A Fuzzy Logic Based Method for Modeling the Spatial Distribution of Indicators of Decomposition in a High Mountain Environment
A Fuzzy Logic Based Method for Modeling the Spatial Distribution of Indicators of Decomposition in a High Mountain Environment
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DOI：
10.1657/aaar0015-073
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发表时间：
2016-11
期刊：
影响因子：
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通讯作者：
Niels Hellwig;Kerstin Anschlag;G. Broll
中科院分区：
文献类型：
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作者：
Niels Hellwig;Kerstin Anschlag;G. Broll
在广泛的生态评价中，将分解指标的样本数据提升到景观尺度往往是必要的。这类数据的数量即使在高采样努力下也大多是稀缺的。此外，高山区的环境条件非常不均匀。因此，我们的目标是在这种情况下找到一种适合的空间建模技术。提出了一种结合决策树分析和模糊隶属函数构造的方法，用于基于gis的分解指示参数映射。并与单纯基于决策树的方法进行了比较。在意大利阿尔卑斯山的一个案例研究中，研究了腐殖质形式的空间分布，根据OH（腐殖化残留物）水平的出现进行了分类。似乎与海拔高度有很强的关系，与坡度暴露的相关性较小。结果表明，基于模糊逻辑的方法适合于对分解指标的空间分布进行建模。映射模糊值允许表示小规模变异性和数据的不确定性，这是由于在非常异构的环境中相对较低的样本量。
ABSTRACT Upscaling of sample data on indicators of decomposition to the landscape scale is often necessary for extensive ecological assessments. The amount of such data is mostly scarce even with high sampling efforts. Moreover, environmental conditions are very heterogeneous in high mountain regions. Therefore, the aim was to find a suitable technique for spatial modeling under these circumstances. A method combining decision tree analysis and the construction of fuzzy membership functions is introduced for a GIS-based mapping of decomposition indicating parameters. It is compared with an approach solely based on decision trees. Within a case study in the Italian Alps the spatial distribution of humus forms, classified by the occurrence of an OH (humified residues) horizon, is examined. There appears to be a strong relationship with elevation and a minor correlation with slope exposition. The fuzzy logic-based approach proves to be suitable for modeling the spatial distribution of indicators of decomposition. Mapping fuzzy values allows for the representation of small-scale variability and uncertainty of data due to a relatively low sample size in a very heterogeneous environment.