An Interpolation Method for DEM Generation by Integration of Morphological Reconstruction and Distance Transformation with Obstacles

LIN Xiangguo

doi:10.13203/j.whugis20140097

Volume 41 Issue 7

Jul. 2016

Turn off MathJax

Article Contents

Abstract

References

Geomatics and Information Science of Wuhan University > 2016 > 41(7): 896-902. > DOI: 10.13203/j.whugis20140097

LIN Xiangguo. An Interpolation Method for DEM Generation by Integration of Morphological Reconstruction and Distance Transformation with Obstacles[J]. Geomatics and Information Science of Wuhan University, 2016, 41(7): 896-902. DOI: 10.13203/j.whugis20140097

Citation:

PDF (20745 KB)

An Interpolation Method for DEM Generation by Integration of Morphological Reconstruction and Distance Transformation with Obstacles

LIN Xiangguo^1,

1.
Institute of Photogrametry and Remote Sensing, Chinese Academy of Surveying and Mapping, Beijing 100830, China

More Information

Received Date: January 25, 2015
Published Date: July 04, 2016

Graphical Abstract

Abstract

Abstract

Contour line is one of the commonly used data sources for DEM generation, and the interpolation method has a significant impact on the accuracy of the contours-derived DEM. However, most of the existing interpolation methods generate low-accuracy DEM due to unreasonable methodologies. In this paper, an interpolation method is presented to build DEM from contour lines by integration of morphological reconstruction and distance transformation with obstacles. Particularly, morphological reconstruction is used to get the elevation values of the higher contour lines and the lower contour lines of any a spatial point between two contour lines, and distance transformation with obstacles is used to get the geodesic distances of the spatial point to the higher contour lines and the lower contour lines respectively. At last, linear interpolation along steepest slope is used to get the elevation values of the pixels to be interpolated. The experiments demonstrate that the accuracy of the DEM generated by our method is higher than the one generated by Hu Peng's MADEM method if only contours are employed to interpolate a DEM.
- morphological reconstruction,
- Euclidean distance transformation with obstacles,
- geodesic distance,
- DEM,
- interpolation

FullText(HTML)

References (16)

References

[1]	李志林, 朱庆. 数字高程模型[M]. 武汉: 武汉大学出版社, 2003) Li Zhilin, Zhu Qing. Digital Elevation Models [M]. Wuhan: Wuhan University Press, 2003
[2]	汤国安, 刘学军, 闾国年. 数字高程模型及地学分析的原理与方法[M]. 北京: 科学出版社, 2005) Tang Guoan, Liu Xuejun, Lv Guonian. Principles and Methods of Digital Elevation Models and Geoanalysis [M]. Beijing: Science Press, 2005
[3]	胡鹏, 杨传勇, 吴艳兰, 等. 新数字高程模型理论、方法、标准和应用[M]. 北京: 测绘出版社, 2007) Hu Peng, Yang Chuanyong, Wu Yanlan, et al. New Theories, Methods, Standards and Applications of Digital Elevation Models [M]. Beijing: Surveying and Mapping Press, 2007
[4]	胡鹏, 黄雪莲, 吴艳兰, 等. DEM若干理论问题思考[J]. 哈尔滨工业大学学报, 2006, 38(12):2143-2147) Hu Peng, Huang Xuelian, Wu Yanlan, et al. Some Problems of DEM Error Theory [J]. Journal of Harbin Institute of Technology, 2006, 38(12): 2143-2147
[5]	胡海, 杨传勇, 胡鹏. DEM最优线性生成技术——MADEM[J]. 华中科技大学学报(自然科学版), 2007, 35(6):118-121) Hu Hai, Yang Chuanyong, Hu Peng. Optimal Linear Method for DEM Generation: MADEM [J]. Journal Huazhong University of Science and Technology (Natural Science Edition), 2007, 35(6): 118-121
[6]	Zhang J, Lin X, Liu Z, Shen J. Semi-automatic Road Tracking by Template Matching and Distance Transformation in Urban Areas [J]. International Journal of Remote Sensing, 2011, 32(23): 8331-8347
[7]	胡鹏, 白轶多, 胡海. 数字高程模型生成中的高程序同构 [J]. 武汉大学学报·信息科学版, 2009, 34(3):352-357) Hu Peng, Bai Yiduo, Hu Hai. Elevation Order Isomorphism Characteristics of DEM [J]. Geomatics and Information Science of Wuhan University, 2009, 34(3):352-357
[8]	胡海, 吴艳兰, 胡鹏. 数字高程模型精度标准、质量理论和科学观念讨论[J]. 武汉大学学报·信息科学版, 2011, 36 (6):713-716) Hu Hai, Wu Yanlan, Hu Peng. Discussion of DEM Standards, Quality Theory and Conceptions [J]. Geomatics and Information Science of Wuhan University, 2011, 36 (6):713-716
[9]	Fan Qingsong. Research on Technologies of DEM Generation by Cartographic Generalization [D]. Wuhan: Wuhan University, 2007: 43-50
[10]	Lantuejoul C, Maisonneuve F. Geodesic Methods in Quantitative Image Analysis [J]. Pattern Recognition, 1984, 17(2): 117-187
[11]	沈晶, 刘纪平, 林祥国. 用形态学重建方法进行机载LiDAR数据滤波[J]. 武汉大学学报·信息科学版, 2011, 36(2):167-170) Shen Jing, Liu Jiping, Lin Xiangguo. Airborne LiDAR Data Filtering by Morphological Reconstruction [J]. Geomatics and Information Science of Wuhan University, 2011, 36(2):167-170
[12]	胡鹏, 游涟, 杨传勇, 等. 地图代数[M]. 武汉: 武汉大学出版社, 2007:127-133) Hu Peng, You Lian, Yang Chuanyong. Map Algebra [M]. Wuhan: Wuhan University Press, 2007: 127-133
[13]	Lantuejoul C, Beucher S. On the Use of Geodesic Metric in Image Analysis [J]. Journal of Microscopy, 1981, 121: 39-49
[14]	Soille P. Morphological Image Analysis: Principles and Applications [M]. Berlin/Heidelberg/New York: Springer-Verlag, 2008
[15]	周培德. 计算几何[M]. 北京: 清华大学出版社, 2002) Zhou Peide. Geometric Algebra [M]. Beijing: Tsinghua University Press, 2002
[16]	张锦明, 游雄, 万刚. 径向基函数算法中插值参数对DEM精度的影响 [J] . 武汉大学学报·信息科学版, 2013, 38 (5): 608-612) Zhang Jinming, You Xiong, Wan Gang. Effects of Interpolation Parameters in Multi-log Radial Basis Function on DEM Accuracy [J] . Geomatics and Information Science of Wuhan University, 2013, 38 (5): 608-612

[1]	YU Daocheng, HWANG Jinway, ZHU Huizhong, LUO Jia, YUAN Jiajia. Enhancing Marine Gravity Field Precision Using SWOT Wideswath Altimetry Data: a Comparative Analysis with Traditional Altimetry Satellites[J]. Geomatics and Information Science of Wuhan University. DOI: 10.13203/j.whugis20240120
[2]	HE Huiyou, FANG Jian. Gravity Anomaly Spectrum Analysis Method and Its Application[J]. Geomatics and Information Science of Wuhan University, 2023, 48(12): 2092-2102. DOI: 10.13203/j.whugis20200510
[3]	XING Zhibin, LI Shanshan, WANG Wei, FAN Haopeng. Fast Approach to Constructing Normal Equation During the Time of Calculating Height Anomaly Difference by Using Vertical Deflections[J]. Geomatics and Information Science of Wuhan University, 2016, 41(6): 778-783. DOI: 10.13203/j.whugis20140491
[4]	DU Jinsong, CHEN Chao, LIANG Qing, ZHANG Yi. Lunar Gravity Anomaly and Its Computational Method[J]. Geomatics and Information Science of Wuhan University, 2012, 37(11): 1369-1373.
[5]	LI Zhenhai, LUO Zhicai, WANG Haihong, ZHONG Bo. Requirements for Gravity Data Within the Given Accuracy of the Interpolated Gravity Anomaly[J]. Geomatics and Information Science of Wuhan University, 2011, 36(11): 1328-1331.
[6]	WU Yunsun, CHAO Dingbo, LI Jiancheng, WANG Zhengtao. Recovery of Ocean Depth Model of South China Sea from Altimetric Gravity Gradient Anomalies[J]. Geomatics and Information Science of Wuhan University, 2009, 34(12): 1423-1425.
[7]	WANG Haihong, NING Jinsheng, LUO Zhicai, LUO Jia. Separation of Gravity Anomalies Based on Multiscale Edges[J]. Geomatics and Information Science of Wuhan University, 2009, 34(1): 109-112.
[8]	CHAO Dingbo, YAO Yunsheng, LI Jiancheng, XU Jusheng. Interpretaion on the Tectonics and Characteristics of Altimeter-derived Gravity Anomalies in China South Sea[J]. Geomatics and Information Science of Wuhan University, 2002, 27(4): 343-347.
[9]	Huang Motao, Guan Zheng, Ouyang Yongzhong. Calculation and Accuracy Estimation of Marine Mean Free-Air Gravity Anomaly[J]. Geomatics and Information Science of Wuhan University, 1995, 20(4): 327-331.
[10]	Guan Zelin, E Dongchen. The Computation of Geoidal Undulation Deflection of Vertical and Gravity Anomalies Using Clenshaw Summation[J]. Geomatics and Information Science of Wuhan University, 1986, 11(4): 75-82.

Cited By

Cited by

Periodical cited type(10)

1.	费婷婷，丁晓婷，阙翔，林津，林健，王紫薇，刘金福. 基于SBM-DEA与STWR模型的中国能源碳排放效率时空异质性分析. 环境工程. 2024(10): 188-200 .
2.	熊景华，郭生练，王俊，尹家波，李娜. 长江流域陆地水储量变化及归因研究. 武汉大学学报(信息科学版). 2024(12): 2241-2248 .
3.	姜栋，赵文吉，王艳慧，万碧玉. 地理加权回归的城市道路时空运行态势空间网格计算方法. 武汉大学学报(信息科学版). 2023(06): 988-996 .
4.	倪杰，吴通华，赵林，李韧，谢昌卫，吴晓东，朱小凡，杜宜臻，杨成，郝君明. 环北极多年冻土区碳循环研究进展与展望. 冰川冻土. 2019(04): 845-857 .
5.	刘大元，张雪梅，岳跃民，王克林，邹冬生. 基于Geodetector的广西喀斯特植被覆盖变化及其影响因素分析. 农业现代化研究. 2019(06): 1038-1047 .
6.	肖屹，何宗宜，苗静，潘峰，杨好. 利用搜索引擎数据模拟疾病空间分布. 测绘通报. 2018(02): 94-98 .
7.	苗月鲜，方秀琴，吴小君，吴陶樱. 基于GWR模型的江西省山洪灾害区域异同性研究. 水土保持通报. 2018(01): 313-318+327 .
8.	陈吕凤，朱国平. 基于地理加权模型的南设得兰群岛北部南极磷虾渔场空间分布影响分析. 应用生态学报. 2018(03): 938-944 .
9.	张雪梅，王克林，岳跃民，童晓伟，廖楚杰，张明阳，姜岩. 生态工程背景下西南喀斯特植被变化主导因素及其空间非平稳性. 生态学报. 2017(12): 4008-4018 .
10.	陈广威，陈吕凤，朱国平，徐玉成，田靖寰，丁博. 南乔治亚岛冬季南极磷虾渔场时空分布及其驱动因子. 生态学杂志. 2017(10): 2803-2810 .

Other cited types(10)

Get Citation

PDF

XML

Article views (1372) PDF downloads (242) Cited by(20)

An Interpolation Method for DEM Generation by Integration of Morphological Reconstruction and Distance Transformation with Obstacles

Abstract

References

Related Articles

Cited by

Periodical cited type(10)

Other cited types(10)

Catalog

Related

An Interpolation Method for DEM Generation by Integration of Morphological Reconstruction and Distance Transformation with Obstacles

Abstract

References

Related Articles

Cited by

Periodical cited type(10)

Other cited types(10)

Catalog

Related

Export File

Citation

Format

Content