LiDAR-derived surface roughness signatures of basaltic lava types at the Muliwai a Pele Lava Channel, Mauna Ulu, Hawai‘i
LiDAR-derived surface roughness signatures of basaltic lava types at the Muliwai a Pele Lava Channel, Mauna Ulu, Hawai‘i
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夏威夷莫纳乌鲁 Muliwai a Pele 熔岩通道的玄武岩熔岩类型的激光雷达衍生表面粗糙度特征
DOI：
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发表时间：
2017
影响因子：
3.5
通讯作者：
J. Bleacher
中科院分区：
文献类型：
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作者：
P. Whelley;P. Whelley;W. Garry;C. Hamilton;J. Bleacher
我们使用光探测和测距（LiDAR）的数据来计算粗糙度模式（均匀性，平均粗糙度和熵）五种熔岩类型在两种不同的分辨率（1.5和0.1米/像素）。我们发现，端元类型（a a和pāhoehoe）在两个尺度上都是可分离的（95%的置信度），这表明粗糙度模式非常适合分析熔岩类型。中间熔岩也进行了探索，我们发现，板状pāhoehoe是可分离的其他端元使用1.5米/像素的数据，但不是在0.1米/像素的分析。这表明，从pāhoehoe到slabby-pāhoehoe的转换是一个米级的过程，pāhoehoe的更精细的粗糙度特征，如绳索和脚趾，没有受到显着影响。此外，我们引入的比率ENTHOM$$ frac{ENT}{HOM} $$（来自熔岩粗糙度）作为代理评估当地的熔岩流率从地形数据。高熵和低均匀性区域与高流速相关，而低熵和高均匀性区域与低流速相关。我们认为，这种关系是没有方向性的，而是通过粗糙度的差异，分别在高和低利率的相关熔岩类型侵位是显而易见的。
We used light detection and ranging (LiDAR) data to calculate roughness patterns (homogeneity, mean-roughness, and entropy) for five lava types at two different resolutions (1.5 and 0.1 m/pixel). We found that end-member types (ʻaʻā and pāhoehoe) are separable (with 95% confidence) at both scales, indicating that roughness patterns are well suited for analyzing types of lava. Intermediate lavas were also explored, and we found that slabby-pāhoehoe is separable from the other end-members using 1.5 m/pixel data, but not in the 0.1 m/pixel analysis. This suggests that the conversion from pāhoehoe to slabby-pāhoehoe is a meter-scale process, and the finer roughness characteristics of pāhoehoe, such as ropes and toes, are not significantly affected. Furthermore, we introduce the ratio ENTHOM$$ frac{ENT}{HOM} $$ (derived from lava roughness) as a proxy for assessing local lava flow rate from topographic data. High entropy and low homogeneity regions correlate with high flow rate while low entropy and high homogeneity regions correlate with low flow rate. We suggest that this relationship is not directional, rather it is apparent through roughness differences of the associated lava type emplaced at the high and low rates, respectively.
影响因子：
5
作者：
Browning, Dawn M.;Karl, Jason W.;Tweedie, Craig E.
通讯作者：
Tweedie, Craig E.