There are three major mathematical problems in digital terrain analysis: (1) interpolation of digital elevation models (DEMs); (2) DEM generalization and denoising; and (3) computation of morphometric variables through calculating partial derivatives of elevation. Traditionally, these three problems are solved separately by means of procedures implemented in different methods and algorithms. In this article, we present a universal spectral analytical method based on high-order orthogonal expansions using the Chebyshev polynomials of the first kind with the subsequent Fejér summation. The method is intended for the processing of regularly spaced DEMs within a single framework including DEM global approximation, denoising, generalization, as well as calculating the partial derivatives of elevation and local morphometric variables.
The method is exemplified by a portion of the Great Rift Valley and central Kenyan highlands. A DEM of this territory (the matrix 480 × 481 with a grid spacing of 30″) was extracted from the global DEM SRTM30_PLUS. We evaluated various sets of expansion coefficients (up to 7000) to approximate and reconstruct DEMs with and without the Fejér summation. Digital models of horizontal and vertical curvatures were computed using the first and second partial derivatives of elevation derived from the reconstructed DEMs. To evaluate the approximation accuracy, digital models of residuals (differences between the reconstructed DEMs and the initial one) were calculated. The test results demonstrated that the method is characterized by a good performance (i.e., a distinct monotonic convergence of the approximation) and a high speed of data processing. The method can become an effective alternative to common techniques of DEM processing. 相似文献
机载LiDAR测深技术被认为是海洋测绘领域极具潜力的对地观测新技术,国内对LiDAR测深的试验大都是针对南海这类水质较清的区域。本研究首次在国内引入先进的CZMIL(Coastal Zone Mapping and Imaging LiDAR)系统,选取较为浑浊的江苏省骆马湖作为试验测区,进行了测深试验。试验结果表明,在测区有着低底部反射率、高漫衰减系数的情况下,CZMIL系统仍能够成功探测到湖底数据,成果精度达到了CZMIL系统标称的测深精度指标,具有较好测深探测能力和精度。 相似文献
