Agricultural Land Suitability Research Articles

Application of Mass Spectrometry-Based Proteomics to Barley Research.

Barley (Hordeum vulgare) is the fourth most cultivated crop in the world in terms of production volume, and it is also the most important raw material of the malting and brewing industries. Barley belongs to the grass (Poaceae) family and plays an important role in food security and food safety for both humans and livestock. With the global population set to reach 9.7 billion by 2050, but with less available and/or suitable land for agriculture, the use of biotechnology tools in breeding programs are of considerable importance in the quest to meet the growing food gap. Proteomics as a member of the “omics” technologies has become popular for the investigation of proteins in cereal crops and particularly barley and its related products such as malt and beer. This technology has been applied to study how proteins in barley respond to adverse environmental conditions including abiotic and/or biotic stresses, how they are impacted during food processing including malting and brewing, and the presence of proteins implicated in celiac disease. Moreover, proteomics can be used in the future to inform breeding programs that aim to enhance the nutritional value and broaden the application of this crop in new food and beverage products. Mass spectrometry analysis is a valuable tool that, along with genomics and transcriptomics, can inform plant breeding strategies that aim to produce superior barley varieties. In this review, recent studies employing both qualitative and quantitative mass spectrometry approaches are explored with a focus on their application in cultivation, manufacturing, processing, quality, and the safety of barley and its related products.

Multi-criteria Land Suitability Analysis for Agriculture in Semi-Arid Region of Kadapa District, Southern India: Geospatial Approaches

This research proposes an integrated methodology for incorporating RS, GIS and AHP techniques for the assessment of agricultural land suitability. In Kadapa district, Andhra Pradesh, India, study is being done on how to best promote agriculture as a source of income to boost the economy of the region. A combined RS, GIS and AHP techniques has been utilized that incorporates organizing AHP hierarchy, criteria specification, pairwise comparison, and criterion map preparation. Land suitability comparison showed that an area of 4.42 km2 (2.62%) is appropriate for irrigation, while an area of 54.39 km2 (32.33%) is appropriate moderately suitable for rainfed agriculture and 95.76 km2 (56.93%) is marginally suitable for agricultural productions. About 13.64 km2 (8.11%) land is currently not suitable for agricultural production. Additionally, the analysis clearly shows the necessity of a decrease in irrigated agricultural land and an increase in dry farm agricultural land. This application of RS, GIS and AHP based agricultural land suitability analysis is helpful in referring agricultural activities to the areas with good physical and environmental conditions, allowing maximum agricultural efficiency in the countryside, increasing non-agricultural uses in areas with low efficiency, and avoiding the construction and environmental pressures on suitable farmland.

Determining agricultural suitable land in peri-urban geography using GIS and Multi Criteria Decision Analysis (MCDA) techniques

Land-use suitability analysis is of significance for the planning and management of cities. The main objective of this study was to develop a spatial model for land suitability assessment for peri-urban agricultural development with the use of geographic information systems (GIS) integrated with Multi Criteria Decision Analysis (MCDA) techniques. Physical attributes, land use, natural resources, accessibility, geology and soil properties were recognised as the key factors influencing land suitability for peri-urban agriculture in the study area. The study follows an integrated approach for the suitability assessment of agricultural development in Pendik District of Istanbul (Turkey) through integrating fuzzy logic model, Analytical Hierarchy Process (AHP) and the technique for order preference by similarity to ideal solution (TOPSIS) methods. Suitability classification of land was done in GIS by using the specified fuzzy membership functions. The weights of the main criteria and their sub-criteria were determined through the AHP method. Eight different zones were ranked according to agricultural development priority by the TOPSIS method. The area classified as suitable amounts to 27% of the total area with 0.07% classified as unsuitable. The highly suitable areas are mainly located in the north where there are villages specialised in agricultural production. The prioritisation of the suitable agricultural areas would assist in land use planning and urban management.

Integrating farmers’ decisions on the assessment of forest regeneration drivers in a rural landscape of Southeastern Brazil

Forest regeneration at large-scales is one of the main paths to achieving the ongoing ambitious restoration commitments. Thus, the identification of the main drivers of this process in agricultural landscapes is critical to understand the drivers determining restoration success. A growing number of studies have explored the biophysical and, less often, the socioeconomic drivers of forest regeneration using remote sensing approaches, but have not directly considered the influence of farmers’ decisions in spatial prediction models of forest regeneration. We explored the influence of biophysical and socioeconomic drivers on forest regeneration in a rural landscape of Southeastern Brazil, where native forest cover increased by 7.7%. We evaluated forest regeneration through the analysis of time series of multi-temporal satellite images and socioeconomic information obtained through a Social Survey with 47 landowners, using each farm as the study unit. Natural forest regeneration was mainly favored by lower land suitability for agriculture and higher proximity (lower distances) to forest remnants, as well by higher numbers of land-uses types in the farm and lower economic dependence of landowners from the farm income. Our results emphasize the importance of considering farmers’ decisions on predictive models of natural forest regeneration, which are critically needed to guide the implementation of large-scale forest restoration initiatives in agricultural landscapes.

Land Suitability Mapping Using Geochemical and Spatial Analysis Methods

Assessing the suitability of urban and agricultural land is essential for planning sustainable urban and agricultural systems. The main objective of this study is to evaluate the suitability of land in Ioannina plain (western Greece) concerning the soil contents of two potentially toxic elements, cadmium (Cd) and cobalt (Co). Geochemical and spatial analysis methods were applied to assess the distribution of Cd and Co in the soil of the Ioannina plain and identify their origin. The primary anthropogenic sources of Cd and Co in the topsoil of the study area can be attributed to traffic emissions, aircraft operations, vehicle crushing and dismantling activities. Element content is compared to international guidelines and screening values. Cadmium and Co concentration in the soil of the study area is well above the European topsoil mean. Thus, the urban and agricultural lands cover the vast majority (92%) of the total area. Cadmium concentration in soil of the study area with a mean (mg kg−1) 1.7 and 2.0 was observed in agricultural and urban land use, respectively. Cobalt content in soil of the area studied with a mean (mg kg−1) 30.8 and 37.1 was recorded in agricultural and urban land use, respectively. Land evaluation suitability by adopting criteria provided from the international literature is discussed.

Land suitability analysis using geographic information system (GIS): a case study in Soppeng district

The agricultural sector is a sector of the economy that is still the flagship in various regions in Indonesia, especially Soppeng regency. The area of Soppeng hills is approximately 800 km2 and is at an average altitude of 200 m above sea level, and has no coastal area. The utilization of Geographic Information Systems (GIS) promises resource management and modeling, especially quantitative models, to be more accessible and simpler. GIS is an efficient and effective way to know the characteristics of a region’s land and its development potential. Land suitability is the suitability of land for a particular purpose of use through the determination of land value (class) and land use patterns connected to the territory’s potential. It can be attempted more targeted land use along with its sustainability maintenance efforts. The spatial analysis involves modeling, testing, and interpreting model results to extract or form new information from a collection of geographic elements. This research will be carried out for 12 Months (1 year) through 4 stages. The research aims to identify land use’s suitability in the analysis of agricultural land suitability using geographical information systems in Soppeng regency area.

Applying the Best–Worst Method for land evaluation: a case study for paddy cultivation in northwest Turkey

Several multi-criteria decision-making methods are used in land suitability analyses. The main objective of this study is to present the potential use of the Best–Worst Method to determine agricultural land suitability. Study was conducted in 6837.26 ha land in Canakkale northwest Turkey. Nine land characteristics (texture, electrical conductivity, drainage, pH, depth, cation exchange capacity, organic matter content, soil fertility index (N, P, K and Zn content) and CaCO3%) were used. Data obtained from the Best–Worst Method were compared with the results of Analytical Hierarchy Process, and Storie Index method. According to the Best–Worst Method, 5.76% of the land was highly suitable, 58.37% were moderately suitable, 31.93% were marginally suitable, and 3.94% were not suitable for paddy cultivation. To Analytical Hierarchy Process, 5.76% of the land was highly suitable, 61.42% were moderately suitable, 29.01% were marginally suitable, and 3.94% were not suitable and with respect to Storie Index method, 5.76% were highly suitable, 0.20% were moderately suitable, 57.78% were marginally suitable, and 36.26% were not suitable for paddy cultivation. There was a statistically positive correlation between the Best–Worst Method and Analytical Hierarchy Process (r = .997) and negative correlation between Storie Index. So, results showed that the data generated with the use of Best–Worst Method were consistent, reliable and complied with the data of Analytical Hierarchy Process. The advantage of the Best–Worst Method to other methods is to conduct less pairwise comparisons and has more practical and fast algorithm. So, the Best–Worst Method can reliably use in crop-based land suitability analyses.

Evaluation of Agricultural Land Suitability Based on RS, AHP, and MEA: A Case Study in Jilin Province, China

The suitability evaluation of agricultural land at the regional scale is of great significance for protecting land and water resources and building sustainable agricultural systems. Based on climate, soil, topographical, and surface water resources, land suitability index (LSI) data for maize, rice, and soybeans are established using an analytical hierarchy process and matter element analysis (AHP–MEA) model in Jilin Province, China. The results show that there is a significant positive linear correlation between the LSI and the measured yield, which indicates that the model has an ideal effect and certain reference and extension significance. The main limiting factors for maize and soybean planting are pH, total nitrogen (TN), available phosphorus (AP), and soil texture, while water shortage limits rice planting. Different spatial structure optimization schemes for planting are established using the LSI and measured yield, along with economic indices. This study shows that the scheme that integrates policy and cost can make full use of land and water resources and promote the economic growth of agriculture. After optimization, the planting areas of maize, rice, and soybeans were 7.22, 2.44, and 0.71 million ha, respectively, representing an increase of 15.71 billion yuan over the agricultural GDP for the existing planting structure. It is expected that this study will provide a basis for follow-up studies on crop cultivation suitability.

Can We Use Machine Learning for Agricultural Land Suitability Assessment?

It is vital for farmers to know if their land is suitable for the crops that they plan to grow. An increasing number of studies have used machine learning models based on land use data as an efficient means for mapping land suitability. This approach relies on the assumption that farmers grow their crops in the best-suited areas, but no studies have systematically tested this assumption. We aimed to test the assumption for specialty crops in Denmark. First, we mapped suitability for 41 specialty crops using machine learning. Then, we compared the predicted land suitabilities with the mechanistic model ECOCROP (Ecological Crop Requirements). The results showed that there was little agreement between the suitabilities based on machine learning and ECOCROP. Therefore, we argue that the methods represent different phenomena, which we label as socioeconomic suitability and ecological suitability, respectively. In most cases, machine learning predicts socioeconomic suitability, but the ambiguity of the term land suitability can lead to misinterpretation. Therefore, we highlight the need for increasing awareness of this distinction as a way forward for agricultural land suitability assessment.

Intelligent Exchange Mechanism of Agriculture Sector for Sustainable Economic Transaction Development in Pathum Thani, Thailand

Pathumthani Province is on fertile plains and river valleys offering suitable land for agriculture. In 2019, A large number of agricultural lands, particularly farmland, is accounted for over 40 percent of the total province. However, the revenue of the agricultural sector contributes less than 3 percent of the gross provincial product (GPP), while the industrial sector becomes a major economic-based activity of this province, accounting for half of the GPP revenue. This research seeks an opportunity to enhance economic values and optimize the efficiency of agricultural-related supply chains. The research aims 1) to assess the need assessment of the agricultural sector in the issue of an intelligent exchange for sustainable economic transaction development, 2) to map a relationship between current situations of the agricultural sector and the commercial sector. Through the process of focus group and in-depth interview, the result of this study demonstrated the potential and current problems include the need to exchange agricultural goods/resources. The results could allow for an enhancement of the exchange of goods, especially agricultural products, to increase the potential of connectivity between producers and consumers in Pathumthani.

Agricultural Land Suitability Analysis for Maize Crop by Using GIS Technology in Case of Debub Gondar Zone, Ethiopia

Food security is the current problem that affects the socio economic standard and living condition of the society. Land suitability analysis is a method of land evaluation which measures the degree of appropriateness of land for a certain use. The aim of this study was to identify and delineate the land that can best support maize production by using GIS technology. The study was carried out in Debub Gondar zone in Ethiopia. Even though agriculture is the main economic activity in the study area, its productivity is insufficient because some of the crops being introduced are not doing well. For this study, three specific objectives were mentioned. These are; identify the suitable area of maize in the study area, identify the unsuitable area of maize in the study area and compare current maize production with suitable and unsuitable area. To accomplish these study four parameters were used such as soil, slope, temperature and rainfall. The parameters were analyzed by ArcGIS 10.3 software. As result the largest portion of the study area was unsuitable for maize production and some part of northern, north western and eastern part of study area was partially suitable for maize production. Finally, we recommended that the concerned bodies should cultivate maize around the suitable part of the study area. Keywords: Debub Gondar, GIS, Maize, Suitability DOI: 10.7176/JEES/11-4-01 Publication date: April 30 th 2021

PENENTUAN KESESUAIAN LAHAN PERTANIAN TANAMAN CABAI MENGGUNAKAN METODE NAÏVE BAYES DI KABUPATEN KUPANG

Tanaman cabai merupakan salah satu tanaman yang dibudidayakan di Nusa Tenggara Timur (NTT). Wilayah Kabupaten Kupang merupakan salah satu wilayah penghasil cabai yang ada di NTT. Produksi cabai secara keseluruhan di Kabupaten Kupang pada tahun 2019 sampai 2020 mengalami peningkatan. Namun peningkatan produksi ini belum maksimal mengingat banyaknya lahan yang belum dimanfaatkan sebagai lahan pertanian. Oleh karena itu dibutuhkan sebuah sistem yang membantu dalam menentukan kesesuaian lahan pertanian untuk penanaman cabai. Dalam penelitian ini penulis menerapkan penalaran berbasis kasus/case-based reasoning (CBR) dalam menentukan kesesuaian lahan pertanian tanaman cabai. Metode yang digunakan dalam penelitian ini adalah Naïve Bayes dengan 7 kriteria yaitu: curah hujan, drainase, tekstur tanah, kedalaman tanah, C-organik, kemiringan lahan dan bahaya terjadinya bencana. Proses pencarian solusi dimulai dengan mengeliminasi data yang tidak relevan menggunakan metode Naive Bayes dan berlanjut dengan perankingan nilai kemiripan terbaik menggunakan KNN. Berdasarkan hasil pengujian dengan 110 kasus lahan cabai didapatkan hasil akurasi tertinggi sebesar 92.2% dan rata-rata hasil akurasi dari keseluruhan fold sebesar 89.1%.

Identifying Agricultural Managed Aquifer Recharge Locations to Benefit Drinking Water Supply in Rural Communities

AbstractThe southern Central Valley of California is one of the most productive agricultural regions in the world. Yet, decades of groundwater use beyond sustainable yield have left rural communities highly vulnerable to shortages and contamination of their drinking water supply. As state regulation begins to address these issues, a need exists to design adaptive and appropriate management systems to increase resilience of rural communities. Targeted managed aquifer recharge on agricultural land (Ag‐MAR) near rural communities is one such strategy that could potentially stabilize groundwater tables and maintain or improve groundwater quality in domestic supply wells. Here we present a geographic information system‐based multicriteria decision analysis that combines biophysical data (soils, land use, and surface water conveyance) with groundwater modeling and particle tracking to identify suitable agricultural land parcels for multibenefit groundwater recharge within well capture zones of 288 rural communities. Parcels are prioritized using a vulnerability index to change in groundwater supply, derived from well reliance and failures, pesticide applications, land subsidence, and socio‐economic data. Our analysis identifies 2,998 suitable land parcels for Ag‐MAR within the well capture zones of 149 of the 288 communities, of which 144 rely mainly on groundwater for drinking water. The majority of identified Ag‐MAR parcels serve communities ranked as having extreme or very high vulnerability to changes in groundwater supply. Our research produces new understanding of factors contributing to community vulnerability and resilience to changes in drinking water supply and can be used to discuss actions to help achieve a stable and high‐quality water supply.

Development of organic agro tourism for optimizing agricultural resources in Ngawi, East Java, Indonesia

Ngawi Regency, part of East Java province in Indonesia, has started to initiate the development of organic tourism based on the organic agriculture potential. This study aimed to explore agricultural resources and land suitability that can be developed as community-based organic tourism attractions and identification of supporting factors and inhibiting factors the development of community-based organic tourism attractions. There were several stages in this study consisting of study field observations, in-depth interviews, and focus group discussion to collect information. In this study data were analyzed by spatial analysis techniques to explore the agricultural resources and land suitability. As the result, we found the needs and roles of community in developing agro-tourism areas. The development of agrotourism areas requires community participation in various sectors. Economic point of view plays an important role in management of agro-tourism areas, as without economic benefits there is no motivation to contribute to community and businesses of agro-tourism. Since the agro-tourism has effects to environment, both natural and cultural, therefore taking advantage of agricultural resources need to be carefully considered in developing a community-based organic tourism attractions. In addition, the environmental elements must be preserved for sustainable benefit and function.

Developing Criteria for the Identification of Suitable Agricultural Land for Expropriation and Redistribution in South Africa: Lessons Learnt from Namibia

There has been a plethora of policy initiatives and academic debate focusing on how land should be acquired in South Africa for redistribution purposes and, if expropriation is to take place, at what value or for how much compensation. However, little attention has been paid to how land will be identified for acquisition in general, and expropriation specifically, for redistribution purposes. Therefore, the aim of this article is not to explore which approach is more suitable for specifically acquiring agricultural land, but rather how agricultural land should be identified prior to being acquired, specifically through expropriation, for redistribution purposes. To this end, the approach and criteria for identifying suitable agricultural land for expropriation as provided for in Namibia’s regulations to the Agricultural (Commercial) Land Reform Act 6 of 1995 may prove to be useful in formulating criteria for the South African context. The article concludes with the recommendation that for the sake of a transparent, procedurally fair and effective redistribution process in South Africa, objective, nonarbitrary criteria for identifying suitable agricultural land for redistribution purposes should be developed and provided for in regulations or policy. The development of criteria for identifying suitable agricultural land will provide the South African government with a useful tool in selecting agricultural land for acquisition and redistribution. The use of the criteria will not only contribute to a transparent, non-arbitrary and procedurally fair selection process, but will also assist landowners in determining the likelihood of their land being earmarked for redistribution.

Comparison of SAW and WP methods to determine the best agricultural land

Rice is a cultivated plant that is very important for human life because it produces rice in making rice. The need for food always increases this is due to the increasing human population. Therefore, rice cultivation must be maximized. Agricultural land used to grow rice greatly affects the production produced. Different characteristics in each region should be considered in selecting suitable agricultural land. The purpose of this research is to determine and map the suitable areas for rice farming in order to obtain maximum production results. The determination of the feasibility of the location of the farm is based on the assessment of the criteria owned by each region. These criteria include soil type, slope, land area, rainfall, and irrigation or water. The criteria for each area will be processed using the Simple Additive Weighting (SAW) and Weighted Product (WP) methods, the process in this method is to find the weight value for each attribute, then a ranking process is carried out which will produce an optimal alternative, namely a suitable area for agriculture. The contribution of this research is to know the comparison of the SAW method with the WP in the process of determining the best agricultural area for rice plants. In this system using the SAW method, resulting in an accuracy rate of 72%. This is better than using the WP method which only produces an accuracy rate of 50%.

Comprehensive economic assessment of land functions for organic production

The article evaluates the functions of agriculturalland for organic production on the example of Lvivregion. An analysis of the suitability of land for organic agriculture in terms of humus content; easilyhydrolyzed nitrogen; by the content of mobile phosphorus compounds by the Chirikov method; on the content of mobile potassium compounds by the Chirikov method in Sokal, Kamyanka-Buzka, Sambir,Radekhiv, Pustomyty districts of the region. It isestablished that the area of suitable lands in terms ofhumus content in the studied areas is 12,782,0 hectares; by the content of easily hydrolyzed nitrogen — 5,790,303; by the content of mobile phosphorus compounds — 7,829,655; on the content of mobile compounds of potassium — 10,342,428 hectares and in these areas it is quite possible to introduce organic agricultural production. This analysis is found to be incomplete. Therefore, we present a scheme-algorithm for identifying factors influencing the formation of the economic assessment of land functions for organic production. According to which the assessment of the functions of land for organic production should be carried out: through the prism of identification of three groups of factors influencing the assessment; at each stage of implementation of this process (preimplementation stage, transition stage, implementation stage); identification of key indicators that will improve the assessment of land functions for organic production, calculation of the integrated assessment indicator. We propose to define this indicator as the sum of the obtained binary characteristics according to the i-th (i = 1/k) characteristic of land function assessment for organic production, which may be due to the nth environmental, economic or social factor influencing the formation of adequate land function assessment management of organic agriculture at a certain stage of implementation of this process. Our proposed approach allows for a detailed analysis of land functions for organic production and to establishthe degree of their impact on the effectiveness of theassessment of land functions.

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.

Effect of asphalt emissions on the health of workers, Najaf City - Iraq A case study

Human activities have the greatest impact on environmental change and natural biological disruption, and there are many forms of this change, whether in the environmental climate, such as the rapid loss of biodiversity and lack of land suitability for agriculture, or the rise in temperature as a result of human changes or environmental health impacts. This research included detecting the effect of asphalt plant pollution on physiological blood parameters for workers in these plants by estimating certain blood markers in samples from 30 workers of different ages, and exposure periods included blood WBC, HGB, HCT, PLT and CO2. The findings showed that the WBC values showed that 93% of employees were above the usual limit, while 84.4% of employees had higher concentrations than control group values, 99% of workers had concentrations above usual HGB levels, while 43% had concentrations below control group values, 86.8% had concentrations below c. 66% of workers have a record lower than the control group 33.4% exceeded the control group values, the results of laboratory CO2 analyzes show that 90% of the CO2 concentrations of this indicator are outside the natural limits and that 100% of the CO2 concentration of workers in their blood is higher than that of the control group.

Comparison between two multicriteria methods for assessing land suitability for agriculture: application in the area of Mleta in western part of Algeria

In order to facilitate the decision making in spatial applications, several methods are available to aggregate the performance of decision-makers. The multitude of these methods makes it difficult to choose one method over another. Two main types of methods are used, the outranking methods which are based on bottom-up approach and the hierarchical analysis methods which are based on top-down approach. These methods can be adapted to this kind of applications and can be integrated into GIS which is an essential tool in spatial management and decision making. Methods developed according to the first approach are different from those developed in accordance with the second one. This study aims to present a comparison between two multicriteria decision-making methods ELECTRE (Elimination Et Choix Traduisant la REalite) Tri and AHP (Analytic Hierarchy Process) to assess land suitability for agriculture. Twelve criteria [water reserve easily utilizable, drainage, permeability, potential of hydrogen (pH), electrical conductivity, active limestone, cation exchange capacity, soil texture, soil useful depth, slope, availability of labor, proximity (roads)] grouped in five factors (agronomic, planning, land enhancement and improvement, soil conservation and environment protection, and socioeconomic conditions) were used in this study. An application has been carried out on the area of Mleta in Algeria. Two land suitability maps for durum wheat have been produced by the two procedures (optimistic and pessimistic) available in ELECTRE Tri, and another map has been obtained by AHP. After the comparison between the obtained results, it was apparent that ELECTRE Tri is more appropriate for the land suitability assessment for agriculture despite its complexity given the large number of required parameters. The subjective parameters available in ELECTRE Tri make it possible to take into account imprecise data. Another advantage of this method lies in the way of the decision-makers' preferences aggregation and the assignment of the land units to classes of predefined categories.