@article{ZieglerPollingerBoelletal.2020, author = {Ziegler, Katrin and Pollinger, Felix and B{\"o}ll, Susanne and Paeth, Heiko}, title = {Statistical modeling of phenology in Bavaria based on past and future meteorological information}, series = {Theoretical and Applied Climatology}, volume = {140}, journal = {Theoretical and Applied Climatology}, issn = {0177-798X}, doi = {10.1007/s00704-020-03178-4}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-232717}, pages = {1467-1481}, year = {2020}, abstract = {Plant phenology is well known to be affected by meteorology. Observed changes in the occurrence of phenological phases arecommonly considered some of the most obvious effects of climate change. However, current climate models lack a representationof vegetation suitable for studying future changes in phenology itself. This study presents a statistical-dynamical modelingapproach for Bavaria in southern Germany, using over 13,000 paired samples of phenological and meteorological data foranalyses and climate change scenarios provided by a state-of-the-art regional climate model (RCM). Anomalies of severalmeteorological variables were used as predictors and phenological anomalies of the flowering date of the test plantForsythiasuspensaas predictand. Several cross-validated prediction models using various numbers and differently constructed predictorswere developed, compared, and evaluated via bootstrapping. As our approach needs a small set of meteorological observationsper phenological station, it allows for reliable parameter estimation and an easy transfer to other regions. The most robust andsuccessful model comprises predictors based on mean temperature, precipitation, wind velocity, and snow depth. Its averagecoefficient of determination and root mean square error (RMSE) per station are 60\% and ± 8.6 days, respectively. However, theprediction error strongly differs among stations. When transferred to other indicator plants, this method achieves a comparablelevel of predictive accuracy. Its application to two climate change scenarios reveals distinct changes for various plants andregions. The flowering date is simulated to occur between 5 and 25 days earlier at the end of the twenty-first century comparedto the phenology of the reference period (1961-1990).}, language = {en} } @article{ReinermannAsamKuenzer2020, author = {Reinermann, Sophie and Asam, Sarah and Kuenzer, Claudia}, title = {Remote Sensing of Grassland Production and Management - A Review}, series = {Remote Sensing}, volume = {12}, journal = {Remote Sensing}, number = {12}, issn = {2072-4292}, doi = {10.3390/rs12121949}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-207799}, year = {2020}, abstract = {Grasslands cover one third of the earth's terrestrial surface and are mainly used for livestock production. The usage type, use intensity and condition of grasslands are often unclear. Remote sensing enables the analysis of grassland production and management on large spatial scales and with high temporal resolution. Despite growing numbers of studies in the field, remote sensing applications in grassland biomes are underrepresented in literature and less streamlined compared to other vegetation types. By reviewing articles within research on satellite-based remote sensing of grassland production traits and management, we describe and evaluate methods and results and reveal spatial and temporal patterns of existing work. In addition, we highlight research gaps and suggest research opportunities. The focus is on managed grasslands and pastures and special emphasize is given to the assessment of studies on grazing intensity and mowing detection based on earth observation data. Grazing and mowing highly influence the production and ecology of grassland and are major grassland management types. In total, 253 research articles were reviewed. The majority of these studies focused on grassland production traits and only 80 articles were about grassland management and use intensity. While the remote sensing-based analysis of grassland production heavily relied on empirical relationships between ground-truth and satellite data or radiation transfer models, the used methods to detect and investigate grassland management differed. In addition, this review identified that studies on grassland production traits with satellite data often lacked including spatial management information into the analyses. Studies focusing on grassland management and use intensity mostly investigated rather small study areas with homogeneous intensity levels among the grassland parcels. Combining grassland production estimations with management information, while accounting for the variability among grasslands, is recommended to facilitate the development of large-scale continuous monitoring and remote sensing grassland products, which have been rare thus far.}, language = {en} } @article{DhillonDahmsKuebertFlocketal.2020, author = {Dhillon, Maninder Singh and Dahms, Thorsten and Kuebert-Flock, Carina and Borg, Erik and Conrad, Christopher and Ullmann, Tobias}, title = {Modelling Crop Biomass from Synthetic Remote Sensing Time Series: Example for the DEMMIN Test Site, Germany}, series = {Remote Sensing}, volume = {12}, journal = {Remote Sensing}, number = {11}, issn = {2072-4292}, doi = {10.3390/rs12111819}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-207845}, year = {2020}, abstract = {This study compares the performance of the five widely used crop growth models (CGMs): World Food Studies (WOFOST), Coalition for Environmentally Responsible Economies (CERES)-Wheat, AquaCrop, cropping systems simulation model (CropSyst), and the semi-empiric light use efficiency approach (LUE) for the prediction of winter wheat biomass on the Durable Environmental Multidisciplinary Monitoring Information Network (DEMMIN) test site, Germany. The study focuses on the use of remote sensing (RS) data, acquired in 2015, in CGMs, as they offer spatial information on the actual conditions of the vegetation. Along with this, the study investigates the data fusion of Landsat (30 m) and Moderate Resolution Imaging Spectroradiometer (MODIS) (500 m) data using the spatial and temporal reflectance adaptive reflectance fusion model (STARFM) fusion algorithm. These synthetic RS data offer a 30-m spatial and one-day temporal resolution. The dataset therefore provides the necessary information to run CGMs and it is possible to examine the fine-scale spatial and temporal changes in crop phenology for specific fields, or sub sections of them, and to monitor crop growth daily, considering the impact of daily climate variability. The analysis includes a detailed comparison of the simulated and measured crop biomass. The modelled crop biomass using synthetic RS data is compared to the model outputs using the original MODIS time series as well. On comparison with the MODIS product, the study finds the performance of CGMs more reliable, precise, and significant with synthetic time series. Using synthetic RS data, the models AquaCrop and LUE, in contrast to other models, simulate the winter wheat biomass best, with an output of high R2 (>0.82), low RMSE (<600 g/m\(^2\)) and significant p-value (<0.05) during the study period. However, inputting MODIS data makes the models underperform, with low R2 (<0.68) and high RMSE (>600 g/m\(^2\)). The study shows that the models requiring fewer input parameters (AquaCrop and LUE) to simulate crop biomass are highly applicable and precise. At the same time, they are easier to implement than models, which need more input parameters (WOFOST and CERES-Wheat).}, language = {en} } @article{UllmannNillSchiestletal.2020, author = {Ullmann, Tobias and Nill, Leon and Schiestl, Robert and Trappe, Julian and Lange-Athinodorou, Eva and Baumhauer, Roland and Meister, Julia}, title = {Mapping buried paleogeographical features of the Nile Delta (Egypt) using the Landsat archive}, series = {E\&G Quartnerny Science Journal}, volume = {69}, journal = {E\&G Quartnerny Science Journal}, number = {2}, doi = {10.5194/egqsj-69-225-2020}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-230349}, pages = {225-245}, year = {2020}, abstract = {The contribution highlights the use of Landsat spectral-temporal metrics (STMs) for the detection of surface anomalies that are potentially related to buried near-surface paleogeomorphological deposits in the Nile Delta (Egypt), in particular for a buried river branch close to Buto. The processing was completed in the Google Earth Engine (GEE) for the entire Nile Delta and for selected seasons of the year (summer/winter) using Landsat data from 1985 to 2019. We derived the STMs of the tasseled cap transformation (TC), the Normalized Difference Wetness Index (NDWI), and the Normalized Difference Vegetation Index (NDVI). These features were compared to historical topographic maps of the Survey of Egypt, CORONA imagery, the digital elevation model of the TanDEM-X mission, and modern high-resolution satellite imagery. The results suggest that the extent of channels is best revealed when differencing the median NDWI between summer (July/August) and winter (January/February) seasons (ΔNDWI). The observed difference is likely due to lower soil/plant moisture during summer, which is potentially caused by coarser-grained deposits and the morphology of the former levee. Similar anomalies were found in the immediate surroundings of several Pleistocene sand hills ("geziras") and settlement mounds ("tells") of the eastern delta, which allowed some mapping of the potential near-surface continuation. Such anomalies were not observed for the surroundings of tells of the western Nile Delta. Additional linear and meandering ΔNDWI anomalies were found in the eastern Nile Delta in the immediate surroundings of the ancient site of Bubastis (Tell Basta), as well as several kilometers north of Zagazig. These anomalies might indicate former courses of Nile river branches. However, the ΔNDWI does not provide an unambiguous delineation.}, language = {en} } @article{Schwalb‐WillmannRemelgadoSafietal.2020, author = {Schwalb-Willmann, Jakob and Remelgado, Ruben and Safi, Kamran and Wegmann, Martin}, title = {moveVis: Animating movement trajectories in synchronicity with static or temporally dynamic environmental data in R}, series = {Methods in Ecology and Evolution}, volume = {11}, journal = {Methods in Ecology and Evolution}, number = {5}, doi = {10.1111/2041-210X.13374}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-214856}, pages = {664 -- 669}, year = {2020}, abstract = {Visualizing movement data is challenging: While traditional spatial data can be sufficiently displayed as two-dimensional plots or maps, movement trajectories require the representation of time in a third dimension. To address this, we present moveVis, an R package, which provides tools to animate movement trajectories, overlaying simultaneous uni- or multi-temporal raster imagery or vector data. moveVis automates the processing of movement and environmental data to turn such into an animation. This includes (a) the regularization of movement trajectories enforcing uniform time instances and intervals across all trajectories, (b) the frame-wise mapping of movement trajectories onto temporally static or dynamic environmental layers, (c) the addition of customizations, for example, map elements or colour scales and (d) the rendering of frames into an animation encoded as GIF or video file. moveVis is designed to display interactions and concurrencies of animal movement and environmental data. We present examples and use cases, ranging from data exploration to visualizing scientific findings. Static spatial plots of movement data disregard the temporal dimension that distinguishes movement from other spatial data. In contrast, animations allow to display relocation in both time and space. We deem animations a powerful way to visually explore movement data, frame analytical findings and display potential interactions with spatially continuous and temporally dynamic environmental covariates.}, language = {en} } @article{GeyerPaisWotte2020, author = {Geyer, Gerd and Pais, Miguel Caldeira and Wotte, Thomas}, title = {Unexpectedly curved spines in a Cambrian trilobite: considerations on the spinosity in Kingaspidoides spinirecurvatus sp. nov. from the Anti-Atlas, Morocco, and related Cambrian ellipsocephaloids}, series = {PalZ}, volume = {94}, journal = {PalZ}, issn = {0031-0220}, doi = {10.1007/s12542-020-00514-x}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-231873}, pages = {645-660}, year = {2020}, abstract = {The new ellipsocephaloid trilobite species Kingaspidoides spinirecurvatus has a spectacular morphology because of a unique set of two long and anteriorly recurved spines on the occipital ring and the axial ring of thoracic segment 8. Together with the long genal spines this whimsical dorsally directed spine arrangement is thought to act as a non-standard protective device against predators. This is illustrated by the body posture during different stages of enrolment, contrasting with the more sophisticated spinosities seen in later trilobites, which are discussed in brief. Kingaspidoides spinirecurvatus from the lower-middle Cambrian boundary interval of the eastern Anti-Atlas in Morocco has been known for about two decades, with specimens handled as precious objects on the fossil market. Similar, but far less spectacular, spine arrangements on the thoracic axial rings are known from other ellipsocephaloid trilobites from the Anti-Atlas of Morocco and the Franconian Forest region of Germany. This suggests that an experimental phase of spine development took place within the Kingaspi-doides clade during the early-middle Cambrian boundary interval.}, language = {en} }