Abstract
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.
Highlights
Vast majority of the feature detection work appears to be in urban areas
From the comparison in figure 11, we found that the auto generated hydro break lines closely matched with the break lines drawn in semi-automated way
At the bottom right corner of the large water body, we found that the break lines did not match
Summary
Vast majority of the feature detection work appears to be in urban areas. Building tops, well defined fields, streets etc. are some of the more common features that are detected from overhead imagery and LiDAR. Combining LiDAR elevation and intensity data gives better classification accuracy for water body detection (Antonarakis et al, 2008; Brzank et al, 2008; Höfle et al, 2009). Höfle et al, (2009) used a seeded region growing algorithm to delineate water surface from land This method requires lots of pre-processing of LiDAR data such as dropout modelling. We proposed a novel histogram analysis of LiDAR elevation data and LiDAR intensity data to automatically detect and delineate water bodies with very little pre-processing. The flow chart for the proposed auto hydro break line generation method is shown in figure 1 The peer-review was conducted on the basis of the abstract
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