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Airborne remote sensing with optical sensor systems is an essential tool for a variety of environmental monitoring applications. Depending on the size of the area to be monitored, either unmanned (UAVs) or manned aircraft are more suitable. For survey areas starting at several square kilometers, piloted aircraft remain the preferred carrier platform. However, a specific class of manned aircraft is often not considered: the gyrocopter-type ultralight aircraft. These aircraft are less expensive to operate than conventional fixed wings. Additionally, they are highly maneuverable, offer a high payload and a long endurance, and thus perfectly fill the niche between UAVs and conventional aircraft. Therefore, the authors have developed a modular and easy-to-use sensor carrier system, the FlugKit, to temporarily convert an AutoGyro MTOsport gyrocopter into a full-fledged aerial remote sensing platform mainly for vegetation monitoring. Accordingly, various suitable optical sensor systems in the visible (VIS), near-infrared (NIR), and longwave infrared (LWIR) were explicitly developed for this carrier system. This report provides a deeper insight into the individual components of this remote sensing solution based on a gyrocopter as well as application scenarios already carried out with the system.

Remote sensing systems based on unmanned aerial vehicles (UAVs) are well suited for airborne monitoring of small to medium-sized farmland in agricultural applications. An imaging system is often used in the form of a multispectral multi-camera system to derive well-established vegetation indices (VIs) efficiently. This study investigates the potential of such a multi-camera system with a novel approach to extend spectral sensitivity from visible-to-near-infrared (VNIR) to short-wave infrared (SWIR) (400–1700 nm) for estimating forage mass from an aerial carrier platform. The system test was performed in a grassland fertilizer trial in Germany near Cologne in late July 2019. Within 37 min, a spectral response in four different wavelength bands in the NIR and SWIR range was acquired during two consecutive flights. Spectral image data were calibrated to reflectance using two different methods. The resulting reflectance data sets were processed to orthomosaics for each wavelength band. From these orthomosaics for both calibration methods, the four-band NIR/SWIR GnyLi VI and the two-band NIR/SWIR Normalized Ratio Index (NRI), were calculated. During both UAV flights, spectral ground truth data were recorded with a spectroradiometer on 12 plots in total for validation of camera-based spectral data. The camera and spectroradiometer data sets were directly compared in resulting reflectance and further analyzed with simple linear regression (SLR) models to predict dry matter (DM) yield. In the camera-based SLRs, the NRI performed best with $$R^2$$ R 2 of 0.73 and 0.75 (RMSE: 0.18 and 0.17) before the GnyLi with $$R^{2}$$ R 2 of 0.71 and 0.73 (RMSE: 0.19 and 0.18). These results clearly indicate the potential of the camera system for applications in forage mass monitoring.

Up-to-date information about vegetation types and hydromorphological structures and features are essential for the management of waterways. They are e.g. used for the monitoring and reporting of ri...

In this paper the development of a lightweight and highly modularized airborne sensor platform for remote sensing applications utilizing a gyrocopter as a carrier platform is described. The current sensor configuration consists of a high resolution DSLR camera for VIS-RGB recordings. As a second sensor modality, a snapshot hyperspectral camera was integrated in the aircraft. Moreover a custom-developed thermal imaging system composed of a VIS-PAN camera and a LWIR-camera is used for aerial recordings in the thermal infrared range. Furthermore another custom-developed highly flexible imaging system for high resolution multispectral image acquisition with up to six spectral bands in the VIS-NIR range is presented. The performance of the overall system was tested during several flights with all sensor modalities and the precalculated demands with respect to spatial resolution and reliability were validated. The collected data sets were georeferenced, georectified, orthorectified and then stitched to mosaics.

Vier Jahre nach dem Start eines Weiterbildungsprogramms zur Forderung der Hausarztmedizin liess der Kanton St. Gallen dessen Nutzen und Effizienz analysieren. Hat das Programm die Hausarztmedizin wirklich gefordert?

This study presents the results from a combined aerial survey performed with a hexacopter and a gyrocopter over a part of the Elbe estuary near Hamburg, Germany. The survey was conducted by the Federal Institute of Hydrology, Germany, and the Fraunhofer Application Center for Multimodal and Airborne Sensors as well as by a contracted engineering company with the aim to acquire spatial thermal infrared (TIR) data of the Hahnofer Nebenelbe, a branch of the Elbe estuary. Additionally, RGB and NIR data was captured to facilitate the identification of water surfaces and intertidal mudflats. The temperature distribution of the Elbe estuary affects all biological processes and in consequence the oxygen content, which is a key parameter in water quality. The oxygen levels vary in space between the main fairway and side channels. So far, only point measurements are available for monitoring and calibration/validation of water quality models. To better represent this highly dynamic system with a high spatial and temporal variability, tidal streams, heating and cooling, diffusion and mixing processes, spatially distributed data from several points of time within the tidal cycle are necessary. The data acquisition took place during two tidal cycles over two subsequent days in the summer of 2015. While the piloted gyrocopter covered the whole Hahnofer Nebenelbe seven times, the unmanned hexacopter covered a smaller section of the branch and tidal mudflats with a higher spatial and temporal resolution (16 coverages of the subarea). The gyrocopter data was acquired with a thermal imaging system and processed and georeferenced using the structure from motion algorithm with GPS information from the gyrocopter and optional ground control points. The hexacopter data was referenced based on ground control points and the GPS and position information of the acquisition system. Both datasets from the gyrocopter and the hexacopter are corrected for the effects of the atmosphere and emissivity of the water surface and compared to in situ measurements, taken during the data acquisition. Of particular interest is the effect of the observation angle on the brightness temperature acquired by the wide angle lenses on the platforms, which is up to 40° at the margins of the imagery. Here, both datasets show deviating temperatures, which are probably not due to actual temperature differences. We will discuss the position accuracy achieved over the water areas, the adaptation of atmospheric and emissivity correction to the observation angle and subsequent improvement of the temperature data. With two datasets of the same research area at different resolutions we will investigate the effects of the acquisition platforms, acquisition system and resolutions on the accuracy of the remotely sensed temperatures as well as their ability to represent temperature patterns of tidal currents and mixing processes.