IGSNRR OpenIR
Robust Interpolation of DEMs From Lidar-Derived Elevation Data
Chen, Chuanfa1; Li, Yanyan2; Zhao, Na3; Yan, Changqing1
2018-02-01
Source PublicationIEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING
ISSN0196-2892
Volume56Issue:2Pages:1059-1068
Corresponding AuthorChen, Chuanfa(chencf@lreis.ac.cn)
AbstractLight detection and ranging (lidar)-derived elevation data are commonly subjected to outliers due to the boundaries of occlusions, physical imperfections of sensors, and surface reflectance. Outliers have a serious negative effect on the accuracy of digital elevation models (DEMs). To decrease the impact of outliers on DEM construction, we propose a robust interpolation algorithm of multiquadric (MQ) based on a regularized least absolute deviation (LAD) technique. The objective function of the proposed method includes a regularization-based smoothing term and an LAD-based fitting term, respectively, used to smooth noisy samples and resist the influence of outliers. To solve the objective function of the proposed method, we develop a simple scheme based on the split-Bregman iteration algorithm. Results from simulated data sets indicate that when sample points are noisy or contaminated by outliers, the proposed method is more accurate than the classical MQ and two recently developed robust algorithms of MQ for surface modeling. Real-world examples of interpolating 1 private and 11 publicly available airborne lidarderived data sets demonstrate that the proposed method averagely produces better results than two promising interpolation methods including regularized spline with tension (RST) and gridded data-based robust thin plate spline (RTPS). Specifically, the image of RTPS is too smooth to retain terrain details. Although RST can keep subtle terrain features, it is distorted by some misclassified object points (i.e., pseudooutliers). The proposed method obtains a good tradeoff between resisting the effect of outliers and preserving terrain features. Overall, the proposed method can be considered as an alternative for interpolating lidar-derived data sets potentially including outliers.
KeywordInterpolation noise robustness surface fitting
DOI10.1109/TGRS.2017.2758795
WOS KeywordLASER-SCANNING DATA ; MULTIQUADRIC METHOD ; OUTLIER DETECTION ; SAMPLING DENSITY ; DATA SETS ; MODELS ; REGRESSION ; ALGORITHMS ; EXTRACTION ; MORPHOLOGY
Indexed BySCI
Language英语
Funding ProjectNational Natural Science Foundation of China[41371367] ; SDUST Research Fund ; Joint Innovative Center for Safe and Effective Mining Technology and Equipment of Coal Resources ; State Key Laboratory of Resources and Environmental Information System
Funding OrganizationNational Natural Science Foundation of China ; SDUST Research Fund ; Joint Innovative Center for Safe and Effective Mining Technology and Equipment of Coal Resources ; State Key Laboratory of Resources and Environmental Information System
WOS Research AreaGeochemistry & Geophysics ; Engineering ; Remote Sensing ; Imaging Science & Photographic Technology
WOS SubjectGeochemistry & Geophysics ; Engineering, Electrical & Electronic ; Remote Sensing ; Imaging Science & Photographic Technology
WOS IDWOS:000424627500036
PublisherIEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
Citation statistics
Cited Times:2[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Identifierhttp://ir.igsnrr.ac.cn/handle/311030/57145
Collection中国科学院地理科学与资源研究所
Corresponding AuthorChen, Chuanfa
Affiliation1.Shandong Univ Sci & Technol, Shandong Prov & Minist Sci & Technol, State Key Lab Min Disaster Prevent & Control, Qingdao 266590, Peoples R China
2.Wuhan Univ, Sch Geodesy & Geomat, Wuhan 430079, Hubei, Peoples R China
3.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, State Key Lab Resources & Environm Informat Syst, Beijing 100101, Peoples R China
Recommended Citation
GB/T 7714
Chen, Chuanfa,Li, Yanyan,Zhao, Na,et al. Robust Interpolation of DEMs From Lidar-Derived Elevation Data[J]. IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING,2018,56(2):1059-1068.
APA Chen, Chuanfa,Li, Yanyan,Zhao, Na,&Yan, Changqing.(2018).Robust Interpolation of DEMs From Lidar-Derived Elevation Data.IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING,56(2),1059-1068.
MLA Chen, Chuanfa,et al."Robust Interpolation of DEMs From Lidar-Derived Elevation Data".IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING 56.2(2018):1059-1068.
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