Niels S. Anders

A Lightweight Hyperspectral Mapping System and Photogrammetric Processing Chain for Unmanned Aerial Vehicles

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 Surface 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.

A network theory approach for a better understanding of overland flow connectivity

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. Copyright

Geomorphological Change Detection Using Object-Based Feature Extraction From Multi-Temporal LiDAR Data

Multi-temporal LiDAR digital terrain models (DTMs) are used for the development and testing of a method for geomorphological change analysis in western Austria. Point data from two airborne LiDAR campaigns of 2003 and 2011 were filtered and interpolated into two 2m DTMs. Seven geomorphological features were mapped by using stratified object-based image analysis (OBIA) using terrain properties derived from the DTMs. Segmentation parameters and classification rules were set and applied to both data sets which allowed analysis of geomorphological change between 2003 and 2011. Volumetric change was calculated and summarized by their landform category. The multi-temporal landform classifications show where landforms changed into other landforms as the result of geomorphological process activity. However, differences in point densities and lack of data points below dense forest hindered accurate geomorphological change detection in these areas. When challenges related to interpolation techniques are tackled, stratified OBIA of multi-temporal LiDAR data sets is a promising tool for geomorphological change detection, and affiliated applications such as monitoring risk and natural hazards, rate of change analyses, and vulnerability assessments.

A light-weight hyperspectral mapping system for unmanned aerial vehicles — The first results

Research opportunities using UAV remote sensing techniques are limited by the payload of the platform. Therefore small UAVs are typically not suitable for hyperspectral imaging due to the weight of the mapping system. In this research, we are developing a light-weight hyperspectral mapping system (< 2 kg) suitable to be mounted on small UAVs. The system is able to produce georeferenced and georectified hyperspectral data cubes in 400–1000nm spectral range at 10–50cm resolution. The georeferenced reflectance factor spectra cubes are to be used in e.g. precision agriculture and soil erosion research. In this paper we describe prototype of the system, the processing chain, and present preliminary results.

A Science Gateway for Biodiversity and Climate Change Research.

Climate and biodiversity systems are closely interlaced across a wide range of scales. To better understand the mutual interaction between climate change and biodiversity there is a strong need for multidisciplinary skills, tools and a large variety of heterogeneous, distributed data sources. In this regard, the EUBrazilCloudConnect project provides a user-centric research environment built on top of a federated cloud infrastructure across Europe and Brazil to serve scientific needs. One of the test cases implemented in this project focuses on climate change and biodiversity research. The BioClimate is the Science Gateway of the use case. It aims at providing the end-users with a highly integrated environment, addressing mainly data analytics requirements. This paper presents a complete overview about BioClimate and the scientific environment delivered to the user community at the end of the project.

Morphodynamic effects of riparian vegetation growth after stream restoration: Morphodynamic effects of riparian vegetation growth after restoration

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 5years 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.