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Multi-scale European Soil Information System (MEUSIS): a multi-scale method to derive soil indicators

机译:多尺度欧洲土壤信息系统(MEUSIS):一种多尺度方法来得出土壤指标

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The Multi-scale Soil Information System (MEUSIS) can be a suitable framework for building a nested system of soil data that could facilitate interoperability through a common coordinate reference system, a unique grid coding database, a set of detailed and standardized metadata, and an open exchangeable format. In the context of INSPIRE Directive, MEUSIS may be implemented as a system facilitating the update of existing soil information and accelerating the harmonization of various soil information systems. In environmental data like the soil one, it is common to generalize accurate data obtained at the field to coarser scales using either the pedotransfer rules or knowledge of experts or even some statistical solutions which combine single values of spatially distributed data. The most common statistical process for generalization is averaging the values within the study area. In this paper, we do not present a simple averaging of numerical values without any further processed information. The upscaling process is accompanied with significant statistical analysis in order to demonstrate the method suitability. The coarser resolution nested grids cells (10 x 10 km) represent broad regions where the calculated soil property (e.g., organic carbon) can be accurately upscaled. Multi-scaled approaches are urgently required to integrate different disciplines (such as Statistics) and provide a meta-model platform to improve current mechanistic modeling frameworks, request new collected data, and identify critical research questions. Past papers have described in detail the up-scaling methodology while our present approach is to demonstrate an important application of this methodology accompanied with statistical evidence.
机译:多尺度土壤信息系统(MEUSIS)可以是构建嵌套土壤数据系统的合适框架,该系统可以通过通用坐标参考系统,独特的网格编码数据库,一组详细而标准化的元数据以及开放的可交换格式。在INSPIRE指令的上下文中,MEUSIS可以作为促进现有土壤信息更新并加速各种土壤信息系统协调的系统来实施。在像土壤这样的环境数据中,通常使用pedotransfer规则或专家知识甚至结合了空间分布数据的单个值的某些统计解决方案,将在野外获得的准确数据推广到更粗的尺度。最通用的统计过程是对研究区域内的值求平均值。在本文中,我们不会在没有任何进一步处理的信息的情况下对数值进行简单的平均。升级过程伴随着重要的统计分析,以证明该方法的适用性。较粗分辨率的嵌套网格单元(10 x 10 km)代表较宽的区域,在这些区域中可以精确地放大计算的土壤属性(例如有机碳)。迫切需要采用多尺度方法来集成不同学科(例如统计学)并提供元模型平台,以改善当前的机械建模框架,请求新收集的数据并确定关键的研究问题。过去的论文详细描述了按比例放大的方法,而我们目前的方法是通过统计证据来证明该方法的重要应用。

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