The Effect of DEM Raster Resolution on First Order, Second Order and Compound Terrain Derivatives
The Effect of DEM Raster Resolution on First Order, Second Order and Compound Terrain Derivatives
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DOI：
10.1111/j.1467-9671.2004.00169.x
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发表时间：
2004-01
影响因子：
2.4
通讯作者：
S. Kienzle
中科院分区：
文献类型：
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作者：
S. Kienzle
众所周知，栅格数字高程模型的网格单元大小对导出的地形变量（如坡度、坡向、平面和剖面曲率或湿度指数）有显著影响。本文对加拿大阿尔伯塔省摄影测量高程点插值生成DEM的质量进行了检验。使用ANUDEM插值方法，从100 m规则间隔的高程点和大量表面特定点高程中插值出网格单元大小为100至5 m的DEM。为了确定与源数据的信息内容相匹配的网格分辨率，采用了三种方法：点高程的密度分析，使用Kolmogorov-Smirnov检验和均方根斜率测量的累积频率分布分析。结果表明，最佳的网格单元尺寸为5和20米之间，这取决于地形复杂性和地形导数。基于100 m定期采样高程点的地形变量与用作基准的独立高分辨率DEM进行比较。随后的相关性分析表明，只有海拔和当地的坡度有很强的正相关关系，而所有其他地形衍生物是不现实的表示时，从一个粗略的DEM。计算的均方根误差和相对均方根误差进一步量化的地形衍生物的质量。
It is well known that the grid cell size of a raster digital elevation model has significant effects on derived terrain variables such as slope, aspect, plan and profile curvature or the wetness index. In this paper the quality of DEMs derived from the interpolation of photogrammetrically derived elevation points in Alberta, Canada, is tested. DEMs with grid cell sizes ranging from 100 to 5 m were interpolated from 100 m regularly spaced elevation points and numerous surface‐specific point elevations using the ANUDEM interpolation method. In order to identify the grid resolution that matches the information content of the source data, three approaches were applied: density analysis of point elevations, an analysis of cumulative frequency distributions using the Kolmogorov‐Smirnov test and the root mean square slope measure. Results reveal that the optimum grid cell size is between 5 and 20 m, depending on terrain com‐plexity and terrain derivative. Terrain variables based on 100 m regularly sampled elevation points are compared to an independent high‐resolution DEM used as a benchmark. Subsequent correlation analysis reveals that only elevation and local slope have a strong positive relationship while all other terrain derivatives are not represented realistically when derived from a coarse DEM. Calculations of root mean square errors and relative root mean square errors further quantify the quality of terrain derivatives.