The Younger Dryas Main Line on Leka, Norway, as determined from a high resolution digital elevation model derived from airborne LiDAR data

Geomorphology ◽  
2015 ◽  
Vol 231 ◽  
pp. 63-71 ◽  
Author(s):  
Fredrik Høgaas ◽  
Harald Sveian
Author(s):  
Beycan Hocaoğlu ◽  
Müge Ağca

Topography represented by high resolution digital elevation models are able to inform past and present morphological process on the terrain. High resolution LiDAR data taken by the General Directorate of Map at the surroundings of the Bergama city shows great opportunities to understand the morphological process on alluvial fan on which the city is located and the flood plain of Bakırçay river near the alluvial fan. In this paper the LiDAR data collected in 2015 have been used to create DEM’s to understand the geomorphological evolution of the alluvial fan and the flood plain around it. Since the proximal roots and medial parts of the alluvial fan have been the scene for a long human settlement most topographical traces of the morphological process have been distorted. Nevertheless, the traces of past and present morphological process at the distal fan which consist the contact zone with the flood plain are very clear on the DEM created from LiDAR data. The levees and some old courses of Bergama and Bakırçay rivers have been shown on the maps which are also important to understand the ancient roads which follows these levees.


2020 ◽  
Author(s):  
S.N. Heinlein ◽  
et al.

<div>Video S1: Grayscale digital elevation model generated from high-resolution lidar data illustrating surface expressions at the 1 m to tens of meters scale. Video S2: False-color digital elevation model generated from high-resolution lidar data illustrating surface expressions at the 1 m to tens of meters scale.<br></div>


2020 ◽  
Author(s):  
S.N. Heinlein ◽  
et al.

<div>Video S1: Grayscale digital elevation model generated from high-resolution lidar data illustrating surface expressions at the 1 m to tens of meters scale. Video S2: False-color digital elevation model generated from high-resolution lidar data illustrating surface expressions at the 1 m to tens of meters scale.<br></div>


2021 ◽  
Author(s):  
Shizhou Ma ◽  
Karen Beazley ◽  
Patrick Nussey ◽  
Chris Greene

Abstract The Active River Area (ARA) is a spatial approach for identifying the extent of functional riparian area. Given known limitations in terms of input elevation data quality and methodology, ARA studies to date have not achieved effective computer-based ARA-component delineation, limiting the efficacy of the ARA framework in terms of informing riparian conservation and management. To achieve framework refinement and determine the optimal input elevation data for future ARA studies, this study tested a novel Digital Elevation Model (DEM) smoothing algorithm and assessed ARA outputs derived from a range of DEMs for accuracy and efficiency. It was found that the tested DEM smoothing algorithm allows the ARA framework to take advantage of high-resolution LiDAR DEM and considerably improves the accuracy of high-resolution LiDAR DEM derived ARA results; smoothed LiDAR DEM in 5-meter spatial resolution best balanced ARA accuracy and data processing efficiency and is ultimately recommended for future ARA delineations across large regions.


Author(s):  
A. İ. Durmaz

DEM (Digital Elevation Models) is the best way to interpret topography on the ground. In recent years, lidar technology allows to create more accurate elevation models. However, the problem is this technology is not common all over the world. Also if Lidar data are not provided by government agencies freely, people have to pay lots of money to reach these point clouds. In this article, we will discuss how we can create digital elevation model from less accurate mobile devices’ GPS data. Moreover, we will evaluate these data on the same mobile device which we collected data to reduce cost of this modeling.


2006 ◽  
Vol 88 (3-4) ◽  
pp. 160-172 ◽  
Author(s):  
Rou-Fei Chen ◽  
Kuo-Jen Chang ◽  
Jacques Angelier ◽  
Yu-Chang Chan ◽  
Benoît Deffontaines ◽  
...  

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