Many freely available global or quasi-global digital elevation model (DEM) datasets, including Advanced Land Observing Satellite (ALOS) World 3 Dimensions (3D) 30 m DEM (AW3D30 DEM), Advanced Spaceborne Thermal Emission and Reflection Radiometer DEM (ASTER DEM), Shuttle Radar Topography Mission DEM (SRTM DEM), Multiple-Error-Removed-Improved-Terrain DEM (MERIT DEM), and TerraSAR-X add-on for Digital Elevation Measurement (TanDEM-X) DEM (TanDEM-X DEM), are extremely useful products for many applications, so it is necessary to make a reasonable analysis of the quality of these DEMs. The quality of these DEMs is affected by both horizontal and vertical errors. However, most related researches have paid little attention to the effects of horizontal errors on the vertical accuracy of DEMs. Herein, after analysing the horizontal errors caused in the data acquisition process from optical stereo pairs and interferometry, experiments were proposed to assess the horizontal errors in DEMs. Then, we used the high accuracy digital surface model (DSM) of the Changsha area generated from the ZiYuan-3 triplet stereos to investigate the impact of horizontal errors on the accuracy of the five freely available DEMs. The subpixel level horizontal errors of the five DEMs were calculated, showing that the TanDEM-X DEM has systematic offsets and the other four DEMs have strip-like geometric errors. All the DEMs, except ASTER DEM, attained an accuracy increase of approximately 10% after the horizontal errors were removed. In mountainous areas, correcting the horizontal errors could eliminate the elevation errors caused by the imaging geometry of the optical camera and radar system. Generally, AW3D30 DEM has the best performance in terms of overall elevation accuracy and geometric accuracy after eliminating horizontal errors, and so it can have wide-ranging applications. These findings demonstrate the importance of removing horizontal errors to improve the elevation accuracy in practical applications using these global freely available DEMs.

Geolocation accuracy is a critical issue for remote sensing applications. To achieve subpixel accuracy, geolocation errors need to be systematically identified and corrected. In this study, we propose a geometric sensor model for FengYun-3D (FY-3D) MERSI-II, a second-generation visible (VIS)/infrared (IR) spectroradiometer, to generate the geolocation lookup table (GLT). The geometric sensor model retrieves the imaging rays from the focal plane to the K-mirrors, 45° scanning mirrors, the platform, and the earth’s surface. After refining the attitude errors with ground control points (GCPs), the rigorous sensor model can achieve subpixel geolocation accuracy. However, significant systematic geolocation errors were identified from the residuals, especially for the area with large view angles. To study the errors of MERSI-II, we proposed a homogenous coordinate in the focal plane. As proven by both theory and experiments, the attitudes were adjusted to a wrong value and introduced systematic errors when there were principal point errors. The pitch angle error of K-mirrors caused the oscillation in the flight direction. The principal distance error introduced line coordinate-related error in the flight direction. Meanwhile, the initial phase angle error between the K-mirror and 45° scanning mirrors caused the line coordinate-related errors in the scanning direction. After correcting all the above-mentioned errors, the systematic geolocation errors of MERSI-II were removed. With 23 independent datasets, the root mean square errors (RMSEs) of 250 m bands were approximately 0.4 pixels, 100 m at nadir.

Analysis ready data (ARD) has recently become a popular standard for medium-resolution satellite images. The most representative datasets, namely Sentinel-2 Level-2A products and Landsat Collection 2 Level-2 Science Products, have met ARD standards, with public access. The Chinese Gaofen (GF) series Level-1A wide field of view (WFV) product, which has a similar ground sampling distance (GSD) to Sentinel-2 Level-2A products, is open to the public for its scenes and rational function model (RFM). However, the lower geometric processing accuracy of WFV products of approximately 3-pixel geolocation deviation restricts their wide application and further development towards ARD. The causes of low accuracy are twofold, namely the impact of calibration errors and the inaccuracy of the exterior orientation parameters. In terms of improving the accuracy of RFM, bundle adjustment and the bias compensation model (BCM) are currently the most widely accepted methods. However, existing approaches do not account for the imaging characteristics of WFV scenes, which are only for narrow field-of-view scenes and do not help with nonlinear internal distortions. To address the shortcomings of these methods, a joint orientation method for WFV cameras is proposed in this study. Owing to the high level of geometric accuracy of Sentinel-2 Level-1C reference scenes, this study analyzed the expression of WFV camera attitude errors on the image side. A polynomial exterior orientation model suitable for WFV cameras is also provided. We performed a refined calibration of the nonlinear internal distortions using multi-temporal GF-6 Level-1A WFV images, because of the additional error introduced by the cross-track inconsistency of the Sentinel-2 reference data. The method developed in this study has been experimentally verified to achieve satisfactory geometric positioning accuracy with GF-6 WFV products from 3-pixel to 0.3-pixel (5 m). This study allows optimization of the geometric performance of GF-6 Level-1A WFV products to the level of Sentinel-2 Level-1C products, which is of considerable importance in developing GF WFV images to ARD.

Due to the difference in surface reflectivity, the laser measurement waveform data recorded in full waveform have a saturation phenomenon. When the signal is saturated, the echo waveform produces peak clipping and pulse spreading, which seriously restrict the accuracy of laser measurement results and the usability of data. Therefore, we conducted a ranging investigation on the “peak clipping” phenomenon of the saturated waveform and found a nonlinear time delay in the range, which is between the two extreme cases of saturated “dead time” and Gaussian fitting peak time as pulse signal reception time. Subsequently, based on the consistent relationship between the geometric characteristics of the high- and low-gain channels of the space-borne laser altimeter, we constructed a laser waveform saturation compensation model, namely, the laser pulse flight time delay compensation and the laser waveform peak intensity compensation, and carried out the data saturation compensation and validation with the dual-channel measurement data from the GaoFen-7 (GF-7) satellite. The experimental results showed that the saturation compensation model (SCM) proposed in this paper could restore the features of the saturated waveform signal and effectively improve the accuracy of the laser ranging. The accuracy of the laser waveform fitting result after saturation compensation improved from 0.7 ns (0.11 m) to 0.14 ns (0.02 m), which greatly improved the usability of the saturated laser measurement waveform data.

The radiometric properties of the lunar nearside have been used as a function of the observation geometry to generate disk-equivalent irradiance and as a reference for satellite measurements. However, lunar libration and non-Lambertian surface are among the factors that limit the accuracy of lunar irradiance models. Radiance knowledge of specific parts of the Moon also provides calibration standards. The regions can be identified in high-resolution lunar views from Moon orbiters and Earth-orbiting spacecraft, and very little work has been done to place the two-dimensional images from the latter under a designated frame. The lunar phase modifies grayscale or texture information, and image-matching algorithms are limited. The panchromatic and multispectral sensor (PMS) on the JiLin-1 GuangPu-02 (JL1GP02) operating in low Earth orbit can obtain spatially resolved images of the Moon by continuous sampling relying on maneuvers. In this work, we propose a geometric sensor model for PMS, construct geographic (or rather selenographic) positions in grid format, and then combine it with global lunar reference map to create simulated images, which are used to identify tie points with Wide Angle Camera (WAC) orthophoto map with similar geometry structure to characterize geometric errors. We also assume imaging as area charge-coupled device (CCD) for simplification and introduce two methods of instrument pointing correction based on image space residuals. The quality of the results is finally discussed. The results can be exploited to determine the geographic location of the observed targets and subdivision regions and to facilitate studies of the photometric properties of the targets in selected domains.

At present, some mapping satellites, such as GaoFen-7 and ZiYuan3-03, are equipped with both optical stereo cameras and laser altimeters that can synchronously obtain stereo images and sparse ground laser altimetry points (LAPs). To effectively improve the geometric accuracy of these satellite stereo images, this study proposed an integrated processing method for LAPs and stereo images derived from the same satellite. This method makes full use of the advantages of synchronously obtaining stereo images and LAPs, and designs measurement technology for accurate pixel coordinates of LAPs in stereo images, which works toward solving a technical difficulty that has restricted their integration to achieve higher accuracy. The method also constructs a combined block adjustment model of LAPs and stereo images. We selected 70 GaoFen-7 stereo images and 463 GaoFen-7 LAPs from Hebei Province, China, and 12 ZiYuan3-03 stereo images and 81 ZiYuan3-03 LAPs from Heilongjiang Province, China, to conduct integrated processing experiments. The vertical accuracy of the GaoFen-7 images in all types of terrain were improved substantially and reached the accuracy requirements of 1:10,000 (even 1:5000) scale mapping in China. The vertical accuracy of the ZiYuan3-03 images in various terrain areas were also improved markedly, satisfying the accuracy requirement of 1:50,000 scale mapping. These experimental results indicate that the working mode of synchronously obtaining LAPs and stereo images using the same satellite is advanced, and the proposed method is correct and effective.