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.

Inland lakes or reservoirs are the main surface water resources, related to people’s survival and social development. On-site water level data are critical for water resource management, while satellite laser and remote sensing data are a significant tool for long-term change monitoring. In this study, we took the Miyun Reservoir, the most important source of drinking water in Beijing, as the research area. We used Landsat images and the Ice, Cloud, and Land Elevation Satellite (ICESat-2) for small-scale water level change monitoring and inversion across unrecorded periods. First, we proposed a new two-step denoising method based on local statistics to denoise the ATL03 single photon data from 2018 to 2020, and extracted the effective elevation information of Miyun Reservoir. Second, based on Landsat images from 1984 to 2020, the MNDWI index was used to extract the water area and generated a percentage map of water occurrence. Finally, the water and land boundary elevation were selected from the effective photon elevation information according to the boundary position under each percentage of the water generation percentage graph, the area, and the water level elevation model (A–E model) was established, and the water level values of unrecorded periods were inverted. The denoising results showed that the denoising accuracy of all data is higher than 95%. The area of Miyun Reservoir has changed greatly in the past 37 years, especially in the northeast corner and northern region. The inverted water level elevation had a strong correlation with the measured value, the correlation coefficient reached 0.97, the root mean square error (RMSE) was 0.553 m, and the estimated water level value was highly consistent with the recorded value and fluctuated dramatically from 1984 to 2020. This method complements the traditional water level mapping method, provides a new idea for the monitoring of water level changes in lakes or reservoirs without field records, and also contributes to the timely and effective monitoring and management of global lake and reservoir water level and time changes.

Satellite platform microvibration is a common phenomenon in earth observation satellite orbits that directly affects the imaging quality and accuracy of surveying and mapping. With the continuous improvement in the spatial resolution, the influence of satellite platform microvibration on image geometric accuracy is becoming increasingly significant. High-precision microvibration detection and compensation are key technologies for eliminating image distortion and location deviation caused by satellite platform microvibration. In this paper, the microvibration detection methods of different satellite platforms are summarized, and the verification and analysis are performed on the data downloaded from the Resource-3 satellite (ZY-3) platform, to provide technical support for subsequent refined processing of satellite attitude.

The three-dimensional (3D) geographic locations of street furniture such as traffic signs comprise the basic content of 3D city construction, and such information is indispensable for periodic statistics for road management and maintenance. This paper presents a novel solution for acquiring 3D information on small traffic signs based on Mobile Mapping System (MMS) data. Firstly, a lightweight backbone network called VGG-L under an optimized Faster Region-based Convolutional Neural Network (R-CNN) detection framework is proposed for the detection of small traffic signs. An Urban Traffic Sign Detection (UTSD) dataset is created based on panoramic images obtained from test areas. Detection results from the UTSD dataset show that VGG-L outperforms other popular networks and achieves a mean average precision of 75.4%, which is 4.2—14.8% higher than those of VGG16, MobileNet, ResNet, and YOLOv3. Secondly, a novel depth-map-based 3D spatial geo-location method is proposed for obtaining the 3D geographic locations of the objects. Then, a center-based method is proposed to automatically extract the final 3D vector of the target. Experimental results illustrate that the proposed method performs 3D positioning and vectorization of the milestones, circular and triangular traffic signs, accurately and effectively, achieving greater than 86% recall and precision for the three types of targets in the test areas. The experiments demonstrate that the overall 3D information acquisition scheme is feasible and has great application potential.