Elevation Error Research Articles

Developing, pilot testing, and refining requirements for 3 EHR-integrated interventions to improve diagnostic safety in acute care: a user-centered approach.

To describe a user-centered approach to develop, pilot test, and refine requirements for 3 electronic health record (EHR)-integrated interventions that target key diagnostic process failures in hospitalized patients. Three interventions were prioritized for development: a Diagnostic Safety Column (DSC) within an EHR-integrated dashboard to identify at-risk patients; a Diagnostic Time-Out (DTO) for clinicians to reassess the working diagnosis; and a Patient Diagnosis Questionnaire (PDQ) to gather patient concerns about the diagnostic process. Initial requirements were refined from analysis of test cases with elevated risk predicted by DSC logic compared to risk perceived by a clinician working group; DTO testing sessions with clinicians; PDQ responses from patients; and focus groups with clinicians and patient advisors using storyboarding to model the integrated interventions. Mixed methods analysis of participant responses was used to identify final requirements and potential implementation barriers. Final requirements from analysis of 10 test cases predicted by the DSC, 18 clinician DTO participants, and 39 PDQ responses included the following: DSC configurable parameters (variables, weights) to adjust baseline risk estimates in real-time based on new clinical data collected during hospitalization; more concise DTO wording and flexibility for clinicians to conduct the DTO with or without the patient present; and integration of PDQ responses into the DSC to ensure closed-looped communication with clinicians. Analysis of focus groups confirmed that tight integration of the interventions with the EHR would be necessary to prompt clinicians to reconsider the working diagnosis in cases with elevated diagnostic error (DE) risk or uncertainty. Potential implementation barriers included alert fatigue and distrust of the risk algorithm (DSC); time constraints, redundancies, and concerns about disclosing uncertainty to patients (DTO); and patient disagreement with the care team's diagnosis (PDQ). A user-centered approach led to evolution of requirements for 3 interventions targeting key diagnostic process failures in hospitalized patients at risk for DE. We identify challenges and offer lessons from our user-centered design process.

A multiangle image aggregation analysis and association algorithm for GNSS-based InSAR

ABSTRACT In the global navigation satellite system-based synthetic aperture radar interferometry (GNSS-based InSAR) system, 3D deformation retrieval needs to associate multiangle images, but due to the low 2D resolution, traditional texture-based algorithm cannot be used in GNSS-based system. At the same time the association error introduced by the elevation error also cannot be compensated for. In this paper, a multiangle images aggregation analysis and association algorithm is proposed under elevation error conditions. Instead of using texture information, focus positions from different angles are adopted here. First, the focus position with elevation error is modelled in the bistatic configuration. Then, the images association is achieved based on the aggregation analysis, which is further quantitatively expressed through minimum circle principle. Raw data from four satellites are used to demonstrate the validity of the proposed algorithm.

Error Analysis for Shipborne-based-based Single Band LiDAR Point Cloud Data

A new measuring technique called a ship-based single band LiDAR system is utilized to swiftly capture underwater terrain to employ dense and precise point cloud data on a vast region for bathymetry. The accuracy of point clouds is strongly impacted by the ease with which numerous error sources might affect shipborne single-band lidar measurement systems. Shipborne-based single-band LiDAR point cloud errors are mostly caused by GPS, attitude angle, range, and integration errors. This research explores and examines the impact of the scanning angle and attitude angle on bathymetry because they can fluctuate significantly throughout the actual measurement process. The point cloud errors resulting from numerous sets of scanning angle and attitude-angle data sets are calculated. The linear relationship and positioning accuracy between the three are intuitively depicted by comparable curves, presuming that other error causes are quantifiable. Analysis reveals that the error will also rise as the scanning angle increases.Additionally, the roll angle inaccuracy in the attitude angle has a minimal impact on the accuracy of the plane but a substantial impact on the accuracy of the elevation. Elevation error significantly impacts plane positioning accuracy but less on elevation accuracy. Positioning is only minimally affected by yaw angle inaccuracy.

An evaluation method of GPS satellite clock in-orbit with periodic terms deducted

The performance of the atomic clock in orbit is of terrific significance for the Global Navigation Satellite System (GNSS). With the rapid development of satellite navigation and atomic clock technology, the periodic error of satellite clocks caused by the environment is more prominent. This paper focuses on the analysis and quantification of the systematic periodic error in the clock offset and proposes a more accurate evaluation method for GPS satellite clocks. The fact that the J2 relativistic effect and orbit radial error are the main sources of the systematic periodic term has been revealed. Then, the Fast Fourier Transform (FFT) is employed using the sliding window to investigate the periodic influence caused by satellite orbit and the J2 relativistic effect on clock offset through six GPS satellites with different orbital planes, these satellites also cover all four types of GPS satellite blocks. The results show that there is an obvious relationship between the sun elevation and orbit radial error, clock offset fitting precision, frequency stability and amplitude. The different geometric configurations of the satellite and the varying environment make this relationship different. Based on the clock offset provided by European Space Agency (ESA), the period of clock offset is extracted and quantized, with the period of 24 h, 12 h, 8 h, 6 h, 4 h, and 3 h. According to the daily extraction results of the time-varying periodic terms, the two most noticeable terms correction on satellite clock offset has been proven to be effective in eliminating periodic errors. Compared to those without periodic correction, the fitting precision and frequency stability can improve by 48.5% and 42.6%, respectively. In addition, all GPS satellite clocks in orbit are evaluated by this periodic correction method, and the results are more approach to the actual performance of the satellite clock. Furthermore, this method can also be adapted to evaluate satellite clocks of other GNSS systems. Therefore, when we evaluate the high-precision atomic clock flying on board GNSS satellites and compare them with the manufacturers’ specifications, the periodic error cannot be neglected.

Identifying the genetic basis of viral spillover using Lassa virus as a test case.

The rate at which zoonotic viruses spill over into the human population varies significantly over space and time. Remarkably, we do not yet know how much of this variation is attributable to genetic variation within viral populations. This gap in understanding arises because we lack methods of genetic analysis that can be easily applied to zoonotic viruses, where the number of available viral sequences is often limited, and opportunistic sampling introduces significant population stratification. Here, we explore the feasibility of using patterns of shared ancestry to correct for population stratification, enabling genome-wide association methods to identify genetic substitutions associated with spillover into the human population. Using a combination of phylogenetically structured simulations and Lassa virus sequences collected from humans and rodents in Sierra Leone, we demonstrate that existing methods do not fully correct for stratification, leading to elevated error rates. We also demonstrate, however, that the Type I error rate can be substantially reduced by confining the analysis to a less-stratified region of the phylogeny, even in an already-small dataset. Using this method, we detect two candidate single-nucleotide polymorphisms associated with spillover in the Lassa virus polymerase gene and provide generalized recommendations for the collection and analysis of zoonotic viruses.

Bare-earth DEM generation from ArcticDEM and its use in flood simulation

Abstract. In urban areas, topography data without above-ground objects are typically preferred in wide-area flood simulation but are not yet available for many locations globally. High-resolution satellite photogrammetric DEMs, like ArcticDEM, are now emerging and could prove extremely useful for global urban flood modelling; however, approaches to generate bare-earth DEMs from them have not yet been fully investigated. In this paper, we test the use of two morphological filters (simple morphological filter – SMRF – and progressive morphological filter – PMF) to remove surface artefacts from ArcticDEM using the city of Helsinki (192 km2) as a case study. The optimal filter is selected and used to generate a bare-earth version of ArcticDEM. Using a lidar digital terrain model (DTM) as a benchmark, the elevation error and flooding simulation performance for a pluvial scenario were then evaluated at 2 and 10 m spatial resolution, respectively. The SMRF was found to be more effective at removing artefacts than PMF over a broad parameter range. For the optimal ArcticDEM-SMRF the elevation RMSE was reduced by up to 70 % over the uncorrected DEM, achieving a final value of 1.02 m. The simulated water depth error was reduced to 0.3 m, which is comparable to typical model errors using lidar DTM data. This paper indicates that the SMRF can be directly applied to generate a bare-earth version of ArcticDEM in urban environments, although caution should be exercised for areas with densely packed buildings or vegetation. The results imply that where lidar DTMs do not exist, widely available high-resolution satellite photogrammetric DEMs could be used instead.

Elevation-based probabilistic mapping of irregularly flooded wetlands along the northern Gulf of Mexico coast

Irregularly flooded wetlands are found above the mean high water tidal datum and are exposed to tides and saltwater less frequently than daily. These wetlands provide important ecosystem services, such as providing habitat for fish and wildlife, enhancing water quality, ameliorating flooding impacts, supporting coastal food webs, and protecting upslope areas from erosion. Mapping irregularly flooded wetlands is challenging given their expansive coverage and dynamic nature. Furthermore, coastal wetlands are expected to change over the coming century due to sea-level rise and changes in the frequency and intensity of extreme storms. Consequently, coastal managers need baseline information on the spatial distribution of wetlands along with efficient and repeatable methods for observing changes. In this study, we used coastal wetlands from existing land use land cover data, best available lidar-derived digital elevation models, and Monte Carlo simulations to incorporate elevation uncertainty to create a probabilistic map of irregularly flooded wetlands along the northern Gulf of Mexico coast (USA). Our approach integrated findings from a review of coastal wetland elevation error in lidar datasets and an analysis of spatial autocorrelations of wetland elevation. We found a positive correlation (r = 0.563, p < 0.0001) when comparing the probability estimated from a digital elevation model and in situ elevation observations. The differences in probability had a mean bias error of −0.04 (i.e., digital elevation model-based probability tends to be slightly lower), a mean absolute error of 0.20, and a root mean square error of 0.26. Beyond this overall validation, we explored error metrics for land cover classes and lidar collection details. To quantify areal coverage of the probabilistic output, we classified the probability values into equal bins using an interval of 0.33. The areal coverage of the lowest probability bin (“unlikely”; probability ≤0.33) was separated into the upper and lower portions of the irregularly flooded wetland zone. Of the coastal wetlands along the northern Gulf of Mexico coast about 38% were classified as unlikely and low with the greatest coverage in south Louisiana and the Everglades and around 33% were classified as unlikely and high with the greatest coverage in the Everglades and Texas. The relative coverage within the highest probability bin (“likely”; probability >0.66) covered around 13%, with the greatest coverage in south Florida, south Louisiana, and Texas. The framework developed in this study can be transferred to other coastal wetland areas and updated to observe changes with sea-level rise.

A Novel Three-Dimensional Block Adjustment Method for Spaceborne InSAR-DEM Based on General Models

Digital Elevation Model (DEM) generated by bistatic Synthetic Aperture Radar Interferometry (InSAR) usually has systematic plane and elevation errors. However, the DEM adjustment method based on the function model can only correct systematic elevation error, affecting the plane accuracy of DEM mosaic products. Given this issue, this paper proposes a three-dimensional InSAR-DEM block adjustment method based on general models with a separate adjustment strategy, that is, first correct vertical error using the adjustment method based on the function model and then correct horizontal error using the method based on Rational Function Model (RFM) after compensating for elevation errors. In order to extract the Tie Points (TPs) and Ground Control Points (GCPs) used in adjustment, we propose a Normalized Correlation Coefficient matching method based on Complex Slope Maps (NCC-CSM). We conduct experiments using 29 TanDEM-X Co-registered Single look Slant range Complex (CoSSC) data. The accuracies of adjustment results are verified using ICESat-2 ATL08 data and selected GCPs, respectively. The adjustment experiments show that the elevation accuracy of InSAR-DEM is improved from 1.70 m to 1.35 m, the absolute and relative plane accuracies are improved by 5.58 m and 11.53 m, respectively, and the horizontal and vertical geometric discontinuity in the overlapping area disappear. The matching experiments of TPs and GCPs show that the proposed NCC-CSM method is superior to the traditional NCC method based on DEM (NCC-DEM), especially in flat areas.

Perceptual evaluation of an ambisonic auralization system of measured 3D acoustics

This paper presents a perceptual experiment aimed at assessing the spatial quality of acoustic environment rendering using a 4th order ambisonic auralization system. A novel test protocol is developed for this purpose, based on comparing the perceived spatial attributes of sound sources in both real (in-situ) and virtual listening conditions (loudspeaker-based ambisonic auralization of measured SRIRs). The perceptual evaluation is conducted using a specific reporting method combined with a virtual reality interface, enabling simultaneous assessment of perceived distance, angular position, and apparent width of sound sources. The test is conducted in three “office like” rooms, varying in reverberation properties and size. The results highlight differences in spatial perception between (a) real rooms and (b) their reproduction through the auralization system. Overall, localization performance is worse in auralized conditions than in real conditions, as evidenced by a clear increase in localization errors in azimuth and elevation, along with an increase in reported source width. This study also reveals that the spatial accuracy of the auralization depends on the rooms being auralized.

A Geometric Calibration Method Without a Field Site of the GF-7 Satellite Laser Relying on a Surface Mathematical Model

The GaoFen-7 (GF-7) satellite, which is used for Earth observations, is equipped with China’s first civil full-waveform laser altimeter. The geometric calibration of the GF-7 satellite laser is vital for ensuring its long-term stability and highly precise global measurements. In this study, a geometric of calibrating satellite laser is proposed. Notably, this method does not require an outdoor calibration field but instead relies on a mathematical surface model. This calibration method converts that to calibrate laser pointing angle error in traditional calibration method to calibrate the three-axis rotation angle error between the laser frame and the satellite body fixed-frame. Assuming that the laser footprints always fall on a fit spatial plane, a new satellite laser geometry calibration model is established. In addition, the GF-7 satellite laser is calibrated by using airborne light detection and ranging (LiDAR) point clouds collected from the sloped terrain of Xinjiang. Taking the laser footprints that are captured by the laser ground detectors as the true values, the positioning error of GF-7 beam 1 is improved from 430 m before calibration to 1.8 m after calibration. And the beam 2 positioning error is improved from 1025 to 6.4 m. Finally, according to the surface elevation of the laser footprints that were measured by a real-time kinematic, the elevation error of the GF-7 laser on flat terrain was verified to be 0.14 m after calibration. In summary, the calibration method proposed in this study is effective and feasible and provides a new method for satellite laser calibration.

Removal of Intra-Array Statics in Seismic Arrays Due to Variable Topography and Positioning Errors

A receiver array is an arrangement of geophones used to enhance the signal-to-noise ratio (S/N) of seismic data. However, deviations from ideal array conditions can lead to the non-optimal performance of the array. This study investigates, quantitatively, the array performance in the presence of topographic variations and positioning errors using 2D seismic data acquired in eastern Saudi Arabia. A receiver array was laid over a sand dune with variable topography underlain by a flat sabkha that has a very shallow water table. The topographic variations and position errors were calculated from Differential Global Positioning System (D-GPS) measurements of source and receiver positions and elevations. The errors in receiver positions, measured relative to the ideal receiver spacing, gave a mean and standard deviation of about 0.35% and 1%, respectively. On the other hand, elevation errors (topographic variations) from a horizontal datum gave a mean and standard deviation of about 25% and 13%, respectively. The ideal array response was found by removing both elevation and position errors. The first-arrival energy of the array was calculated after removal of elevation and position errors separately and compared to the ideal-array energy. Comparison showed a 64% enhancement in the first-arrival energy after correcting for elevation errors alone and almost no enhancement after correcting for position errors alone. The proposed approach can be used to calculate accurate static corrections for seismic reflection processing and to generate high-resolution subsurface images for engineering applications.

Accuracy Analysis of Oblique Photogrammetry Measurement in 3D Modeling of Power Line Selection Design

The measurement of power line selection in the field is one of the key works of route design. The traditional manual measurement is inefficient, and ground objects are prone to losses and leakage, often resulting in frequent line changes. With the promotion of 3D real scene work, power line design has also entered the 3D era. In this study, taking the line design near Dengtai Village in Dalian as an example, the UAV is used to carry a multi-viewer camera to obtain three-dimensional information on the ground surface. The power supply line is generally selected in the field far away from residential areas. The characteristics of weak texture bring certain difficulties to the Oblique photogrammetry method. A few control points and checkpoints are arranged to control the accuracy of the ground model, and the accuracy analysis and evaluation are carried out. The results show that the UAV Oblique photography technology has obvious advantages in the process of three-dimensional model construction. The maximum errors of the model result in X, Y, and Z directions are -0.1820 m, -0.1200 m, and -0.3860 m, respectively, the mean square error in the plane is ± 0.0595 m, and the mean square error in elevation is ± 0.2198 m. The 3D model accuracy can meet the actual needs of 1:2000 mapping, thus verifying the feasibility and reliability of the UAV Oblique photography technology to build a high-precision real scene three-dimensional digital model in the application of power line selection measurement.

An urban DEM reconstruction method based on multisource data fusion for urban pluvial flooding simulation

A digital elevation model (DEM) is crucial for hydraulic/hydrodynamic simulation of urban pluvial flooding. To reduce the simulation error caused by the low resolution and poor vertical accuracy of DEM data, a novel urban terrain reconstruction method is proposed based on multisource data fusion (MDF). A 1D-2D coupled pluvial flood model under the typhoon rainfall scenario is built to verify the superiority of the proposed method. The results show that the systematic elevation error of terrain is reduced with MDF-kriging and MDF-IDW, and the performances of simulations are improved by 5% and 23% in terms of peak water-level error compared to using conventional kriging and IDW methods, and by 0.13m and 0.11m in terms of manhole water level accuracy compared to using raw DEM. Moreover, the temporospatial patterns of the flooding simulation results are more rational with the scattered flooding eliminated, and the proportion of flood area with ground elevation lower than 8 m increased from 37.9% to 92.34% and 89.33%, respectively. This method is proven to be a notably effective and low-cost DEM reconstruction method for improving the accuracy of urban pluvial flooding simulation.

Satellite Laser Altimetry Data-Supported High-Accuracy Mapping of GF-7 Stereo Images

GaoFen 7 (GF-7) is China’s first submeter high-resolution stereo mapping satellite with dual-linear-array cameras and a laser altimeter system onboard for high-precision mapping. To further take advantage of the very high elevation accuracy of laser altimetry data and the high relative accuracy with stereo images, an innovative combined adjustment method for GF-7 stereo images with laser altimetry data is presented in this paper. In this method, two flexible and effective schemes were proposed to extract the elevation control point according to the registration of footprint images and stereo images and then utilized as vertical control in the block adjustment to improve the elevation accuracy without ground control points (GCPs). The validation experiments were conducted in Shandong, China, with different terrains. The results demonstrated that, after using the laser altimetry data, the root mean square error (RMSE) of elevation was dramatically improved from the original 2.15 m to 0.75 m, while the maximum elevation error was less than 1.6 m. Moreover, by integrating a few horizontal control points, the planar and elevation accuracy can be simultaneously improved. The results show that the method will be useful for reducing the need for field survey work and improving mapping efficiency.

Analytical inverse solution of a rotational achromatic Risley prism based on Fourier series fitting

High-precision analytical inverse solution is a significant issue faced by the rotational achromatic Risley prism system. The current inverse solution method is based on numerical iteration, which is time-consuming. To solve this problem, we propose an analytical inverse solution method for a rotational achromatic Risley prism system based on Fourier series fitting. In the proposed method, the expression of the difference between the rotation angle and elevation angle of beam deflection is inversely fitted using the forward solution model. The analytical inverse solution is achieved using a two-step method based on this fitted expression. Simulation results of the analytical inverse solution show that the maximum azimuthal error was less than 2.23e−8 arcsec and the maximum elevation error was less than 1.33e−4 arcsec. Experimental results prove that with 1 arcsec pointing accuracy, the time consumption of the proposed method is only 0.108 ms, whereas that of the previous numerical-iteration-based method is 1.480 ms.

An improved MUSLE model incorporating the estimated runoff and peak discharge predicted sediment yield at the watershed scale on the Chinese Loess Plateau

An accurate prediction of sediment yield at the watershed scale is critical not only for sustainable watershed management but also for improving knowledge regarding the relationship between sediment yield and its determinant factors, which often rely on the varying model complexity. In this study, a modified sediment yield formula based on the modified universal soil loss equation (MUSLE) model was developed by introducing a channel factor into the original formula. The reliability of the proposed method was tested using data from 1,341 storm events in 38 watersheds and was applied to 256 storm events in five application watersheds using the optimized parameters. Results indicated that the proposed method is very accurate, as demonstrated by the Nash–Sutcliffe efficiency (NSE) values of 88.18 %, 85.72 %, and 85.51 % during calibration, validation, and application, respectively. The performance of the proposed model was superior to that of the original MUSLE model. Subsequently, the proposed method was used to predict sediment yield from the last five typical watersheds. This prediction utilized the parameters derived from the initial 38 watersheds; the peak discharge predicted by the modified Chemicals, Runoff, and Erosion from Agricultural Management Systems (CREAMS); and the runoff estimated by the modified Soil Conservation Service Curve Number (SCS-CN) method. Elevated NSE (61.88–81.42 %) and low root mean square error values (2.35–11.40 t ha−1) were calculated for the five watersheds. From the results, the proposed sediment yield model, combined with the modified SCS-CN method and CREAMS, was found to accurately predict the event-based sediment yield, peak discharge, and runoff in the Loess Plateau region under varying hydrological and geomorphic conditions.

TFIIH mutations can impact on translational fidelity of the ribosome.

TFIIH is a complex essential for transcription of protein-coding genes by RNA polymerase II, DNA repair of UV-lesions and transcription of rRNA by RNA polymerase I. Mutations in TFIIH cause the cancer prone DNA-repair disorder xeroderma pigmentosum (XP) and the developmental and premature aging disorders trichothiodystrophy (TTD) and Cockayne syndrome. A total of 50% of the TTD cases are caused by TFIIH mutations. Using TFIIH mutant patient cells from TTD and XP subjects we can show that the stress-sensitivity of the proteome is reduced in TTD, but not in XP. Using three different methods to investigate the accuracy of protein synthesis by the ribosome, we demonstrate that translational fidelity of the ribosomes of TTD, but not XP cells, is decreased. The process of ribosomal synthesis and maturation is affected in TTD cells and can lead to instable ribosomes. Isolated ribosomes from TTD patients show an elevated error rate when challenged with oxidized mRNA, explaining the oxidative hypersensitivity of TTD cells. Treatment of TTD cells with N-acetyl cysteine normalized the increased translational error-rate and restored translational fidelity. Here we describe a pathomechanism that might be relevant for our understanding of impaired development and aging-associated neurodegeneration.

Assessing Through-Water Structure-from-Motion Photogrammetry in Gravel-Bed Rivers under Controlled Conditions

Structure-from-Motion (SfM) photogrammetry has become a popular solution for three-dimensional topographic data collection in geosciences and can be used for measuring submerged bed surfaces in shallow and clear water systems. However, the performance of through-water SfM photogrammetry has not been fully evaluated for gravel-bed surfaces, which limits its application to the morphodynamics of gravel-bed rivers in both field investigations and flume experiments. In order to evaluate the influence of bed texture, flow rate, ground control point (GCP) layout, and refraction correction (RC) on the measurement quality of through-water SfM photogrammetry, we conducted a series of experiments in a 70 m-long and 7 m-wide flume with a straight artificial channel. Bed surfaces with strongly contrasting textures in two 4 m-long reaches were measured under five constant flow regimes with three GCP layouts, including both dry and underwater GCPs. All the submerged surface models with/without RC were compared with the corresponding dry bed surfaces to quantify their elevation errors. The results illustrated that the poorly sorted gravel-bed led to the better performance of through-water SfM photogrammetry than the bed covered by fine sand. Fine sediment transport caused significant elevation errors, while the static sand dunes and grain clusters did not lead to noticeable errors in the corrected models with dry GCPs. The elevation errors of the submerged models linearly increased with water depth for all the tested conditions of bed textures, GCP layouts, and discharges in the uncorrected models, but the slopes of the increasing relations varied with texture. The use of underwater GCPs made significant improvements to the performance of direct through-water SfM photogrammetry, but counteracted with RC. The corrected models with dry GCPs outperformed the uncorrected ones with underwater GCPs, which could still be used to correct the underestimation in surface elevation caused by RC. Based on the new findings, recommendations for through-water SfM photogrammetry in measuring submerged gravel-bed surfaces were provided.

Uncertainty of ICESat-2 ATL06- and ATL08-derived snow depths for glacierized and vegetated mountain regions

Seasonal snow melt dominates the hydrologic budget across a large portion of the globe. Snow accumulation and melt vary over a broad range of spatial scales, preventing accurate extrapolation of sparse in situ observations to watershed scales. The lidar onboard the Ice, Cloud, and land Elevation, Satellite (ICESat-2) was designed for precise mapping of ice sheets and sea ice, and here we assess the feasibility of snow depth-mapping using ICESat-2 data in more complex and rugged mountain landscapes. We explore the utility of ATL08 Land and Vegetation Height and ATL06 Land Ice Height differencing from reference elevation datasets in two end member study sites. We analyze ∼3 years of data for Reynolds Creek Experimental Watershed in Idaho's Owyhee Mountains and Wolverine Glacier in southcentral Alaska's Kenai Mountains. Our analysis reveals decimeter-scale uncertainties in derived snow depth and glacier mass balance at the watershed scale. Both accuracy and precision decrease as slope increases: the magnitudes of the median and median of the absolute deviation of elevation errors (MAD) vary from ∼0.2 m for slopes <5° to >1 m for slopes >20°. For glacierized regions, failure to account for intra- and inter-annual evolution of glacier surface elevations can strongly bias ATL06 elevations, resulting in under-estimation of the mass balance gradient with elevation. Based on these results, we conclude that ATL08 and ATL06 observations are best suited for characterization of watershed-scale snow depth and mass balance gradients over relatively shallow slopes with thick snowpacks. In these regions, ICESat-2 elevation residual-derived snow depth and mass balance transects can provide valuable watershed scale constraints on terrain parameter- and model-derived estimates of snow accumulation and melt.

Ground Positioning Method of Spaceborne SAR High-Resolution Sliding-Spot Mode Based on Antenna Pointing Vector

As a new high-resolution spaceborne SAR observation mode, sliding-spot imaging has the characteristics of a large squint, long aperture time, and azimuth aliasing, and because of the dechirp operation in the imaging algorithm of this mode, it is difficult to construct a direct range–Doppler equation for its geometric processing. In this paper a conformation model based on an antenna pointing vector is presented, which fully considers the influence of the dechirp operation on the range image, starts from the relative position of the dechirped range image points and the satellite, and establishes a strict conversion model between the image coordinates and geographic coordinates using the accurate satellite–ground geometric conditions. Then the forward and reverse formulas for geometric processing of the sliding-spot mode are given based on this model. Finally, geometric calibration and positioning experiments under different conditions and field spaceborne SAR data are executed. Results show that after geometric errors caused by the SAR payload have been calibrated and other factors such as atmospheric delay, platform position, and elevation error have been compensated, the uncontrolled geometric positioning accuracy can reach within 1 m–2 m, which fully proves the effectiveness of this method in the geometric positioning of high-resolution sliding-spot images.