The Gao Fen 7 (GF‐7) satellite is China's first submeter, high‐resolution Earth observation and remote sensing satellite for natural resource monitoring, land surveying, and other industrial applications in China. The GF‐7 laser altimeter system is the successor of the ZiYuan3‐02 (ZY3‐02 satellite) laser altimeter. The key objective of the GF‐7 laser altimetry system is to provide high‐precision ground elevation control points that assist in optical imaging to achieve 1:10000 mapping in China. This paper introduces the GF‐7 laser altimeter system payload specifications, mission objectives, in‐orbit calibration plan, data products, and service policy. In the future, the GF‐7 laser altimeter system will also serve multidisciplinary and professional applications through its precise elevation measurement capabilities. In addition, it will play a vital role in Earth observation, climate change monitoring, and environmental protection.

The GaoFen-7 (GF-7) satellite, which was launched on November 3, 2019, is China's first civilian submeter stereo mapping satellite. The satellite is equipped with the first laser altimeter officially in China for earth observation. Except for the laser altimeter, the GF-7 spaceborne laser altimeter system also includes two laser footprint cameras and a laser optical axis surveillance camera. The laser altimeter system is designed and used to assist improving the elevation accuracy without Ground Control Points (GCPs) of the two line-array stereo mapping cameras. This paper details the design of the GF-7 spaceborne laser altimeter system, its ranging performance in the laboratory and its data processing method. The type of data products is also released. These data will play a vital role in the application of geography, glaciology, forestry and other industries.

The second-generation spaceborne LiDAR-Ice, Cloud and Land Elevation Satellite-2 (ICESat-2) carries the Advanced Topographic Laser Altimeter System (ATLAS), which can penetrate a certain depth of water, and is one of the important means to obtain the water depth information of nearshore water. However, due to the influence of the atmospheric environment, water quality and color, the system itself and other factors, the photon point cloud introduces survey noise, which restricts the survey accuracy and reliability of nearshore water depth. Therefore, in this study, we presented a photon denoising algorithm for layered processing of submarine surface. Firstly, rough denoising of the original photon data was completed by smoothing filtering. Then, elevation histogram statistics were carried out on the photon data, two peaks of the histogram were fitted by a double Gaussian function, and the intersection of two curves was then taken to separate the water surface and underwater photons. The surface photons were denoised by the DBSCAN clustering algorithm. Then according to the distribution characteristics of underwater signal photons, a single-photon point cloud filtering bathymetric method was proposed based on improved local distance statistics (LDSBM), which was used for fine denoising of underwater point cloud data. Finally, the Gaussian function was used to fit the frequency histogram, and the signal photons were screened to extract the water depth information. In this study, 13 groups of the ATL03 dataset from the Xisha Islands, the St. Thomas and the Acklins Island were used for denoising. The denoising results were compared with the signal photons manually marked and the signal photons extracted by the official built-in method (OM). The experimental results showed that, compared with the official method results of ATL03, the LDSBM had a higher F value (comprehensive evaluation index), with an average of more than 96.70%. In conclusion, the proposed underwater single-photon point cloud filtering bathymetric method was superior to the traditional algorithm and could recover terrain information accurately.

The pointing bias of the laser altimeter would change because of the launch vibration, variations in the space environment or other factors, which is one of the most important factors affecting the geometric accuracy of a laser altimeter. To calibrate pointing bias and improve the measuring accuracy of spaceborne laser altimeter, this paper proposed an in-orbit calibration method based on terrain matching with pyramid-search for this spaceborne laser altimeter. First, we used published digital terrain data as a reference to match with stripes of a point cloud obtained by the geolocation model of the laser altimeter, and then the optimal matching terrain could be determined by a pyramid search. Finally, the pointing bias of the laser altimeter was calibrated. The proposed method was applied in calibration experiment of ZY3-02 laser altimeter. Several tracks of ZY3-02 laser data and advanced Land Observation Satellite Digital Surface Model (AW3D30) with a 30-m grid size were deployed for calibration and validation. After calibration, the systematic error was effectively eliminated. The elevation accuracy of the laser altimeter was improved from more than 100 to 3 m approximately, and the algorithm efficiency with pyramid search was improved by 10 times at least. The experimental result demonstrates that the proposed method is an effective means to calibrate the current spaceborne laser altimeters.

The two-beam GaoFen-7 (GF-7) laser altimeter is China's first formal spaceborne laser altimeter system for Earth observations. In this article, a calibration method based on simulation waveform matching is proposed to correct the laser pointing error now that the satellite is in orbit. In the method, the optimal position of the laser footprint is searched using simulated and actual waveforms. Then, the laser pointing is calibrated based on the laser footprint optimal position. In this paper, after calibration of the GF-7 laser pointing, infrared detectors are used to capture laser footprints for accuracy verification. The results show that the GF-7 laser pointing accuracy is greatly improved by the method; the laser pointing accuracy of beam 1 is approximately 5.4 arcsec, and that of beam 2 is approximately 5.7 arcsec. Subsequently, two laser footprints are selected for GF-7 laser calibration in the Helan Mountains, China, and AW3D30 digital surface model (DSM) and GPS/RTK data are used to verify the laser elevation measurement accuracy (EMA). The results show that the EMA of the GF-7 laser is significantly improved after calibration. Over flat terrain, the EMA of the GF-7 laser is improved by 10 times, from 3.74 ± 0.55 m to 0.35 ± 0.50 m, verifying the effectiveness of the proposed method.

On-orbit geometric calibration of satellite-borne laser based on infrared detectors is the key tool to ensure the elevation measurement accuracy, and the accuracy of on-orbit geometric calibration is directly determined by laser spots captured by detectors. Mathematical methods, such as gray-scale barycenter, are widely applied for centroid extraction of spots captured by infrared detectors and completely depend on the energy values at points measured by detectors, which have low precision and are greatly affected by the consistency of the detectors and other factors at present. Based on the above question, considering the consistency between the real laser footprint shape and spot captured by detectors, a centroid extraction method of laser spots captured by infrared detectors combining laser footprint images and detector observation data is proposed for making up this defect to some extent. First, the self-adaptive “two-step method” is used to denoise footprint images hierarchically to obtain the real shape of footprints for constraining the spots captured by detectors, and then the centroids of spots are extracted by using the energy-weighted barycenter method based on regional blocks. In the experiment, Gaofen-7 (GF-7) satellite is taken as the research object, and the proposed method, as well as the other six methods, are used for the centroid extraction of laser spots captured by detectors, the calculation of calibration parameters based on the single-beam and dual-beam laser calibration models, the positioning of laser footprints, and cross verification. According to the results, the plane accuracy of centroid extraction using the proposed method is as follows: 0.34 grids for Beam 1 and 0.33 grids for Beam 2. In addition, on flat terrain, the elevation accuracy of Beam 1 and Beam 2 in 2021 is 5.2 cm and 5.0 cm, respectively, 0.6 cm and 4.2 cm higher than those in the most accurate one among other methods; the elevation accuracy in 2020 is 23.3 cm and 7.1 cm, respectively, 7.7 cm and 2.7 cm higher than those in the most accurate one among other methods. On slopes and gentle slopes, the method proposed is also superior to other methods. Since the change of pointing angle caused by satellite jitter, atmosphere, etc., between different years, the accuracy drops when laser footprints of 2020 are located using the parameters of 2021. In summary, under different terrains and years, the results fully demonstrate the effectiveness and accuracy of the proposed method, which has more significant advantages than other traditional methods.