An interpolation method for lack of DEM data area in tidal creeks based on neural network

Author

Zhu, Ang ; Ding, Xianrong ; Li, Qing ; Cheng, Ligang ; Zhang, Jiajia ; Ge, Xiaoping ; Huang, Bi

Author_Institution

State Key Laboratory of Hydrology-Water Resources and Hydraulic Engineering, Hohai University, Nanjng 210098, China

fYear

2010

fDate

4-6 Dec. 2010

Firstpage

6440

Lastpage

6443

Abstract

This paper researches an interpolation method for lack of LiDAR DEM data area in tidal creeks. The study area is tidal flats in the yellow sea radial sand ridges eastern China. Based on a large of tidal creeks surveying data, combined with topography and geomorphology laws, this research focuses on an interpolation method for lack of LiDAR DEM data area in tidal creek by neural network. The interpolation model structure is 2 hidden layers, 6 neurons in every layer. The calculated terrain of tidal creek that is lack of DEM data is very similar to the actual surveyed terrain. RMSE is 0.117m. R² is 0.716. Residual distribution is normal. The study value is creative to repair the terrain where is lack of LiDAR DEM in tidal flats.

Keywords

Artificial neural networks; Interpolation; Laser radar; Remote sensing; Soil; Surface topography; BP Neural Network; interpolation method; the yellow sea radial sand ridges; tidal creek;

fLanguage

English

Publisher

ieee

Conference_Titel

Information Science and Engineering (ICISE), 2010 2nd International Conference on

Conference_Location

Hangzhou, China

Print_ISBN

978-1-4244-7616-9

Type

conf

DOI

10.1109/ICISE.2010.5691855

Filename

5691855