Evaluation of BRDF Information Retrieved from Time-Series Multiangle Data of the Himawari-8 AHI

Recently, much attention has been given to using geostationary Earth orbit (GEO) meteorological satellite data for retrieving land surface parameters due to their high observation frequencies. However, their bidirectional reflectance distribution function (BRDF) information content with a single viewing angle has not been sufficiently investigated, which lays a foundation for subsequent quantitative estimation. In this study, we aim to comprehensively evaluate BRDF information from time-series observations from the Advanced Himawari Imager (AHI) onboard the GEO satellite Himawari-8. First, ~6.2 km monthly multiangle surface reflectances from POLDER onboard a low-Earth-orbiting (LEO) satellite with good angle distributions over various land types during 2008 were used as reference data, and corresponding 0.05° high-quality MODIS (i.e., onboard LEO satellites) and AHI datasets during four months in 2020 were obtained using cloud and aerosol property products. Then, indicators of angle distribution, BRDF change, and albedos were retrieved by the kernel-driven Ross-Li BRDF model from the three datasets, which were used for comparisons over different time spans. Generally, the quality of sun-viewing geometries varies dramatically for accumulated AHI observations according to the weight-of-determination, and wide-ranging anisotropic flat indices are obtained. The root-mean-square-errors of white sky albedos between AHI and MODIS half-month data are 0.018 and 0.033 in the red and near-infrared bands, respectively, achieving smaller values of 0.004 and 0.007 between the half-month and daily AHI data, respectively, due to small variances in sun-viewing geometries. The generally wide AHI BRDF variances and good consistency in albedo with MODIS show their potential for retrieving anisotropy information and albedo, while angle accumulation quality of AHI time-series observations must be considered.

Effect of off-stoichiometry on the thermal conductivity of amorphous GeTe

The reversible phase change of Germanium Telluride (GeTe) is essential for developing advanced non-volatile devices. We investigate off-stoichiometric effect on the thermal and structural properties of amorphous Ge$_{1-\delta}$Te (0 $\le$ $\delta$ $\le$ 0.12) via molecular dynamics. The structural optimization due to off-stoichiometry was taken into account with an empirical potential. Our simulated thermal conductivity is in the range of experimental observations. With increasing $\delta$, the thermal conductivity tends to be slightly reduced. Analysis on the coordinate number and the bond angle distribution indicates that the off-stoichiometric Ge$_{1-\delta}$Te still retain its ability of rapid phase transition. These results are helpful in reliable device design and modeling.

Early-Time Non-Equilibrium Pitch Angle Diffusion of Electrons by Whistler-Mode Hiss in a Plasmaspheric Plume Associated with BARREL Precipitation

In August 2015, the Balloon Array for Radiation belt Relativistic Electron Losses (BARREL) observed precipitation of energetic (<200 keV) electrons magnetically conjugate to a region of dense cold plasma as measured by the twin Van Allen Probes spacecraft. The two spacecraft passed through the high density region during multiple orbits, showing that the structure was spatial and relatively stable over many hours. The region, identified as a plasmaspheric plume, was filled with intense hiss-like plasma waves. We use a quasi-linear diffusion model to investigate plume whistler-mode hiss waves as the cause of precipitation observed by BARREL. The model input parameters are based on the observed wave, plasma and energetic particle properties obtained from Van Allen Probes. Diffusion coefficients are found to be largest in the same energy range as the precipitation observed by BARREL, indicating that the plume hiss waves were responsible for the precipitation. The event-driven pitch angle diffusion simulation is also used to investigate the evolution of the electron phase space density (PSD) for different energies and assumed initial pitch angle distributions. The results show a complex temporal evolution of the phase space density, with periods of both growth and loss. The earliest dynamics, within the ∼5 first minutes, can be controlled by a growth of the PSD near the loss cone (by a factor up to ∼2, depending on the conditions, pitch angle, and energy), favored by the absence of a gradient at the loss cone and by the gradients of the initial pitch angle distribution. Global loss by 1-3 orders of magnitude (depending on the energy) occurs within the first ∼100 min of wave-particle interaction. The prevalence of plasmaspheric plumes and detached plasma regions suggests whistler-mode hiss waves could be an important driver of electron loss even at high L-value (L ∼6), outside of the main plasmasphere.

Quantitative Investigation of Hand Grasp Functionality: Hand Joint Motion Correlation, Independence, and Grasping Behavior

Modeling and understanding human grasp functionality are fundamental in prosthetics, robotics, medicine, and rehabilitation, since they contribute to exploring motor control mechanism, evaluating grasp function, and designing and controlling prosthetic hands or exoskeletons. However, there are still limitations in providing a comprehensive and quantitative understanding of hand grasp functionality. After simultaneously considering three significant and essential influence factors in daily grasping contained relative position, object shape, and size, this paper presents the tolerance grasping to provide a more comprehensive understanding of human grasp functionality. The results of joint angle distribution and variance explained by PCs supported that tolerance grasping can represent hand grasp functionality more comprehensively. Four synergies are found and account for 93 % ± 1.5 % of the overall variance. The ANOVA confirmed that there was no significant individual difference in the first four postural synergies. The common patterns of grasping behavior were found and characterized by the mean value of postural synergy across 10 subjects. The independence analysis demonstrates that the tolerance grasping results highly correlate with unstructured natural grasping and more accurately correspond to cortical representation size of finger movement. The potential for exploring the neuromuscular control mechanism of human grasping is discussed. The analysis of hand grasp characteristics that contained joint angle distribution, correlation, independence, and postural synergies, presented here, should be more representative to provide a more comprehensive understanding of hand grasp functionality.

Simulation of the Scattering of Continuously Injected Pickup Ions outside the Heliopause

Hybrid simulations in 2D space and 3D velocity dimensions with continuous injection of pickup ions (PUIs) provide insight into the plasma processes that are responsible for the pitch angle scattering of PUIs outside the heliopause. The present investigation includes for the first time continuous injection of PUIs and shows how the scattering depends on the energy of the PUIs and the strength of the background magnetic field as well as the dependence on the injection rate of the time for the isotropization of the pitch angle distribution. The results demonstrate that, with the gradual injection of PUIs of a narrow ring velocity distribution perpendicular to the background magnetic field, oblique mirror mode waves develop first, followed by the growth of quasiparallel propagating ion cyclotron waves. Subsequently, the PUIs are scattered by the excited waves and gradually approach an isotropic distribution. A time for isotropization is defined to be the time at which T ∣∣/T ⊥, i.e., the ratio of the parallel to perpendicular PUI thermal energy changes from ≈0 to ≈0.15. By varying the PUI injection rate, estimates of the time for the PUI distribution to be isotropized are presented. The isotropization time obtained is shorter, ≈ months, than the time, ≈ years, required by the conventional secondary ENA mechanism to explain the IBEX ENA ribbon.

Characterizing Genotype-Specific Rice Architectural Traits Using Smart Mobile App and Data Modeling

The quantity and quality of light captured by a plant’s canopy control many of its growth and development processes. However, light quality-related processes are not very well represented in most traditional and functional–structural crop models, which has been a major barrier to furthering crop model improvement and to better capturing the genetic control and environment modification of plant growth and development. A main challenge is the difficulty in obtaining dynamic data on plant canopy architectural characteristics. Current approaches on the measurement of 3D traits often relies on technologies that are either costly, excessively complicated, or impractical for field use. This study presents a methodology to estimate plant 3D traits using smart mobile app and data modeling. Leaf architecture data on 16 genotypes of rice were collected during two crop seasons using the smart-app PocketPlant3D. Quadratic Bézier curves were fitted to leaf lamina for estimation of insertion angle, elevation angle, and curve height. Leaf azimuth angle distribution, leaf phyllotaxis, canopy leaf angle distribution, and light extinction coefficients were also analyzed. The results could be used for breeding line selection or for parameterizing or evaluating rice 3D architectural models. The methodology opens new opportunities for strengthening the integration of plant 3D architectural traits in crop modeling, better capturing the genetic control and environment modification of plant growth and development, and for improving ideotype-based plant breeding.

Modeling of Anisotropy Dynamics of the Proton Pitch Angle Distribution in the Earth’s Magnetosphere

Last years the attention to research of anisotropy of the charged particle pitch angle distribution has considerably increased. Therefore for research of anisotropy dynamics of the proton pitch angle distribution is used the two-dimensional Phenomenological Model of the Ring Current (PheMRC 2-D), which includes the radial and pitch angle diffusions with consideration of losses due to wave-particle interactions. Experimental data are collected on the Polar/MICS satellite during the magnetic storm on October 21–22, 1999. Solving the non-stationary two-dimensional equation of pitch angle and radial diffusions, numerically was determined the proton pitch angle distribution anisotropy index (or parameter of the proton pitch angle distribution) for the pitch angle of 90 degrees during the magnetic storm, when the geomagnetic activity Kp-index changed from 2 in the beginning of a storm up to 7+ in the end of a storm. Dependence of the perpendicular proton pitch angle distribution anisotropy index with energy E = 90 keV during the different moments of time from the McIlwain parameter L (2.26 < L < 6.6) is received. It is certain at a quantitative level for the magnetic storm on October 21–22, 1999, when and where on the nightside of the Earth’s magnetosphere (MLT = 2300) to increase in the geomagnetic activity Kp-index there is a transition from normal (pancake) proton pitch angle distributions to butterfly proton pitch angle distributions. That has allowed to determine unequivocally and precisely the anisotropy dynamics of the proton pitch angle distribution in the given concrete case. It is shown, that with increase of the geomagnetic activity Kp-index the boundary of isotropic proton pitch angle distribution comes nearer to the Earth, reaching L ≈ 3.6 at Kp = 7+

Why can we detect lianas from space?

Lianas are found in virtually all tropical forests and have strong impacts on the forest carbon cycle by slowing tree growth, increasing tree mortality and arresting forest succession. In a few local studies, ecologists have successfully differentiated lianas from trees using various remote sensing platforms including satellite images. This demonstrates a potential to use remote sensing to investigate liana dynamics at spatio-temporal scales beyond what is currently possible with ground-based inventory censuses. However, why do liana-infested tree crowns and forest stands display distinct spectral signals? And is the spectral signal of lianas only locally unique or consistent across continental and global scales? Unfortunately, we are not yet able to answer these questions, and without such an understanding the limitations and caveats of large-scale application of automated classifiers cannot be understood. Here, we tackle the questions of why we can detect lianas from airborne and spaceborne remote sensing platforms. We identify whether a distinct spectral distribution exists for lianas, when compared to their tree hosts, at the leaf, canopy and stand scales in the solar spectrum (400 to 2500 nm). To do so, we compiled databases of (i) leaf reflectance spectra for over 4771 individual leaves of 571 species, (ii) fine-scale (~1m2) surface reflectance from 999 tree canopies characterized by different levels of liana infestation in Panama and Malaysia, and (iii) coarse-scale (>100 m2) surface reflectance from hundreds of hectares of heavily infested liana forest stands in French Guiana and Bolivia. Using these data, we find consistent spectral signal of liana-infested canopies across sites with a mean inter-site correlation of 89% (range 74-94%). However, as we find no consistent difference between liana and tree leaves, a distinct liana spectral signal appears to only manifests at the canopy and stand scales (>1m2). To better understand this signal, we implement mechanistic radiative transfer models capable of modeling the vertically stratificatied non-linear mixing of spectral signals intrinsic to lianas infestation of forest canopies. Next, we inversely fit the models to observed spectral signals of lianas at all scales to identify key biochemical or biophysical processes. We then corroborate our model results with field data on liana leaf chemistry and canopy structural properties. Our results suggest that a liana-specific spectral distribution arises due to the combination of cheaply constructed leaves and efficient light interception. A model experiment revealed that the spectral distribution was most sensitive to lower leaf and water mass per unit area, affecting the absorption of NIR and SWIR radiation, and a more planophile (flatter) leaf angle distribution. Finally, we evaluate the theoretical discernibility of lianas from trees and how this varies with remote sensing platforms and resolution. We end by discussing the potential, limitations and risks of applying automated classifiers to detect lianas from remotely sensed data at large scales.