-region. The results demonstrated that the optimized WLC-ALSE model outperformed the comparison models using conventional methods in terms of the consistency between the evaluation results and current land use. Owing to the increasing limitations of topography, soil conditions, spatial accessibility, and land use, the proportions of suitable land in Zone 1, Zone 2, and Zone 3 were 77.4%, 67.5%, and 30.9%, respectively. The agricultural land unsuitable for agriculture (14.5%) was less than non-agricultural land suitable for agriculture (7.4%), indicating that agricultural land had low growth potential in Handan. Finally, specific recommendations were made to improve agricultural land suitability, alleviate land use conflicts, and further optimize the model. The results can provide effective guidance for WLC-ALSE and land use decision-making for sustainable agriculture.

A GIS Approach Land Suitability and Availability Analysis of Jatropha Curcas L. Growth in Mexico as a Potential Source for Biodiesel Production

Jatropha curcas L. (JCL) commercial plantations in Mexico, one of the most important JCL origin centers, have failed due to a variety of biological, political and technical factors affecting their productivity. This study explores feasible sites of JCL cultivation as a potential source for biodiesel production in Mexico, given agroclimatic and agroecological considerations. We propose a GIS-based approach for estimating suitable and available lands to grow JCL by integrating an Analytical Hierarchy Process (AHP) in the ArcGIS software. Spatial analysis combined multiple data, different evaluation criteria, three land availability classes (high, medium and low potential) and took into account ecological, ethical, and political restrictions, and considering two scenarios with different restriction levels. Suitability and availability maps were generated using agroclimatic information (climatic, land use/soil, and climate change and extreme weather events risk) together with other socioeconomic factors. Approximately 15.3% of Mexican territory is available for JCL production yielding a biodiesel production of 9.683 Mm3/year. Amelioration of the available land is necessary to improve land selection. GIS-based analysis represents a first approach to establish a successful biodiesel project that avoids, competition with food or feed production, maintains biodiversity conservation, and promotes biofuel supply chain development. This procedure would also be applicable to other energy crops such as oil palm and Ricinus communis.

Mapping of GIS-Land Use Suitability in the Rural–Urban Continuum between Ar Riyadh and Al Kharj Cities, KSA Based on the Integrating GIS Multi Criteria Decision Analysis and Analytic Hierarchy Process

The management of land use in big cities and capitals and the surrounding adjacent urban aggregates is still of major importance in the field of urban development, especially in cities with populations of millions and various types of land uses and economic activities. The rural–urban continuum between the cities of Ar Riyadh and Al Kharj suffers from an unclear general land use trend, due to urban expansion at the expense of the agriculture lands, the imbalance of the population compound, the deterioration of the urban fabric, lack and poor distribution of services, and the dominance of industrial land use at the expense of other uses. These factors have led to an increase in environmental changes and loss of the environmental and ecological characteristics of this area between Ar Riyadh and Al Kharj. The present study aims at evaluating the land use suitability for urban development in the rural–urban continuum between Ar Riyadh and Al Kharj cities. This is achieved by using the GIS-based Multi Criteria decision Analysis (GIS-MCDA) on twelve various economic, environmental, urban, and law criteria. The weights of criteria were determined using the Analytic Hierarchy Process (AHP) method. The results of the spatial suitability map of the land use for sustainable urban development revealed that there are five categories of spatial suitability ranging in suitability from 32% to 86%. The recommended areas for sustainable urban development are those with a spatial suitability upwards of 70% in the rural–urban continuum corridor between Ar Riyadh and Al Kharj cities. The sustainable development in this corridor can be achieved by executing high priority projects that ensure and support the urban sustainable development plan through establishing four local urban development centers and upgrading four current villages to rural communities, aiming at strengthening the functional bonds between the rural communities and the local urban development centers. These projects will limit the sustainable urban development to specific areas without allowing random expansion, avoiding the urban conjugation of the two Ar Riyadh and Al Kharj cities through the connecting area between them.

Optimal Soybean (Glycine max L.) Land Suitability Using GIS-Based Multicriteria Analysis and Sentinel-2 Multitemporal Images

Soybean is regarded as one of the most produced crops in the world, presenting a source of high-quality protein for human and animal diets. The general objective of the study was to determine the optimal soybean land suitability and conduct its mapping based on the multicriteria analysis. The multicriteria analysis was based on Geographic Information System (GIS) and Analytic Hierarchy Process (AHP) integration, using Sentinel-2 multitemporal images for suitability validation. The study area covered Osijek-Baranja County, a 4155 km2 area located in eastern Croatia. Three criteria standardization methods (fuzzy, stepwise and linear) were evaluated for soybean land suitability calculation. The delineation of soybean land suitability classes was performed by k-means unsupervised classification. An independent accuracy assessment of calculated suitability values was performed by a novel approach with peak Normalized Difference Vegetation Index (NDVI) values, derived from four Sentinel-2 multispectral satellite images. Fuzzy standardization with the combination of soil and climate criteria produced the most accurate suitability values, having the top coefficient of determination of 0.8438. A total of 14.5% of the study area (602 km2) was determined as the most suitable class for soybean cultivation based on k-means classification results, while 64.3% resulted in some degree of suitability.

Sustainable Applications of Remote Sensing and Geospatial Information Systems to Earth Observations

The Special Issue on “Sustainable Applications of Remote Sensing and Geospatial Information Systems to Earth Observations” is published. A total of 20 qualified papers are published in this Special Issue. The topics of the papers are the application of remote sensing and geospatial information systems to Earth observations in various fields such as (1) object change detection, (2) air pollution, (3) earthquakes, (4) landslides, (5) mining, (6) biomass, (7) groundwater, and (8) urban development using the techniques of remote sensing and geospatial information systems. More than 100 researchers have participated in this Special Issue. We hope that this Special Issue is helpful for sustainable applications.