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Semi-automatic derivation of channel network from a high-resolution DTM: the example of an Italian alpine region
- Source :
- European Journal of Remote Sensing 46 (2013): 152–174. doi:10.5721/EuJRS20134609, info:cnr-pdr/source/autori:Cavalli M, Trevisani S, Goldin B, Mion E, Crema S, Valentinotti R/titolo:Semi-automatic derivation of channel network from a high-resolution DTM: the example of an Italian alpine region/doi:10.5721%2FEuJRS20134609/rivista:European Journal of Remote Sensing/anno:2013/pagina_da:152/pagina_a:174/intervallo_pagine:152–174/volume:46
- Publication Year :
- 2013
- Publisher :
- Informa UK Limited, 2013.
-
Abstract
- High-resolution digital terrain models (HR-DTMs) of regional coverage open interesting scenarios for the analysis of landscape, including derivation and analysis of channel network. In this study, we present the derivation of the channel network from a HR-DTM for the Autonomous Province of Trento. A preliminary automatic extraction of the raw channel network was conducted using a curvature-based algorithm applied to a 4 m resolution DTM derived from an airborne LiDAR survey carried out in 2006. The raw channel network automatically extracted from the HR-DTM underwent a supervised control to check the spatial pattern of the hydrographic network. The supervised control was carried out by means of different informative layers (i.e. geomorphometric indexes, orthophoto imagery and technical cartography) resulting in an accurate and fine-scale channel network.
- Subjects :
- Atmospheric Science
Channel network
010504 meteorology & atmospheric sciences
Applied Mathematics
Resolution (electron density)
0207 environmental engineering
geomorphometry
Terrain
02 engineering and technology
high-resolution DTM
01 natural sciences
Geography
Geomorphometry
Semi automatic
Computers in Earth Sciences
020701 environmental engineering
0105 earth and related environmental sciences
General Environmental Science
Remote sensing
Subjects
Details
- ISSN :
- 22797254
- Volume :
- 46
- Database :
- OpenAIRE
- Journal :
- European Journal of Remote Sensing
- Accession number :
- edsair.doi.dedup.....6287f21a607a927e978b06f86d877840