The geometrical measurement precision of laser spots is affected by the deviation between the parameters of the laser altimeter and the laboratory measurement results, and the inversion accuracy of ...surface object height is also limited. The measurement parameters and the load state can be obtained by calibration of the laser altimeter system. Usually, ground detectors are deployed to calibrate the measurement parameters of the laser altimeter, including the divergence angle and the energy distribution of the laser beam. A calibration method for a laser footprint spot without a calibration field was proposed in this paper, focused on the airborne large-footprint laser altimeter system. The geometric parameters of the laser spot were calibrated through the laser echo waveforms of a specific terrain. The experimental results show that geometric calibration of the large-footprint laser altimeter can be achieved in the area of the step surface. The divergence angle of the laser beams obtained from the six experimental areas is 4.604 ± 0.359 mRad, and the consistency of the energy distribution from each laser spot reaches 92.67%. A new method of on-orbit calibration and verification is provided for the satellite laser altimeter system.
Due to the difference in surface reflectivity, the laser measurement waveform data recorded in full waveform have a saturation phenomenon. When the signal is saturated, the echo waveform produces ...peak clipping and pulse spreading, which seriously restrict the accuracy of laser measurement results and the usability of data. Therefore, we conducted a ranging investigation on the “peak clipping” phenomenon of the saturated waveform and found a nonlinear time delay in the range, which is between the two extreme cases of saturated “dead time” and Gaussian fitting peak time as pulse signal reception time. Subsequently, based on the consistent relationship between the geometric characteristics of the high- and low-gain channels of the space-borne laser altimeter, we constructed a laser waveform saturation compensation model, namely, the laser pulse flight time delay compensation and the laser waveform peak intensity compensation, and carried out the data saturation compensation and validation with the dual-channel measurement data from the GaoFen-7 (GF-7) satellite. The experimental results showed that the saturation compensation model (SCM) proposed in this paper could restore the features of the saturated waveform signal and effectively improve the accuracy of the laser ranging. The accuracy of the laser waveform fitting result after saturation compensation improved from 0.7 ns (0.11 m) to 0.14 ns (0.02 m), which greatly improved the usability of the saturated laser measurement waveform data.
The Gaofen-7 (GF-7) satellite system adds a footprint camera that shares the same optical path as its laser altimeter to ensure consistent spatial referencing between the laser footprint point and ...the obtained optical images. However, this introduces additional errors between the two different loads while ensuring the geometric relations of the laser altimeter and footprint camera. First, the accuracy and error analyses of laser altimeter and footprint camera are carried out based on the working mode of the GF-7 satellite laser altimeter and footprint camera in this study. A rigorous sensor model of laser geometric positioning is proposed based on the coupled footprint camera, which is achieved for the geometric correlation of laser spots on the ground and the focal plane of footprint camera. The satellite laser altimeter simulation platform was used to analyses the various error sources on the geometric positioning of the laser altimeter, and GF-7 satellite data were used to verify the proposed geometric positioning model of the laser altimeter and footprint camera. The results show that the positioning error of GF-7 footprint camera is less than 5 m (RMSE) relative to the dual-line array image, which can provide ground control points for stereo mapping.
The Chinese Gaofen-3 (GF-3) mission was launched in August 2016, equipped with a full polarimetric synthetic aperture radar (SAR) sensor in the C-band, with a resolution of up to 1 m. The absolute ...positioning accuracy of GF-3 is of great importance, and in-orbit geometric calibration is a key technology for improving absolute positioning accuracy. Conventional geometric calibration is used to accurately calibrate the geometric calibration parameters of the image (internal delay and azimuth shifts) using high-precision ground control data, which are highly dependent on the control data of the calibration field, but it remains costly and labor-intensive to monitor changes in GF-3's geometric calibration parameters. Based on the positioning consistency constraint of the conjugate points, this study presents a geometric cross-calibration method for the rapid and accurate calibration of GF-3. The proposed method can accurately calibrate geometric calibration parameters without using corner reflectors and high-precision digital elevation models, thus improving absolute positioning accuracy of the GF-3 image. GF-3 images from multiple regions were collected to verify the absolute positioning accuracy after cross-calibration. The results show that this method can achieve a calibration accuracy as high as that achieved by the conventional field calibration method.
Geometric deep learning has been revolutionizing the molecular modeling field. Despite the state-of-the-art neural network models are approaching ab initio accuracy for molecular property prediction, ...their applications, such as drug discovery and molecular dynamics (MD) simulation, have been hindered by insufficient utilization of geometric information and high computational costs. Here we propose an equivariant geometry-enhanced graph neural network called ViSNet, which elegantly extracts geometric features and efficiently models molecular structures with low computational costs. Our proposed ViSNet outperforms state-of-the-art approaches on multiple MD benchmarks, including MD17, revised MD17 and MD22, and achieves excellent chemical property prediction on QM9 and Molecule3D datasets. Furthermore, through a series of simulations and case studies, ViSNet can efficiently explore the conformational space and provide reasonable interpretability to map geometric representations to molecular structures.
Abstract As the most abundant organic substances in nature, carbohydrates are essential for life. Understanding how carbohydrates regulate proteins in the physiological and pathological processes ...presents opportunities to address crucial biological problems and develop new therapeutics. However, the diversity and complexity of carbohydrates pose a challenge in experimentally identifying the sites where carbohydrates bind to and act on proteins. Here, we introduce a deep learning model, DeepGlycanSite, capable of accurately predicting carbohydrate-binding sites on a given protein structure. Incorporating geometric and evolutionary features of proteins into a deep equivariant graph neural network with the transformer architecture, DeepGlycanSite remarkably outperforms previous state-of-the-art methods and effectively predicts binding sites for diverse carbohydrates. Integrating with a mutagenesis study, DeepGlycanSite reveals the guanosine-5’-diphosphate-sugar-recognition site of an important G-protein coupled receptor. These findings demonstrate DeepGlycanSite is invaluable for carbohydrate-binding site prediction and could provide insights into molecular mechanisms underlying carbohydrate-regulation of therapeutically important proteins.
To uncover the internal mechanisms of various drought stress intensities affecting the soluble sugar content in organs and its regulation by endogenous abscisic acid (ABA), we selected the saplings ...of
, a typical tree species in the Beijing area, as our research subject. We investigated the correlation between tree soluble sugars and endogenous ABA in the organs (comprised of leaf, branch, stem, coarse root, and fine root) under two water treatments. One water treatment was defined as T1, which stopped watering until the potted soil volumetric water content (SWC) reached the wilting coefficient and then rewatered the sapling. The other water treatment, named T2, replenished 95% of the total water loss of one potted sapling every day and irrigated the above-mentioned sapling after its SWC reached the wilt coefficients. The results revealed that (1) the photosynthetic physiological parameters of
were significantly reduced (
< 0.05) under fast and slow drought processes. The photosynthetic physiological parameters of
in the fast drought-rehydration treatment group recovered faster relative to the slow drought-rehydration treatment group. (2) The fast and slow drought treatments significantly (
< 0.05) increased the ABA and soluble sugar contents in all organs. The roots of the
exhibited higher sensitivity in ABA and soluble sugar content to changes in soil moisture dynamics compared to other organs. (3) ABA and soluble sugar content of
showed a significant positive correlation (
< 0.05) under fast and slow drought conditions. During the rehydration stage, the two were significantly correlated in the T2 treatment (
< 0.05). In summary, soil drought rhythms significantly affected the photosynthetic parameters, organ ABA, and soluble sugar content of
. This study elucidates the adaptive mechanisms of
plants to drought and rehydration under the above-mentioned two water drought treatments, offering theoretical insights for selecting and cultivating drought-tolerant tree species.
Extreme drought events during spring have been predicted to increase and can profoundly threaten the grassland ecosystem through influencing the early growing season stages. However, whether these ...impacts are recoverable still remain controversial, and the role of grassland degradation status is also unclear. By selecting three grassland fields with different degradation levels (extreme, moderate, and light degradation) on a Leymus chinensis steppe in Northern China, we conducted a simulated extreme drought experiment during the late spring (mid-May to mid-June) using the rainfall shelters, to determine the influences on the vegetation growth. Soil moisture, leaf water potential (LWP), and vegetation cover were measured during the growing season, and aboveground biomass was harvested in autumn. The results showed that although spring drought could significantly reduce soil moisture up to 50 %, the drought effects did not cause a significant decrease in the LWP of L. chinensis. The water stress induced by spring drought had transferred to significant declines in vegetation coverage by approximately 45 % in the end of the simulated drought. However, the vegetation coverage fully recovered at the end of the growing season, with no drought effect on the aboveground biomass for the community as well as L. chinensis. The vegetation growth of degraded grasslands showed a certain degree of resistance to spring drought through compensatory growth. Altogether, the result of this study can be used as a reference for grassland degradation management, especially under extreme climate conditions.
•Spring drought decreased soil moisture and vegetation coverage of grasslands.•Drought effects were diminished on aboveground biomass due to compensatory growth.•Impact of drought stress were affected by grassland degradation levels.
With the larger size of wind turbine blades, coupled-mode flutter of long, flexible rotating blades has become an issue that cannot be neglected. Recent studies have shown that flutter speed can be ...predicted accurately using a three-dimensional, finite-element model by deterministic aeroelastic analysis. However, modeling uncertainty is an important, non-negligible issue as it influences probability of flutter failure. The stochastic flutter problem is investigated herein to understand the influence of uncertainty in selected input characteristics: (i) aerodynamic loads and (ii) blade structural properties. Physical Model Monte Carlo simulation is usually utilized for stochastic flutter analysis. Surrogate Model Monte Carlo simulation is proposed to obtain the solution more efficiently in terms of computing time. Surrogate models include: least squares fit and collocation methods. A nonlinear relationship between the input and output random variables is incorporated for least squares fit. For collocation methods, Lagrange polynomials are employed to perform random simulations. Results indicate that surrogate models efficiently facilitate the stochastic flutter analysis with acceptable errors.
•Stochastic flutter of wind turbine blades is investigated by Monte Carlo simulation.•Surrogate models are implemented by least squares fit and collocation methods.•Effects of flow forces and natural frequencies on flutter onset are investigated.•Surrogate models efficiently improve stochastic flutter analysis with small errors.
Accuracy verification of airborne large-footprint lidar data is important for proper data application but is difficult when ground-based laser detectors are not available. Therefore, we developed a ...novel method for lidar accuracy verification based on the broadened echo pulse caused by signal saturation over water. When an aircraft trajectory crosses both water and land, this phenomenon and the change in elevation between land and water surfaces can be used to verify the plane and elevation accuracy of the airborne large-footprint lidar data in conjunction with a digital surface model (DSM). Due to the problem of echo pulse broadening, the center-of-gravity (COG) method was proposed to optimize the processing flow. We conducted a series of experiments on terrain features (i.e., the intersection between water and land) in Xiangxi, Hunan Province, China. Verification results show that the elevation accuracy obtained in our experiments was better than 1 m and the plane accuracy was better than 5 m, which is well within the design requirements. Although this method requires specific terrain conditions for optimum applicability, the results can lead to valuable improvements in the flexibility and quality of lidar data collection.
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