Soil science
Sahar Akhavan; Ahmad Jalalian; N. Toomanian; N. Honarjoo
Abstract
IntroductionLand suitability analysis and land use mapping are one of the most practical applications of Geographic Information Systems in land resource management. Complexities in soil have briefly limited studies on how it functions (Karlen, 2008). There are many methods from different centers including ...
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IntroductionLand suitability analysis and land use mapping are one of the most practical applications of Geographic Information Systems in land resource management. Complexities in soil have briefly limited studies on how it functions (Karlen, 2008). There are many methods from different centers including food and agriculture organizations (FAO), to evaluate land suitability. These methods are based on the characteristics of the land and the needs of the plant. Soil quality indicators are a set of measurable soil characteristics that affect crop production or the environment and are sensitive to land use change, management or conservation operations. (Brejda, 2000; Aparico and Costa, 2007). As a result, there is a global need for environmental issues, improvement of soil quality assessment methods for sustainable agricultural development and recognition of the sustainability of soil management and land use systems. Until now, various methods have been used to collect data, measure and evaluate soil quality, and laboratory analysis is the most common method, which has the advantage of being easy to use and characterizing and the quantitative characteristics of the test on different soil quality indicators (and Wang, 1998 Gong). Criteria for soil quality indicators should be a set of physical, chemical, biological characteristics or a combination of them (Doran and Parkin, 1997).Materials and MethodsIn the present study, the qualitative assessment of land suitability was investigated using fuzzy and parametric hierarchical analysis process models for the irrigated wheat and alfalfa crops. Soil characteristics, climatic conditions, topography and accessibility were selected based on the Food and Agriculture Organization framework and expert opinions. The interpolation function was used to plot values to points in terms of quality/ terrain characteristics for the type of operation and the evaluation was performed based on parametric and fuzzy analytical hierarchy process models. The process of evaluation is based on the FAO qualitative land evaluation system (FAO 1976a, b, 1983, 1985), which compares climatic conditions and land qualities/characteristics including topography, erosion hazard, wetness, soil physical properties, soil fertility, and chemical properties, soil salinity and alkalinity with each specific crop requirements developed by Sys et al. (1991a, b, 1993). Based on morphological and physical/chemical properties of soil profiles some 10 land units were identified in the study area.Climate data related to different stages of wheat growth were taken from ten years of meteorological data of the region (2007-2017) and the climatic requirements of the crop were extracted from the Table developed by (Sys et al., 1993). An interpolation technique using the ArcGIS ver 10.3 helped in managing the spatial data and visualizing the land index results in both models for preparing the final land suitability evaluation maps. The FAHP method and (Chang, 1996) method, which is a very simple method for generalizing the hierarchical analysis process to the fuzzy space, was used in order to assign weight to the criteria through. This method is based on computational mean of the experts’ opinion and the time normalization method and the use of triangular fuzzy numbers. A pairwise comparison matrix has been made fuzzy based on the experts’ opinion and using the triangular fuzzy numb. After calculating the weights of the criteria in the present research through the FAHP method, the entire criteria maps were overlaid through the use of the GIS function and the suitability maps were prepared for the main criteria. The main suitability maps went through weight overlaying eventually and the final map of suitability for wheat and alfalfa cultivation was produced. Results and DiscussionThe results of this study showed that the FAHP was an efficient strategy to increase the accuracy of weight allocation to criteria that affect the analysis of ground fit. The inability of conventional decision-making methods to account for uncertainty paves the way for the use of fuzzy decision-making methods. One of the drawbacks of the AHP is its inability to account for the uncertainty of judgments in pairwise comparison matrices. This defect is compensated by the FAHP method. Instead of considering a specific number in a pairwise comparison, a range of values in the FAHP is used for uncertainty for decision makers. The present research method can be useful for prioritizing lands, improving exploitation, conserving resources, and creating sustainable management. The results of this study, considering the main criteria of cultivation in the study area and the opinion of domestic experts, can provide useful insights into choosing the appropriate cultivation pattern in the region. The use of different fuzzy AHP methods as well as comparing the results of different fuzzy AHP methods in future research is recommended.
Soil science
M. Eskandari; A. Zeinadini; M.N. Navidi; A. Salmanpour
Abstract
IntroductionSaffron, which its cultivation is compatible with the arid and semi-arid climate of Iran, is one of the most valuable agricultural products in the world. Therefore, the cultivation of this crop in different parts of the country has been enormously developed in recent years. More than 95% ...
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IntroductionSaffron, which its cultivation is compatible with the arid and semi-arid climate of Iran, is one of the most valuable agricultural products in the world. Therefore, the cultivation of this crop in different parts of the country has been enormously developed in recent years. More than 95% of the world production of this precious product is allocated to Iran, which is mainly located in the two provinces of Khorasan Razavi and Southern Khorasan. The objective of this study was to determine the priority of lands for saffron cultivation by using TOPSIS method. Furthermore, in this study, TOPSIS, which is the second most widely used approach among multi-criteria decision making methods, was compared with the conventional parametric one to assess the land suitability for saffron production.Materials and MethodsTo achieve the objective of this study, 135 saffron farms in Khorasan Razavi, Southern Khorasan, Fars, Markazi and Kerman provinces were selected. In each farm, one pedon was dug and studied in detail. Soil samples were collected from different horizons of the pedons and taken to the laboratory for the designated physicochemical analyses. The average quantity of saffron yield in the last three years was recorded for each study point. The selected areas did not have climatic restrictions for saffron cultivation. For this purpose, in addition to local experience, the climate suitability index was calculated using the saffron climatic requirement table by its phenological period in each region. The effective soil criteria conditioned on the saffron yield were obtained using statistical analyses. By constructing a decision matrix and normalizing it, weighting the criteria by ranking order method and constructing a weighted matrix, determining the positive and negative ideal and then calculating the relative proximity of each alternative to the positive ideal, the preference of each alternative by TOPSIS method for saffron cultivation was determined. Then, the prioritization of alternatives was compared with the actual yield of saffron. Soil suitability index was also calculated using the table of soil and landscape requirements for saffron, and then compared with actual yield. Finally, the two schemes were validated and compared with each other.Results and DiscussionThe climate suitability index for saffron cultivation in the five studied areas indicated that the climate conditions in all areas were relatively similar. Consequently, soil properties can be considered as the only factors affecting the priority of lands for saffron cultivation in the studied areas. The results further revealed that three variables of lime content, salinity and exchangeable sodium percentage of soils under saffron cultivation in the country were higher than the critical level for saffron production. Therefore, these three variables are considered as the most important soil properties affecting the saffron yield. The order of weights assigned to the variables included salinity, exchangeable sodium percentage, lime, gravel, gypsum, organic carbon and soil reaction. Comparison of the order of priority of 135 options by TOPSIS with the actual yield of saffron showed an acceptable accuracy (R2 = 0.92) for this method. The soil index calculated by the parametric square root method for 135 soil profiles was also compared with the actual yield. The coefficient of determination obtained in this case was about 0.9, showing that TOPSIS was able to determine the suitability of lands for saffron cultivation better than the parametric method. Due to the ability of TOPSIS to evaluate a large number of evaluation criteria, this method is superior to the parametric method, which can consider a maximum of eight criteria in estimating the index.ConclusionThe outcome of this study showed a high accuracy of TOPSIS method in determining land suitability for development of saffron cultivation. This method is well able to use a large number of criteria that have negative or positive effects on the priority of alternatives. Furthermore, depending on the conditions of the decision making problem, one of the methods of weighting the criteria can be employed and combined with the TOPSIS method. The high accuracy of this method can be attributed to the use of mathematical relationships and matrices, data standardization by Euclidean soft method, and the nature of comparing both distances from the positive and negative ideals.
Soil science
A. Farajnia; K. Moravej; P. Alamdari; M. Eslahi
Abstract
Introduction: FAO agro-ecological model determines the production capacity, creating a logical relationship between the natural potential of the environment, the needs of communities, human activities, and sustainable adaptation. With the development of plant growth simulation models, researchers have ...
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Introduction: FAO agro-ecological model determines the production capacity, creating a logical relationship between the natural potential of the environment, the needs of communities, human activities, and sustainable adaptation. With the development of plant growth simulation models, researchers have begun a large-scale effort to agroecological zoning of various crops on a regional scale. In this method, an area was divided into homogeneous units with maximum similarity in terms of climate and land characteristics. Then, the potential yield map predicted by a simulation model is used for zoning. Pistachio is a subtropical plant that has long been cultivated in the central areas of Iran. With the occurrence of drought in the last two decades, farmers cultivated Pistachio in East Azerbaijan province without considering this crop requirement. This study aimed to use the AHP model to evaluate the suitability of East Azerbaijan lands for cultivating pistachio.
Methods and Materials: East Azerbaijan province is located in the northwest of Iran, between the latitudes of 36˚ and 45' to 39˚ and 26' N and the longitudes of 45˚ and 5' to 48˚ and 22' E based on the geographic coordinate system. The area of the province is 45800 square kilometers. The climate is generally cold and semi-arid, but it has different climates due to its diverse and extensive topography. The area of agricultural lands is estimated to be 18,000 square kilometers, which is about 39% of the total area. In this research, climatic data were collected for 30 years from Tabriz, Jolfa, Mianeh, Sarab, Maraghe, and Malekan synoptic stations, and from four neighboring stations of Orumieh, Khoy, Miandoab, and Parsabad. Three criteria (i.e. climate, land, and soil) and 11 sub-criteria were studied. The sub-climatic criteria included the average temperature of the growing season, average temperature in the pollination stage, absolute minimum temperature in the coldest month of the year, and average percentage of relative humidity in the flowering stage. Land criteria were land use sub-criteria, land slope, and slope directions, and soil criteria were salinity (electrical conductivity of saturated extract), pH, soil texture, and soil lime content (CaCO3). The results of the analysis of about 9000 soil samples were prepared for zoning of soil factors from East Azerbaijan Agricultural and Natural Resources Research Center. Land characteristics of slope map and aspects were prepared from the digital elevation map of the study area and land use map was obtained base on the map provided by the Forests and Rangelands Research Institute of Iran. The parameters were then weighted upon AHP by the parameter importance for each region. Data were transferred to Expert Choice software and clustered, rated, integrated for producing the final layer.
Results and Discussion: According to the AHP model, there are no entirely suitable class areas for pistachio cultivation in East Azerbaijan province. Because one or more factors or sub-criteria created low restrictions for the cultivation of this crop. The results showed that 3887 square kilometers or 8.5% of the area was classified as a relatively suitable class. Although this area has low restrictions for pistachio planting, the profitability of this complex has increased the area of pistachio orchards rapidly. The suitable lands are mainly located by the agricultural lands and if water requirement could be met, they can be allocated for planting. The low water requirement and tolerance to salinity compared to other crops can be considered as the advantages of cultivating pistachio. Since 1998, droughts have occurred in different areas of the province. It caused a decrease in agricultural products by up to 35%. The declining water level of Lake Urmia is one of the consequences of the recent droughts, deteriorating the groundwater quantity and quality. The 6250 square kilometers (13.6%) of the province's lands was classified as the critically suitable class. Some of the sub-criteria studied in these lands such as the average temperature of pollination period, the average temperature of the growth period, amount and direction of slope, and soil texture were in the critical classes. The 35663 square kilometers (77.9%) of the studied lands were found to be unsuitable (N). The main reason for the unsuitability was the very high salinity of lands, as seen in the soil salinity map. Although it is a modifiable factor, the lack of quality for leaching, heavy soil texture, and the impossibility of draining drainage due to flatness, render the reclamation of these lands impossible. Under the current situation, East Azerbaijan province is much more capable of planting this crop. However, it is necessary to conduct more detailed studies to avoid pistachio cultivation in marginal suitable lands.
Soil science
A. Zeinadini; M.N. Navidi; A. Asadi Kangarshahi; M. Eskandari; S.A. Seyed jalali; A. Salmanpour; J. Seyedmohammadi; M. Ghasemi; S.A. Ghaffarinejad; Gh. Zareian
Abstract
Introduction: Iran is one of the most important countries in citrus (oranges) production. Citrus fruits are grown in different soils with a wide range of physical, chemical and fertility properties in the country, although some restrictions in the cultivated lands cause yield loss. In this regard, the ...
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Introduction: Iran is one of the most important countries in citrus (oranges) production. Citrus fruits are grown in different soils with a wide range of physical, chemical and fertility properties in the country, although some restrictions in the cultivated lands cause yield loss. In this regard, the present study was conducted to investigate the effect of physical, chemical and soil fertility characteristics on citrus yield in important areas under cultivation, the regression relationships of characteristics with yield, and the rating of soil and land parameters. Materials and Methods: The 138 oranges orchards (118 orchards for rating and 20 orchards for validation) were selected in Fars, Mazanderan, Kerman and Guilan provinces. In each garden, a questionnaire was completed, a soil pedon was studied and soil samples were taken to carry out the appropriate physicochemical analyses. The selected soil and land characteristics were soil salinity (EC), exchangeable sodium percentage (ESP), pH, gypsum content, soil calcium carbonate (TNV), organic carbon (OC), clay, sand, silt, gravel, and soil available phosphorus and potassium contents. From the whole obtained data, 20 data were considered for validation purpose and the remaining data were used for modeling based on stepwise multivariate and simple regression methods. In these equations, the relationship between yield, as dependent variable, with soil and land characteristics, as independent variables, was investigated. Finally, land characteristics rating was obtained by the FAO method and the proposed crop requirements table was evaluated using the validation dataset. Results and Discussion: The results of descriptive statistics analysis showed that the variance values for available potassium, sand, clay, gravel and TNV were high and for pH and OC and gypsum were negligible. Therefore, most soil properties have a wide range of variation which could be related to the fact that oranges are grown in a wide range of soil types. The value of TNV varied between 10 and 33.3%. The presence of carbonate in soil reduces the availability of macro- and micronutrient elements in direct and indirect manners. The average of EC in the studied orchards was 5.4 dS.m-1. Minimum, maximum and average of ESP were 1.7, 28 and 10.7, respectively. The lowest and highest salinity and sodicity were observed in Mazandaran and Kerman soils, respectively. Maximum, minimum and average percentage of gypsum were 12, 0.36 and 3.54%, respectively. The highest amount of gypsum was observed in Bam and Shahdad regions of Kerman province and the lowest gypsum content was observed in Mazandaran and Guilan provinces. The soil pH varied from 6.63 to 8.8 with the average of 7.8. The soil OC values were between 0.05 and 3.53% and its average was 0.89%, showing the fact that the most studied soils were poor in organic matters. The average of soil available phosphorus and potassium in the studied orchards for citrus was less than the critical level. The average, minimum and maximum of available potassium were 224, 100 and 360 mg.kg-1, respectively. The mean, minimum and maximum amounts of available phosphorus were 21.6, 8 and 45.9 mg.kg-1, respectively. According to the multivariate regression model, among soil properties, EC, ESP, TNV, gypsum, gravel, available phosphorus and potassium were selected by the model. The determination coefficient of the model was 0.95, indicating that these properties have the greatest effect on citrus yield. Simple regression equations demonstrated that TNV, gypsum, EC, ESP, sand, clay, gravel, available potassium and phosphorous had the highest correlation (R2 > 0.6); and soil OC and pH had the lowest correlation (R2<0.2) with yield. The equations also revealed that soil EC, ESP, gypsum, TNV and gravel percentage had the greatest effect in yield loss, and soil organic carbon, absorbed phosphorus and potassium had the greatest effect on increasing citrus yield. As stated in equations, reported permissible and critical thresholds for effective soil properties on citrus yield, were 2.4 dS.m-1 for EC, 5 for ESP, 1.5% for gypsum, 20% for TNV, 22 mg.kg-1 for available phosphorus, 280 mg.kg-1 for available potassium, 110 cm for soil depth, and >2 m for groundwater level. Finally, evaluating the proposed crop requirements table with validation dataset fitted between citrus yield and soil index, resulted in the determination coefficient value of 0.79, denoting the acceptable accuracy of proposed table. Conclusion: Overall results showed that the main land limiting characteristics for orange production were soil salinity and sodicity, high amount of soil calcium carbonate and gypsum. Among unsuitable physical and fertility properties of soil, salinity and sodicity are the most effective factors affecting yield reduction. Consequently, proper management practices such as introducing cultivars compatible with these soil conditions, soil remediation and leaching operations to reduce soil salinity and sodicity are necessary. Furthermore, in most areas under orange cultivation such as Fars and Kerman provinces, the soil calcium carbonate content is more than the critical level for plant growth. In addition, the averages of soil available phosphorus and potassium were less than the critical levels, which should be considered for nutrient management of orchards. The proposed table of crop requirements seems to be accurate enough to conduct land suitability studies for orange varieties, especially cultivars grown in the north and south of the country.
H. Dialami; J. Givi
Abstract
Abstract Introduction: This research aimed to evaluate the qualitative land suitability for irrigated cultivation of Date Palm (Phoenix dactylifera L. cv Kabkab) using FAO (parametric -the second root formula) and Multi-criteria approaches. The FAO approach has been used by many scholars in different ...
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Abstract Introduction: This research aimed to evaluate the qualitative land suitability for irrigated cultivation of Date Palm (Phoenix dactylifera L. cv Kabkab) using FAO (parametric -the second root formula) and Multi-criteria approaches. The FAO approach has been used by many scholars in different parts of the world and Iran for land suitability assessment. In this approach, the most commonly used method is the parametric method. The FAO approach uses Boolean logic to assess land suitability. This logic has been criticized by a number of land evaluation researchers. Because it does not take into account the continuous nature of the soil variations along the earth's surface and the uncertainty in the measurements. To overcome these shortcomings, the fuzzy analytical hierarchy process (FAHP) was presented to determine the land suitability classes. Land suitability should be determined based on a fuzzy analytical hierarchy process, in which, unlike the Boolean logic, unequal importance of different land characteristics and continuity of soil variations are considered. Materials and Methods: The studied area is located in Kheshet and Komaroj plain, Kazerun County, Fars province, southwestern- Iran; between latitudes 29º 32΄ and 29º 36΄ N and longitudes 51º 20΄ and 51º 22΄ E. Its surface area is 5000 ha. The mean annual rainfall and temperature are 377mm and 23 °C, respectively. The soil temperature and moisture regimes are hyperthermic and xeric, respectively. The physiographic unit is river alluvial plain with a very gently sloping. The entire Kabkab date palm plantation of Fars Province is located in this plain. To fulfill the objectives 10 date palm groves, each with an area of at least 0.5 ha and palm date (Kabkab cultivar) cultivation, aged between 20 and 25 years, identical in soil management and vary soil characteristics were selected. A soil profile was dug randomly in each date palm grove, with dimensions of 1.5 (length), 1(width) and 1.5 (depth) meters and described, using soil profile description (Soil Survey Staff). Soil samples were collected from each horizon. After pre-treatments soil samples were analyzed and some physical and chemical characteristics were measured using standard laboratory methods. The profile site was chosen to have a date palm tree in each of the four corners of the profile. The yield of the four trees in four corners of each profile was measured and their average yield was considered as the yield of the corresponding profile. Meteorological data was collected for a period of 10 year from the nearest synoptic station (Kazerun). Land indices were calculated, using soil and climatic data and FAO (parametric-second root formula) and fuzzy AHP and AHP methods. Weighted average of the climatic and the soil data were used and a land index was calculated for each soil profile. In the fuzzy AHP and AHP methods, relative weight of each of the studied criteria was determined by analytical hierarchy analysis using a pair wise comparison matrix. In the fuzzy AHP method the membership degree for each soil and climatic criteria was determined through an appropriate membership function and finally, land suitability class for each soil profile was determined. Landscape characteristics such as slope, drainage and soil depth were not considered in the land evaluation, because these characteristics did not show any limitation for the date production in the studied area. Finally the accuracy of the methods was compared. Results and Discussion: The results of qualitative land suitability evaluation based on FAO (parametric-second root formula) method showed that about 10 and 90 percent of the studied area were classified as S2 and S3, respectively. Based upon fuzzy AHP method, 100 percent of the studied area was classified as S2 and according to AHP method about 90 and 10 percent of the studied area were in S1 and S2, respectively. According to the results, the suitability classes resulted from AHP method was higher than of the fuzzy AHP and FAO methods. Correlation coefficients between the measured yields and the calculated land indexes showed that the fuzzy AHP method results was more correlated to the measured yield than of the other two methods which indicated that the fuzzy AHP was the most appropriate method for land suitability assessment for Kabkab Date palm plantation compared to the FAO (parametric-second root formula) and AHP methods. Conclusion: According to the results of this research, the fuzzy AHP was the most appropriate method for qualitative land suitability evaluation for Kabkab Date in compared to the other two methods in Fars province, Iran.
Fatemeh Rahmati; Ardavan Kamali
Abstract
Introduction: Land suitability evaluation is a process to examine the degree of land fitness for specific utilization and also makes it possible to estimate land productivity potential. In 1976, FAO provided a general framework for land suitability classification. It has not been proposed a specific ...
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Introduction: Land suitability evaluation is a process to examine the degree of land fitness for specific utilization and also makes it possible to estimate land productivity potential. In 1976, FAO provided a general framework for land suitability classification. It has not been proposed a specific method to perform this classification in the framework. In later years, a collection of methods was presented based on the FAO framework. In parametric method, different land suitability aspects are defined as completely discrete groups and are separated from each other by distinguished and consistent ranges. Therefore, land units that have moderate suitability can only choose one of the characteristics of predefined classes of land suitability. Fuzzy logic is an extension of Boolean logic by LotfiZadeh in 1965 based on the mathematical theory of fuzzy sets, which is a generalization of the classical set theory. By introducing the notion of degree in the verification of a condition, fuzzy method enables a condition to be in a state other than true or false, as well as provides a very valuable flexibility for reasoning, which makes it possible to take into account inaccuracies and uncertainties. One advantage of fuzzy logic in order to formalize human reasoning is that the rules are set in natural language. In evaluation method based on fuzzy logic, the weights are used for land characteristics. The objective of this study was to compare four methods of weight calculation in the fuzzy logic to predict the yield of wheat in the study area covering 1500 ha in Kian town in Shahrekord (Chahrmahal and Bakhtiari province), Iran.
Materials and Methods: In such investigations, climatic factors, and soil physical and chemical characteristics are studied. This investigation involves several studies including a lab study, and qualitative and quantitative land suitability evaluation with fuzzy logic for wheat. Factors affecting the wheat production consist of climatic conditions like mean, maximum and minimum air temperatures during growing period as well as edaphologic properties like EC, pH, ESP, percent of clay, silt, sand, gravel, gypsum and CaCO3 content. Climatic data collected from the Shahrekord synoptic station were used to assess climatic land suitability for wheat. Qualitative land suitability evaluation was carried out using the fuzzy approach. Potential yield was calculated using the method proposed by FAO. Using MATLAB software, qualitative and quantitative land evaluation were classified based on fuzzy logic approach. In fuzzy method, climatic factors are used to achieve climatic index. Clay and sand percent were applied to calculate soil texture. To determine the membership degrees,bell membership functions were used. Parameters of function shapes were transformed to equations with variable coefficients and the best coefficients were eventually chosen based on the model determination coefficient. In evaluation method based on fuzzy logic, the weights are used for land characteristics. In fuzzy logic method, weights were calculated by four methods. These methods consist of neural network using 1 neuron and 4 neurons, multivariate and Partial Least Squares (PLS) regressions. Comparison of the coefficient of determination results of multivariate regression and RMSE is carried out between observed and predicted yield. Weight calculations were conducted by using MINITAB software to PLS and multivariate regression. Also, Neurosolution 5 was used for weight calculation based on neural network.
Results and Discussion: The calculated weights were differed by using the four applied methods. In all methods, the maximum weight was related to gravel, and minimum weight was related to clay. The results of land index and predicted yield calculation were different in some points (3, 6, 7, 13, 14, 19, and 21) for four methods. The coefficient of determination of calculated weights were 0.595, 0.56, 0.6 and 0.56 for neural network, 1 neuron, 4 neurons, multivariate regression and PLS and RMSE values in these methods were 6.38, 6.4, 6.38 and 6.38 Ton/ha, respectively. The correlation coefficient between the observed and predicted yield indicated the partially appropriate selection of the factors and evaluation approach.
Conclusion: The results of weight calculation were not showed significant difference in three methods (neural network, PLS, regression). The predicted yield was somewhat closer to the observed yield when 1 neuron was introduced to the neural network than 4 neurons. The maximum coefficient of determination as well as the minimum RMSE was achieved for weights calculated by multivariate regression. Because the method is almost accurate and easy to use, it is recommended in this study. The coefficient of determination generally became low because different traditional management practices were carried out in the study area. Finally, in regard to achieved results about the used methods, it is suggested to take into account the management factors in land suitability processes and compare the other weight calculated methods in land suitability evaluation based on fuzzy logic.
Mohammad Taleai
Abstract
According to predictions, due to population increase and income growth, demand for food will continue to rise by over 3% annually. Wheat with providing over 33% of global world foods is one of the main sources for food security and meeting the needs of increased population. Land suitability assessment ...
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According to predictions, due to population increase and income growth, demand for food will continue to rise by over 3% annually. Wheat with providing over 33% of global world foods is one of the main sources for food security and meeting the needs of increased population. Land suitability assessment (LSA) is one of the basic approaches for obtaining maximum profit while protecting environmental resources for future. In this context, the suitability of arable lands of Miyaneh County is assessed for rain-fed wheat based on the FAO model and Fuzzy-AHP-OWA technique in GIS environment. In this study, with considering regional conditions and previous scientific researches, 8 environmental parameters (depth and texture of soil, erosion, slope, elevation, rainfall, temperature and degree days), 3 economic parameters (cooperatives, distance to markets and communication lines) and a social parameter (force labor) are used for land evaluation. These parameters were aggregated in two-stage using OWA model. Resulted suitability maps based on environmental criteria and fuzzy linguistic quantifier (LQ) includes: at least one, few, some, half, many, most and all, illustrate an overall accuracy, 26.7, 61, 84.3, 57, 44 , 8, 38.5 and 22% respectively, in compared with ground truth map.The final suitability maps based on social and economical criteria present 21.5, 61.8, 88.2, 53.7, 39.6, 38 and 19.3% overall accuracy. Based on this research finding,the proposed approach based on Fuzzy-AHP-OWA has great potential to model land use suitability evaluation problem. In addition, from the used criteria climate, soil, slope, number of co-operatives, distance to markets and communication lines are most important in evaluating land suitability for rain-fed wheat
