During the last years commercial hyperspectral imaging sensors have been miniaturized and their performance has been demonstrated on Unmanned Aerial Vehicles (UAV). However currently the commercial hyperspectral systems still require minimum payload capacity of approximately 3 kg, forcing usage of rather large UAVs. In this article we present a lightweight hyperspectral mapping system (HYMSY) for rotor-based UAVs, the novel processing chain for the system, and its potential for agricultural mapping and monitoring applications. The HYMSY consists of a custom-made pushbroom spectrometer (400-950 nm, 9 nm FWHM, 25 lines/s, 328 px/line), a photogrammetric camera, and a miniature GPS-Inertial Navigation System. The weight of HYMSY in ready-to-fly configuration is only 2.0 kg and it has been constructed mostly from off-the-shelf components. The processing chain uses a photogrammetric algorithm to produce a Digital 11014Surface Model (DSM) and provides high accuracy orientation of the system over the DSM. The pushbroom data is georectified by projecting it onto the DSM with the support of photogrammetric orientations and the GPS-INS data. Since an up-to-date DSM is produced internally, no external data are required and the processing chain is capable to georectify pushbroom data fully automatically. The system has been adopted for several experimental flights related to agricultural and habitat monitoring applications. For a typical flight, an area of 2-10 ha was mapped, producing a RGB orthomosaic at 1-5 cm resolution, a DSM at 5-10 cm resolution, and a hyperspectral datacube at 10-50 cm resolution.

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Hydrological connectivity describes the physical coupling (linkages) of different elements within a landscape regarding (sub-) surface flows. A firm understanding of hydrological connectivity is important for catchment management applications, for example, habitat and species protection, and for flood resistance and resilience improvement. Thinking about (geomorphological) systems as networks can lead to new insights, which has also been recognized within the scientific community, seeing the recent increase in the use of network (graph) theory within the geosciences. Network theory supports the analysis and understanding of complex systems by providing data structures for modelling objects and their linkages, and a versatile toolbox to quantitatively appraise network structure and properties. The objective of this study was to characterize and quantify overland flow connectivity dynamics on hillslopes in a humid sub-Mediterranean environment by using a combination of high-resolution digital-terrain models, overland flow sensors and a network approach. Results showed that there are significant differences between overland flow connectivity on agricultural areas and semi-natural shrubs areas. Significant positive correlations between connectivity and precipitation characteristics were found. Significant negative correlations between connectivity and soil moisture were found, most likely because of soil water repellency and/or soil surface crusting. The combination of structural networks and dynamic networks for determining potential connectivity and actual connectivity proved a powerful tool for analysing overland flow connectivity. Figure 4. Structural networks for all three years, with 2014 being subdivided in an east (with shrubs) and a west (only agriculture) part. The insets show the networks on the hillslope with their corresponding contributing areas 214 R. J. H. MASSELINK ET AL.

Digital Elevation Models (DEMs) are 3D representations of the Earth's surface and have numerous applications in geomorphology, hydrology and ecology. Structure-from-Motion (SfM) photogrammetry using photographs obtained by unmanned aerial vehicles (UAVs) have been increasingly used for obtaining high resolution DEMs. These DEMs are interpolated from point clouds representing entire landscapes, including points of terrain, vegetation and infrastructure. Up to date, there has not been any study clearly comparing different algorithms for filtering of vegetation. The objective in this study was, therefore, to assess the performance of various vegetation filter algorithms for SfM-obtained point clouds. The comparison was done for a Mediterranean area in Murcia, Spain with heterogeneous vegetation cover. The filter methods that were compared were: color-based filtering using an excessive greenness vegetation index (VI), Triangulated Irregular Networks (TIN) densification from LAStools, the standard method in Agisoft Photoscan (PS), iterative surface lowering (ISL), and a combination of iterative surface lowering and the VI method (ISL_VI). Results showed that for bare areas there was little to no difference between the filtering methods, which is to be expected because there is little to no vegetation present to filter. For areas with shrubs and trees, the ISL_VI and TIN method performed best. These results show that different filtering techniques have various degrees of success in different use cases. A default filter in commercial software such as Photoscan may not always be the best way to remove unwanted vegetation from a point cloud, but instead alternative methods such as a TIN densification algorithm should be used to obtain a vegetation-less Digital Terrain Model (DTM).LiDAR (Light Detection And Ranging) is one of the most widely used techniques to acquire point clouds for the creation of DEMs [6]. With LiDAR, a laser scanner is positioned on a satellite, aircraft/helicopter, boat/vehicle or tripods which measures the travel time between emission and reception of a laser pulse after it was reflected by an object. The strength of the returned signal provides information on the characteristics of the object, and is used to e.g., classify points representing, among others, bare ground, vegetation, water or human infrastructure. Classified point clouds help to analyze the object of interest, speed up calculations and reduce noise. For example, when vegetation points are separated from ground points, only these ground points can be used to interpolate into a continuous surface of the terrain without vegetation, i.e., a Digital Terrain Model (DTM). When extracted from the vegetated surface (DSM, Digital Surface Model), DTMs can be used to estimate vegetation height (Canopy Height Model, CHM) and derivatives such as total aboveground biomass [7]. Although LiDAR is extremely useful, the acquisition of airborne laser scans is expensive.DTMs themselves are valuable tools to model geomorphological and hydrological process...

The prediction of the morphological evolution of renaturalized streams is important for the success of restoration projects. Riparian vegetation is a key component of the riverine landscape and is therefore essential for the natural rehabilitation of rivers. This complicates the design of morphological interventions, since riparian vegetation is influenced by and influences the river dynamics. Morphodynamic models, useful tools for project planning, should therefore include the interaction between vegetation, water flow and sediment processes. Most restoration projects are carried out in USA and Europe, where rivers are highly intervened and where the climate is temperate and vegetation shows a clear seasonal cycle. Taking into account seasonal variations might therefore be relevant for the prediction of the river morphological adaptation. This study investigates the morphodynamic effects of riparian vegetation on a re‐meandered lowland stream in the Netherlands, the Lunterse Beek. The work includes the analysis of field data covering 5 years and numerical modelling. The results allow assessment of the performance of a modelling tool in predicting the morphological evolution of the stream and the relevance of including the seasonal variations of vegetation in the computations. After the establishment of herbaceous plants on its banks, the Lunterse Beek did not show any further changes in channel alignment. This is here attributed to the stabilizing effects of plant roots together with the small size of the stream. It is expected that the morphological restoration of similarly small streams may result in important initial morphological adaptation followed by negligible changes after full vegetation establishment. Copyright © 2018 John Wiley & Sons, Ltd.