Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XL-2/W2, 99-104, 2013
https://doi.org/10.5194/isprsarchives-XL-2-W2-99-2013
© Author(s) 2013. This work is distributed under
the Creative Commons Attribution 3.0 License.
 
21 Aug 2013
A NOVEL METHOD FOR AUTOMATION OF 3D HYDRO BREAK LINE GENERATION FROM LIDAR DATA USING MATLAB
G. J. Toscano, U. Gopalam, and V. Devarajan Dept. of Electrical Engineering, University of Texas at Arlington, Texas, USA
Keywords: LiDAR, Water body, Classification, Break lines, Histogram Abstract. Water body detection is necessary to generate hydro break lines, which are in turn useful in creating deliverables such as TINs, contours, DEMs from LiDAR data. Hydro flattening follows the detection and delineation of water bodies (lakes, rivers, ponds, reservoirs, streams etc.) with hydro break lines. Manual hydro break line generation is time consuming and expensive. Accuracy and processing time depend on the number of vertices marked for delineation of break lines. Automation with minimal human intervention is desired for this operation. This paper proposes using a novel histogram analysis of LiDAR elevation data and LiDAR intensity data to automatically detect water bodies. Detection of water bodies using elevation information was verified by checking against LiDAR intensity data since the spectral reflectance of water bodies is very small compared with that of land and vegetation in near infra-red wavelength range. Detection of water bodies using LiDAR intensity data was also verified by checking against LiDAR elevation data. False detections were removed using morphological operations and 3D break lines were generated. Finally, a comparison of automatically generated break lines with their semi-automated/manual counterparts was performed to assess the accuracy of the proposed method and the results were discussed.
Conference paper (PDF, 635 KB)


Citation: Toscano, G. J., Gopalam, U., and Devarajan, V.: A NOVEL METHOD FOR AUTOMATION OF 3D HYDRO BREAK LINE GENERATION FROM LIDAR DATA USING MATLAB, Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XL-2/W2, 99-104, https://doi.org/10.5194/isprsarchives-XL-2-W2-99-2013, 2013.

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