HR: 10:50h
AN: H52E-03 [Abstracts]
TI: Automatic Delineation of Drainage Basins From Contour Elevation Data Using Skeleton Construction Techniques
AU: Moretti, G
EM: giovanni.moretti@unimore.it
AF: Dipartimento di Scienze Agrarie, Università degli Studi di Modena e Reggio Emilia, Via
Amendola 2, Reggio Emilia, 42100, Italy
AU: * Orlandini, S
EM: stefano.orlandini@unimore.it
AF: Dipartimento di Scienze Agrarie, Università degli Studi di Modena e Reggio Emilia, Via
Amendola 2, Reggio Emilia, 42100, Italy
AB:
A new method for automatic delineation of drainage basins from contour elevation data is presented. As a
preprocessing step, contour line vertices are used to construct Delaunay and Voronoi diagrams along with other
useful structures known in computational geometry as the crust and the skeleton or medial axis transform. Using
the skeleton of contour lines, a recursive algorithm is then developed to solve critical topographic structures such
as ridges, saddles, and peaks in a fully-automated and accurate manner. Numerical experiments based on high-
accuracy contour elevation data of real terrains (generated from LiDAR surveys) show that the proposed method
is able to process automatically any topographic structure and to produce results that are comparable to those
that can be interpreted visually from contour lines. The gain in accuracy over state-of-the-art solutions is generally
found to be significant and to increase as the contour interval increases. Finally, it is shown how the proposed
method can be easily applied to construct accurate flow nets in a fully-automated manner. Skeleton construction
techniques allow the morphological information implicitly present in contour elevation data to be explicitly
revealed and appropriately processed by a computer program, and therefore appear useful means for improving
the accuracy with which physiographic features of drainage basins are determined. The proposed method can be
used to advance the construction of flow nets and contour-based digital elevation models (as outlined in this
study) and to test the reliability of algorithms for the analysis of more efficient and straightforward, gridded or
triangulated, elevation data (as shown in a companion study).
DE: 1804 Catchment
DE: 1805 Computational hydrology
DE: 1824 Geomorphology: general (1625)
DE: 1879 Watershed
DE: 1894 Instruments and techniques: modeling
SC: Hydrology [H]
MN: 2007 Fall Meeting