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Effects of Input Uncertainty on the Outcome of a Raster-Based Model for Structural Landscape Classification

机译:输入不确定性对结构景观分类栅格基于栅格模型的影响

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This paper presents the results of a study aimed at assessing the effects of input data uncertainty on the outcome of a raster-based model for structural landscape classification. The model uses a DEM and a land-use map as input, and calculates four structural indices from these data. The first two indices determine the openness of the landscape, the other two determine the degree of landscape homogeneity. By combining both aspects nine different landscape types are defined. Applying Monte Carlo simulation, the effect of DEM error, uncertainty in land-use classification, and the combined effect of both sources of uncertainty on the outcome of the landscape model are evaluated. Special attention is paid to the spatial structure of uncertainty in both data sources.
机译:本文介绍了一项研究的结果,旨在评估输入数据不确定性对结构景观分类的基于光栅模型的结果的影响。该模型使用DEM和陆地使用地图作为输入,并从这些数据计算四个结构索引。前两个指数决定了景观的开放性,另外两个决定了景观均匀性的程度。通过组合两个方面,定义了九种不同的景观类型。评估了Monte Carlo模拟,DEM误差,土地使用分类中的不确定性的影响,以及对景观模型结果的不确定源的综合效果。在两个数据源中的不确定性的空间结构上会特别注意。

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