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Using ordered weight averaging (OWA) aggregation for multi-criteria soil fertility evaluation by GIS (case study: southeast Iran)

机译:使用有序重量平均(OWA)GIS进行多标准土壤肥力评估的聚集(案例研究:伊朗东南部)

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The Multi-criteria Decision Analysis (MCDA) and the Geographical Information Systems (GIS) are used to provide more accurate decisions for decision makers in order to evaluate the effective factors of the natural science. One of the popular algorithms of the multi-criteria analysis is the Ordered Weighted Averaging (OWA). The OWA procedure depends on some parameters which can be specified by means of the fuzzy logic. The aim of this study is to take the advantage of incorporating the fuzzy logic into GIS-based soil fertility analysis by OWA in the west of Shiraz, Fars province, Iran. In fact, different soil fertility maps with different risk level are prepared in the present study. This study introduces a method for farmers in case of make balance between their budget and their farm soil parameters. A farmer can accept more risk it can use more areas for farming and also the amount of needed budget increases too. For determining the soil fertility maps, the OWA parameters such as potassium (K), phosphor (P), copper (Cu), iron (Fe), manganese (Mn), organic carbon (OC) and zinc (Zn) were used. After generating the interpolation maps with the Inverse Distance Weighted (IDW), the fuzzy maps were generated by the membership functions for each parameter. Finally, by utilizing OWA, six fertility maps with different risk levels (degrees of uncertainty) were made. The results show that by decreasing the risk (no trade-off), increasing the risk, more area within the study area was suitable in terms of the soil fertility. Therefore, using OWA can generate many maps with different risk levels. This leads to different managements based on different financial conditions of farmers. (c) 2016 Elsevier B.V. All rights reserved.
机译:多标准决策分析(MCDA)和地理信息系统(GIS)用于为决策者提供更准确的决策,以评估自然科学的有效因素。多标准分析的流行算法之一是有序加权平均(OWA)。 OWA过程取决于可以通过模糊逻辑指定的一些参数。本研究的目的是利用在伊朗Shiraz西部的Owa将模糊逻辑纳入GIS的土壤肥力分析。事实上,在本研究中制备了不同风险水平的不同土壤肥力图。本研究介绍了农民的方法,以便在其预算与农场土壤参数之间进行平衡。农民可以接受更多风险,它可以使用更多的农业领域,并且所需的预算量也增加了。为了确定土壤肥力图,使用诸如钾(K),磷光体(P),铜(Cu),铁(Fe),锰(Mn),有机碳(OC)和锌(Zn)的OWA参数。在使用逆距离加权(IDW)生成插值映射之后,由每个参数的隶属函数生成模糊贴图。最后,通过利用OWA,制造了六种具有不同风险水平的生育率图(不确定度)。结果表明,通过降低风险(无权衡),增加风险,研究区域内的更多区域是适合土壤肥力的。因此,使用OWA可以生成具有不同风险级别的许多地图。这导致基于农民的不同财务状况的不同管理。 (c)2016年Elsevier B.v.保留所有权利。

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