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Introduction

In the last two decades the use of Light Detection and Ranging (LiDAR) technology which is also known as laser scanning has rapidly increased (Hohenthal et al. 2011, Höfle & Rutzinger 2011). Thereby the acquisition of high-detailed 3D geoinformation has experienced a veritable revolution and has developed into the state-of-the-art technology in fields of topographic survey (Vosselman & Maas 2010). As active remote sensing method, LiDAR works with the basic principle of the time-of-flight measurement. The sensor measures the time t of the round-trip of the emitted near-infrared laser pulses between the device and the target object. Under the assumption of the speed of light (ca. 3·108 m/s) the distance R can be computed (R= c · t/2). Together with the exact position of the sensor determined by a Global Navigation Satellite System (GNSS) as well as the angle of the emitted pulse consequently the XYZ coordinates of the reflective target object can be calculated. This leads to high-resolution 3D models composed of up to several million points, the so-called point cloud (Heritage & Large 2009, Shan & Toth 2008). The LiDAR systems are distinguished by the scanner platform: Airborne Laser Scanning (ALS) is operating from airplanes, helicopters or drones; Mobile Laser Scanning (MLS) on moving vehicles like cars or boats and Terrestrial Laser Scanning (TLS) is performed statically on the ground (Höfle & Rutzinger 2011).

High-resolution Digital Elevation Models (DEMs) are dealing with point densities of 10-50 points/m² depending on the system and the surveying area. This high density leads to huge point clouds containing up to several million points. Beside the 3D information recent systems record the whole backscattered signal echo, the full-waveform (Mallet & Bretar 2009). This information provides a few more physical properties of scanned objects since the reflected information is dependent on the objects' surface properties. LiDAR data are already applied in diverse research fields mainly of geography and related fields like natural hazard management, agriculture, forestry, archaeology, glaciology, renewable energy or city modeling (e.g. Geist et al. 2009, Heritage & Large 2009, Höfle et al. 2012). Also public institutions have begun to generate regional or nationwide DEMs derived from LiDAR data. Due to a growing understanding of geomorphological and hydrological surface processes also applications in fluvial studies require more accurate topographic information such as Digital Terrain Models (DTMs) (Hohenthal et al. 2011). More detailed capturing of the topography can hereby be used to model river flows or flood predictions as well as for erosion and sedimentation processes (Eitel et al. 2011, Höfle & Rutzinger 2011, Mandlburger et al. 2009, Vetter et al. 2011).

The study project HydroChange³ deals with the assessment and description of fluvial dynamics by means of TLS data. In 2011 and 2012 scientists and students of the Institute of Geography, University of Heidelberg, carried out two field campaigns whereby fluvial processes of the Neckar at Ilvesheim/Seckenheim have been investigated (Hämmerle et al. 2013). This study project aims at continuing the multi-temporal data acquisition and to improve and automate analysis workflows. The objectives of the study are divided into different investigation foci which are treated by 5 different working groups. These are dealing with:

  1. the creation and implementation of an automated workflow to derive DTMs;
  2. automatic (hydraulic) roughness mapping and comparison of different methods;
  3. multi-temporal fine registration and volume balances;
  4. comparison of DTMs and effect on hydraulic modeling (1D/2D);
  5. multimedia visualization of processes and evolution of gravel bar

After describing the survey area and the field campaign each topic and the corresponding theory, methods and results are treated separately in own chapters before the overall result is being concluded.

The Study Area

In the context of three study projects in 2011, 2012 and 2013, TLS field campaigns are conducted. The field campaigns cover a gravel bar of approximately 150 m in length and 25 m width which is located in a side branch of the Neckar river near Heidelberg between Ladenburg and Ilvesheim (49_28’36”N, 8_34’32”E, Fig. 1.1). The gravel bar is situated in a nature reserve with natural river characteristics which includes seasonally changing water levels. These flood events flood the gravel bar periodically and change their morphology.

Survey map of the study area (TK 25 BW) with satellite image of the gravel bar (Google Earth 2013)