The advantages of remote sensing using Unmanned Aerial Vehicles (UAVs) are a high spatial resolution of images, temporal flexibility and narrow-band spectral data from different wavelengths domains. This enables the detection of spatio-temporal dynamics of environmental variables, like plant-related carbon dynamics in agricultural landscapes. In this paper, we quantify spatial patterns of fresh phytomass and related carbon (C) export using imagery captured by a 12-band multispectral camera mounted on the fixed wing UAV Carolo P360. The study was performed in 2014 at the experimental area CarboZALF-D in NE Germany. From radiometrically corrected and calibrated images of lucerne (Medicago sativa), the performance of four commonly used vegetation indices (VIs) was tested using band combinations of six near-infrared bands. The highest correlation between ground-based measurements of fresh phytomass of lucerne and VIs was obtained for the Enhanced Vegetation Index (EVI) using near-infrared band b₈₉₉. The resulting map was transformed into dry phytomass and finally upscaled to total C export by harvest. The observed spatial variability at field- and plot-scale could be attributed to small-scale soil heterogeneity in part.

Physical models are a well-established tool in education to strengthen hydrological understanding. They facilitate the straightforward visualization of hydrological processes and allow the communication of hydrological concepts, research and questions of general interest to the public. In order to visualize the water cycle in a landscape of postglacial sediments, in particular the subsurface part, a physical model was constructed. In two videos, (1) a detailed construction manual and (2) visualization examples of hydrological concepts and processes are presented. With our contribution, we like to encourage professionals in the field of hydrology to share methods and tools of knowledge transfer and communication of hydrological concepts. Copyright © 2016 John Wiley & Sons, Ltd.