CubeSat constellations provide enhanced crop phenology and digital agricultural insights using daily leaf area index retrievals

Satellite remote sensing has great potential to deliver on the promise of a data-driven agricultural revolution, with emerging space-based platforms providing spatiotemporal insights into precisionlevel attributes such as crop water use, vegetation health and condition and crop response to management practices. Using a harmonized collection of high-resolution Planet CubeSat, Sentinel-2, Landsat-8 and additional coarser resolution imagery from MODIS and VIIRS, we exploit a multisatellite data fusion and machine learning approach to deliver a radiometrically calibrated and gap-filled time-series of daily leaf area index (LAI) at an unprecedented spatial resolution of 3 m. The insights available from such high-resolution CubeSat-based LAI data are demonstrated through tracking the growth cycle of a maize crop and identifying observable within-field spatial and temporal variations across key phenological stages. Daily LAI retrievals peaked at the tasseling stage, demonstrating their value for fertilizer and irrigation scheduling. An evaluation of satellite-based retrievals against field-measured LAI data collected from both rain-fed and irrigated fields shows high correlation and captures the spatiotemporal development of intra- and inter-field variations. Novel agricultural insights related to individual vegetative and reproductive growth stages were obtained, showcasing the capacity for new high-resolution CubeSat platforms to deliver actionable intelligence for precision agricultural and related applications

Search for the γ decay of the narrow near-threshold proton resonance in 11B

The γ decay of the elusive narrow, near-threshold proton resonance in 11B was investigated at Laboratori Nazionali di Legnaro (INFN) in a particle-γ coincidence experiment, using the 6Li(6Li,pγ) fusion-evaporation reaction and the GALILEO-GALTRACE setup. No clear signature was found for a possible E1 decay to the 1/2 , first-excited state of 11B, predicted by the Shell Model Embedded in the Continuum (SMEC) with a branching of with respect to the dominant particle-decaying modes. The statistical analysis of the γ-ray spectrum provided an average upper limit of for this γ-ray branching, with a global significance of 5σ. On the other hand, by imposing a global confidence level of 3σ, a significant excess of counts was observed for E keV, corresponding to a resonance energy of 11429(20) keV (namely 200(20) keV above the proton separation energy of 11B) and a γ-ray branching of . This result is compatible with the SMEC calculations, potentially supporting the existence of a near-threshold proton resonance in 11B.This work was supported by the Italian Istituto Nazionale di Fisica Nucleare, the Polish National Science Centre, Poland under research project No. 2020/39/D/ST2/03443 , the PRIN2017 call for funding, under the project 2017P8KMFT CTADIR from the Italian Ministry of Education, University and Research, the Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education, grant no. 2020R1A6A3A03039081 , the MCIN/AEI/10.13039/501100011033, Spain with grant PID2020-118265GB-C42 , by Generalitat Valenciana, Spain with grant CIAPOS/2021/114 and by the EU FEDER funds.Departamento de Física Aplicad

The role of topography, soil, and remotely sensed vegetation condition towards predicting crop yield

Foreknowledge of the spatiotemporal drivers of crop yield would provide a valuable source of information to optimize on-farm inputs and maximize profitability. In recent years, an abundance of spatial data providing information on soils, topography, and vegetation condition have become available from both proximal and remote sensing platforms. Given the wide range of data costs (between USD $0−50/ha), it is important to understand where often limited financial resources should be directed to optimize field production. Two key questions arise. First, will these data actually aid in better fine-resolution yield prediction to help optimize crop management and farm economics? Second, what level of priority should stakeholders commit to in order to obtain these data? Before fully addressing these questions a remaining challenge is the complex nature of spatiotemporal yield variation. Here, a methodological framework is presented to separate the spatial and temporal components of crop yield variation at the subfield level. The framework can also be used to quantify the benefits of different data types on the predicted crop yield as well to better understand the connection of that data to underlying mechanisms controlling yield. Here, fine-resolution (10 m) datasets were assembled for eight 64 ha field sites, spanning a range of climatic, topographic, and soil conditions across Nebraska. Using Empirical Orthogonal Function (EOF) analysis, we found the first axis of variation contained 60–85 % of the explained variance from any particular field, thus greatly reducing the dimensionality of the problem. Using Multiple Linear Regression (MLR) and Random Forest (RF) approaches, we quantified that location within the field had the largest relative importance for modeling crop yield patterns. Secondary factors included a combination of vegetation condition, soil water content, and topography. With respect to predicting spatiotemporal crop yield patterns, we found the RF approach (prediction RMSE of 0.2−0.4 Mg/ha for maize) was superior to MLR (0.3−0.8 Mg/ha). While not directly comparable to MLR and RF the EOF approach had relatively low error (0.5–1.7 Mg/ha) and is intriguing as it requires few calibration parameters (2–6 used here) and utilizes the climate-based aridity index, allowing for pragmatic long-term predictions of subfield crop yield

A multi-scale hierarchical framework for developing understanding of river behaviour to support river management

The work leading to this paper was funded through the European Union’s FP7 programme under Grant Agreement No. 282656 (REFORM). The framework methodology was developed within the context of Deliverable D2.1 of the REFORM programme, and all partners who contributed to the development of the four parts of this deliverable are included in the author list of this paper. More details on the REFORM framework can be obtained from part 1 of Deliverable D2.1 (Gurnell et al. 2014), which is downloadable from http://​www.​reformrivers.​eu/​results/​deliverables

Testing ab initio nuclear structure in neutron-rich nuclei: Lifetime measurements of second 2+ state in 16C and 20O

To test the predictive power of ab initio nuclear structure theory, the lifetime of the second 2+ state in neutron-rich 20O,τ(2+2)=150+80−30fs, and an estimate for the lifetime of the second 2+ state in 16C have been obtained for the first time. The results were achieved via a novel Monte Carlo technique that allowed us to measure nuclear state lifetimes in the tens-to-hundreds of femtoseconds range by analyzing the Doppler-shifted γ-transition line shapes of products of low-energy transfer and deep-inelastic processes in the reaction 18O(7.0MeV/u)+181Ta. The requested sensitivity could only be reached owing to the excellent performances of the Advanced γ-Tracking Array AGATA, coupled to the PARIS scintillator array and to the VAMOS++ magnetic spectrometer. The experimental lifetimes agree with predictions of ab initio calculations using two- and three-nucleon interactions, obtained with the valence-space in-medium similarity renormalization group for 20O and with the no-core shell model for 16C. The present measurement shows the power of electromagnetic observables, determined with high-precision γ spectroscopy, to assess the quality of first-principles nuclear structure calculations, complementing common benchmarks based on nuclear energies. The proposed experimental approach will be essential for short lifetime measurements in unexplored regions of the nuclear chart, including r-process nuclei, when intense beams, produced by Isotope Separation On-Line (ISOL) techniques, become available

Le criticità delle relazioni negoziali

Il lavoro si prefigge di fornire un quadro informativo articolato ed aggiornato sulle principali criticità del mercato della distribuzione moderna in modo da favorire una condivisione delle aree su cui costruire un nuovo modello negoziale