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Landslides are common geological hazards that take a heavy toll on human life and infrastructure every year, making it crucial to identify potential landslides. Landslide susceptibility (LS) mapping evaluates landslide proneness with the help of static data (e.g., topography, geology, and hydrology) that hardly change over decades; whereas the ground deformation map (GDM) produced by Interferometric Synthetic Aperture Radar (InSAR) works as a powerful reinforcement for determining landslide threats. The integration of the two could prompt the evaluation of the LS, yet the existing joint approaches exhibit certain defects. Therefore, a novel LS evaluation approach integrating the weight of evidence (WOE) model and InSAR results was proposed in this study. First, the GDM of the study area was obtained through InSAR process; meanwhile, an initial LS map was produced using the WOE model; subsequently, the LS map was coupled with GDM to develop a refined zoning and identification of landslide hazards. The proposed method was applied in Enshi, China, and achieved a higher AUC of 0.869. In addition, the accuracy of the susceptibility level of geological hazards found during field survey of the study area was improved, indicating that the LS map generated using the proposed method is more sensitive to landslide hazards and produces more accurate results.

This study designs a coherence-based multi-master-image stacking InSAR workflow as an efficient large-scale expressway stability monitoring method, which can improve the overall coherence and number of interferometric pairs via multi-master-image stacking and an average coherence threshold. The average annual ground deformation rate of Shanxi Province, China, was determined using Sentinel-1A data from 2017 to 2021 with a parallel processing strategy to improve efficiency. Compared to global navigation satellite system data, the InSAR results have a root mean square error of 2.90 mm/year. To evaluate the relationship between different factors and the occurrence of geohazards along the expressway network, we conducted a binary logistic regression analysis. The result shows that the deformation rate, annual precipitation, bedrock hardness, distance to stream, and traffic load are significantly related to the occurrence of geohazards along the expressway network in Shanxi Province, among which the deformation rate has the highest significant value, while the traffic load has the lowest, indicating that using InSAR alone to determine geohazards along expressway network is biased and it takes more than InSAR to conduct a comprehensive yet accurate expressway geohazard vulnerability evaluation. This study provides guidance for the road maintenance to ensure the safe operation of expressway systems.

After mastering the key technologies of manufacturing spaceborne Synthetic Aperture Radar (SAR), China’s SAR satellites have been successfully launched into space. As the only civil microwave satellite listed in the “National High-resolution Earth Observation System Major Project,” the Gaofen-3 (GF-3) 01 satellite is the first C-band multi-polarization SAR satellite with a resolution of 1 m. GF-3 series satellites stand out among civil SAR satellites worldwide because of their high resolution, wide swath, high geometric radiation quality, multiple imaging modes, and long operation time. Taking GF-3 series satellites as an example, this study introduces the development of China’s civil SAR satellites, as well as their processing strategies and applications. The success of the GF-3 series satellites shows that China’s SAR remote sensing technology has stepped into a new era of high-quality and high-precision Earth observations.

Due to the long synthetic aperture time, the large squint angle, and the large imaging width of medium Earth orbit (MEO) and high Earth orbit (HEO) SAR satellites, it is difficult to simulate the geometric positioning accuracy of MEO- and HEO-SAR satellites through the SAR image simulation methods. In this paper, one non-zero Doppler simulation method of geometric positioning accuracy was proposed without simulating SAR images. In order to simulate the geometric positioning accuracy under different errors and imaging observation conditions, the virtual simulation geometric model was constructed by the simulated satellite ephemeris and the coordinates of ground control points (GCPs). On this basis, one geometric accuracy simulation method based on mean value compensation was proposed to simulate the geometric positioning accuracy with GCPs. The experimental results showed that the impact of Doppler center frequency error and velocity error of MEO- and HEO-SAR satellites on geometric positioning accuracy is significant compared with the LEO-SAR satellites, and the maximum error they affect can reach about 1597 m. In addition, the geometric positioning accuracies of MEO- and HEO-SAR satellites with GCPs can be achieved to 1~10 m and 7~29 m, respectively.

Evapotranspiration (ET), as a key eco-hydrological parameter, plays an important role in understanding sustainable ecosystem development. Each plant category has a unique functional trait on transpiration and photosynthesis, with ET implying that water cycle and energy transformation is linked with vegetation type. Changes in surface vegetation directly alter biophysical land surface properties, hence affecting energy and ET transfer. With the rapid increase in land surface changes, there is a need to further understand and quantify the effects of vegetation change on ET, especially over the vulnerable water-cycle region in the arid and semi-arid regions of Northwest China. We adopted the GlobalLand30 land cover and MOD16A2 in 2010 and 2020 to investigate, discuss the spatio-temporal characteristics of annual and seasonal ET of cultivated land, grassland, and forests in Northwest China, and quantify the impact on vegetation changes with absolute and relative changes from different climatic subecoregions on ET. Our results show the following: (1) Forest ET was generally the highest at 688 mm, followed by cultivated land and grassland with 200–400 mm in arid climatic subecoregions. (2) Returning cultivated land to forests and cultivated land expansion potentially enhances ET by 90–110 mm/10a, with the relative rate of change increasing by 22.1% and 45.8%, respectively, away from unchanged vegetation within identical subecoregions. (3) The ET of most investigated areas gains the highest value in summer, followed by spring, autumn, and winter. This study provides reference for sustainable ecosystem development and the reasonable utilization of limited water resources in Northwest China.

Surface albedo, as a key parameter determining the partition of solar radiation at the Earth’s surface, has been developed into a satellite-based product from various Earth observation systems to serve numerous global or regional applications. Studies point out that apparent uncertainty can be introduced into albedo retrieval without consideration of surface anisotropy, which is a challenge to albedo estimation especially from observations with fewer angular samplings. Researchers have begun to introduce smoothed anisotropy prior knowledge into albedo estimation to improve the inversion efficiency, or for the scenario of observations with signal or poor angular sampling. Thus, it is necessary to further understand the potential influence of smoothed anisotropy features adopted in albedo estimation. We investigated the albedo variation induced by BRDF smoothing at both temporal and spatial scales over six typical landscapes in North America using MODIS standard anisotropy products with high quality BRDF inversed from multi-angle observations in 500 m and 5.6 km spatial resolutions. Components of selected typical landscapes were assessed with the confidence of the MCD12 land cover product and 30 m CDL (cropland data layer) classification maps followed by an evaluation of spatial heterogeneity in 30 m scale through the semi-variogram model. High quality BRDF of MODIS standard anisotropy products were smoothed in multi-temporal scales of 8 days, 16 days, and 32 days, and in multi-spatial scales from 500 m to 5.6 km. The induced relative and absolute albedo differences were estimated using the RossThick-LiSparseR model and BRDFs smoothed before and after spatiotemporal smoothing. Our results show that albedo estimated using BRDFs smoothed temporally from daily to monthly over each scenario exhibits relative differences of 11.3%, 12.5%, and 27.2% and detectable absolute differences of 0.025, 0.012, and 0.013, respectively, in MODIS near-infrared (0.7–5.0 µm), short-wave (0.3–5.0 µm), and visible (0.3–0.7 µm) broad bands. When BRDFs of investigated landscapes are smoothed from 500 m to 5.6 km, variations of estimated albedo can achieve up to 36.5%, 37.1%, and 94.7% on relative difference and absolute difference of 0.037, 0.024, and 0.018, respectively, in near-infrared (0.7–5.0 µm), short wave (0.3–5.0 µm), and visible (0.3–0.7 µm) broad bands. In addition, albedo differences caused by temporal smoothing show apparent seasonal characteristic that the differences are significantly higher in spring and summer than those in autumn and winter, while albedo differences induced by spatial smoothing exhibit a noticeable relationship with sill values of a fitted semi-variogram marked by a correlation coefficient of 0.8876. Both relative and absolute albedo differences induced by BRDF smoothing are demonstrated to be captured, thus, it is necessary to avoid the smoothing process in quantitative remote sensing communities, especially when immediate anisotropy retrievals are available at the required spatiotemporal scale.

YaoGan 13 (YG-13) represents the most advanced Chinese synthetic aperture radar satellite currently in use. This paper reports on experiments conducted to assess the slant-range accuracy of YG-13. Error sources in the YG-13 ranging system, such as atmospheric path delay and the internal electronic delay of the instrument were analysed. A real-time atmospheric delay correction model was established to consider both tropospheric and ionospheric delays. Six corner reflectors (CRs) were set up to ensure the accuracy of validation methods. Results showed that pixel location accuracies of up to 0.427 m standard deviation could be achieved. Furthermore, adjustment of the CRs can cause a marginal loss of ranging precision. After eliminating this error, the ranging accuracy was improved to 0.162 m. For YG-13, a single frequency GPS receiver is used and the orbital accuracy is the biggest factor restricting its slant-range accuracy. Results show that the YG-13 slant-range can achieve decimetre-level accuracy. YG-13 provides convenience in terms of access to control points and target locations that does not depend on ground equipment.

Usually, the rational polynomial coefficient (RPC) model of spaceborne synthetic aperture radar (SAR) is fitted by the original range Doppler (RD) model. However, the radar signal is affected by two-way atmospheric delay, which causes measurement error in the slant range term of the RD model. In this paper, two atmospheric delay correction methods are proposed for use in terrain-independent RPC fitting: single-scene SAR imaging with a unique atmospheric delay correction parameter (plan 1) and single-scene SAR imaging with spatially varying atmospheric delay correction parameters (plan 2). The feasibility of the two methods was verified by conducting fitting experiments and geometric positioning accuracy verification of the RPC model. The experiments for the GF-3 satellite were performed by using global meteorological data, a global digital elevation model, and ground control data from several regions in China. The experimental results show that it is feasible to use plan 1 or plan 2 to correct the atmospheric delay error, no matter whether in plain, mountainous, or plateau areas. Moreover, the geometric positioning accuracy of the RPC model after correcting the atmospheric delay was improved to better than 3 m. This is of great significance for the efficient and high-precision geometric processing of spaceborne SAR images.

In recent years, China has launched YaoGan-13 and GaoFen-3, high-resolution synthetic aperture radar (SAR) satellites that can acquire global high-resolution images. The absolute positioning accuracy of such satellites is important for mapping areas without ground reference points and for automated processing. However, satellites without geometric calibration have poor absolute positioning accuracy, greatly restricting their application (e.g., land resource surveys). Therefore, they cannot meet national demands for high-resolution SAR images with good geometric accuracy. Here, we propose a series of methods to improve the absolute positioning accuracy of YaoGan-13 and GaoFen-3, such as the multiple-image combined calibration strategy and geometric calibration model for a real continuously moving configuration, including consideration of atmospheric propagation delay. Using high-accuracy ground control data collected from different areas, the 2-D and 3-D absolute positioning accuracies of YaoGan-13 and GaoFen-3 were assessed after implementation of the improvement measures. Experimental results showed that, after calibration, the 2-D absolute positioning accuracy of YaoGan-13 and GaoFen-3 are improved from 43.86 m to 2.57 m and from 30.34 m to 4.29 m, respectively. In addition, the 3-D absolute positioning accuracies of YaoGan-13 in plane and elevation are 3.21 m and 2.22 m, respectively. Improving the absolute positioning accuracy of these satellites could broaden the scope of their potential applications in the future.

Geometric calibration is an important means of improving the absolute positioning accuracy of space-borne synthetic aperture radar imagery. The conventional calibration method is based on a calibration field, which is simple and convenient, but requires a great deal of manpower and material resources to obtain ground control points. Although newer cross-calibration methods do not require ground control points, calibration accuracy still depends on a periodically updated reference image. Accordingly, this study proposes a geometric self-calibration method based on the positioning consistency constraint of conjugate image points to provide rapid and accurate calibration of the YaoGan-13 satellite. The proposed method can accurately calibrate geometric parameters without requiring ground control points or high-precision reference images. To verify the absolute positioning accuracy obtained using the proposed self-calibration method, YaoGan-13 Stripmap images of multiple regions were collected and evaluated. The results indicate that high-accuracy absolute positioning can be achieved with a plane accuracy of 3.83 m or better for Stripmap data, without regarding elevation error. Compared to the conventional calibration method using high-accuracy control data, the difference between the two methods is only about 2.53 m, less than the 3-m resolution of the image, verifying the effectiveness of the proposed self-calibration method.

The Gaofen-3 (GF-3) satellite is the first C-band multi-polarization synthetic aperture radar (SAR) with the ability of high-accuracy mapping in China. However, the Ground Control Points (GCPs) are essential to ensure the accuracy of mapping for GF-3 SAR imagery at present. In this paper, we analyze the error sources that affect the geometric processing and propose a new block adjustment method without GCPs for GF-3 SAR imagery. Firstly, the geometric calibration of GF-3 image is carried out. Secondly, the rational polynomial coefficient (RPC) model is directly generated after the geometric calibration parameters compensation of each image. Finally, we solve the orientation parameters of the GF-3 images through DEM assisted planar block adjustment and conduct ortho-rectification. With two different imaging modes of GF-3 satellite, which include the QPSI and FS2, we carry out the block adjustment without GCPs. Experimental results of testing areas including Wuhan city and Hubei province in China show that the geometric mosaic accuracy and the absolute positioning accuracy of the orthophoto are better than one pixel, which has laid a good foundation for the application of GF-3 image in global high-accuracy mapping.

To better reduce image speckle noise while also maintaining edge information in synthetic aperture radar (SAR) images, we propose a novel anisotropic diffusion algorithm using weighted Euclidean distance (WEDAD). Presented here is a modified speckle reducing anisotropic diffusion (SRAD) method, which constructs a new edge detection operator using weighted Euclidean distances. The new edge detection operator can adaptively distinguish between homogenous and heterogeneous image regions, effectively generate anisotropic diffusion coefficients for each image pixel, and filter each pixel at different scales. Additionally, the effects of two different weighting methods (Gaussian weighting and non-linear weighting) of de-noising were analyzed. The effect of different adjustment coefficient settings on speckle suppression was also explored. A series of experiments were conducted using an added noise image, GF-3 SAR image, and YG-29 SAR image. The experimental results demonstrate that the proposed method can not only significantly suppress speckle, thus improving the visual effects, but also better preserve the edge information of images.

The Chinese Gaofen-3 (GF-3) mission was launched in August 2016, equipped with a full polarimetric synthetic aperture radar (SAR) sensor in the C-band, with a resolution of up to 1 m. The absolute positioning accuracy of GF-3 is of great importance, and in-orbit geometric calibration is a key technology for improving absolute positioning accuracy. Conventional geometric calibration is used to accurately calibrate the geometric calibration parameters of the image (internal delay and azimuth shifts) using high-precision ground control data, which are highly dependent on the control data of the calibration field, but it remains costly and labor-intensive to monitor changes in GF-3’s geometric calibration parameters. Based on the positioning consistency constraint of the conjugate points, this study presents a geometric cross-calibration method for the rapid and accurate calibration of GF-3. The proposed method can accurately calibrate geometric calibration parameters without using corner reflectors and high-precision digital elevation models, thus improving absolute positioning accuracy of the GF-3 image. GF-3 images from multiple regions were collected to verify the absolute positioning accuracy after cross-calibration. The results show that this method can achieve a calibration accuracy as high as that achieved by the conventional field calibration method.

The GaoFen-3 (GF-3) satellite is the first C-band multi-polarization synthetic aperture radar (SAR) imaging satellite with a resolution up to 1 m in China. It is also the only SAR satellite of the High-Resolution Earth Observation System designed for civilian use. There are 12 different imaging models to meet the needs of different industry users. However, to use SAR satellite images for related applications, they must possess high geometric accuracy. In order to verify the geometric accuracy achieved by the different modes of GF-3 images, we analyze the SAR geometric error source and perform geometric correction tests based on the RPC model with and without ground control points (GCPs) for five imaging modes. These include the spotlight (SL), ultra-fine strip (UFS), Fine Strip I (FSI), Full polarized Strip I (QPSI), and standard strip (SS) modes. Experimental results show that the check point residuals are large and consistent without GCPs, but the root mean square error of the independent checkpoints for the case of four corner control points is better than 1.5 pixels, achieving a similar level of geometric positioning accuracy to that of international satellites. We conclude that the GF-3 satellite can be used for high-accuracy geometric processing and related industry applications.

The GF-3 satellite is the first multi-polarization synthetic aperture radar (SAR) imaging satellite in China, which operates in the C band with a resolution of 1 m. Although the SAR satellite system was geometrically calibrated during the in-orbit commissioning phase, there are still some system errors that affect its geometric positioning accuracy. In this study, these errors are classified into three categories: fixed system error, time-varying system error, and random error. Using a multimode hybrid geometric calibration of spaceborne SAR, and considering the atmospheric propagation delay, all system errors can be effectively corrected through high-precision ground control points and global atmospheric reference data. The geometric calibration experiments and accuracy evaluation for the GF-3 satellite are performed using ground control data from several regions. The experimental results show that the residual system errors of the GF-3 SAR satellite have been effectively eliminated, and the geometric positioning accuracy can be better than 3 m.