The smoothness of HASM |
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| Authors: | Chuanfa Chen Tianxiang Yue Honglei Dai Maoyi Tian |
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| Institution: | 1. Geomatics College , Shandong University of Science and Technology , Qingdao , China chencf@lreis.ac.cn;3. State Key Laboratory of Resources and Environment Information System , Institute of Geographical Sciences and Natural Resources Research , Beijing , China;4. Geomatics College , Shandong University of Science and Technology , Qingdao , China |
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| Abstract: | To smooth noises inherent in uniformly sampled dataset, the smoothness of high accuracy surface modeling (HASM) was explored, and a smoothing method of HASM (HASM-SM) was developed based on a penalized least squares method. The optimal smoothing parameter of HASM-SM was automatically obtained by means of the generalized cross-validation (GCV) method. For an efficient smoothing computation, discrete cosine transform was employed to solve the system of HASM-SM and to estimate the minimum GCV score, simultaneously. Two examples including a numerical test and a real-world example were employed to compare the smoothing ability of HASM-SM with that of GCV thin plate smoothing spline (TPS) and kriging. The numerical test indicated that the minimum GCV HASM-SM is averagely more accurate than TPS and kriging for noisy surface smoothing. The real-world example of smoothing a lidar-derived Digital Elevation Model (DEM) showed that HASM-SM has an obvious smoothing effect, which is on a par with TPS. In conclusion, HASM-SM provides an efficient tool for filtering noises in grid-based surfaces like remote sensing–derived images and DEMs. |
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| Keywords: | error modeling digital elevation or terrain models |
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