地形有时被认为是不随尺度发生变化或是随机的面,然而定性的观测结果却表明它们含有特征空间尺度。我们通过分析从加利福尼亚州北部两个地形高分辨率地形图中提取的二维傅里叶功率谱,定量研究了存在于这两个地区的特征地形空间尺度。发现两处地形的谱能量在大致对应于斜坡长度的频率都迅速衰减,意味着地形在较小的尺度上都相对光滑。功率谱图还显示两处地形均具有准周期的脊-谷构造,从中我们也得到了脊-谷构造波长的精确测量结果。通过该频谱与随机生成的地形面的统计频谱特征的比较,我们发现这种均匀的谷间隔不可能产生在随机面上。除了特征空间尺度的识别外,我们还论述了多种谱分析在地貌学上的潜在应用,包括可用于测量诸如在特定尺度或特定方位上局部起伏等地形属性的滤波技术。 Topographies are sometimes regarded as not changing or random surfaces, yet qualitative observations show that they contain spatial scales of features. We quantitatively studied the characteristic terrain spatial scales existing in these two regions by analyzing the two-dimensional Fourier power spectrum extracted from two topographic high-resolution topographies in northern California. The spectral energy of the two terrains was found to decay rapidly at frequencies roughly corresponding to the length of the slope, meaning that the terrain is relatively smooth on smaller scales. The power spectrum also shows quasi-periodic ridge-valley tectonics in both terrains, from which we also obtained accurate measurements of ridge-valley tectonic wavelengths. By comparing this spectrum with the statistical spectral features of randomly generated terrain, we find that such uniform valley intervals can not occur on random surfaces. In addition to the identification of feature space scales, we also discuss the potential geomorphological applications of multiple spectral analyzes, including filtering techniques that can be used to measure terrain properties such as local undulations at particular scales or particular orientations.