Consumer-grade UAV imagery facilitates semantic segmentation of species-rich savanna tree layers

Conventional forest inventories are labour-intensive. This limits the spatial extent and temporal frequency at which woody vegetation is usually monitored. Remote sensing provides cost-effective solutions that enable extensive spatial coverage and high sampling frequency. Recent studies indicate that convolutional neural networks (CNNs) can classify woody forests, plantations, and urban vegetation at the species level using consumer-grade unmanned aerial vehicle (UAV) imagery. However, whether such an approach is feasible in species-rich savanna ecosystems remains unclear. Here, we tested whether small data sets of high-resolution RGB orthomosaics suffice to train U-Net, FC-DenseNet, and DeepLabv3 + in semantic segmentation of savanna tree species. We trained these models on an 18-ha training area and explored whether models could be transferred across space and time. These models could recognise trees in adjacent (mean F1-Score = 0.68) and distant areas (mean F1-Score = 0.61) alike. Over time, a change in plant morphology resulted in a decrease of model accuracy. Our results show that CNN-based tree mapping using consumer-grade UAV imagery is possible in savanna ecosystems. Still, larger and more heterogeneous data sets can further improve model robustness to capture variation in plant morphology across time and space

Abiotic conditions shape the relationship between indigenous and exotic species richness in a montane biodiversity hotspot

Montane ecosystems are more prone to invasions by exotic plant species than previously thought. Besides abiotic factors, such as climate and soil properties, plant-plant interactions within communities are likely to affect the performance of potential invaders in their exotic range. The biotic resistance hypothesis predicts that high indigenous species richness hampers plant invasions. The biotic acceptance hypothesis, on the other hand, predicts a positive relationship between indigenous and exotic species richness. We tested these two hypotheses using observational data along an elevational gradient in a southern African biodiversity hotspot. Species composition data of indigenous and exotic plants were recorded in 20 road verge plots along a gradient of 1775–2775 m a.s.l. in the Drakensberg, South Africa. Plots were 2 × 50 m in size and positioned at 50 m elevational intervals. We found a negative correlation between indigenous and exotic richness for locations with poorly developed mineral soils, suggesting biotic resistance through competitive interactions. A strong positive correlation for plots with very shallow soils at high elevations indicated a lack of biotic resistance and the possibility of facilitating interactions in harsher environments. These results suggest that biotic resistance is restricted to the lower and mid elevations while biotic acceptance prevails in presence of severe abiotic stress, potentially increasing the risk of plant invasions into montane biodiversity hotspots

A high-flux BEC source for mobile atom interferometers

Quantum sensors based on coherent matter-waves are precise measurement devices whose ultimate accuracy is achieved with Bose-Einstein condensates (BEC) in extended free fall. This is ideally realized in microgravity environments such as drop towers, ballistic rockets and space platforms. However, the transition from lab-based BEC machines to robust and mobile sources with comparable performance is a challenging endeavor. Here we report on the realization of a miniaturized setup, generating a flux of $4 \times 10^5$ quantum degenerate $^{87}$Rb atoms every 1.6$\,$s. Ensembles of $1 \times 10^5$ atoms can be produced at a 1$\,$Hz rate. This is achieved by loading a cold atomic beam directly into a multi-layer atom chip that is designed for efficient transfer from laser-cooled to magnetically trapped clouds. The attained flux of degenerate atoms is on par with current lab-based BEC experiments while offering significantly higher repetition rates. Additionally, the flux is approaching those of current interferometers employing Raman-type velocity selection of laser-cooled atoms. The compact and robust design allows for mobile operation in a variety of demanding environments and paves the way for transportable high-precision quantum sensors.Comment: 22 pages, 6 figure

Reduction of radiation biases by incorporating the missing cloud variability by means of downscaling techniques: a study using the 3-D MoCaRT model

Handling complexity to the smallest detail in atmospheric radiative transfer models is unfeasible in practice. On the one hand, the properties of the interacting medium, i.e., the atmosphere and the surface, are only available at a limited spatial resolution. On the other hand, the computational cost of accurate radiation models accounting for three-dimensional heterogeneous media are prohibitive for some applications, especially for climate modelling and operational remote-sensing algorithms. Hence, it is still common practice to use simplified models for atmospheric radiation applications. <br><br> Three-dimensional radiation models can deal with complex scenarios providing an accurate solution to the radiative transfer. In contrast, one-dimensional models are computationally more efficient, but introduce biases to the radiation results. <br><br> With the help of stochastic models that consider the multi-fractal nature of clouds, it is possible to scale cloud properties given at a coarse spatial resolution down to a higher resolution. Performing the radiative transfer within the cloud fields at higher spatial resolution noticeably helps to improve the radiation results. <br><br> We present a new Monte Carlo model, MoCaRT, that computes the radiative transfer in three-dimensional inhomogeneous atmospheres. The MoCaRT model is validated by comparison with the consensus results of the Intercomparison of Three-Dimensional Radiation Codes (I3RC) project. <br><br> In the framework of this paper, we aim at characterising cloud heterogeneity effects on radiances and broadband fluxes, namely: the errors due to unresolved variability (the so-called plane parallel homogeneous, PPH, bias) and the errors due to the neglect of transversal photon displacements (independent pixel approximation, IPA, bias). First, we study the effect of the missing cloud variability on reflectivities. We will show that the generation of subscale variability by means of stochastic methods greatly reduce or nearly eliminate the reflectivity biases. Secondly, three-dimensional broadband fluxes in the presence of realistic inhomogeneous cloud fields sampled at high spatial resolutions are calculated and compared to their one-dimensional counterparts at coarser resolutions. We found that one-dimensional calculations at coarsely resolved cloudy atmospheres systematically overestimate broadband reflected and absorbed fluxes and underestimate transmitted ones

iSense: a technology platform for cold atom based quantum technologies

A breakthrough in cold atom quantum technology is hindered by a bottleneck in the supporting technologies. We discuss a cold atom technology platform developed within the European iSense project, aiming at a gravimeter as demonstrator

Mână de mână cu Boala Celiacă (BC)

Proiectul CD SKILLS PP13 a Universității de Stat de Medicină și Farmacie “Nicolae Testemițanu” din Republica Moldova și permisă spre traducere din limba engleză cu suportul tehnic al echipei de implementare: Tatiana Raba, Olesea Nicu, Anton Pivtora

Space-borne Bose-Einstein condensation for precision interferometry

Space offers virtually unlimited free-fall in gravity. Bose-Einstein condensation (BEC) enables ineffable low kinetic energies corresponding to pico- or even femtokelvins. The combination of both features makes atom interferometers with unprecedented sensitivity for inertial forces possible and opens a new era for quantum gas experiments. On January 23, 2017, we created Bose-Einstein condensates in space on the sounding rocket mission MAIUS-1 and conducted 110 experiments central to matter-wave interferometry. In particular, we have explored laser cooling and trapping in the presence of large accelerations as experienced during launch, and have studied the evolution, manipulation and interferometry employing Bragg scattering of BECs during the six-minute space flight. In this letter, we focus on the phase transition and the collective dynamics of BECs, whose impact is magnified by the extended free-fall time. Our experiments demonstrate a high reproducibility of the manipulation of BECs on the atom chip reflecting the exquisite control features and the robustness of our experiment. These properties are crucial to novel protocols for creating quantum matter with designed collective excitations at the lowest kinetic energy scales close to femtokelvins.Comment: 6 pages, 4 figure

Challenges of Harmonizing 40 Years of AVHRR Data: The TIMELINE Experience

Earth Observation satellite data allows for the monitoring of the surface of our planet at predefined intervals covering large areas. However, there is only one medium resolution sensor family in orbit that enables an observation time span of 40 and more years at a daily repeat interval. This is the AVHRR sensor family. If we want to investigate the long-term impacts of climate change on our environment, we can only do so based on data that remains available for several decades. If we then want to investigate processes with respect to climate change, we need very high temporal resolution enabling the generation of long-term time series and the derivation of related statistical parameters such as mean, variability, anomalies, and trends. The challenges to generating a well calibrated and harmonized 40-year-long time series based on AVHRR sensor data flown on 14 different platforms are enormous. However, only extremely thorough pre-processing and harmonization ensures that trends found in the data are real trends and not sensor-related (or other) artefacts. The generation of European-wide time series as a basis for the derivation of a multitude of parameters is therefore an extremely challenging task, the details of which are presented in this paper