جستجوی مقالات مرتبط با کلیدواژه « land evaluation » در نشریات گروه « کشاورزی »

Al land use changes pose a most serious challenge to agricultural production, resulting in the loss of fertile soil and food security. The present study was conducted to investigate the challenges associated with fertile agricultural lands in Iran as an attempt to examine and identify the different aspects of the threats agricultural lands are faced with. As a second step, the laws and regulations governing land use change in different countries and in Iran were reviewed and the general policies related to the protection of agricultural lands were examined.  The review of land use laws in Iran showed that, despite their abundance, they have suffered from poor law enforcement as a result of both social and historical reasons as well as a public negligence of and non-adherence to the laws. Evaluations of temporal changes in the growth and development of metropolises as provincial centers revealed that they had greatly expanded beyond their original limits to annex fertile agricultural lands in the suburbs to these large cities. The five-year statistics of the requests submitted for land use change in each province also revealed landlords’ increasing demands submitted for land use change motivated by more profits out of their property, which result in loss of fertile soil, decreased agricultural production, and endangered food security.

Climate has an important role in agricultural activities and can be examined from two perspectives. First, what locations are suitable for a specific plant, and second, what plants are suitable for a climate. The latter approach is less considered; thus in this study, it has been investigated by introducing a standard method (Sys method). The study area is located in Mako city. Climatic suitability evaluation was performed by numerical (parametric) method using the Maku Synoptic Station data for pistachio, almond, pears, plum, sour cherry and sweet cherry. The findings showed that except for pistachio, with marginally suitable class (S3), other plants were classified as moderately suitable class (S2) but the value of climatic index for each crop was different. The introduced method made it possible to identify the most important effective climatic factors for the cultivation of each plant and determine the most limiting factor in the phenological period. Such findings showed that there is a close relationship between crops, phenological period, climatic characteristic and location. Based on this, the most suitable plant or plant species can be selected for a region, using the phenological period of the plant and climatic characteristics. However, for sustainable development, other components of the land, such as soil and/or topography, should also be evaluated. In general, the introduced approach can be used as an efficient tool, both for choosing the most suitable plants in a climate and for choosing the most suitable place (in terms of climate) for specific plants.

The recently introduced concept of soil security stems from deep scientific concern about global soil degradation and its impact on sustainable development. Although land degradation is a physical process, its main drivers are rooted in the socio-economic and political environment. Soil security by integrating five dimensions, including soil condition and capabilities, soil biophysical aspects, as well as capital, covers the relationship and legislation of socio-economic and political factors affecting soil. Therefore, the aim of this study is to identify and validate soil security indicators with fuzzy Delphi technique.

The current research is applied in terms of its purpose and it is qualitative research in terms of the type of research. Also, the current research is a descriptive (non-laboratory) type of researches that was conducted with a survey method. The information needed for this research was mainly obtained through survey and library methods, and in this regard, secondary data such as scientific and gray documents and several reports of government documents that describe the studied area were used. The information required for this research has been collected according to the objectives determined by the questionnaire. In total, 30 experts in relevant departments and institutions were used to complete the study.

The results of the study showed that from soil capability aspect soil erosion rate index and in terms of soil organic carbon index have the most validity in measuring soil security. In relation to soil security, the index of cultural values has a high priority to measure soil security. Also, in this dimension, indicators of active soil science graduates, soil management skills and access to statistics and information were removed. In terms of soil capital, the index of total production is a highly reliable index for measuring soil security. In this dimension, three indicators of wet or dry agricultural land, trading value of land and benefit from irrigation water were removed. In the dimension of soil security legislation, the index of soil protection projects is mentioned as the most valid indicator for measuring soil security.

This study is the first attempt to collect indicators of five dimensions of soil security to evaluate soil security in Iran. Identification of soil security assessment indicators has led to obtaining a list of important indicators approved by the country's soil experts, which can be made available to other researchers in the future to assess the soil security situation in different parts of the country. According to the study process, a total of 38 indicators were identified and validated for each dimension of soil security. Finally, eight indicators were removed from this total in the study process.

Land evaluation and production potential modeling are essential for determining environmental production limitations and proper cultivation planning. It is the aim of the present study to estimate production potential using different regression models and to evaluate quantitatively land suitability for wheat cultivation in some calcareous soils south of Behbahan. To achieve these goals, semi-detailed soil studies of Sardasht region were performed to extract soil data for land evaluation. For qualitative assessment, the Sys Table and the square root parametric method were employed to define climatic and topographic specifications as well as soil conditions as the adaptability criteria for plant growth while unit yield and potential production were used as measures of quantitative assessment. Radiative thermal potential of wheat production, mean land production potential as determined by the square root method, and mean farmer production were measured to be 7121, 3885, and 3255 kg.ha-1 respectively, so that management level in most farms was categorized as intermediate (S2) while only 5% of the land farms were classified as non-suitable (N). It was concluded that the current decline in crop performance in some land units could be attributed to such limiting factors as lime, texture, salinity, and alkalinity. Production potential modeling by the standard and stepwise regression methods revealed coefficients of determination equal to 0.84 and 0.82 and standard errors (ME) of 0.52 and 0.59, respectively. This is while coefficients of determination calculated via the second- and third-degree estimation curve methods for linear modeling were 0.90, 0.91, and 0.92 with the corresponding standard errors of 0.51, 0.50, and 0.50, respectively. The third-degree estimation curve method that draws upon the FAO growth model to predict crop performance, therefore, seems to outperform the standard and stepwise regression models that only takes into account the effects of land characteristics and the observed performance. Thus, the proposed methods were found effectively capable of identifying production limitations of the lands in the study area for use in the optimal management and production potential modeling of wheat as a strategic crop in the region.

With the new concepts and goals defined under global ecosystem sustainability and the potential contributions of soil ecosystems to the sustainability of nature and natural resources, efforts have been made to redefine the role of the science of evaluation in achieving the goals thereby defined. Introducing the components of a sustainable ecosystem, the present study strives to explore the functions of soil ecosystem and to define the role of land assessment in developing a road map toward environmental sustainability. Although the science of evaluation serves as the foundation for decision and policy making processes, it has not yet been properly and systematically exploited to achieve optimally integrated resource management. Environmental assessment, no matter how it is employed, is still the missing link in decision and policy making processes as part of sustainable resource management. It, indeed, requires due consideration in all such processes as it plays a pivotal role in bridging all environmental, economic, and engineering disciplines. Land evaluation is a disciple that characterizes soil composition in terms of its quality, degradation, flexibility, safety, health, productivity, behavior, and efficiency and, in conjunction with an evaluation of soil ecosystem functions, defines the roles each of the soil characteristics plays in integrated land management.

Prioritizing different types of irrigation systems is essential for proper management of soil and water resources in the south of Ahar (9000 hectares). For this purpose, the physical and chemical properties of 44 soil profiles (soil texture, depth, lime, gypsum, salinity and alkalinity) were used and the ability of the soil to be irrigated using the limitations system as well as the suitability of the study area for the drip, sprinkler and surface irrigation systems were determined by parametric method. The application of the limitation system results showed that soil and topography were the most important limiting factors and the irrigation capacity of the study area was in classes III (arable land) and IV (limited arable land) with approximate extension of 75% and 25% respectively. Based on the results of the parametric method for surface irrigation application, only 4% of the land is classified as S1 (highly suitable) and S2 (suitable), S3 (relatively suitable), N1 (almost non-suitable) and N2 (non-suitable) with extension of about 31%, 46%, 17% and 2% in the study area. In addition, the southern parts of the area were not suitable for surface irrigation due to the high slope, and the lands for sprinkler and drip irrigation classified in S2 and S3 classes and covers 70% and 25% of the study zones and so the rest of the lands are more susceptible to sprinkler irrigation than drip ones. Based on prepared maps, about 5000 hectares of lands

Introduction:

 planning is essential for increasing production per unit area of strategic agricultural products. In this regard, land suitability evaluation is one of the most important key steps. While the FAO framework for land suitability evaluation is the most commonly used method, to overcome problems related to vagueness in definition and other uncertainties, methods such as Micro LEIS system models can be useful. Terraza, Cervatana and Almagra are the models of Micro LEIS package that are used to evaluate land suitability for agricultural activity. Considering the limitations in water resources required to produce this strategic product, the present research focuses on evaluation of Khodaafarin region lands suitability by Micro LEIS models for this utilization type.

Materials and Methods:

 This research was carried out in an area of about 16555 ha in Khodaafarin, an important region in agricultural production, located in East Azerbaijan province, northwest of Iran. The major geological formation is composed of Quaternary sediments with sandstone. According to climatic data from Khomarlo synoptic weather forecasting data station, the average annual precipitation and temperature of the region are 281 mm and 14.7 °C, respectively, and the soil moisture and temperature regimes are Aridic border to Xeric and Thermic. The study area was divided to 11 land units by geopedology method. In each land unit, a soil profile was dug, described and sampled for physico-chemical analysis. After preparing soil samples in the laboratory, soil physico-chemical routine analyses, which are important in soil classification and evaluation, were completed by standard methods, and then studied soils were classified by the 12th edition of soil taxonomy. To conduct land suitability investigations, three models of Micro LEIS package including Terraza (to determine bioclimatic deficiency), Cervatana (to determine land capability) and Almagra (to determine the suitability evaluation of the studied area) were used. Finally, according to adopted models, land capability and suitability class and sub-class were determined in actual and potential condition for sugar beet, and their maps were prepared by Arc Map 10.2.

Results and Discussion :

According to the results obtained from description of soil profiles and physical and chemical analyses, soils can be classified as a different family of Aridisols and Entisols on the basis of USDA soil taxonomy system. Based on the Terraza model, bioclimatic deficiency class for the studied utilization type is C3 (h2-f3) or h2 moisture deficit and f3 frost risk classes, whose combination leads to C3 final class. This class revealed that during the growth period, 2-5 months annually the temperature goes under biological zero and production would decrease by 20 to 40%. Therefore, it is recommended to have safe irrigation and frost risk management. The results of Cervatana model indicated that for slope, climate, erosion and soil limitations with various degrees, 77.01% of the study area was placed in S2 land capability class. Also, 18.16% and 4.83% were classified as S3 and N1 classes, respectively. Among the above-mentioned factors, soil depth limitation was identified as the most restrictive and climate as the mildest one all over the study area. According to S2 class suggested by the Almagra model, 82.98% of the study area is acceptable for this utilization type. Suitability class for 7.62% of the study area is S3, which would increase the costs. Also, 9.4% of the study area is never suitable for sugar beet due to intensive limitation of soil useful depth and texture, which leads to S5 class. The nature of the limiting factors in land units suggests that they might be resolved. Based on this fact, in 19.64% of study area suitability class can shift to the upper one due to land improvement, while in 22.99% of the study area it is impossible for such a shift. In other parts, although some of the limitations can be solved, land suitability class remains stable and only their sub-class changes.

Conclusion :

Considering land evaluation and the  nature and professional use of Micro LEIS system models, Terrraza, Cervatana and Almagra models should be used hierarchically. Hierarchical use of models can help reduce costs because it is designed as a multiple-stage approach of land evaluation that assesses various biophysical properties of lands step by step. Accommodation of the values related to the studied land properties within the specified range presented in the models indicates that these models are calibrated for evaluating this utilization type in north-west of Iran. Therefore, traditional evaluation systems can be replaced by Micro LEIS system. According to the obtained actual and potential suitability class for sugar beet, it seems that it is a reasonable utilization type in the study area. Land improvement does not have a significant effect on the rise of land suitability class and profitability; nevertheless, it is recommended to have pilot land improvement programs to find factors which might have been ignored and might bring about further limitations.

Determination of land suitability is one of the land evaluation methods that can determine the best use of land in each area. The purpose of this research was to determine the land suitability of Mirza Kuchak Khan's cultivation and industry fields based on the soil quality indicators and a geographic information system (GIS), and compare the results with those obtained by methods of land evaluation and root strategies. For this purpose, information on soil profiles and the amount of organic matter, phosphorus, nitrogen, potassium, zinc, drainage, texture, depth, topography, surface rocks and gravel, impervious layer depth, hydraulic conductivity, water holding capacity, electrical conductivity, reaction PH), calcium carbonate, and exchangeable sodium percent of the study area were collected. Land suitability classes based on the quality indices of fertility, chemical quality, and physical quality of soil were defined. The results showed that 27.4% of the land belonged to the very good class (S1), 62.83% of the land could be assigned to the suitable class (S2), 11.7% of the land was put in the low proportion class (S3), and 2.66% the land was in the inappropriate class (N). Also, based on the comparison of the results of the method based on the soil quality with the square root method, Kappa coefficient was 0.82, while it was equal to 0.38 for the Storie method.

Site selection is a key factor in any aquaculture operation which makes land use sustainable. This study was conducted to identify the appropriate sites for development of shrimp culture in the southern cost of Bushehr Province using geographical information systems (GIS) and Multi Criteria Evaluation (MCE) by creating a database of information layers, criterias and effective alternatives including pond construction (slope, elevation, land use types and soil thickness), soil quality (type, texture and pH of soil), sea water availability (distance to sea and type of water source), and social and economic infrastructure (population density and distance to roads, local markets, and hatcheries) were obtained from the Landsat 8 satellite images and processed in GIS environment. The constraint layer was excluded from the areas that were not allowed to implement shrimp farming. An Analytical hierarchy model was developed to identify and prioritize the most suitable areas for shrimp farming. The Landsat images and 13 thematic layers were analyzed using ENVI and GIS. By consolidating and overlaying the data layers, the final map of the appropriate places for shrimp farming was prepared and classified the area of study in four various zones (most suitable, suitable, moderately suitable and not suitable). The study revealed that 18781 ha (16%) was categorized in the most suitable group, 46899 ha (40%) was suitable, 47784 ha (40.7%) was moderately suitable and 3818 ha (3.3%) was not suitable. These results were consistent with field verification. The map accuracy was evaluated by the method of Relative Operating Characteristic (ROC). The result of ROC (0.749) indicated the validity of the presented model. The results of the present study can help to develope shrimp farms and increase diversity of the economic activities in the coastal zone.

Land suitability evaluation (LSE) may be considered as a worldwide accepted procedure to achieve optimum utilization of the available land resources for sustainable agriculture. The common LSE procedures, like the widely accepted “A framework for land evaluation” presented by FAO, however, do not consider variability of soil quality parameters; whereas, the soil quality and its suitability for different uses are influenced by highly variable land management strategies. Therefore, assessing the spatial variability pattern of environmental variables and their accumulative effects on land suitability for specific crops, is the key for achieving to thoughtful land use planning for sustainable use. The present study was done aimed to evaluation of spatial variability of land suitability for irrigated wheat in Zanjan plain using accumulated limitation scores and geostatistics.
The study area is located in the southern part of Zanjan city, northwestern Iran, between the latitudes 36° 33′ and 36° 40′ N and the longitudes 48° 23′ and 48° 37′ E, covering an area of about 7000 ha. A total of 85 sampling locations were designed using a systematic sampling grid with an interval of 1000 m and consequently, soil samples at all sampling sites were collected from the depths of 0–25, 25-50, 50–75 and 75–100 cm. The soil samples were taken to the laboratory, where they were air-dried and then passed through a 2 mm sieve. Prepared samples were subsequently analyzed for required soil properties in LSE (Sys et al., 1993) using standard methods. Besides, required climatic data for LSE were obtained from Znajan Synoptic Meteorological Station for a 50 years period (1961– 2011). Then, the limitation degrees for all of the important properties for wheat cropping were determined (Sys et al., 1993). Afterwards, the determined limitation degrees were converted to limitation scores using standard tables presented by Zhang (1989). Then, accumulated limitation scores were calculated for all locations and using an exponential equation, land-suitability membership scores were achieved. Finally, these scores were interpolated using ordinary kriging method in ArcGIS software (ver. 10.2; ESRI) and the final suitability map was produced.
The results showed that the climatic conditions for irrigated wheat was relatively good; so that the region received just 1 limitation score arisen from the mean temperature of the growing cycle. On the other hand, among the studied soil properties, the content of coarse fragments made some serious limitations for wheat farming in the studied area; so that more than half of sampling points showed moderate to very severe limitations in respect of this property. This high observed limitation of coarse fragments may be attributed to the youthfulness of studied soils; because according to Soil Taxonomy, the studied soils are mainly classified as Entisols, which are poorly developed and immature soils maintaining their rock structure to some extent. Other studied soil properties, like soil texture and calcium carbonate equivalent content, made no or slight limitations for wheat farming in the studied soils. Accumulated effects of limiting properties led to elevated limitation scores in some sampling locations, especially in northwestern parts of the area and consequently, their suitability classes were decreased. Attributing the specific land suitability classes to each sampling location based on the calculated limitation scores revealed some sharp variability in suitability classes thorough the relatively small distances, which seems to be less compatible with the widely accepted generality of soil continuity. Totally, the spatial distribution map of land-suitability membership scores showed appreciable variability thorough the area. This may suggest that the studied soil properties have relatively high short-range variations, which is originated from the soil substantial characteristics or management practices. Comparison of the interpolated suitability map with the point map revealed that the spatial variability pattern of land suitability for irrigated wheat was more gradual and more obvious in interpolated map.
Compared with common conventional land suitability procedures, continuous pattern of land suitability variation based on the fuzzy viewpoint to the soil variability, lead to more compatible results with the continuous nature of environmental variables. However, due to the long and short-range variations of various soil properties thorough the studied area, appreciable variations in land suitability for wheat farming was observed. Controlling this highly variable suitability of studied lands for irrigated wheat farming needs precise and thoughtful management strategies.

In this study evaluation of erosion rate in Bolhasan area locating in south Zagros wasperformed using six-factor FAO method. Inthis method estimation of soil erosion rate was done based on evaluating 6 factors including geology, soil, topography and slope, soil cover, land use, the current state of erosion and sediment production in the watershed. After grading all the factors in hydrologic units in study area, using the sum of these grades, the intensityof soil erosion was determined and was classified into six classes. The results showed that approximately 42% of soils of the study area are in class III and 58% in class IV that revisions in the management strategy in both classes is necessary. In order to analyze the most important factors of erosion in the study area TOPSIS method was used. Results confirmed that the current situation of erosion with the weight of 0.5855 is the most important factor of erosion in the study site. Then the next important factors of erosion were soil cover with score 0.4143, geology with score0.4141,land use with score0.4140, slope with score0.4138 and soil with score0.4135.In this study, combining the field observations with application of GIS caused a higher accuracy in evaluationprocess.

Land evaluation and its consistency with simulation model’s outputs could assist decision making to develop plants for cultivation. In this study land suitability and potential yield of cumin was determined using CUMMOD and sum of values method by climatic and topographic factors, respectively, as a case study in Khorasans provinces. Results revealed that despite of the majority of favorable and completely favorable zones, potential yield was not the same in studied provinces. The CUMMOD results revealed that southern, a part of central and a part of northern areas of northern Khorasan province have considerable capability to produce cumin (2.5 to 3 ton ha-1). Potential yield was in two classified ranges as 2- 2.5 ton ha-1 and < 2 ton ha-1, while, predicted potential yield for central and southern parts of South Khorasan province was <2 ton ha-1 and 2-2.5 ton ha-1 for corresponding northern parts. Slope and aspect for northern, aspect and maximum temperature for Razavi and maximum temperature for southern Khorasan were the most limiting factors. In this study, although limiting factors were detected, but the majority of zones were located in favorable and completely favorable zones, because sum of values method avoids exaggerated effects of some factors. Therefore, results are more realistic. Overall, our results confirmed that the potential yield will decrease along with moving from northern Khorasan province toward South Khorasan province, which stems from shortening of the growing season.

This study was conducted to evaluate land suitability in Zarinshahr and Mobarakeh areas located in Isfahan Province using Analytical Hierarchy Process (AHP) technique. The hierarchy structure for evaluation was established to select the proper land use for 32 land units. Two alternative land utilization types (the cultivation of wheat and rice) were selected at the lowest level. The intermediate levels of the hierarchy were comprised of seven criteria for evaluating the alternative land uses including soil، climate، gross income، water resources، market، physical environmental impacts and chemical environmental impacts. The weight for each element was calculated using 30 questionnaires which were completed by experts and software EXPERT CHOICE 2000. Then the overall weight for each land use was obtained by multiplying standardized attributes and local weights. The results showed that maximum and minimum calculated land indices for wheat cultivation were 77. 4 (unit 2-3) and 18. 86 (unit 4-9) and for rice 26. 85 (unit 4-10) and 7. 43 (unit 4-11)، respectively. The climate suitability was the most important factor for selecting the proper land use، followed by soil suitability. The least importance was contributed to market accessibility. The inconsistency ratio related for all the matrices was 9 percent. The results of this study showed that the cultivation of wheat has higher performance for production in all land units.

One of the best agricultural policies in developing countries for food security is the evaluation of arable lands and agricultural potential to support the current and future agricultural uses. FAO framework for lands suitability evaluation uses a Boolean mapping approach which has been criticized by a number of authors, because the Boolean representations ignore the continuous nature of soil, landscape variation and uncertainties in measurement. In this research, the parametric Square Root Method via a Fuzzy Set Theory was used to evaluate the suitability of alfalfa for 7335 ha lands in Khajeh region located in East Azerbaijan province. The analysis was done with MATLAB analytical software. The results revealed that, calculated correlation coefficients values between the land index and yield with fuzzy method was (r= 0.917) more than that with the Parametric method (r= 0.685) and relatively large difference in calculated correlation coefficients revealed that, there was a need for calibration of the Sys proposed tables about requirements of the climate, landscape and soil in this region. Based on the suitably selected transition zone, MATLAB Software was able to accurately estimate the weights. Although the fuzzy approach provided better results than the parametric square root method, but its results surely depended on the type and determination of the transition zone and membership functions.

The study area is located in south west of Iran، Agili plain، Gotvand، Khuzestan province. Based on Shoushtar synoptic station، the climatic type of the area is semi-desertic. The maximum daily air temperature is 46. 6 °C in June and the minimum daily air temperature is 8. 1 °C in December. The annual rainfall is about 324 mm. The aim of this research was to elaborate an approach for the prediction of the land production potential for irrigated winter wheat، taking into account the environmental condition in the study area. The results showed that irrigated potential yield based on crop growth model method was 8041 kg/ha in the study area and land production potential for irrigated wheat، taking into account the effect of soil limitations، ranged between 2454 to 6687 kg/ha with Square Root method، and between 2296 to 6756 kg/ha for Storie method. The reduction in yield was due to high calcium carbonate، poor drainage، salinity and alkalinity، and management method. For evaluation of the model، three different regression methods، namely، standard multiple regression، stepwise regression، and curve estimation were used for comparison of the yield predicted by the model with the yield harvested by the farmers. Based on the results، coefficient of determination (r2) for predicted yield with Storie، square root، and characteristics methods were 0. 83، 0. 80، and 0. 33. These results show that the predicted yield can estimate the observed yield with 83 percent accuracy for Storie method، 80 percent for Square Root method، and 33 percent for Land Characteristics. Meanwhile، the Root Mean Square Error was، respectively، 598، 648، and 1258 kg/ha. Based on the results، it can be concluded that Storie method can predict yield better that the other methods because of higher coefficient of determination and lower RMSE.