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首页> 外文期刊>International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences >QUANTIFYING EFFECTS OF CHANGING SPATIAL SCALE ON SPATIAL ENTROPY INDEX: USE OF FRACTAL DIMENSION
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QUANTIFYING EFFECTS OF CHANGING SPATIAL SCALE ON SPATIAL ENTROPY INDEX: USE OF FRACTAL DIMENSION

机译：不断变化空间尺度对空间熵指数的影响：使用分形维数

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Quantifying landscape heterogeneity and its organization at different scales is essential for understanding ecosystems and landscapes. Among hundreds of landscape metrics, entropy-related index represents an efficient tool to quantify and characterize landscape patterns. A recent development is Spatial Entropy index (Hs), and it has been validated as flexible and effective in landscape pattern analysis. However, the effects of changing spatial scale on Hs has not been quantified. This paper applies the fractal method to measure the spatial scale (grain size) sensitivity of Hs. Using the initial land-use data of Yanhe watershed, which is located in northwest of China, eleven different spatial scales were created in order to investigate the scale effects on Hs. A linear log–log regression model was then constructed based on the power law to calculate the coefficient of determination (COD) of the model and the fractal dimension (FD) of Hs. The result indicates that Spatial Entropy index shows a robust fractal feature, and it decreases as the spatial scale (or grain size) becomes lager in a moderate degree. In total, we believe that this study will help us to get a better understanding of Hs, and to facilitate further applications of this entropy-related index.
机译：量化景观异质性及其在不同尺度上的组织对于了解生态系统和景观至关重要。在数百个横向度量中，熵相关的索引代表了一种有效的工具来量化和表征横向模式。最近的发展是空间熵指数（HS），它已被验证为景观模式分析中的灵活有效。然而，尚未量化改变空间尺度对HS的影响。本文采用分形法测量HS的空间尺度（晶粒尺寸）敏感性。利用位于中国西北部的延河流域的初始土地使用数据，创建了11种不同的空间尺度，以调查对HS的规模效应。然后基于电力法构建线性对数回归模型，以计算模型的确定系数和HS的分形维数（FD）。结果表明，空间熵指数显示了鲁棒的分形特征，随着空间尺度（或粒度）在中等程度下变为储存而降低。总的来说，我们认为这项研究将有助于我们更好地了解HS，并促进这种熵相关指数的进一步应用。

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