Longitudinal spectra of wind velocity in the atmospheric surface layer perturbed by a small topographic ridge

Turbulence measurements carried out in the near neutral surface layer are presented. The wind velocity components were measured with sonic anemometers at 2 and 10 m height. Three masts are considered, placed about 4 km upwind, on the top and about 6 km downwind of Inexpressible Island, a relief 300 m high and 1 km in cross-section. Spectral features are discussed in detail. Local equilibrium is found in the inertial subrange and in (at least in part of) the intermediate range, characterized by different slopes upwind and downwind (k−1 and k−5/3, respectively) for the components parallel to the terrain

Computationally efficient stochastic MPC: A probabilistic scaling approach

In recent years, the increasing interest in stochastic model predictive control (SMPC) schemes has highlighted the limitation arising from their inherent computational demand, which has restricted their applicability to slow-dynamics and high-performing systems. To reduce the computational burden, in this paper we extend the probabilistic scaling approach to obtain a low-complexity inner approximation of chance-constrained sets. This approach provides probabilistic guarantees at a lower computational cost than other schemes for which the sample complexity depends on the design space dimension. To design candidate simple approximating sets, which approximate the shape of the probabilistic set, we introduce two possibilities: i) fixed-complexity polytopes, and ii) ell_{p-norm based sets. Once the candidate approximating set is obtained, it is scaled around its center so to enforce the expected probabilistic guarantees. The resulting scaled set is then exploited to enforce constraints in the classical SMPC framework. The computational gain obtained with respect to the scenario approach is demonstrated via simulations, where the objective is the control of a fixed-wing UAV performing a crop-monitoring mission over a sloped vineyard

Cooperation of unmanned systems for agricultural applications: A theoretical framework

Agriculture 4.0 comprises a set of technologies that combines sensors, information systems, enhanced machinery, and informed management with the objective of optimising production by accounting for variabilities and uncertainties within agricultural systems. Autonomous ground and aerial vehicles can lead to favourable improvements in management by performing in-field tasks in a time-effective way. In particular, greater benefits can be achieved by allowing cooperation and collaborative action among unmanned vehicles, both aerial and ground, to perform in-field operations in precise and time-effective ways. In this work, the preliminary and crucial step of analysing and understanding the technical and methodological challenges concerning the main problems involved is performed. An overview of the agricultural scenarios that can benefit from using collaborative machines and the corresponding cooperative schemes typically adopted in this framework are presented. A collection of kinematic and dynamic models for different categories of autonomous aerial and ground vehicles is provided, which represents a crucial step in understanding the vehicles behaviour when full autonomy is desired. Last, a collection of the state-of-the-art technologies for the autonomous guidance of drones is provided, summarising their peculiar characteristics, and highlighting their advantages and shortcomings with a specific focus on the Agriculture 4.0 framework. A companion paper reports the application of some of these techniques in a complete case study in sloped vineyards, applying the proposed multi-phase collaborative scheme introduced here

Cooperative Agricultural Operations of Aerial and Ground Unmanned Vehicles

Precision agriculture comprises a set of technologies that combines sensors, information systems, enhanced machinery, and informed management to optimize production by accounting for variability and uncertainties within agricultural systems. Autonomous ground and aerial vehicle can lead to favorable improvements in management by performing in-field tasks in a time-effective way. Greater benefits can be achieved by allowing cooperation and collaborative action among Unmanned Aerial Vehicles (UAVs) and Unmanned Ground Vehicles (UGVs). A multi-phase approach is here proposed, where each unmanned vehicle involved has been conceived and will be designed to implement innovative solutions for automated navigation and infield operations within a complex irregular and unstructured scenario as vineyards in sloped terrains

Intuitive geometry and visuospatial working memory in children showing symptoms of nonverbal learning disabilities.

Visuospatial working memory (VSWM) and intuitive geometry were examined in two groups aged 11-13, one with children displaying symptoms of nonverbal learning disability (NLD; n = 16), and the other, a control group without learning disabilities (n = 16). The two groups were matched for general verbal abilities, age, gender, and socioeconomic level. The children were presented with simple storage and complex-span tasks involving VSWM and with the intuitive geometry task devised by Dehaene, Izard, Pica, and Spelke (2006 ). Results revealed that the two groups differed in the intuitive geometry task. Differences were particularly evident in Euclidean geometry and in geometrical transformations. Moreover, the performance of NLD children was worse than controls to a larger extent in complex-span than in simple storage tasks, and VSWM differences were able to account for group differences in geometry. Finally, a discriminant function analysis confirmed the crucial role of complex-span tasks involving VSWM in distinguishing between the two groups. Results are discussed with reference to the relationship between VSWM and mathematics difficulties in nonverbal learning disabilities

3D Map Reconstruction of an Orchard using an Angle-Aware Covering Control Strategy

In the last years, unmanned aerial vehicles are becoming a reality in the context of precision agriculture, mainly for monitoring, patrolling and remote sensing tasks, but also for 3D map reconstruction. In this paper, we present an innovative approach where a fleet of unmanned aerial vehicles is exploited to perform remote sensing tasks over an apple orchard for reconstructing a 3D map of the field, formulating the covering control problem to combine the position of a monitoring target and the viewing angle. Moreover, the objective function of the controller is defined by an importance index, which has been computed from a multi-spectral map of the field, obtained by a preliminary flight, using a semantic interpretation scheme based on a convolutional neural network. This objective function is then updated according to the history of the past coverage states, thus allowing the drones to take situation-adaptive actions. The effectiveness of the proposed covering control strategy has been validated through simulations on a Robot Operating System. Copyright (C) 2022 The Authors

Synthetic ozone deposition and stomatal uptake at flux tower sites

We develop and evaluate a method to estimate O-3 deposition and stomatal O-3 uptake across networks of eddy covariance flux tower sites where O-3 concentrations and O-3 fluxes have not been measured. The method combines standard micrometeorological flux measurements, which constrain O-3 deposition velocity and stomatal conductance, with a gridded dataset of observed surface O-3 concentrations. Measurement errors are propagated through all calculations to quantify O-3 flux uncertainties. We evaluate the method at three sites with O(3 )flux measurements: Harvard Forest, Blodgett Forest, and Hyytiala Forest. The method reproduces 83 % or more of the variability in daily stomatal uptake at these sites with modest mean bias (21 % or less). At least 95 % of daily average values agree with measurements within a factor of 2 and, according to the error analysis, the residual differences from measured O-3 fluxes are consistent with the uncertainty in the underlying measurements. The product, called synthetic O-3 flux or SynFlux, includes 43 FLUXNET sites in the United States and 60 sites in Europe, totaling 926 site years of data. This dataset, which is now public, dramatically expands the number and types of sites where O-3 fluxes can be used for ecosystem impact studies and evaluation of air quality and climate models. Across these sites, the mean stomatal conductance and O-3 deposition velocity is 0.03-1.0 cm s(-1). The stomatal O-3 flux during the growing season (typically April-September) is 0.5-11.0 nmol O-3 m(-2) s(-1) with a mean of 4.5 nmol O(3 )m(-2) s(-1) and the largest fluxes generally occur where stomatal conductance is high, rather than where O-3 concentrations are high. The conductance differences across sites can be explained by atmospheric humidity, soil moisture, vegetation type, irrigation, and land management. These stomatal fluxes suggest that ambient O-3 degrades biomass production and CO2 sequestration by 20 %-24 % at crop sites, 6 %-29 % at deciduous broadleaf forests, and 4 %-20 % at evergreen needleleaf forests in the United States and Europe.Peer reviewe

Detecting Inter-Annual Variations in the Phenology of Evergreen Conifers Using Long-Term MODIS Vegetation Index Time Series

Long-term observations of vegetation phenology can be used to monitor the response of terrestrial ecosystems to climate change. Satellite remote sensing provides the most efficient means to observe phenological events through time series analysis of vegetation indices such as the Normalized Difference Vegetation Index (NDVI). This study investigates the potential of a Photochemical Reflectance Index (PRI), which has been linked to vegetation light use efficiency, to improve the accuracy of MODIS-based estimates of phenology in an evergreen conifer forest. Timings of the start and end of the growing season (SGS and EGS) were derived from a 13-year-long time series of PRI and NDVI based on a MAIAC (multi-angle implementation of atmospheric correction) processed MODIS dataset and standard MODIS NDVI product data. The derived dates were validated with phenology estimates from ground-based flux tower measurements of ecosystem productivity. Significant correlations were found between the MAIAC time series and ground-estimated SGS (R-2 = 0.36-0.8), which is remarkable since previous studies have found it difficult to observe inter-annual phenological variations in evergreen vegetation from satellite data. The considerably noisier NDVI product could not accurately predict SGS, and EGS could not be derived successfully from any of the time series. While the strongest relationship overall was found between SGS derived from the ground data and PRI, MAIAC NDVI exhibited high correlations with SGS more consistently (R-2 > 0.6 in all cases). The results suggest that PRI can serve as an effective indicator of spring seasonal transitions, however, additional work is necessary to confirm the relationships observed and to further explore the usefulness of MODIS PRI for detecting phenology.Peer reviewe

Evaluation of the LSA-SAF gross primary production product derived from SEVIRI/MSG data (MGPP)

The objective of this study is to describe a completely new 10-day gross primary production (GPP) product (MGPP LSA-411) based on data from the geostationary SEVIRI/MSG satellite within the LSA SAF (Land Surface Analysis SAF) as part of the SAF (Satellite Application Facility) network of EUMETSAT. The methodology relies on the Monteith approach. It considers that GPP is proportional to the absorbed photosynthetically active radiation APAR and the proportionality factor is known as the light use efficiency ε. A parameterization of this factor is proposed as the product of a εmax, corresponding to the canopy functioning under optimal conditions, and a coefficient quantifying the reduction of photosynthesis as a consequence of water stress. A three years data record (2015–2017) was used in an assessment against site-level eddy covariance (EC) tower GPP estimates and against other Earth Observation (EO) based GPP products. The site-level comparison indicated that the MGPP product performed better than the other EO based GPP products with 48% of the observations being below the optimal accuracy (absolute error < 1.0 g m−2 day−1) and 75% of these data being below the user requirement threshold (absolute error < 3.0 g m−2 day−1). The largest discrepancies between the MGPP product and the other GPP products were found for forests whereas small differences were observed for the other land cover types. The integration of this GPP product with the ensemble of LSA-SAF MSG products is conducive to meet user needs for a better understanding of ecosystem processes and for improved understanding of anthropogenic impact on ecosystem services.The objective of this study is to describe a completely new 10-day gross primary production (GPP) product (MGPP LSA-411) based on data from the geostationary SEVIRI/MSG satellite within the LSA SAF (Land Surface Analysis SAF) as part of the SAF (Satellite Application Facility) network of EUMETSAT. The methodology relies on the Monteith approach. It considers that GPP is proportional to the absorbed photosynthetically active radiation APAR and the proportionality factor is known as the light use efficiency epsilon. A parameterization of this factor is proposed as the product of a epsilon(max), corresponding to the canopy functioning under optimal conditions, and a coefficient quantifying the reduction of photosynthesis as a consequence of water stress. A three years data record (2015-2017) was used in an assessment against site-level eddy covariance (EC) tower GPP estimates and against other Earth Observation (EO) based GPP products. The site-level comparison indicated that the MGPP product performed better than the other EO based GPP products with 48% of the observations being below the optimal accuracy (absolute error <1.0 g m(-2) day(-1)) and 75% of these data being below the user requirement threshold (absolute error <3.0 g m(-2) day(-1)). The largest discrepancies between the MGPP product and the other GPP products were found for forests whereas small differences were observed for the other land cover types. The integration of this GPP product with the ensemble of LSA-SAF MSG products is conducive to meet user needs for a better understanding of ecosystem processes and for improved understanding of anthropogenic impact on ecosystem services.Peer reviewe