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Procrustes analysis as a tool for land management

机译:进行分析作为土地管理的工具

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摘要

Generalized Procrustes analysis (GPA) is a multivariate technique that involves transformations of data matrices to provide optimal comparability. We propose GPA to quantify the concordance among sets of variables that characterize natural, human and productive subsystems. When the land use fits in with the physical support of agricultural production, people's well-being should be evident in a high concordance between the land use and the social conditions. In a situation of instability each set of variables operates in diverse directions resulting in lower resilience and sustainability. Two GPA were performed, between physical support and land use data sets (concordance = 67.4%), and between land use and social conditions data sets (concordance = 65.3%). The interplay between the pair of concordance values constitutes a bi-dimensional index which serves as an ecological indicator. Based on bootstrap confidence interval, the 49 counties of the Pampa Ecoregion, Argentina, were classified in medium, high or low concordance. The lack of concordance is an indicator of imbalances which may contribute to guide environmental management.
机译:广义Procrustes分析(GPA)是一种多变量技术,涉及数据矩阵的转换以提供最佳的可比性。我们提出GPA来量化代表自然,人类和生产子系统的变量集之间的一致性。当土地利用与农业生产的物质支持相吻合时,土地利用与社会条件之间的高度协调就应当体现人民的福祉。在不稳定的情况下,每组变量在不同的方向上运行,导致较低的弹性和可持续性。在物理支持和土地使用数据集之间(一致性= 67.4%)以及在土地使用和社会条件数据集之间(一致性= 65.3%)执行了两个GPA。这对一致性值之间的相互作用构成了二维指标,该指标用作生态指标。根据引导置信区间,阿根廷潘帕生态区的49个县按中,高或低一致性分类。缺乏协调性是不平衡的指标,可能有助于指导环境管理。

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