Qualitative Land Suitability Evaluation Research Articles

Quantitative and qualitative land suitability assessment for rice cultivation, north of Iran

<p>Evaluation of arable lands and agricultural potential to support current and future agricultural uses is one of the best agricultural policies for food security in developing countries. Hence, studies related to land suitability evaluation can lead to sustainable land use. The aims of this research were qualitative land suitability evaluation, land production potential prediction and quantitative land suitability evaluation on the basis of the FAO model for rice in Sangar region, northern Iran. Qualitative evaluation was carried out using the maximum limitation and parametric methods. Land production potential was determined by the agro-ecological zoning (AEZ) model. Land suitability classes according to maximum limitation, Storie and square root parametric methods are determined S3, S3-N1 and S2-S3, respectively. Rice radiation-thermal production potential was calculated as 7.65 t/ha; mean land production potentials, using Storie and square root formulas were predicted respectively, as 3.69 and 4.52 t/ha and mean actual yield was estimated as 2.81 t/ha. The results of this study showed that use of the square root formula is more appropriate than Storie formula as far as land production potential calculation is concerned. Soil limitations and weak management level have caused majority of land units to have moderate quantitative suitability (S2) for rice cultivation. Comparison between qualitative and quantitative suitability classes demonstrates that quantitative suitability classes are significantly increased due to crop adaptation with climate agents.</p>

Using a fuzzy logic decision system to optimize the land suitability evaluation for a sprinkler irrigation method

Land evaluation for irrigation is the process of predicting land use potential on the basis of soil attributes. The Food and Agriculture Organization (FAO) framework for land suitability evaluation is the most commonly used and is based on the biophysical properties of lands. The FAO framework method for land suitability application Boolean approach that has been criticized by some researchers. Because the Boolean representations ignore the continuous nature of soil and uncertainties in measurement and also its inability for overcoming problems related to vagueness in definition and other uncertainties, fuzzy set methodologies have been proposed. In the present study, the qualitative land suitability evaluation for sprinkler irrigation using parametric-based FAO learning and fuzzy inference system was carried out in an area of 5175 ha in Northwest Iran. By overlaying the layers (soil texture, soil depth, lime, electric conductivity, drainage, and slope) and use of spatial data modeler in ArcGIS 9.3, land evaluation maps for sprinkler irrigation were provided for the area under study. Results showed that based on the parametric approach, 1598 ha of the study area were classified as highly suitable (S1 class) for sprinkler irrigation; the area of highly suitable lands in the parametric method was about five times the area of highly suitable lands obtained through the fuzzy method. In addition, the two methods were completely different in determining moderately suitable lands (S2). Accordingly, 787 ha in the area was moderately suitable using the parametric method, which was about two times that obtained through the fuzzy method. This showed the significant difference between two methods applied to evaluate the lands. Moreover, fuzzy approaches accommodate the continuous nature of some soil properties and produce more intuitive distributions of land suitability indexes.

Assessment of land suitability for Norway maple and black locust plantations in the northeast of Iran

In the present study the qualitative land suitability evaluation by parametric and analytic hierarchy process (AHP) approaches was investigated for two tree species including Norway maple and black locust in the Toroq watershed, a semiarid region, in the northeast of Iran. The values of land suitability indices by the parametric approach for Norway maple and black locust plantations ranged from 22.46 to 67.50 and 23.23 to 75.11 respectively, while by the AHP approach they varied between 35.91 and 84.58 for Norway maple and from 32.87 to 94.31 for black locust plantations. The suitability classes for both tree species by the parametric approach were classified into moderately suitable in the eastern part of the basin, and not suitable in the middle and western parts of the study area. According to the AHP approach the suitability classes varied from highly suitable in some parts in the east to moderately suitable in the middle, east and some parts in the west and not suitable in some parts in the north and southwest of the basin.

Parametric-based neural networks and TOPSIS modeling in land suitability evaluation for alfalfa production using GIS

Land evaluation is the process of predicting land use potential on the basis of its attributes. In the present study, the qualitative land suitability evaluation using parametric based neural networks and TOPSIS models was investigated for irrigated alfalfa production in Joveyn plain, Northeast of Iran. Some twenty-six land units were studied at the study area by a precise soil survey and their morphological and physicochemical properties. Our results indicated that the most limiting factor for alfalfa cultivation in the study area was soil fertility properties. The values of land indexes by neural networks model ranged from 46.39 in some parts in east and west to 75.91 in the middle parts of the study area, which categorized the plain from moderate (S3) to high (S1) suitable classes. The TOPSIS preference values for alfalfa cultivation in the study area varied between 0.388 and 0.773 which classified from moderate to very high classes. The coefficient of determination revealed a high correlation between the output results of two models (R2 = 0.961).

Modeling land suitability evaluation for wheat production by parametric and TOPSIS approaches using GIS, northeast of Iran

Land evaluation is the process of predicting land use potential on the basis of its attributes. In the present study, the qualitative land suitability evaluation by parametric and TOPSIS models was investigated for irrigated wheat crop based on FAO land evaluation frameworks (FAO 1976a, b, 1983, 1985) and the proposed methods by Sys et al. (1991b) and Hwang and Yoon (1981) in Joveyn plain, Northeast of Iran. Some 26 land units were studied at the study area by a precise soil survey and their morphological and physicochemical properties. The climatic and land qualities/characteristics for wheat crop were determined using the tables of soil and crop requirements developed by Sys et al. (1993). An interpolation function was used to map values to scores in terms of land qualities/characteristics for the land utilization type and the evaluation was carried out according to parametric and TOPSIS models. Our results indicated that the most limiting factor for wheat cultivation in the study area was soil fertility properties. The values of land indexes by parametric model ranged from 62.71 in some parts in east and west to 87.24 in the middle parts of the study area, which categorized the plain from moderate (S2) to high (S1) suitable classes. The TOPSIS preference values for wheat cultivation in the study area varied between 0.438 and 0.916 which categorized from moderate to very high classes for wheat production. The coefficient of determination between the parametric land index values and the corresponding TOPSIS preference values revealed a high correlation (R 2 = 0.961) between two models. The correlation coefficient (R 2) between the parametric land indexes and TOPSIS preference values with the observed wheat yield varied between 0.943 and 0.861, respectively, which verify the validation of both models in estimating land suitability for irrigated wheat production in the study area.

Land suitability modeling by parametric-based neural networks and fuzzy methods for soybean production in a semi-arid region

Land evaluation is the process of predicting land use potential on the basis of its attributes. In the present study, the qualitative land suitability evaluation using parametric learning neural networks and fuzzy models was investigated for irrigated soybean production based on FAO land evaluation frameworks (FAO 1976, 1983, 1985) and the proposed methods by Sys et al. (1991c) and Hwang and Yoon (1981) in Neyshabour plain, Northeast of Iran. Some 41 land units were studied at the study area by a precise soil survey and their morphological and physicochemical properties. The Climatic and land qualities/characteristics for soybean crop were determined using the tables of soil and crop requirements developed by Sys et al. (1993). An interpolation function in GIS was used to map values to scores in terms of land qualities/characteristics for the land utilization type. Our results indicated that the most limiting factor for soybean cultivation in the study area was soil fertility properties. The values of land indexes by neural networks model ranged from 29.77 in some parts in west and middle to 57.45 in the north west and east parts of the study area, which categorized the plain from marginally suitable (S3) to moderately suitable (S2) classes. The land index values by fuzzy model varied between 16.10 and 47.80 which classified from marginally not suitable (N1) to marginally suitable (S3) classes. The coefficient of determination between the neural network land index values and the corresponding fuzzy values revealed a high correlation (R 2 = 0.966) between two models. The exponential regression coefficient (R 2) between the land indexes of neural networks and fuzzy models with the observed soybean yield in the study area varied between 0.610 and 0.514 respectively, which revealed higher performance of neural networks in predicting land suitability for irrigated soybean production in the study area.

Qualitative Land Suitability Evaluation by Parametric and Fuzzy Approaches for Sugar Beet Crop in Sabzevar Plain, Northeast of Iran

Land evaluation is the process of predicting land-use potential on the basis of its attributes. In the present study, the qualitative land suitability evaluation by parametric and fuzzy approaches was investigated for sugar beet crop in Sabzevar plain, Northeast of Iran. Our results indicated that the most limiting factor for sugar beet cultivation in the study area is soil organic carbon. In both models, the suitability classes for sugar beet cultivation were classified into high (S1) in north parts of the plain to moderate suitable (S2) due to lower values of soil organic carbon in southwest and scattered part in the center of the plain. The values of land indexes by parametric and fuzzy logic approaches ranged from 60.55 and 50.50 in some parts in the center and south west to 84.95 and 83.20 in the northern parts of the plain, respectively. The coefficient of determination between the results obtained from both models was R 2 = 0.995, which shows a high correlation between the calculated land index values from two approaches. The correlation coefficient between the land index values and the observed sugar beet yield (R 2) varied between 0.86 and 0.94 by parametric and fuzzy approaches which verify the validation of both models in estimating land suitability for sugar beet production in the study area.

Qualitative Land Suitability Evaluation for Wheat and Barley Crops in Khorasan-Razavi Province, Northeast of Iran

Land evaluation is applicable both in areas where there is strong competition between existing land uses in highly populated zones as well as in zones that are largely undeveloped. In the present study, the qualitative land suitability evaluation based on parametric approach of multi criteria method was investigated for selected crops, including wheat, maize, and cotton, based on FAO land evaluation frame works in 39 plains of Khorasan-Razavi, northeast of Iran. Climatic and land qualities/characteristics for selected crops were determined using the tables of crop and land evaluation. On this basis some 15 soil physical and chemical parameters from 33 soil profiles were collected and interpolated ArcGIS ver.9.3 for preparing the qualitative land suitability evaluation maps. The interpolated qualitative land suitability maps for both crops were finally divided into 39 plain polygons of Khorasan-Razavi after the ArcGIS zonal statistic extension. The results of land suitability evaluation for wheat and barley crops revealed that the plains of the study area belong to land classes from moderately suitable (S2) to currently non-suitable (N1). The results of qualitative land suitability evaluation for selected crops indicated the priority of barley cultivation over wheat at the study area.

Qualitative Land Suitability Evaluation for Main Irrigated Crops in the Shahrekord Plain, Iran: A Geostatistical Approach Compared with Conventional Method

The purity of soil map units and their quality for various uses like land suitability evaluation are always questioned. The main objective of this study was to compare the precision of qualitative land suitability classification based on geostatistical and conventional soil mapping methods for main irrigated crops in the Shahrekord Plain, Central Iran. A regular grid sampling method consisting 104 sample points was designed and soil samples were collected. Ordinary kriged maps were achieved for all studied soil attributes after physico-chemical analyses. Afterward, to combine kriged maps and ecological requirements of the studied crops, a script was designed in ILWIS 3.4 software and consequently, kriged qualitative land suitability maps were generated. Conventional qualitative land suitability was also mapped based on the representative pedon analysis in each soil map unit. Finally, comparison of the conventional and kriged maps was carried out using the statistical method, error matrix. The results showed that the overall accuracies of wheat, sugar beet, potato and alfalfa maps were 39.8%, 24.3%, 18.7% and 18.6% at subclass category, respectively, whereas these values increased to 80.9%, 82.3%, 23.7% and 82.3% at class level, respectively. Hence, it can be stated that thanks to the relative facility of conventional soil survey compared with geostatistical methods, this method can be expressed as a preferable way for handling a usual land suitability evaluation design; but using soil map units as land suitability delineations may lead to unsatisfactory results in estimation of quantity and type of existing limitations.

Qualitative Land Suitability Evaluation for the Growth of Rice and Off-seasons Crops as Rice Based Cropping System on Paddy Fields of Central Guilan, Iran

Land suitability evaluation analysis is a necessecary to achieve optimum management and utilization of the available land resources for sustainable agricultural crops production. One of the most serious and urgent constraint in lowland paddy fields of Iran is to improve agricultural land management and cropping patterns either to increase the agricultural production with proper land use resources or to get more income from out of season plant as a second crops.Therefore, the objective of this study was to find the most suitable off-season crops after rice. Qualitative Land Suitability (QLS) classification of fifteen first and second agricultural crops in the paddy fields of the Guilan plain in Iranunder RBCS that covers an area of 40567 ha was carried out. By using the semi-detailed method of soil classification, 24 soil unites at 11 soil series in five different physiographic units were indentified (river alluvial plains (5 series), low lands (2 series), river banks (2 series) and coastal plains and sand dunes (2 series)). Land and climate characteristics of each crop with its requirements were also determined and rated based upon Parametric and simple limitation method proposed by Sys et al. [1]. The obtained indexes indicated that land suitability classes varied from S2 (moderately suitable) to N (Not suitable). The highest land suitability class for crops are: S2 for Rice, Spinach, Beans, Radish, Garlic, Shall cress, Clover, Lettuce, Rape seed, Bean (vulgaris and faba cultivars) and S3 for Wheat, Carrot, Barley, Triticale, and Rice (Ratoon). The most important limiting factors are: climate (low temperature and high rainfall at vegetative and reproductive growth stages), drainage (shallow water table depth), soil (texture) and fertility (low organic carbon content, pH) (alone or in combination) respectively, those influence adversely on the land suitability classes, especially climatic and drainage limitation, because of growing season in autumn and winter Verification of the factors and their relative significance is very important for decision on land suitability.Keywords: Land Suitability, Paddy Fields, Rice, Second Crops.

Qualitative land suitability evaluation for Tobacco (Nicotiana tabacum) in Talesh, Iran

Land suitability assessment was conducted for flue-cure Tobacco (Nicotiana tabacum) in an area including 2880 ha in Talesh site in Guilan province, north of Iran. Using the findings of the semi-detailed soil studies for this area, 18 land units were selected. Then morphological and physico-chemical properties were determined. The results showed that soils were in three orders (Inceptisols, Entisols and Alfisols). The simple limitation method, the limitation method regarding number and intensity (second method) and the parametric methods including the Square root and the Storie methods were used for qualitative land suitability evaluation. Results of simple limitation method and the limitation method regarding number and intensity showed similar marginally suitability classes (S3). According to these methods, the major limiting factors were climate (total rainfall), fertility (pH and CaCO3) and physical soil (texture) characteristics. In addition, the results of Storie method showed unsuitable condition (N2) for all of land units. The results of root square method showed non-suitable but correctable conditions (N1) for 13 land units and unsuitable condition (N2) for other land units. Based on these results (especially on those obtained with the parametric square-root method, which seems to be the best), the cultivation of tobacco cannot be recommended for this area. Key words: Flue-cure tobacco, land suitability, qualitative land evaluation, soil characteristics.

Qualitative Land Suitability Evaluation for Growth of Wheat in Northeast of Iran

Qualitative Land Suitability Evaluation for Growth of Wheat in Northeast of Iran

Qualitative land suitability evaluation for the growth of onion, potato, maize, and alfalfa on soils of the Khalat pushan research station

An area suitability assessment for crop production requires a considerable effort, which can provide necessary information for optimum land use. Agricultural land use has benefited significantly from the use of suitability systems in recent years. These systems have jointly showed their capabilities in the evaluation and assessment of suitable sites for a variety of crops.