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Abstract The Wide-Lane (WL) and Narrow-Lane (NL) Uncalibrated Phase Delays (UPDs) are the prerequisites in the traditional Precise Point Positioning (PPP) Ambiguity Resolution (AR). As the generation mechanism of various biases becomes more complex, we systematically studied the impact factors of four satellite systems WL and NL UPDs from the perspective of parameter estimation. Approximately 100 stations in a global network are used to generate the UPDs. The results of different satellite systems show that the estimation method, update frequency, and solution mode need to be treated differently. Two regional networks with different receiver types, JAVAD, and Trimble, are also adopted. The results indicate that the receiver-dependent bias has an influence on UPD estimation. Also, the hardware delays can inhibit the satellite-side UPDs if these receiver-specific errors are not fully deployed or even misused. Furthermore, the temporal stability and residual distribution of NL UPDs are significantly enhanced by utilizing a regional network, with the improvements by over 68% and 40%, respectively. It demonstrates that different network scales exhibit the different implication of unmodeled errors, and the unmodeled errors cannot be ignored and must be handled in UPD estimation.

The global bathymetry models are usually of low accuracy over the coastline of polar areas due to the harsh climatic environment and the complex topography. Satellite altimetric gravity data can be a supplement and plays a key role in bathymetry modeling over these regions. The Synthetic Aperture Radar (SAR) altimeters in the missions like CryoSat-2 and Sentinel-3A/3B can relieve waveform contamination that existed in conventional altimeters and provide data with improved accuracy and spatial resolution. In this study, we investigate the potential application of SAR altimetric gravity data in enhancing coastal bathymetry, where the effects on local bathymetry modeling introduced from SAR altimetry data are quantified and evaluated. Furthermore, we study the effects on bathymetry modeling by using different scale factor calculation approaches, where a partition-wise scheme is implemented. The numerical experiment over the South Sandwich Islands near Antarctica suggests that using SAR-based altimetric gravity data improves local coastal bathymetry modeling, compared with the model calculated without SAR altimetry data by a magnitude of 3.55 m within 10 km of offshore areas. Moreover, by using the partition-wise scheme for scale factor calculation, the quality of the coastal bathymetry model is improved by 7.34 m compared with the result derived from the traditional method. These results indicate the superiority of using SAR altimetry data in coastal bathymetry inversion.

Long-distance water transfer is a critical engineering measure to rectify disparities in water resource distribution across regions. The effective operation and safety of such projects are paramount to their success, as localized issues can have cascading consequences, potentially disrupting the entire network. Conventional ground-based monitoring methods have limitations in measuring the deformation of large-scale structures. In this paper, InSAR is employed to monitor the deformation of the Shuangwangcheng (SWC) Reservoir, which features a long embankment dam as part of the South-to-North Water Diversion Project in China. We utilize data from both Sentinel-1 and TerraSAR-X satellites to derive 7-year deformation. Results reveal that the entire dam experiences continuous subsidence, with the maximum deformation in the line-of-sight direction measuring ~160 mm. While minor differential settlements are noted in different sections of the dam, the gradient is not significant due to the dam’s substantial length. The InSAR deformation results from multiple geometries demonstrate good consistency, with the highest correlation observed between the Sentinel-1 ascending and descending datasets, exceeding 0.9. Validation against the GNSS observations of the three sites on the SWC Dam shows the accuracy of InSAR displacements is ~8 mm. Water level changes do impact deformation, but consolidation settlement appears to be the primary controlling factor during the monitoring period. This study underscores the potential of InSAR in long-distance water transfer projects and highlights that spatially continuous deformation is the most significant advantage.

Selecting a representative optical deep-water area is crucial for accurate satellite-derived bathymetry (SDB) based on semi-theoretical and semi-empirical models. This study proposed a deep-water area selection method where potential areas were identified by integrating remote sensing imagery with existing global bathymetric data. Specifically, the effects of sun glint correction for deep-water areas on SDB estimation were investigated. The results indicated that the computed SDB had significant instabilities when different optical deep-water areas without sun glint correction were used for model training. In comparison, when sun glint correction was applied, the SDB results from different deep-water areas had greater consistency. We generated bathymetric maps for the Langhua Reef in the South China Sea and Buck Island near the U.S. Virgin Islands using Sentinel-2 multispectral images and 70% of the Ice, Cloud, and Land Elevation Satellite-2 (ICESat-2) bathymetry data. Additionally, 30% of the ICESat-2 bathymetry data and NOAA NGS Topo-bathy Lidar data served as the validation data to evaluate the qualities of the computed SDB, respectively. The results showed that the average quality of the SDB significantly improved with sun glint correction application by a magnitude of 0.60 m in terms of the root mean square error (RMSE) for two study areas. Moreover, an evaluation of the SDB data computed from different deep-water areas showed more consistent results, with RMSEs of approximately 0.4 and 1.4 m over the Langhua Reef and Buck Island, respectively. These values were consistently below 9% of the maximum depth. In addition, the effects of the optical image selection on SDB inversion were investigated, and the SDB calculated from the images over different time periods demonstrated similar results after applying sun glint correction. The results showed that this approach for optical deep-water area selection and correction could be used for improving the SDB, particularly in challenging scenarios, thereby enhancing the accuracy and robustness of SDB.

In this paper, we address some questions with respect to the Tianshan Mountains that are necessary for understanding the present deformation rate in this region. A series of thrust nappe structures are distributed on the north and south sides of the Tianshan Mountains, and many of them are currently active. To analyze the deformation characteristics and movement rates of different fold-and-thrust belts on the northern and southern margins of Tianshan, we use InSAR observations (Sentinel-1A/B, 2015–2020) to produce a rate map for the entire observation period on four ascending and four descending tracks. In order to reduce phase artifacts, we reconstruct multi-temporal scenes with atmospheric-corrected and orbital-corrected interferograms via a small baseline subset. The results show that the Bolokenu-Aqikekuduke Fault exhibits a right-lateral strike-slip motion, with the western segment moving at about 4.95 ± 0.38 mm/yr and the eastern segment at approximately 2.34 ± 0.34 mm/yr. The Manas-Tugulu anticline in the northern fold-and-thrust belt reaches ~5–8 mm/yr at 86°E–86.5°, and the Qiulitage anticline in the south reaches ~6–9 mm/yr at ~83°–85°. The post-seismic time series cumulative displacement map of the Jinghe earthquake reveals no significant post-seismic deformation signal in the epicenter area. The Qiulitage thrust belt, situated within the fold-and-thrust belts flanking the Tianshan, features extensive thrust accompanied by a right-lateral strike-slip component. And the Manas-Tugulu anticline exhibits sustained deformation, including pronounced coseismic and post-seismic effects from the Hutubi earthquake. This study highlights the potential of a multi-temporal InSAR analysis and emphasizes future opportunities presented by new generations of SAR platforms with shorter revisit periods for quantifying the spatial and temporal behavior of post-seismic and interseismic periods.

Abstract Despite the extensive investigation on the stress and displacement distributions in tunnels, few have considered the influences of the damaged zone around a tunnel on the strength and stiffness parameters of the surrounding rock, including the gradual variation in the damaged factor D and dimensionless damaged radius $$\rho^{{\text{d}}}$$ ρ d , under the effect of excavation disturbance. In this paper, a numerical solution is presented for the stresses and displacement of a circular tunnel excavated in a Hoek–Brown rock mass considering the progressive destruction of the damaged zone. First, the results obtained using the proposed algorithm are compared with those obtained using other numerical solutions, demonstrating a high degree of accuracy through some examples. Second, the influences of the damaged factor $$D$$ D and dimensionless damaged radius $$\rho^{d}$$ ρ d on the stresses, radial displacement, plastic radii, and ground response curve are investigated. The results show that, as the damaged factor D increases, the radial displacement and plastic radius increase, whereas the tangential stress decreases. Both the plastic radius and displacement decrease with decreasing $$\rho^{{\text{d}}}$$ ρ d . This shows that the damaged factor D has a significant effect on tunnel convergence.

Earth observation technologies have great potential in the investigation, monitoring and assessment of various geohazards. Stacking is an efficient InSAR method for estimating deformation rates and helps in the generation and update of the geohazard inventories. However, it relies on the assumption that the atmospheric statistics are stationary, which does not always hold in large-scale interferograms processing. The nonstationary signal, caused by turbulence and stratification of atmosphere, will bias the deformation estimate and lead to misinterpretations of the geophysical processes. In this paper, we propose an enhanced InSAR stacking method integrated with atmospheric correction. Atmospheric errors in the interferograms are first corrected, and then the mean deformation rate is estimated based on least squares. Applications are conducted in ground subsidence monitoring in the Yellow River Delta as well as landslide detection along the Jinsha River, China, with the deformation results evaluated by spatial structure function, semi-variogram and correlation. Spatial dependence in the subsidence results of the Yellow River Delta decreases from 757 km to 220 km, suggesting that the influence of atmospheric turbulence on deformation is mitigated. Correlation between deformation rate and elevation along the Jinsha River reduces from 0.40 to 0.15, indicating that stratification is suppressed. The proposed method adopts the strategies of simplicity and effectiveness, and the outcomes, which can meet the requirements of geohazards general survey, will be beneficial to rapid geohazard detection.

With the influence of rapid urbanization, land subsidence in Nanchang has caused obvious surface cracks in urban roads. It is necessary to use effective deformation monitoring methods to grasp the current situation and causes of land subsidence in the urban area of Nanchang. Multi-temporal C-band Sentinel-1A images were processed by Small Baseline Subset Interferometric Synthetic Aperture Radar (SBAS InSAR) technique, and we obtained the land deformation in Nanchang urban area from 2018 to 2020. Deformation rate results show that most of the land in the study area was stable, and about 94% of the monitoring points had a deformation rate of −5 to 5 ​mm/year. However, small-scale subsidence occurred in the west, north, and south of the study area, with the maximum subsidence rate of −30 ​mm/year. Compared with the leveling data, InSAR-derived results reached the centimeter-level accuracy. Time-series deformation analysis reveals that the main factors causing land subsidence were urban constructions, including building construction, vehicle load, and Nanchang Metro operation. The most severe settlement in the study area was caused by vehicle load, which had significant spatial distribution characteristics. In addition, the acute subsidence that occurred in the construction and early operation stages of the metro gradually stabilized in less than two years.

Landslides are common hazards in reservoir areas and significantly affect dam operation and human lives. For the prevention and management of landslides, accurate assessment of the factors influencing their generation is essential. This study evaluated the key external factors influencing horizontal and vertical displacements of Luobogang Reservoir Slope in Hanyuan County, China. Displacements had been monitored by a surface-displacement-monitoring system consisting of 118 GPS stations during 2012–2015. To identify the external driving factors, their influence zones, and slope responses, we analyzed 32 months of displacement measurements and other multi-source datasets using the empirical orthogonal function. Overall, the results show that slope aging effect, rainfall, and reservoir water levels are three main driving factors. For horizontal displacement, aging effect is the most critical factor and predominantly affects the edges of landslides, the gob cave, and the public building zones. The secondary factor is the reservoir water level, which mainly acts on the boundary between the slope and reservoir water surface. The closer the slope zone is to the reservoir water, the more significant the impact is. Regarding vertical displacement, the most important factor is rainfall. The vertical displacement caused by rainfall accounts for 56.76% of the total vertical displacements. However, rainfall induces elastic displacements that generally cause less damage to the slope. The secondary factor is aging effect, and the vertical displacement caused by aging effect accounts for 9.42%. However, seven individual zones are highly affected by slope aging effect, which is consistent with the distribution of public buildings.

Coastal aquaculture monitoring is vital for sustainable offshore aquaculture management. However, the dense distribution and various sizes of aquacultures make it challenging to accurately extract the boundaries of aquaculture ponds. In this study, we develop a novel combined framework that integrates UNet++ with a marker-controlled watershed segmentation strategy to facilitate aquaculture boundary extraction from fully polarimetric GaoFen-3 SAR imagery. First, four polarimetric decomposition algorithms were applied to extract 13 polarimetric scattering features. Together with the nine other polarisation and texture features, a total of 22 polarimetric features were then extracted, among which four were optimised according to the separability index. Subsequently, to reduce the “adhesion” phenomenon and separate adjacent and even adhering ponds into individual aquaculture units, two UNet++ subnetworks were utilised to construct the marker and foreground functions, the results of which were then used in the marker-controlled watershed algorithm to obtain refined aquaculture results. A multiclass segmentation strategy that divides the intermediate markers into three categories (aquaculture, background and dikes) was applied to the marker function. In addition, a boundary patch refinement postprocessing strategy was applied to the two subnetworks to extract and repair the complex/error-prone boundaries of the aquaculture ponds, followed by a morphological operation that was conducted for label augmentation. An experimental investigation performed to extract individual aquacultures in the Yancheng Coastal Wetlands indicated that the crucial features for aquacultures are Shannon entropy (SE), the intensity component of SE (SE_I) and the corresponding mean texture features (Mean_SE and Mean_SE_I). When the optimal features were introduced, our proposed method performed better than standard UNet++ in aquaculture extraction, achieving improvements of 1.8%, 3.2%, 21.7% and 12.1% in F1, IoU, MR and insF1, respectively. The experimental results indicate that the proposed method can handle the adhesion of both adjacent objects and unclear boundaries effectively and capture clear and refined aquaculture boundaries.

On 1 May 2020, the Sardoba Reservoir in Uzbekistan breached its western wall, and the uncontrolled release of water caused casualties, environmental damages and economic losses. We investigate the dam failure based on three sets of Earth observation data, including: (i) satellite altimetry products, i.e., ICESat-2 data, with the aim of understanding the topographic features in the study area; (ii) multi-geometry Sentinel-1 SAR data to retrieve the pre-failure deformation along the vertical and horizontal east-west directions between 2017 and 2020; (iii) optical images from Sentinel-2 satellites and Global Precipitation Measurement (GPM) products, which are involved in exploring the environmental status before the failure. We analyse the possible causes of the collapse in terms of both physical and human factors. The differential settlement of ∼60 mm revealed by InSAR at the failure section is a sign of internal erosion through the embankment, which is the physical factor contributing to the failure. The opportunity to prevent the collapse were missed due to the human factor of ignorance brought by limitations of the conventional monitoring methods. Neither ground observations nor satellite-based GPM products show extreme precipitation in the region, ruling out the likelihood of rainfall-induced overtopping. The settlement rate of the embankment shows no decaying trend, indicating that the dam is undergoing the primary consolidation phase of total settlement. Maximum settlement of ∼270 mm (∼0.8% of the dam height) has happened on the north bank since the reservoir impoundment, which should raise concern in future monitoring and surveillance. The results reveal that InSAR can discern the failure precursor by detecting surface motion, and that the deformation signals can help to warn of risks and avoid dam damage. We recommend InSAR deformation monitoring be included in future safety programs, providing detailed deformation and resisting risks of ignorance.

Theoretically, five-frequency observations can form combined observations with longer wavelength, smaller ionospheric delay and smaller noise, which may improve the performance of cycle slip detection and repair. Four geometry-free phase combinations and one geometry-free phase and pseudorange combination are formed to detect and repair the cycle slips in real time. Firstly, the high-quality geometry-free phase combinations of three, four and five frequencies are discussed, then the optimal five-frequency geometry-free phase combinations are selected to detect the cycle slips. Secondly, one geometry-free phase and pseudorange combination which is linearly independent with the above four phase combinations is added to ensure that all the cycle slips can be detected. Thirdly, a real-time cycle slip repair algorithm based on the LAMBDA search method is deduced. The five-frequency real-time cycle slip detection and repair method has been tested by using BDS-3 undifferenced data, even under the condition of active ionospheric and low sampling interval. The results showed that the proposed method is capable of detecting and repairing all the simulated cycle slips on the five carriers in real time.

Much attention has been paid to the subsidence monitoring of large-scale man-made linear features, which are usually characterized by long-distance, large-scale, and nonuniform distribution. The multitemporal interferometric synthetic aperture radar (InSAR) technique can provide ground deformation maps for a large area with high spatial resolution and millimeter precision at low costs. The technique overcomes the limitations of ground-based survey instruments. However, the variable atmospheric turbulent component in flat areas has impacts on InSAR detection capability, especially over low-amplitude quasi-stable deformation areas. We propose an imagewise stacking method, which can improve the InSAR time-series analysis by reducing residual noise while retaining the ground deformation signal. We integrate persistent scatterer and distributed scatterer in our processing strategy and conduct a tentative test on the roadbed subsidence monitoring of the Lianyan high-speed railway using 47 medium-resolution Sentinel-1 images. Comparing the InSAR displacement time series and the results with a continuous BeiDou navigation satellite system network, the standard deviation of 3.3 mm and the mean absolute error of 2.2 mm are obtained. The proposed method reduced the above two error measures by 66.3% and 65.6%, respectively, compared with the spatiotemporal filtering. Moreover, the analysis of the spatiotemporal characteristics of the railway deformations also tells that the railway under study is stable.

The BeiDou Global Navigation Satellite System (BDS), including the second generation (BDS-2) and the third generation (BDS-3), has been widely used in areas of positioning, navigation, and timing (PNT). One of the essential prerequisites for accurate PNT service is the precise satellite orbits of multi-frequency and multi-constellation BDS-2 and BDS-3 satellites. As usual, the precise orbit products can be obtained from analysis centers (ACs) of the international GNSS Service (IGS). The precise orbits can also be downloaded from the international GNSS Monitoring and Assessment System (iGMAS). Compared with the IGS ACs, the iGMAS can provide featured services such as satellite orbits based on the new B1C/B2a BDS signals. Considering the indispensability of the new signals, the performance of all BDS precise orbits from iGMAS needs to be known. However, there is no comprehensive assessment of BDS-2 and BDS-3 precise orbits based on B1I/B3II and B1C/B2a frequencies from iGMAS, especially for the period after the BDS entered the stable operation stage. In this paper, BDS-2/BDS-3 final (ISC), rapid (ISR), and ultra-rapid (ISU) products based on B1I/B3I and B1C/B2a frequencies from iGMAS are all assessed comprehensively. Specifically, at first, the precise orbits from iGMAS are compared with the ones from the IGS ACs. Based on this, the satellite laser ranging inspects the precise orbits from iGMAS. Finally, the orbit errors are discussed systematically by considering the beta and elongation angles. Using one year of data, the orbit accuracy of geostationary orbit, inclined geosynchronous orbit, and medium earth orbit (MEO) satellites can almost reach meter to decimeter level, decimeter to sub-decimeter level, and centimeter level, respectively, where the ISC products are the best. The ISC, ISR, and ISU products based on B1I/B3I frequencies are generally better than the ones based on B1C/B2a frequencies. Additionally, according to the SLR data, the results show that the accuracy of precise orbits of BDS-3 is better than that of BDS-2. The mean values of orbit biases of BDS-3 MEO satellites are approximately 2.88 cm. In addition, the orbit errors are related to the beta angle and elongation angle to some extent, and the manufacturers may also have an influence on the orbit errors.

The filtering procedure is usually mandatory for modeling mean dynamic topography (MDT) when a geodetic approach based on the Mean Sea Surface (MSS) and the Global Geopotential Model (GGM) is used. This is due to the inconsistent spectral contents between MSS and GGM. However, traditional isotropic filtering algorithms (e.g., Gaussian filter) consider neither the MDT locations nor their azimuth when smoothing the signal within the filtering radius. Hence, the isotropic filtering will attenuate the MDT signal near the current and filter the current signal into the surrounding ocean, which may lead to signal contamination and distortion. In this study, we set up a least squares-based (LS) approach to model MDT signal from the altimeter-derived MSS and geoid height using spherical harmonics from GGMs, where MDT is parameterized by Lagrange Basis Functions (LBFs). The design matrix is segmentally established, considering the error information of GGM in various spectral bands. Numerical experiments in the Gulf Stream show that applications of full error variance-covariance matrix or only diagonal error variance of GGM may have marginal effects on the MDT modeling. The MDT computed from this LS-based approach using the latest releases of Gravity Field and Steady-state Ocean Circulation Explorer (GOCE) geoid models, i.e., GO_CONS_GCF_2_DIR_R6 and Gravity Observation Combination 06s model (GOCO06s), have the best agreement with the comparison data, especially near the current region. Deduced geostrophic velocities based on the MDT solutions show that the LS-based approach recovers the current signal better than the Gaussian filtering by 1.8 cm/s. Estimated error map illustrates that errors are more concentrated near the coastal region.

This article discusses the sea level determination using raw intermediate frequency data transmitted from the Global Navigation Satellite System (GNSS) and received by spaceborne GNSS-Reflectometry satellites, TechDemoSat-1. The reflected signals scattered from a sea ice surface and a rough sea surface are investigated. The altimetry method based on the bistatic group delay (code phase) from GNSS signals for sea level estimation are introduced. The two raw IF datasets recorded on January 18 and 27, 2015 for a duration of 40 s are analyzed to drain more information than Level 1 data. The results show a good consistence with mean sea surface (MSS) model. The orbit error of the GNSS-R satellite is corrected by a proposed method that combines the MSS and the least squares solution, which help evaluate the actual altimetry precision. The defect of fixed temporal resolution and fixed four onboard processing channels of Level 1 data can be improved by postprocessing using software define receiver to mine more information, so as to explore the potential. At the end, fake high signal-to-noise ratio Doppler delay maps from the raw data are analyzed, which provides a reference for the altimetry of GNSS-R technique using raw data.

Abstract The use of water-soluble chemical fertilizers for years under drip irrigation conditions results in soil compaction, fertility decline, and fruit quality decrease in arid areas. Currently, little research has been reported regarding the effects of increasing organic fertilizer and reducing drip chemical fertilizer on the growth of grape plants under different conditions in arid areas. In this study, five different treatments were conducted. Compared with no fertilizer for 3 consecutive years (CK) and single fertilizer for 3 consecutive years (T0), organic fertilizer plus 1 year of reducing drip chemical fertilizer (T1), organic fertilizer plus 2 years of reducing drip chemical fertilizer (T2), and organic fertilizer plus 3 years of reducing drip chemical fertilizer (T3) improved the soil pH, electrical conductivity (EC) values, and soil organic matter content to different degrees during early growth stages (15 days after anthesis) and mature stages (75 days after anthesis). The available N, P, and K contents in the T1 and T2 treatments increased significantly. With the T2 treatment, the longitudinal and transverse diameters of the ‘Summer Black’ grapes were the largest during the two fruit expansion periods. The anthocyanin content of grape peel with the T2 treatment was 22.0% higher than that with the T0 treatment. The soluble solids, sugar–acid ratio, various sugar contents, vitamin C, and total phenol of the fruit increased significantly with the T2 treatment, indicating that the T2 treatment was best for promoting grape growth and fruit quality and that the T3 treatment was the second best.

The development of the global geopotential model (GGM) broadens its applications in ocean science, which emphasizes the importance for model assessment. We assess the recently released high-degree GGMs over the South China Sea through heterogeneous geodetic observations and synthetic/ocean reanalysis data. The comparisons with a high resolution (∼3 km) airborne gravimetric survey over the Paracel Islands show that XGM2019e_2159 has relatively high quality, where the standard deviation (SD) of the misfits against the airborne gravity data is ∼3.1 mGal. However, the comparisons with local airborne/shipborne gravity data hardly discriminate the qualities of other GGMs that have or truncated to the same expansion degree. Whereas, the comparisons with the synthetic/ocean reanalysis data demonstrate that the qualities of the values derived from different GGMs are not identical, and the ones derived from XGM2019e_2159 have better performances. The SD of the misfits between the mean dynamic topography (MDT) derived from XGM2019e_2159 and the ocean data is 2.5 cm; and this value changes to 7.1 cm/s (6.8 cm/s) when the associated zonal (meridian) geostrophic velocities are assessed. In contrast, the values derived from the other GGMs show deteriorated qualities compared to those derived from XGM2019e_2159. In particular, the contents computed from the widely used EGM2008 have relatively poor qualities, which is reduced by 3.9 cm when the MDT is assessed, and by 4.0 cm/s (5.5 cm/s) when the zonal (meridian) velocities are assessed, compared to the results derived from XGM2019e_2159. The results suggest that the choice of a GGM in oceanographic study is crucial, especially over coastal zones. Moreover, the synthetic/ocean data sets may be served as additional data sources for global/regional gravity field assessment, which are useful in regions that lack of high-quality geodetic data.

Filtering methods are usually used to combine the mean sea surface (MSS) and geoid (computable by global geopotential model (GGM)) into a common subspace, to model mean dynamic topography (MDT), which may lead to signal leakage and distortion problems. The use of the rigorous least squares (LS) method and multivariate objective analysis (MOA) alleviates these problems, and the derived MDTs from these two methods show better performance than MDTs derived from filtering methods. However, the advantages and disadvantages of these two methods have not been evaluated, and no direct comparison has yet been conducted between these two approaches regarding the performances in MDT recovery. In this study, we compare the performances of the MOA method with the LS method, providing information with respect to the usability of different methods in MDT modeling over regions with heterogeneous ocean states and hydrological conditions. We combined a recently published mean sea surface called DTU21MSS, and a satellite-only GGM named GO_CONS_GCF_2_DIR_R6, for MDT computation over four typical study areas. The results showed that the MDTs derived from the LS method outperformed the MOA method, especially over coastal regions and ocean current areas. The root mean square (RMS) of the discrepancies between the LS-derived MDT and the ocean reanalysis data was lower than the RMS of the discrepancies computed from the MOA method, by a magnitude of 1–2 cm. The formal error of the MDT estimated by the LS method was more reasonable than that derived from the MOA method. Moreover, the geostrophic velocities calculated by the LS-derived MDT were more consistent with buoy data than those calculated by the MOA-derived solution, by a magnitude of approximately 1 cm/s. The reason can be attributed to the fact that the LS method forms the design matrix segmentally, based on the error characteristics of the GGM, and suppresses high-frequency noise by applying constraints in different frequency bands, which improves the quality of the computed MDT. Our studies highlight the superiority of the LS-derived method versus the MOA method in MDT modeling.

The atmospheric effect represents one of the major error sources in Interferometric Synthetic Aperture Radar (InSAR), and its mitigation is found crucial for high-precision InSAR applications. Numerous studies on InSAR atmospheric correction methods and applications covering a wide range of regions worldwide have been reported with varying degrees of success. However, more efforts on the performance assessment are needed, and the conclusions may lack statistical significance due to the limited interferograms involved in most of these analyses. To optimally utilise different InSAR atmospheric correction methods and avoid potential uncertainty caused, appropriate statistical metrics to assess the correction performance must be set up. In this work, we provide a general guideline for statistical assessment of InSAR atmospheric correction. Based on the physical properties of the atmosphere, three metrics are applied: (i) the phase standard deviation which assesses the overall performance of the correction; (ii) the spatial structure function which evaluates the reduction of the long-wavelength atmospheric effect; and (iii) the phase-elevation correlation coefficient which measures the reduction of the stratified component of the atmospheric delay. The performance of the Generic Atmospheric Correction Online Service for InSAR (GACOS) products for two typical terrains in Eastern China is evaluated. Statistical results of the 1250 Sentinel-1 interferograms covering the Yellow River Delta and Shandong hilly region show that (i) GACOS reduces the interferometric phase standard deviation in 84.6% of the interferograms by an average of 36.4%; (ii) the phase decorrelation distance decreases from 321 km to 225 km on average after correction; and (iii) the mean phase-elevation correlation declines by 33.3% for the areas with considerable topographic variations. The results verify the effectiveness of GACOS products in Eastern China for the first time, and the three proposed metrics further characterise the sources of improvement after correction.

Deformation monitoring plays an important role in performance monitoring to ensure the reservoir dams and embankments are functioning as designed. This work should be the first deformation monitoring application of GNSS in China's huge South-to-North Water Diversion Project. A GNSS deformation monitoring system, equipped with 4G data transmission and automated data processing software, is established at Shuangwangcheng Reservoir, an important regulation control project on the Eastern Route. Precision evaluations of different observation sessions from both GPS and BDS are conducted, and results show that the performance of BDS is comparable to that of GPS, especially for longer observation session solutions. The 1 mm horizontal and 2 mm vertical precisions of daily solutions meet the deformation monitoring requirement of the project. The deformation time series reveal an uneven settlement of Shuangwangcheng Reservoir dam. The causes of deformation are analyzed and the water level change in the reservoir is deemed as the main factor.

The coarse resolution of land surface temperatures (LSTs) retrieved from thermal-infrared (TIR) satellite images restricts their usage. One way to improve the resolution of such LSTs is downscaling using high-resolution remote sensing images. Herein, Gaofen-6 (GF-6) and Landsat-8 images were used to obtain original and retrieved LSTs (Landsat-8- and GF-6-retrieved-LSTs) to perform LST downscaling in the Ebinur Lake Watershed. Downscaling model was constructed, and the regression kernel was explored. The results of downscaling LST using the GF-6 normalized difference vegetation index with red-edge band 2, ratio built-up index, normalized difference sand index, and normalized difference water index as multi-remote sensing indices with multiple remote sensing indices with random forest regression method provided optimal downscaling results, with R2 of 0.836, 0.918, and 0.941, root mean square difference of 1.04 K, 2.06 K, and 1.80 K, and the number of pixels with LST errors between −1 K and +1 K of 87.2%, 76.4%, and 81.9%, respectively. The expression of spatial distribution of 16 m-LST downscaling results corresponded with that of Landsat-8- and GF-6-retrieved-LST, and provided additional details spatial description of LST variations, which was absent in the Landsat-8- and GF-6-retrieved LSTs. The results of downscaling LST could satisfy the application requirements of LST spatial resolution.

The spaceborne Global Navigation Satellite Systems Reflectometry (GNSS-R) offers versatile Earth surface observation. While the accuracy of the computed geometry, required for the implementation of the technique, degrades when Earth’s surface topography is complicated, previous studies ignored the effects of the local terrain surrounding the ideal specular point at a suppositional Earth reference surface. The surface slope and its aspect have been confirmed that it can lead to geolocation-related errors in the traditional radar altimetry, which will be even more intensified in tilt observations. In this study, the effect of large-scale slope on the spaceborne GNSS-R technique is investigated. We propose a new geometry computation strategy based on the property of ellipsoid to carry out forward and inverse calculations of path geometries. Moreover, it can be extended to calculate unusual reflected paths over versatile Earth’s topography by taking the surface slope and aspects into account. A simulation considering the slope effects demonstrates potential errors as large as meters to tens kilometers in geolocation and height estimations in the grazing observation condition over slopes. For validation, a single track over the Greenland surface received by the TechDemoSat 1 (TDS-1) satellite with a slope range from 0% to 1% was processed and analyzed. The results show that using the TanDEM-X 90 m Digital Elevation Model (DEM) as a reference, a slope of 0.6% at an elevation angle of 54 degrees can result in a geolocation inaccuracy of 10 km and a height error of 50 m. The proposed method in this study greatly reduces the standard deviation of geolocations of specular points from 4758 m to 367 m, and height retrievals from 28 m to 5.8 m. Applications associated with topography slopes, e.g., cryosphere could benefit from this method.

MDT recovery over coastal regions is challenging, as the mean sea surface (MSS) and geoid/quasi-geoid models are of low quality. The altimetry satellites equipped with the synthetic aperture radar (SAR) altimeters provide more accurate sea surface heights than traditional ones close to the coast. We investigate the role of using the SAR-based MSS in coastal MDT recovery, and the effects introduced by the SAR altimetry data are quantified and assessed. We model MDTs based on the multivariate objective analysis, where the MSS and the recently released satellite-only global geopotential model are combined. The numerical experiments over the coast of Japan and southeastern China show that the use of the SAR-based MSS improves the local MDT. The root mean square (RMS) of the misfits between MDT-modeled with SAR altimetry data and the ocean data is lower than that derived from MDT computed without SAR data—by a magnitude of 4–8 mm. Moreover, the geostrophic velocities derived from MDT modeled with the SAR altimetry data have better fits with buoy data than those derived from MDT modeled without SAR data. In total, our studies highlight the use of SAR altimetry data in coastal MDT recovery.

The marine gravity field recovery close to land/island is challenging owing to the scarcity of measured gravimetric observations and sorely contaminated satellite radar altimeter-derived data. The satellite missions that carried the synthetic aperture radar (SAR) altimeters supplied data with improved quality compared to that retrieved from the conventional radar altimeters. In this study, we combine the satellite altimeter-derived gravity data for marine gravity field augmentation over island areas; in particular, the feasibility for regional augmentation by incorporating the SAR altimeter-derived gravity data is investigated. The gravity field modeling results over the Spratly Islands demonstrate that the marine gravity field is augmented by the incorporation of newly published satellite altimeter-derived gravity data. By merging the gravity models computed with the Sentinel-3A/B SAR altimetry data, the quasi-geoid and mean dynamic topography are dramatically improved, by a magnitude larger than 4 cm around areas close to islands, in comparison with the results directly derived from a combined global geopotential model alone. Further comparison of regional solutions computed from heterogeneous gravity models shows that the ones modeled from the SAR-based gravity models have better performances, the errors of which are reduced by a magnitude of 2~4 cm over the regions close to islands, in comparison with the solutions modeled with the gravity models developed without SAR altimetry data. These results highlight the superiority of using the SAR-based gravity data in marine gravity field recovery, especially over the regions close to land/island.

Past studies on deep-lying tunnels under the assumption of plane strain have generally neglected the influence of intermediate principal stress even though this affects the surrounding rocks in the plastic zone. This study proposes a finite difference method to compute the stress strain plastic region and displacement of a tunnel based on the Drucker–Prager (D–P) yield criterion and non-associated flow rule and considering the influences of intermediate principal stress and the strain-softening behavior of surrounding rock. The computed results were compared with those of other well-known solutions and the accuracy and validity of the method were confirmed through some examples. Parameter analysis was conducted to investigate the effects of intermediate principal stress on stress-strain, the plastic region, the ground response curve, and the dilatability of surrounding rock. The results showed that the plastic radius Rp, the residual radius Rd, and radial displacement of surrounding rock first decreased and then increased with increasing intermediate principal stress coefficient b from 0 to 1, with the minimums occurring at b = 0.75. On the contrary, the peak and rate of variation of the dilatancy coefficient first increased and then decreased with increasing b and the dilatancy coefficient Kψ gradually transitioned from nonlinear to linear variation. Meanwhile, the inhibition of the plastic radius and radial displacement gradually weakened with increasing support pressure, whereas the dilatancy coefficient of the tunnel opening gradually increased.

Sea-level monitoring is important for the safety of coastal cities and analysis of ocean and climate. Sea levels can be estimated based using the global navigation satellite system–interferometry reflectometry (GNSS–IR). The frequency in a signal-to-noise ratio (SNR) arc has been found to be related to the height between the GNSS antenna and reflecting surface, which is called reflector height (RH, h). The height variation of the reflecting surface causes an error, and this error is the most significant error in the GNSS–IR sea-level retrieval. The key to the correction of height variation error lies in the determination of the RH variation rate h˙. The classical correction method determines h˙ based on tide analysis of a coarse RH series over a longer time period. Therefore, h˙ inherits errors in coarse RH series, which contains significant bias during a storm surge, and correcting this requires data accumulation. This study proposes a correction method of height variation error based on just one SNR arc based on wavelet analysis and least-square estimation. First, using wavelet analysis, instantaneous frequencies are extracted in one SNR arc; these frequencies are then converted to RH series. Second, using least-square estimation, h and h˙ are conjointly solved based on the RH series from wavelet analysis. Data of GNSS site HKQT located in Hong Kong, China, during a period of time that includes Typhoon Hato were used. The root-mean-square errors (RMSEs) of retrievals were 21.5 cm for L1, 9.5 cm for L2P, 9.3 cm for L2C, and 7.6 cm for L5 of GPS; 16.8 cm for L1C, 14.1 cm for L1P, 12.6 cm for L2C, and 10.7 cm for L2P of GLONASS; 15.7 cm for L1, 11.2 cm for L5, 12.2 cm for L7, and 9.6 cm for L8 of Galileo. Results showed this method can correct the height variation error based on just one SNR arc, can avoid the inheritance of errors, and can be used during periods of storm surge.

Mean dynamic topography (MDT) is crucial for research in oceanography and climatology. The optimal interpolation method (OIM) is applied to MDT modeling, where the error variance–covariance information of the observations is established. The global geopotential model (GGM) derived from GOCE (Gravity Field and Steady-State Ocean Circulation Explorer) gravity data and the mean sea surface model derived from satellite altimetry data are combined to construct MDT. Numerical experiments in the Kuroshio over Japan show that the use of recently released GOCE-derived GGM derives a better MDT compared to the previous models. The MDT solution computed based on the sixth-generation model illustrates a lower level of root mean square error (77.0 mm) compared with the ocean reanalysis data, which is 2.4 mm (5.4 mm) smaller than that derived from the fifth-generation (fourth-generation) model. This illustrates that the accumulation of GOCE data and updated data preprocessing methods can be beneficial for MDT recovery. Moreover, the results show that the OIM outperforms the Gaussian filtering approach, where the geostrophic velocity derived from the OIM method has a smaller misfit against the buoy data, by a magnitude of 10 mm/s (17 mm/s) when the zonal (meridional) component is validated. This is mainly due to the error information of input data being used in the optimal interpolation method, which may obtain more reasonable weights of observations than the Gaussian filtering method.

This paper proposes an accurate quantitative segmentation method by analyzing the probability distribution of tracking variance and strict derivation based on the tracking loop theory. The segmentation points are taken as characteristics of phase lock loop (PLL) and frequency lock loop (FLL) performances, and the two factors that cause the performance difference are discriminator gain and filtering coefficient, which denote proportional and integration coefficients, respectively. The filtering coefficients lead to a difference of 2.5 dB-Hz between the FLL and PLL. Moreover, through the analysis of the normalized bandwidth and phase margin, it is found that the integration time and bandwidth need a dynamic balance to achieve the best performance. Finally, the simulation results and real data are in good agreement with the theoretical analysis results. The minimum mean error rate of the deviation between the real data and the theoretical data is only 1.8%. In the proposed method, the influence of external hardware factors on the tracking loop is removed, and the loop design factors are modeled directly. Instead of testing the denoising performance based on the ranging and angle measuring error after location calculation, the filter coefficient is proposed to evaluate the processing performance of the tracking loop objectively and directly at the theoretical level, which proposes a new performance evaluation method at the theoretical level. The results presented in this study provide theoretical support for the design of a new-type tracking loop with enhanced performances.

Probability of collision between non-cooperative space object (NCSO) and the reference spacecraft (RS) has been increased drastically over the past few decades. The traditional method is difficult to identify the maneuvering of non-cooperative space object. In the present paper, not only positions and velocities, but also accelerations of non-cooperative space object are estimated as parameters by the extended Kalman filtering based on setting up the state linear equation and measurement model of the non-cooperative space object. The algorithm for predicting collision probability is derived from position error ellipsoid, and the algorithm for determining maneuvering probability is derived from maneuvering acceleration and its error ellipsoid, which can be employed to identify whether the upcoming space object is being maneuvered. An epoch Earth-centered inertial (EECI) coordinate system is suggested to replace Earth-centered inertial (ECI) to simplify coordinate transformation. Finally, a set of simulations were conducted to validate the proposed algorithms with the simulated measurement data of the reference spacecraft space-borne millimeter-wave (MMW) radar.

Ground-based synthetic aperture radar interferometry (GB-InSAR) is a valuable tool for deformation monitoring. The 2D interferograms obtained by GB-InSAR can be integrated with a 3D terrain model to visually and accurately locate deformed areas. The process has been preliminarily realized by geometric mapping assisted by terrestrial laser scanning (TLS). However, due to the line-of-sight (LOS) deformation monitoring, shadow and layover often occur in topographically rugged areas, which makes it difficult to distinguish the deformed points on the slope between the ones on the pavement. The extant resampling and interpolation method, which is designed for solving the scale difference between the point cloud and radar pixels, does not consider the local scattering characteristics difference of slope. The scattering difference information of road surface and slope surface in the terrain model is deeply weakened. We propose a differentiated method with integrated GB-InSAR and terrain surface point cloud. Local geometric and scattering characteristics of the slope were extracted, which account for pavement and slope differentiating. The geometric model is based on a GB-InSAR system with linear repeated-pass and the topographic point cloud relative observation geometry. The scattering model is based on k-nearest neighbor (KNN) points in small patches varies as radar micro-wave incident angle changes. Simulation and a field experiment were conducted in an open-pit mine. The results show that the proposed method effectively distinguishes pavement and slope surface deformation and the abnormal area boundary is partially relieved.

The tracking accuracy of a traditional Frequency Lock Loop (FLL) decreases significantly in a complex environment, thus reducing the overall performance of a satellite receiver. In order to ensure high tracking accuracy of a receiver in a complex environment, this paper proposes a new tracking loop combining the vector FLL (VFLL) with a robust least squares method, which accurately matches the weights of received signals of different qualities to ensure high positioning accuracy. The weights of received signals are selected at the signal level, not at the observation level. In this paper, the ranges of strong and weak signals of the loop are determined according to the different expressions of the distribution function at different signal strengths, and the concept of loop segmentation is introduced. The segmentation results of the FLL are taken as a basis of the weight selection, and then combined with the Institute of Geodesy and Geophysics (IGGIII) weight function to obtain the equivalent weight matrix; the experiments are conducted to prove the advantages of the proposed method over the traditional methods. The experimental results show that the proposed VFLL tracking method has strong denoising capability under both normal- signal and harsh application environment conditions. Accordingly, the proposed model has a promising application perspective.

The utilization of advanced remote sensing methods to monitor the coastal wetlands is essential for conservation and sustainable development. With multiple polarimetric channels, the polarimetric synthetic aperture radar (PolSAR) is increasingly employed in land cover classification and information extraction, as it has more scattering information than regular SAR images. Polarimetric decomposition is often used to extract scattering information from polarimetric SAR. However, distinguishing all land cover types using only one polarimetric decomposition in complex ecological environments such as coastal wetlands is not easy, and thus integration of multiple decomposition algorithms is an effective means of land cover classification. More than 20 decompositions were used in this research to extract polarimetric scattering features. Furthermore, a new algorithm combining random forest (RF) with sequential forward selection (SFS) was applied, in which the importance values of all polarimetric features can be evaluated quantitatively, and the polarimetric feature set can be optimized. The experiments were conducted in the Jiangsu coastal wetlands, which are located in eastern China. This research demonstrated that the classification accuracies were improved relative to regular decision tree methods, and the process of polarimetric scattering feature set optimization was intuitive. Furthermore, the scattering matrix elements and scattering features derived from H / α , Yamaguchi3, VanZyl3, and Krogager decompositions were determined to be very supportive of land cover identification in the Jiangsu coastal wetlands.

Snow is one of the most critical sources of freshwater, which influences the global water cycle and climate change. However, it is difficult to monitor global snow variations with high spatial−temporal resolution using traditional techniques due to their costly and labor-intensive nature. Nowadays, the Global Positioning System Interferometric Reflectometry (GPS-IR) technique can measure the average snow depth around a GPS antenna using its signal-to-noise ratio (SNR) data. Previous studies focused on the use of GPS data at sites located in flat areas or on very gentle slopes. In this contribution, we propose a strategy called the Tilted Surface Strategy (TSS), which uses the SNR data reflected only from the flat quadrants to estimate the snow depth instead of the conventional strategy, which employs all the SNR data reflected from the whole area around a GPS antenna. Three geodetic GPS sites from the Plate Boundary Observatory (PBO) project were chosen in this experimental study, of which GPS sites p683 and p101 were located on slopes with their gradients up to 18% and the site p025 was located on a flat area. Comparing the snow depths derived with the GPS-IR TSS method with the snow depth results provided with the GPS-PBO, i.e., GPS-IR with the conventional strategy, the Snowpack Telemetry (SNOTEL) network measurements and gridded Snow Data Assimilation System (SNODAS) estimates, it was found that the snow depths derived with the four methods had a good agreement, but the snow depth time series with the GPS-IR TSS method were closer to the SNOTEL measurements and the SNODAS estimates than those with GPS-PBO method. Similar observations were also obtained from the cumulative snowfall time series. Results generally indicated that for those GPS sites located on slopes, the TSS strategy works better.

The satellite clock prediction is crucial to support real-time global satellite precise positioning services. Currently, the clock prediction for the Chinese BeiDou navigation satellite system (BDS) is still challenging to satisfy the precise positioning applications. Based on the exploration of existing prediction models, an improved model combing the spectrum analysis model (SAM) and the least-squares support-vector machine (LS-SVM) is proposed especially for BDS-2/3 satellites. Considering satellite-specific characteristics, the parameters of the LS-SVM method are optimized satellite by satellite, including input length, regularization and kernel parameters. The improved model is evaluated by comparing the predicted clocks of existing methods and the improved model. The bias of the predicted clock offsets are within ±1.0 ns for most medium Earth orbits (MEOs) over three hours employing the improved model, which is better than that of the existing methods and can be applied for several real-time precise positioning applications. The predicted clock offsets are further evaluated by applying clock corrections to precise point positioning (PPP) in both static and kinematic modes for 10 international GNSS service (IGS) Multi-GNSS Experiment (MGEX) stations, including five stations in the Asia-Pacific region. According to the practical engineering experience, 2 dm and 5 dm are defined for static and kinematic PPP, respectively, as a convergence threshold. Then, in the static PPP, the improved model is demonstrated to be effective, and positioning accuracies of some stations obtain more than 15% improvements on average for each direction, which enables them to get sub-decimeter positioning, especially in the Asia-Pacific region. In the kinematic PPP, the improved model performs much better than the others in terms of both the convergence time and the positioning accuracy. The convergence time can be shortened from 1.0 h to below 0.5 h, while the positioning accuracies are enhanced by 16.3%, 10.8%, and 18.9% on average in east, north, and up direction, respectively.

A GNSS station, located on the shore of sea and inland waters, and equipped with standard geodetic receivers and antennas, can be used to measure water levels using a technique called GNSS Interferometric Reflectometry (GNSS-IR). The classical GNSS-IR method is based on SNR data and LSP spectrum analysis method. In order to promote the application of GNSS-IR, the accuracy of the results needs to be further improved, and quality control needs to be achieved better. Classical quality control methods include denoising filtering based on data source SNR; post-processing filtering based on results; morphological analysis based on parameters, such as the ratio of the maximum peak value to the background noise mean, the ratio of the maximum peak to the sub-peak, and the amplitude of the maximum peak. All three methods have the problem of correct frequency extraction under multiple approximate peak conditions. This paper focuses on the performance analysis of three methods of quality control for two situations with real examples, summarizes the advantages and disadvantages of each method, and discusses the measures in applications. Considering the limitations in the threshold setting for the third method, a new quality control method combining multiple parameters and external constraints is proposed. This method is more flexible, especially in dealing with a periodogram with multiple similar peaks, breaking through the premise that the frequency corresponding to the maximum peak is the correct frequency, and validated in two different environments. The experimental results show that the proposed method can improve the accuracy of the measured water level while ensuring the amount of the results. It eliminates the gross errors effectively and uses the data efficiently.

Monitoring ocean waves plays a crucial role in, for example, coastal environmental and protection studies. Traditional methods for measuring ocean waves are based on ultrasonic sensors and accelerometers. However, the Global Positioning System (GPS) has been introduced recently and has the advantage of being smaller, less expensive, and not requiring calibration in comparison with the traditional methods. Therefore, for accurately measuring ocean waves using GPS, further research on the separation of the wave signals from the vertical GPS-mounted carrier displacements is still necessary. In order to contribute to this topic, we present a novel method that combines complementary ensemble empirical mode decomposition (CEEMD) with a wavelet threshold denoising model (i.e., CEEMD-Wavelet). This method seeks to extract wave signals with less residual noise and without losing useful information. Compared with the wave parameters derived from the moving average skill, high pass filter and wave gauge, the results show that the accuracy of the wave parameters for the proposed method was improved with errors of about 2 cm and 0.2 s for mean wave height and mean period, respectively, verifying the validity of the proposed method.

Aimed at mapping time variations in the Earth’s gravity field, the Gravity Recovery and Climate Experiment (GRACE) satellite mission is applicable to access terrestrial water storage (TWS), which mainly includes groundwater, soil moisture (SM), and snow. In this study, SM and accumulated snow water equivalent (SWE) are simulated by the Global Land Data Assimilation System (GLDAS) land surface models (LSMs) and then used to isolate groundwater anomalies from GRACE-derived TWS in Pennsylvania and New York States of the Mid-Atlantic region of the United States. The monitoring well water-level records from the U.S. Geological Survey Ground-Water Climate Response Network from January 2005 to December 2011 are used for validation. The groundwater results from different combinations of GRACE products (from three institutions, CSR, GFZ and JPL) and GLDAS LSMs (CLM, NOAH and VIC) are compared and evaluated with in-situ measurements. The intercomparison analysis shows that the solution obtained through removing averaged simulated SM and SWE of the three LSMs from the averaged GRACE-derived TWS of the three centers would be the most robust to reduce the noises, and increase the confidence consequently. Although discrepancy exists, the GRACE-GLDAS estimated groundwater variations generally agree with in-situ observations. For monthly scales, their correlation coefficient reaches 0.70 at 95% confidence level with the RMSE of the differences of 2.6 cm. Two-tailed Mann-Kendall trend test results show that there is no significant groundwater gain or loss in this region over the study period. The GRACE time-variable field solutions and GLDAS simulations provide precise and reliable data sets in illustrating the regional groundwater storage variations, and the application will be meaningful and invaluable when applied to the data-poor regions.

The purpose of this study was to examine how different polarimetric parameters and an object-based approach influence the classification results of various land use/land cover types using fully polarimetric ALOS PALSAR data over coastal wetlands in Yancheng, China. To verify the efficiency of the proposed method, five other classifications (the Wishart supervised classification, the proposed method without polarimetric parameters, the proposed method without an object-based analysis, the proposed method without textural and geometric information and the proposed method using the nearest-neighbor classifier) were applied for comparison. The results indicated that some polarimetric parameters, such as Shannon entropy, Krogager_Kd, Alpha, HAAlpha_T11, VanZyl3_Vol, Derd, Barnes2_T33, polarization fraction, Barnes1_T33, Neuman_delta_mod and entropy, greatly improved the classification results. The shape index was a useful feature in distinguishing fish ponds and rivers. The distance to the sea can be regarded as an important factor in reducing the confusion between herbaceous wetland vegetation and grasslands. Furthermore, the decision tree algorithm increased the overall accuracy by 6.8% compared with the nearest neighbor classifier. This research demonstrated that different polarimetric parameters and the object-based approach significantly improved the performance of land cover classification in coastal wetlands using ALOS PALSAR data.

Haiyang-2A (HY-2A) has been working in-flight for over seven years, and the accuracy of HY-2A calibration microwave radiometer (CMR) data is extremely important for the wet troposphere delay correction (WTC) in sea surface height (SSH) determination. We present a comprehensive evaluation of the HY-2A CMR observation using the numerical weather model (NWM) for all the data available period from October 2011 to February 2018, including the WTC and the precipitable water vapor (PWV). The ERA(ECMWF Re-Analysis)-Interim products from European Centre for Medium-Range Weather Forecasts (ECMWF) are used for the validation of HY-2A WTC and PWV products. In general, a global agreement of root-mean-square (RMS) of 2.3 cm in WTC and 3.6 mm in PWV are demonstrated between HY-2A observation and ERA-Interim products. Systematic biases are revealed where before 2014 there was a positive WTC/PWV bias and after that, a negative one. Spatially, HY-2A CMR products show a larger bias in polar regions compared with mid-latitude regions and tropical regions and agree better in the Antarctic than in the Arctic with NWM. Moreover, HY-2A CMR products have larger biases in the coastal area, which are all caused by the brightness temperature (TB) contamination from land or sea ice. Temporally, the WTC/PWV biases increase from October 2011 to March 2014 with a systematic bias over 1 cm in WTC and 2 mm in PWV, and the maximum RMS values of 4.62 cm in WTC and 7.61 mm in PWV occur in August 2013, which is because of the unsuitable retrieval coefficients and systematic TB measurements biases from 37 GHz band. After April 2014, the TB bias is corrected, HY-2A CMR products agree very well with NWM from April 2014 to May 2017 with the average RMS of 1.68 cm in WTC and 2.65 mm in PWV. However, since June 2017, TB measurements from the 18.7 GHz band become unstable, which led to the huge differences between HY-2A CMR products and the NWM with an average RMS of 2.62 cm in WTC and 4.33 mm in PWV. HY-2A CMR shows high accuracy when three bands work normally and further calibration for HY-2A CMR is in urgent need. Furtherly, 137 global coastal radiosonde stations were used to validate HY-2A CMR. The validation based on radiosonde data shows the same variation trend in time of HY-2A CMR compared to the results from ECMWF, which verifies the results from ECMWF.

Although there are already several real-time precise positioning service providers, unfortunately, not all users can use the correction information due to either cost of the service and limitation of their equipment or out of the service coverage. An alternative way is to enhance the accuracy of the predicted satellite clocks for precise real-time positioning. Based on the study of existing prediction models, an improved model combing the spectrum analysis (SA) and the generalized regression neural network (GRNN) model is proposed especially for BeiDou satellite navigation system (BDS)-2 satellites. The periodic terms and GRNN-related parameters including length and interval of sample data, as well as a smooth factor, are optimized satellite by satellite to consider satellite-specific characteristics for all the fourteen BDS-2 satellites. The improved model is validated by comparing the predicted clocks of existing models and the improved model with precisely estimated ones. The bias of the predicted clock is within ±0.5 ns over three hours and better than that of the other models and can be used for several real-time precise applications. The clock prediction is further evaluated by applying clock corrections to precise point positioning (PPP) in both static and kinematic mode for eight IGS (International GNSS Service) MGEX (Multi-GNSS Experiment) stations in the Asia-Pacific region. In the static PPP, the improved model is validated to be effective, and position accuracies of some IGS MGEX stations achieve more than 30.0% improvements on average for each component, which enables us to obtain sub-decimeter positioning. In the kinematic PPP, the improved model performs much better than the others in terms of both the convergence time and the position accuracy. The convergence time can be shortened from 1−2 h to 0.5−1 h, while the position accuracy is enhanced by 15.4%, 21.6% and 19.3% on average in east, north and up component, respectively.

To keep the global navigation satellite system functional during extreme conditions, it is a trend to employ autonomous navigation technology with inter-satellite link. As in the newly built BeiDou system (BDS-3) equipped with Ka-band inter-satellite links, every individual satellite has the ability of communicating and measuring distances among each other. The system also has less dependence on the ground stations and improved navigation performance. Because of the huge amount of measurement data, the centralized data processing algorithm for orbit determination is suggested to be replaced by a distributed one in which each satellite in the constellation is required to finish a partial computation task. In the present paper, the balanced extended Kalman filter algorithm for distributed orbit determination is proposed and compared with the whole-constellation centralized extended Kalman filter, the iterative cascade extended Kalman filter, and the increasing measurement covariance extended Kalman filter. The proposed method demands a lower computation power; however, it yields results with a relatively good accuracy.

The measurement of total basin discharge along coastal regions is necessary for understanding the hydrological and oceanographic issues related to the water and energy cycles. However, only the observed streamflow (gauge-based observation) is used to estimate the total fluxes from the river basin to the ocean, neglecting the portion of discharge that infiltrates to underground and directly discharges into the ocean. Hence, the aim of this study is to assess the total discharge of the Yangtze River (Chang Jiang) basin. In this study, we explore the potential response of total discharge to changes in precipitation (from the Tropical Rainfall Measuring Mission—TRMM), evaporation (from four versions of the Global Land Data Assimilation—GLDAS, namely, CLM, Mosaic, Noah and VIC), and water-storage changes (from the Gravity Recovery and Climate Experiment—GRACE) by using the terrestrial water budget method. This method has been validated by comparison with the observed streamflow, and shows an agreement with a root mean square error (RMSE) of 14.30 mm/month for GRACE-based discharge and 20.98 mm/month for that derived from precipitation minus evaporation (P − E). This improvement of approximately 32% indicates that monthly terrestrial water-storage changes, as estimated by GRACE, cannot be considered negligible over Yangtze basin. The results for the proposed method are more accurate than the results previously reported in the literature.

In an airborne laser bathymetry system, the full-waveform echo signal is usually recorded by discrete sampling. The accuracy of signal recognition and the amount of effective information that can be extracted by conventional methods are limited. To improve the validity and reliability of airborne laser bathymetry data and to extract more information to better understand the water reflection characteristics, we select the effective portion of the original waveform for further research, suppress random noise, and decompose the selected portion progressively using the half-wavelength Gaussian function with the time sequence of the received echo signals. After parameter optimization, a reasonable and effective reflection component selection mechanism is established to obtain accurate parameters for the reflected components. The processing strategy proposed in this paper reduces the problems of unreasonable decomposition and the reflected pulse peak-position shift caused by echo waveform superposition and offers good precision for waveform decomposition and peak detection. In another experiment, the regional processing result shows an obvious improvement in the shallow water area, and the bottom point cloud is as accurate as the intelligent waveform digitizer (IWD), a subsystem of airborne laser terrain mapping (ALTM). These findings confirm that the proposed method has high potential for application.

Brazil has recently experienced one of its worst droughts in the last 80 years, with wide-ranging consequences for water supply restrictions, energy rationing, and agricultural losses. Northeast and Southeast Brazil, which share the São Francisco River basin (SFRB), have experienced serious precipitation reduction since 2011. We used terrestrial water-storage (TWS) fields, inverted from the Gravity Recovery and Climate Experiment (GRACE) mission measurements, to assess and quantify the ongoing drought over the SFRB. We found a water loss rate of 3.30 km3/year over the time-span of April 2002 to March 2015. In addition, the TWS drought index (TWSDI) showed the extension of the recent drought that has jeopardized the SFRB since January 2012, and which reached its maximum in July 2015 (the end of TWS time series). In this sense there seems to be a linkage between the TWSDI (wetness/dryness) and the El Niño Southern Oscillation (ENSO), in terms of the wavelet coherence, at the semi-annual and biennial bands, suggesting a relationship between the two. While acknowledging that further investigation is needed, we believe that our findings should contribute to the water management policies by quantifying the impact of this drought event over the SFRB.