Multiresolution analysis of characteristic length scales with high‐resolution topographic data
Multiresolution analysis of characteristic length scales with high‐resolution topographic data
复制标题
高分辨率地形数据特征长度尺度的多分辨率分析
DOI：
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复制
发表时间：
2017
期刊：
影响因子：
--
通讯作者：
P. Passalacqua
中科院分区：
文献类型：
--
作者：
H. Sangireddy;C. Stark;P. Passalacqua
特征长度尺度（CLS）定义景观结构和划定地貌过程。在这里，我们使用多分辨率分析（MRA）从高分辨率地形数据中估计这些尺度。MRA采用渐进式地形散焦，通过卷积的地形数据与高斯内核的增加标准偏差，并计算在每个平滑分辨率（i）曲率和地形指数（定义为斜率的概率分布，以对数尺度面积）和（ii）的特征空间模式的发散和收敛地形通过分析地形的曲率。首先使用CLS已知的合成1-D和2-D信号探索MRA。然后，它验证了对一组MARSSIM（景观演化模型）稳态景观，其CLS通过不同的山坡扩散率和模拟噪声幅度进行调整。已知的CLS与地形指数和曲率分布显示标度突变的尺度相匹配，表明MRA可以根据地形属性的标度行为识别景观中的CLS。最后，MRA部署测量CLS的五个自然景观米分辨率数字地形模型数据。CLS是从地形指数和曲率分布的尺度突变推断出来的，并等同于（i）小尺度粗糙度特征和（ii）山坡长度尺度。
Characteristic length scales (CLS) define landscape structure and delimit geomorphic processes. Here we use multiresolution analysis (MRA) to estimate such scales from high‐resolution topographic data. MRA employs progressive terrain defocusing, via convolution of the terrain data with Gaussian kernels of increasing standard deviation, and calculation at each smoothing resolution of (i) the probability distributions of curvature and topographic index (defined as the ratio of slope to area in log scale) and (ii) characteristic spatial patterns of divergent and convergent topography identified by analyzing the curvature of the terrain. The MRA is first explored using synthetic 1‐D and 2‐D signals whose CLS are known. It is then validated against a set of MARSSIM (a landscape evolution model) steady state landscapes whose CLS were tuned by varying hillslope diffusivity and simulated noise amplitude. The known CLS match the scales at which the distributions of topographic index and curvature show scaling breaks, indicating that the MRA can identify CLS in landscapes based on the scaling behavior of topographic attributes. Finally, the MRA is deployed to measure the CLS of five natural landscapes using meter resolution digital terrain model data. CLS are inferred from the scaling breaks of the topographic index and curvature distributions and equated with (i) small‐scale roughness features and (ii) the hillslope length scale.
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DOI：
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发表时间：
2006
期刊：
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影响因子：
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作者：
G.
通讯作者：
G.
影响因子：
3.3
作者：
Grieve, Stuart W. D.;Mudd, Simon M.;Hurst, Martin D.
通讯作者：
Hurst, Martin D.
影响因子：
3.9
作者：
Hurst, Martin D.;Mudd, Simon M.;Yoo, Kyungsoo
通讯作者：
Yoo, Kyungsoo
影响因子：
3.4
作者：
Grieve, Stuart W. D.;Mudd, Simon M.;Furbish, David J.
通讯作者：
Furbish, David J.