A fine construction method of urban road DEM considering road morphological characteristics

被引:3
作者
Tao, Yu [1 ,3 ]
Tian, Lei [2 ]
Wang, Chun [1 ,3 ]
Dai, Wen [4 ]
Xu, Yan [1 ]
机构
[1] Chuzhou Univ, Sch Geog Informat & Tourism, Chuzhou 239000, Anhui, Peoples R China
[2] Nanjing Forestry Univ, Coll Forestry, Nanjing 210037, Jiangsu, Peoples R China
[3] Anhui Prov Key Lab Phys Geog Environm, Chuzhou 239000, Anhui, Peoples R China
[4] Nanjing Univ Informat Sci & Technol, Sch Geog Sci, Nanjing 210044, Jiangsu, Peoples R China
关键词
LIDAR DATA; GENERATION; FEATURES;
D O I
10.1038/s41598-022-19349-4
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
Urban road DEM is not only an important basic geographic information data of the city, but also an important element to describe and express the urban topography, and it is an indispensable part of the construction of the smart digital city, urban planning and urban surface process simulation. Previous methods for constructing urban road DEMs do not sufficiently consider the actual morphological characteristics of urban roads, and morphological distortion is evident in the expression of urban roads, seriously affecting the application of urban rainfall flood simulation and urban pipe network design. In response to these problems, this study proposed a considering morphological characteristics fine (CMCF) method of urban road DEM construction, selected a typical urban road area in the Jianye District of Nanjing City in China as the study area, used the 1:500 digital line graphic as data source, hierarchized roads in accordance with different morphological characteristics from the perspective of DEM construction, constructed the corresponding DEMs, and finally merged all levels of road DEMs to produce a complete high-precision urban road DEM. Results showed that the DEM constructed using the CMCF method not only exhibited higher elevation accuracy than the urban road DEM constructed using previous methods, i.e., inverse distance weighting (IDW) and triangulated irregular network (TIN) methods, with a mean error and a root-mean-square error of 0.015 and 0.060, respectively, but it can also accurately express the spatial element composition form and road morphological characteristics of urban roads, avoiding the distorted expression of road morphological characteristics. This study can provide a reference for a new DEM construction method and data support for smart digital city construction and urban surface simulation.
引用
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页数:15
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