Local variance for multi-scale analysis in geomorphometry.
Local variance for multi-scale analysis in geomorphometry.
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DOI：
10.1016/j.geomorph.2011.03.011
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发表时间：
2011-07-15
期刊：
影响因子：
--
通讯作者：
Strasser T
中科院分区：
文献类型：
--
作者：
Drăguţ L;Eisank C;Strasser T
高分辨率数字高程模型（DEM）的日益增加的可用性导致了地貌尺度问题的范式转变，促使新的解决方案来科普多尺度分析和特征尺度的检测。我们测试了当地的方差（LV）的方法，最初开发的图像分析，多尺度分析地貌的适用性。该方法包括：1）从DEM中提取地表参数; 2）计算LV作为每个尺度水平的3 × 3移动窗口内的平均标准差（SD）; 3）计算LV从一个水平到另一个水平的变化率（ROC-LV）;以及4）将如此获得的值与尺度水平作图。我们将ROC-LV图中的峰解释为尺度水平的标记，其中单元或片段匹配以（相对）相等程度的均匀性为特征的模式元素的类型。所提出的方法已被应用到激光雷达DEM在两个不同的测试领域的粗糙度：低浮雕和山区，分别。对于每个测试区域，通过重新扫描（基于细胞）或图像分割（基于对象）以恒定增量生成斜率梯度、平面和剖面曲率的比例水平。视觉评估显示，令人信服地关联到不同尺度的地表参数模式均匀的地区。我们发现，LV方法在通过分割生成的尺度水平上的表现优于通过重新缩放生成的尺度水平。结果表明，耦合多尺度模式分析与描绘的形态测量基元是可能的。这种方法可以进一步用于开发地形要素的层次分类。对地貌测量学中的多尺度分析方法--局部方差法进行了检验。我们比较了基于细胞的方法与基于对象的方法（OBIA）的分析。ESPILV方法指示数据中存在哪些尺度和形态测量模式。基于对象的方法比基于单元的方法性能更好。多尺度模式分析可以与形态测量对象的描绘相结合。
Increasing availability of high resolution Digital Elevation Models (DEMs) is leading to a paradigm shift regarding scale issues in geomorphometry, prompting new solutions to cope with multi-scale analysis and detection of characteristic scales. We tested the suitability of the local variance (LV) method, originally developed for image analysis, for multi-scale analysis in geomorphometry. The method consists of: 1) up-scaling land-surface parameters derived from a DEM; 2) calculating LV as the average standard deviation (SD) within a 3 × 3 moving window for each scale level; 3) calculating the rate of change of LV (ROC-LV) from one level to another, and 4) plotting values so obtained against scale levels. We interpreted peaks in the ROC-LV graphs as markers of scale levels where cells or segments match types of pattern elements characterized by (relatively) equal degrees of homogeneity. The proposed method has been applied to LiDAR DEMs in two test areas different in terms of roughness: low relief and mountainous, respectively. For each test area, scale levels for slope gradient, plan, and profile curvatures were produced at constant increments with either resampling (cell-based) or image segmentation (object-based). Visual assessment revealed homogeneous areas that convincingly associate into patterns of land-surface parameters well differentiated across scales. We found that the LV method performed better on scale levels generated through segmentation as compared to up-scaling through resampling. The results indicate that coupling multi-scale pattern analysis with delineation of morphometric primitives is possible. This approach could be further used for developing hierarchical classifications of landform elements. ► We test the method of local variance (LV) for multi-scale analysis in geomorphometry. ► We compare the analysis in a cell-based approach with an object-based (OBIA) one. ► LV method indicates which scales and morphometric patterns are present in the data. ► The object-based approach performs better than the cell-based one. ► Multi-scale pattern analysis can be coupled with delineation of morphometric objects.
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DOI：
10.1559/152304091783805626
发表时间：
1991-01-01
期刊：
CARTOGRAPHY AND GEOGRAPHIC INFORMATION SYSTEMS
影响因子：
--
作者：
CHANG, KT;TSAI, BW
通讯作者：
TSAI, BW
影响因子：
10.6
作者：
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McCloy, KR
DOI：
10.1016/s0166-2481(08)00028-7
发表时间：
2009-01-01
期刊：
GEOMORPHOMETRY: CONCEPTS, SOFTWARE, APPLICATIONS
影响因子：
--
作者：
Gessler, P.;Pike, R.;Reuter, H. I.
通讯作者：
Reuter, H. I.
影响因子：
3.3
作者：
Benito-Calvo, A.;Perez-Gonzalez, A.;Meza, P.
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影响因子：
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作者：
Arrell, K. E.;Fisher, P. F.;Bastin, L.
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