STEREO Spacecraft Research Articles

Improved modelling of SEP event onset within the WSA–Enlil–SEPMOD framework

Multi-spacecraft observations of solar energetic particle (SEP) events not only enable a deeper understanding and development of particle acceleration and transport theories but also provide important constraints for model validation efforts. However, because of computational limitations, a given physics-based SEP model is usually best suited to capture a particular phase of an SEP event, rather than its whole development from onset through decay. For example, magnetohydrodynamic (MHD) models of the heliosphere often incorporate solar transients only at the outer boundary of their so-called coronal domain – usually set at a heliocentric distance of 20–30 R⊙. This means that particle acceleration at coronal mass ejection (CME)-driven shocks is also computed from this boundary onwards, leading to simulated SEP event onsets that can be many hours later than observed, since shock waves can form much lower in the solar corona. In this work, we aim to improve the modelled onset of SEP events by inserting a “fixed source” of particle injection at the outer boundary of the coronal domain of the coupled WSA–Enlil 3D MHD model of the heliosphere. The SEP model that we employ for this effort is Solar Energetic Particle MODel (SEPMOD), a physics-based test-particle code based on a field line tracer and adiabatic invariant conservation. We apply our initial tests and results of SEPMOD’s fixed-source option to the 2021 October 9 SEP event, which was detected at five well-separated locations in the inner heliosphere – Parker Solar Probe, STEREO-A, Solar Orbiter, BepiColombo, and near-Earth spacecraft.

Relationship between solar energetic particle intensity and coronal mass ejections and its associated type II radio bursts

Based on the multiple-vantage observations of STEREO, SOHO, wind and other spacecraft, the fast and wide coronal mass ejections (CME) during the 24th solar cycle from January 2010 to September 2014 are selected in this paper. Using the outputs of Richardson’s (2014) empirical model of solar energetic particle (SEP) intensity under different conditions, the effects of its associations such as CME, pre-CME, and type II radio bursts, on SEP intensity are analyzed, and the relationship between SEP event and these characteristics is also discussed. The main conclusions are as follows. 1) The presence or absence of pre-CME within 13 h before fast CME significantly improves the model prediction effect and has a significant influence on whether fast CME produces SEP event. Compared with the events without pre-CMEs, the events with pre-CMEs have a low proportion of false alarms (FR: 47.7% <i>vs.</i> 70%). However, the number of pre-CMEs does not improve the model output. 2) CMEs with type-II radio bursts have significantly lower FR to generate SEP events than fast CMEs without type-II radio bursts (42% <i>vs.</i> 68%). And selecting type-II radio bursts as a constraint will filter out some small/weak SEP events, the relationship between model predictions and observations especially for large SEP events (e.g. <i>I</i><sub>p</sub> ≥ 0.01 pfu/MeV) will stand out. Moreover, if the type-II radio enhancement is taken into account, FR can be further reduced to 29.4%, and the proportion of hits can be further increased (HR: 48.5%), and the model prediction is significantly improved. 3) The larger the start frequency of type II radio bursts, the smaller the end frequency is, and FR decreases slightly, but at the same time, a large number of SEP events are excluded by this condition, and the results show that the constraints on the start/end frequency of type-II radio bursts do not improve the model predictions distinctly. 4) If the sub-classification of type-II radio bursts is considered as the model constraint, the CMEs associated with multi-band type-II radio bursts have better model predictions than those with single-band events. For example, m-DH-km type-II radio bursts have lower FR (35.4%) and higher HR (48%), and the accuracy of empirical model is higher. In summary, we find that in addition to the velocity and angular width of CME, the associations of pre-CME, type II radio bursts and their enhancement, and multi-band sub-classification are the favorable conditions for CME to generate SEP events. The SEP intensities obtained by the empirical model have better consistency with the observations, and better predictions can be obtained. This investigation indicates that SEP events are more likely generated by fast and wide CMEs accompanied by pre-CMEs, multi-band type II radio bursts and their enhancements, which seem to serve as discriminative signal for SEP-rich and SEP-poor CMEs.

Enhancing Triangulation of Interplanetary Type III Bursts through Wavevector Correction

Interplanetary Type III bursts, generated by relativistic electron beams at solar flare reconnection sites, are explored through an investigation of 152 instances observed by the Solar Terrestrial Relations Observatory mission. This study reveals that the absolute values of the wavevector deviations from the Sun–spacecraft line are statistically 3.72 and 2.10 larger than predicted by the density model, assuming fundamental and harmonic emission, respectively. Through Monte Carlo simulations, we examine the impact of scattering by density inhomogeneities on the apparent locations of radio emissions in the interplanetary medium. The findings indicate that relative density fluctuations of 0.40 can account for the observed angular shift, a conclusion supported by the multiple flux-tube solar wind model, which confirms the presence of such magnitude of relative perpendicular density fluctuations in the solar wind. We propose a wavevector correction that incorporates this effect to enhance the triangulation of interplanetary Type III bursts, demonstrating that radio triangulation, with this correction, can reliably track electron beams in the interplanetary medium.

A General Deep Learning Framework Guided by Sparse Matching for Disparity Estimation in High-Resolution Satellite Stereo Imagery

A General Deep Learning Framework Guided by Sparse Matching for Disparity Estimation in High-Resolution Satellite Stereo Imagery

3-D Model Extraction Network Based on RFM-Constrained Deformation Inference and Self-Similar Convolution for Satellite Stereo Images

3-D Model Extraction Network Based on RFM-Constrained Deformation Inference and Self-Similar Convolution for Satellite Stereo Images

Six Consecutive Seasons of High‐Resolution Mountain Snow Depth Maps From Satellite Stereo Imagery

AbstractFine‐scale seasonal snow depth observations can improve estimates of snow water equivalent at critical times of year. Airborne lidar is the current gold standard for snow depth measurement, but it involves high costs and relatively limited coverage. Using very‐high‐resolution satellite stereo images from WorldView‐2, WorldView‐3, and Pléiades‐HR 1A/1B, we produced a six‐year time series (2017–2022) of spatially continuous digital elevation models for an 874 km2 study area over Grand Mesa, Colorado. We generated high‐resolution stereo snow depth maps that capture intra‐ and interannual variability and span multiple anomalous years (58%–158% of median peak SNOTEL snow depth). Comparisons with near‐contemporaneous airborne lidar snow depth measurements showed good agreement, with median offset of −0.13 m, precision of 0.19 m and accuracy of 0.31 m. Our results suggest that satellite stereo can provide snow depth observations with the spatiotemporal coverage needed to improve operational forecast models and inform adaptive management strategies.

ACCURACY EVALUATION OF ICESAT-2 ATL08 IN FINLAND

Abstract. ATL08 is level-3A land and vegetation height product of ICESat-2 data, which recorded the terrain elevation and surface height parameters at 100 m fixed-length along the ground track. It has been used widely not only in vegetation monitoring at large scale, but also in improving the accuracy of satellite stereo mapping, so, the accuracy of ATL08 product is the precondition of its application. Although some studies have evaluated the terrain and canopy height retrieval accuracy of ATL08, it is still not comprehensive that most studies focus on the accuracy in vegetation area. In this study, the performance on terrain and surface height retrieval of ATL08 was evaluated both in forested and non-forested area based on DEM and ALS data in Finland. A total of 6,682,846 and 3,980,235 segments were used to evaluate the accuracy of terrain and surface height retrieval, respectively. The result showed that, firstly, terrain elevation retrieval from ICESat-2/ATLAS is accurate, e.g., sub-meter level both in forested and non-forested area and slope was an important factor affecting the accuracy of terrain retrieval, while, surface height retrieval was low accurate, e.g., the RMSE of surface height retrieval were more than 5 m. Secondly, the accuracy of terrain elevation retrieval in non-forested area was slightly higher than that in forested area showed by MAE and RMSE. Finally, the accuracy of surface height retrieval in forested area was higher than that in non-forested area, and it should be emphasized that there is a significantly difference on RMSE% between forested and non-forested area. The study indicated that the terrain elevation retrieval from ATL08 is relative reliable and recommended to use when the accuracy is not strictly required, while, the use of surface height should be considered carefully and avoid to use low accuracy observation.

ATTENTION-GUIDED COST VOLUME REFINEMENT NETWORK FOR SATELLITE STEREO IMAGE MATCHING

Abstract. In remote sensing, disparity calculation using stereo images is a very necessary task and provides information for estimating the terrain elevation. The fields using disparity of stereo satellite images are used in various fields such as terrain models, autonomous driving using 3D maps, and content development. However, extracting disparity from stereo satellite images is a very difficult task, and inaccurate disparity may be extracted due to complex environments, façade areas of buildings, and texture-less areas. Our proposed method improves feature extraction and 3D aggregation steps based on Gwc-Net using stereo images rectified through RPC (Rational Polynomial Coefficients). To this achieve, we first improve the accuracy of the initial cost volume by extracting important features using the attention module 2D CBAM. In addition, in the aggregation step, we use 3D CBAM to extract important features from the cost volume and use GCE (Correlate-and-Excite) to guide image features to the cost volume to improve disparity. To evaluate the proposed method, the accuracy of disparity is evaluated using RPC-corrected stereo satellite images of DFC2019 data track2 of the US3D dataset. As a result of the experiment, the proposed method exhibited improvement compared to the baseline Gwc-Net.

CONTINUOUS 3D-LABEL SEMI-GLOBAL MATCHING FOR SATELLITE STEREO

Abstract. We present Continuous 3D-Label Semi-Global Matching (CoSGM), a new dense stereo matching algorithm for satellite stereo. CoSGM overparameterizes the disparity map as an array of local planes, so it can regularize the first-order smoothness of the estimated disparity. Furthermore, the algorithm can produce a dense normal map beside the disparity map. We show experimentally that CoSGM could achieve denser depth maps with comparable accuracy to traditional semi-global matching algorithms.

3D RECONSTRUCTION FROM MULTI-VIEW GOOGLE EARTH SATELLITE STEREO IMAGES BY GENERATING VIRTUAL RPC BASED ON 3D HOMOGRAPHY-BASED GEOREFERENCING

Abstract. In this paper, we propose a method for performing 3D reconstruction by generating virtual RPC parameters from multi-view satellite stereo images provided by Google Earth (GE) software. In the multi-view stereo (MVS) image in a general case, after the pose and parameters of the camera are estimated, a dense 3D surface can be reconstructed. However, in the case of satellite images, it is not easy to obtain the original images with pose parameters of an area of interest. In the case of GE software, which can obtain images across the globe, the images provided are georeferenced and modified to fit the ground control point (GCP), so there is no camera model to explain the projection relationship. Therefore, the purpose of the proposed method is to perform 3D reconstruction by generating virtual camera parameters in modified satellite images obtained from GE software. In the proposed method, satellite images obtained from GE are estimated to be pinhole images using structure from motion (SfM) for initial reconstruction. After initial reconstruction, the 3D model is transformed from a distorted hexahedral space formed along a pixel ray to a UTM coordinate system metric space through a 3D homography-based georeferencing. A virtual rational polynomial camera (RPC) parameter is calculated through the satellite images and the 3D interspace correspondence point of UTM coordinates. The result is generated by virtual RPC and the MVS method using the RPC model. The reconstructed DSM using virtual RPC is improved over the initial reconstruction of the proposed process, and error measurement in the area with GT obtained significant results with an average of 1.366m on an MAE method.

GEOMETRIC EVALUATION OF GAOFEN-7 STEREO DATA

Abstract. China’s first sub-metre stereo satellite, GaoFen-7, was launched on 7 November 2019. One of the main criteria for a stereo mapping satellite is the geometric accuracy of the images. In this paper, we present a systematic evaluation of the geometry accuracy of Gaofen-7 on two scenes over the centre of Munich, Germany. The geometry accuracy is evaluated in a three-step workflow: 1) direct georeferencing accuracy; 2) image orientation using bundle adjustment with ground control points; 3) height accuracy of the generated digital surface model (DSM). In addition to dense LiDAR point clouds, ground control points were measured in the field. These were used as references. The results show that RPC bundle adjustment with 0 order bias correction is sufficient to achieve sub-metre absolute accuracy. The height accuracy of the generated digital surface models varies with land cover type, ranging from 0.9m (NMAD) in open areas to 4.5m in urban areas.

Building damage assessment using improved combined adjustment and automatic building corners extraction method

ABSTRACTAccurately estimating the collapse height of buildings during earthquakes holds great significance. Acquiring precise height information of buildings using dual-phase high-resolution stereo satellite images (HRSSIs) requires high-precision ground control points, which are difficult to obtain in earthquake-stricken areas. Spaceborne laser data has been validated to significantly improve the vertical accuracy of HRSSIs. Therefore, this paper first proposes the application of a combined stereo adjustment model in building collapse estimation and thoroughly verifies its feasibility. Firstly, the laser altimetry points (LAPs) acquired by GF-7 and ICESat-1 serve as elevation control points (ECPs), and the tie points from HRSSIs were used as constraint to conduct combined adjustment to improve the consistency of stereoscopic positioning accuracy between HRSSIs before and after the earthquake. Subsequently, a footprints-to-conners, coarse-to-fine, automatic building corners extraction method was performed. Avoiding the time-consuming generation of large-scale DSM while also improving the accuracy of building collapse assessment. Finally, according to the height change of building corners calculated from HRSSIs, building damage assessment was completed. According to the above methods, independent experiments were carried out respectively for the Oaxaca earthquake in Mexico in 2020 and the Kahramanmaras earthquake in Türkiye in 2023. GF-7 HRSSIs was used to verify the accuracy and stability of the proposed method for 3D assessment of building damage. The results indicate that the RMSE of elevation positioning accuracy has been greatly reduced in both regions, ranging from 10.29 m to 0.95 m and from 6.67 m to 0.99 m, respectively. This accuracy guarantees the feasibility of detecting the building floor-level collapse. And 2541 building corner points were extracted from two disaster areas, with correct corner points accounting for 85.18%. A total of 520 buildings were correctly extracted corner points, with an accuracy rate of 94.12% for assessing the degree of damage.

Causal Analysis of Influence of the Solar Cycle and Latitudinal Solar-Wind Structure on Co-Rotation Forecasts

Studying solar-wind conditions is central to forecasting the impact of space weather on Earth. Under the assumption that the structure of this wind is constant in time and co-rotates with the Sun, solar-wind and thereby space-weather forecasts have been made quite effectively. Such co-rotation forecasts are well studied with decades of observations from STEREO and near-Earth spacecraft. Forecast accuracy is primarily determined by three factors: i) the longitudinal separation of spacecraft from Earth determines the corotation time (and hence forecast lead time) [δ\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$\\delta$\\end{document}t] over which the solar wind must be assumed to be constant, ii) the latitudinal separation (or offset) between Earth and spacecraft [δθ\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$\\delta\ heta$\\end{document}]] determines the degree to which the same solar wind is being encountered at both locations, and iii) the solar cycle, via the sunspot number (SSN), acts as a proxy for both how fast the solar-wind structure is evolving and how much it varies in latitude. However, the precise dependencies factoring in uncertainties are a mixture of influences from each of these factors. Furthermore, for high-precision forecasts, it is important to understand what drives the forecast accuracy and its uncertainty. Here we present a causal inference approach based on information-theoretic measures to do this. Our framework can compute not only the direct (linear and nonlinear) dependencies of the forecast mean absolute error (MAE) on SSN, Δθ\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$\\Delta \ heta $\\end{document}, and Δt\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$\\Delta t$\\end{document}, but also how these individual variables combine to enhance or diminish the MAE. We provide an initial assessment of this with the potential of aiding data assimilation in the future.

Rotation of a Stealth CME on 2012 October 5 Observed in the Inner Heliosphere

Coronal mass ejections (CMEs) are subject to changes in their direction of propagation, tilt, and other properties. This is because CMEs interact with the ambient solar wind and other large-scale magnetic field structures. In this work, we report on the observations of the 2012 October 5 stealth CME using coronagraphic and heliospheric images. We find clear evidence of a continuous rotation of the CME, i.e., an increase in the tilt angle, estimated using the graduated cylindrical shell (GCS) reconstruction at different heliocentric distances, up to 58 R ⊙. We find a further increase in the tilt at L1 estimated from the toroidal and cylindrical flux rope fitting on the in situ observations of interplanetary magnetic field (IMF) and solar wind parameters. This study highlights the importance of observations of Heliospheric Imager (HI), on board the Solar Terrestrial Relations Observatory. In particular, the GCS reconstruction of CMEs in the HI field of view promises to bridge the gap between the near-Sun and in situ observations at the L1. The changes in the CME tilt have significant implications for the space weather impact of stealth CMEs.

Energetics of a Solar Flare and a Coronal Mass Ejection Generated by a Hot Channel Eruption

Hot channels (HCs) are prevalent in the solar corona and play a critical role in driving flares and coronal mass ejections (CMEs). In this paper, we estimate the energy content of an X1.4 eruptive flare with a fast CME generated by an HC eruption on 2011 September 22. Originating from NOAA Active Region 11302, the HC is the most dramatic feature in 131 and 94 Å images observed by the Atmospheric Imaging Assembly (AIA) on board the Solar Dynamics Observatory (SDO). The flare is simultaneously observed by SDO/AIA, the Reuven Ramaty High-energy Solar Spectroscopic Imager, and the Extreme-ultraviolet Imager on board the “behind” Solar Terrestrial Relations Observatory (STEREO). The CME is simultaneously detected by the white-light coronagraphs of the Large Angle Spectroscopic Coronagraph on board the Solar and Heliospheric Observatory and the COR1 coronagraph on board the behind STEREO. Using multiwavelength and multiview observations of the eruption, various energy components of the HC, flare, and CME are calculated. The thermal and kinetic energies of the HC are (1.77 ± 0.61) × 1030 erg and (2.90 ± 0.79) × 1030 erg, respectively. The peak thermal energy of the flare and total radiative loss of the soft X-ray–emitting plasma are (1.63 ± 0.04) × 1031 erg and (1.03–1.31) × 1031 erg, respectively. The ratio between the thermal energies of the HC and flare is 0.11 ± 0.03, suggesting that the thermal energy of the HC is not negligible. The kinetic and potential energies of the CME are (3.43 ± 0.94) × 1031 erg and (2.66 ± 0.49) × 1030 erg, yielding a total energy of (3.69 ± 0.98) × 1031 erg for the CME. Continuous heating of the HC is required to balance the rapid cooling by heat conduction, which probably originates from intermittent magnetic reconnection at the flare current sheet. Our investigation may provide insight into the buildup, release, and conversion of energies in large-scale solar eruptions.

Multi-spacecraft Observations of the 2022 March 25 CME and EUV Wave: An Analysis of Their Propagation and Interrelation

This paper reports on a well-defined EUV wave associated with a coronal mass ejection (CME) observed on 2022 March 25. The CME was observed by Solar Orbiter (SolO) during its first close perihelion (0.32 au) and by several other spacecraft from different viewpoints. The EUV wave was visible by the Extreme Ultraviolet Imager on board the Solar Terrestrial Relations Observatory (STEREO-A/STA) in near quadrature to SolO. We perform a detailed analysis of the early phase of this CME in relation to the evolution of the associated EUV wave. The kinematics of the EUV wave and CME are derived via visual identification of the fronts using both the STA and SolO data. The analysis of an associated metric type II radio burst provides information on the early phase of the CME and wave propagation. Finally, we compare the EUV speed to the local magnetic field and Alfvén speed using standard models of the corona. The analysis of the decoupling between the EUV wave and the CME driver via imaging, kinematic study, radio data analysis, and comparison with maps/models clearly indicates that the EUV front is consistent with a wave initially driven by the lateral expansion of the CME, which evolves into a fast-mode magnetosonic wave after decoupling from the CME.

Separating the effects of earthside and far side solar events. A case study

On 8 November 2013 a halo-type coronal mass ejection (CME) was observed, together with flares and type II radio bursts, but the association between the flares, radio bursts, and the CME was not clear. Our aim is to identify the origin of the CME and its direction of propagation, and to exclude features that were not connected to it. On the Earth-facing side, a GOES C5.7 class flare occurred close to the estimated CME launch time, followed by an X1.1 class flare. The latter flare was associated with an EUV wave and metric type II bursts. On the far side of the Sun, a filament eruption, EUV dimmings, and ejected CME loops were observed by imaging instruments onboard the Solar TErrestrial RElations Observatory (STEREO) spacecraft that were viewing the backside of the Sun. The STEREO radio instruments observed an interplanetary (IP) type II radio burst at decameter-hectometric wavelengths, which was not observed by the radio instrument onboard the Wind spacecraft located at L1 near Earth. We show that the halo CME originated from the eruption on the far side of the Sun, and that the IP type II burst was created by a shock wave ahead of the halo CME. The radio burst remained unobserved from the earthside, even at heliocentric source heights larger than 9 solar radii. During the CME propagation, the X-class flare eruption caused a small plasmoid ejection earthward, the material of which was superposed on the earlier CME structures observed in projection. The estimated heights of the metric type II burst match well with the EUV wave launched by the X-class flare. As this radio emission did not continue to lower frequencies, we conclude that the shock wave did not propagate any further. Either the shock driver died out, as a blast wave, or the driver speed no longer exceeded the local Alfven speed.

The Evolution of Ion Charge States in Coronal Mass Ejections

We model the observed charge states of the elements C, O, Mg, Si, and Fe in the ejecta of coronal mass ejections (CMEs). We concentrate on “halo” CMEs observed in situ by the Advanced Composition Explorer/Solar Wind Ion Composition Spectrometer to measure ion charge states, and also remotely by the Solar Terrestrial Relations Observatory when in near quadrature with the Earth, so that the CME expansion can be accurately specified. Within this observed expansion, we integrate equations for the CME ejecta ionization balance, including electron heating parameterized as a fraction of the kinetic and gravitational energy gain of the CME. We also include the effects of non-Maxwellian electron distributions, characterized as a κ function. Focusing first on the 2010 April 3 CME, we find a somewhat better match to the observed charge states with κ close to the theoretical minimum value of κ = 3/2, implying a hard spectrum of nonthermal electrons. Similar but more significant results come from the 2011 February 15 event, although it is quite different in terms of its evolution. We discuss the implications of these values, and of the heating required, in terms of the magnetic reconnection Lundquist number and anomalous resistivity associated with CME evolution close to the Sun.

Near-Sun In Situ and Remote-sensing Observations of a Coronal Mass Ejection and its Effect on the Heliospheric Current Sheet

During the thirteenth encounter of the Parker Solar Probe (PSP) mission, the spacecraft traveled through a topologically complex interplanetary coronal mass ejection (ICME) beginning on 2022 September 5. PSP traversed through the flank and wake of the ICME while observing the event for nearly two days. The Solar Probe ANalyzer and FIELDS instruments collected in situ measurements of the plasma particles and magnetic field at ∼13.3 R S from the Sun. We observe classical ICME signatures, such as a fast-forward shock, bidirectional electrons, low proton temperatures, low plasma β, and high alpha particle to proton number density ratios. In addition, PSP traveled through two magnetic inversion lines, a magnetic reconnection exhaust, and multiple sub-Alfvénic regions. We compare these in situ measurements to remote-sensing observations from the Wide-field Imager for Solar PRobe Plus instrument on board PSP and the Sun Earth Connection Coronal and Heliospheric Investigation on the Solar Terrestrial Relations Observatory. Based on white-light coronagraphs, two CMEs are forward modeled to best fit the extent of the event. Furthermore, Air Force Data Assimilative Flux Transport magnetograms modeled from Global Oscillation Network Group magnetograms and Potential Field Source Surface modeling portray a global reconfiguration of the heliospheric current sheet (HCS) after the CME event, suggesting that these eruptions play a significant role in the evolution of the HCS.

Precision Terrain Modeling Approach in Complex Mountainous Areas Based on Compact UAV Ka-InSAR Data

A High-Precision digital elevation model (DEM) is useful for disaster investigation and evaluation in cloudy, rainy, and complex mountainous areas. However, clouds and rain make the optical images and laser point cloud data acquisition difficult, while noise prohibits obtaining accurate surface information. Additionally, the complex elevation difference in mountainous areas increases the data processing difficulty, such as phase unwrapping and filtering. To overcome these problems, first, we introduce a new airborne multi-baseline Ka-Interferometric Synthetic Aperture Radar (InSAR) system developed by the Beijing Institute of Radio Measurement. The system affords high resolution, small volume, is lightweight, has a good top view angle, and is flexible. Thus, it reduces the flight platform’s dependence and improves the aircrafts adaptability and universality. Moreover, a multi-baseline phase unwrapping method of a two-stage programming approach (TSPA) is selected to overcome the influence of severe noise and the phase continuity assumption limitation. Additionally, an adaptive filtering method for InSAR point clouds considering coherence and optimal bending energy is proposed. This methods validity is verified using stereo satellite images, ground observation point precision checks, and geomorphic texture analysis against existing DEM results. The experimental results demonstrate that the proposed scheme has a good filtering effect on noise, vegetation, residential building areas, and bridges, significantly reducing manual intervention. Moreover, the results highlight that our method is well integrated with stereo images and has more texture details than conventional stereo mapping results, with a mean square error of elevation of 1.938m.