Spatial linear features are often represented as a series of line segments joined by measured endpoints in surveying and geographic information science. There are not only the measuring errors of the endpoints but also the modeling errors between the line segments and the actual geographical features. This paper presents a Brownian bridge error model for line segments combining both the modeling and measuring errors. First, the Brownian bridge is used to establish the position distribution of the actual geographic feature represented by the line segment. Second, an error propagation model with the constraints of the measuring error distribution of the endpoints is proposed. Third, a comprehensive error band of the line segment is constructed, wherein both the modeling and measuring errors are contained. The proposed error model can be used to evaluate line segments’ overall accuracy and trustability influenced by modeling and measuring errors, and provides a comprehensive quality indicator for the geospatial data.

With the continuous improvement of the performance and the increasing variety of optical mapping and remote sensing satellites, they have become an important support for obtaining global accurate surveying and mapping remote sensing information. At present, optical mapping and remote sensing satellites already have sub-meter spatial resolution capabilities, but there is a serious lag problem in mapping and remote sensing information services. It is urgent to develop intelligent mapping and remote sensing satellites to promote the transformation and upgrading to real-time intelligent services. Firstly, based on the three imaging systems of the optical mapping and remote sensing satellites and their realization methods and application characteristics, this paper analyzes the applicable system of the intelligent mapping and remote sensing satellites. Further, according to the application requirements of real-time, intelligence, and popularization, puts forward the design concept of integrated intelligent remote sensing satellite integrating communication, navigation, and remote sensing and focuses on the service mode and integrated function composition of intelligent remote sensing satellite. Then expounds on the performance and characteristics of the Luojia-3 01 satellite, a new generation of intelligent surveying and mapping remote sensing scientific test satellite. And finally summarizes and prospects the development and mission of intelligent mapping remote sensing satellites. Luojia-3 01 satellite integrates remote sensing and communication functions. It explores an efficient and intelligent service mode of mapping and remote sensing information from data acquisition to the application terminal and provides a real service verification platform for on-orbit processing and real-time transmission of remote sensing data based on space-ground internet, which is of great significance to the construction of China’s spatial information network.

In the construction and maintenance of particle accelerators, all the accelerator elements should be installed in the same coordinate system, only in this way could the devices in the actual world be consistent with the design drawings. However, with the occurrence of the movements of the reinforced concrete cover plates at short notice or building deformations in the long term, the control points upon the engineering structure will be displaced, and the fitness between the subnetwork and the global control network may be irresponsible. Therefore, it is necessary to evaluate the deformations of the 3D alignment control network. Different from the extant investigations, in this paper, to characterize the deformations of the control network, all of the congruent models between the points measured in different epochs have been identified, and the congruence model with the most control points is considered as the primary or fundamental model, the remaining models are recognized as the additional ones. Furthermore, the discrepancies between the primary S-transformation parameters and the additional S-transformation parameters can reflect the relative movements of the additional congruence models. Both the iterative GCT method and the iterative combinatorial theory are proposed to detect multiple congruence models in the control network. Considering the actual work of the alignment, it is essential to identify the competitive models in the monitoring network, which can provide us a hint that, even the fitness between the subnetwork and the global control network is good, there are still deformations which may be ignored. The numerical experiments show that the suggested approaches can describe the deformation of the 3D alignment control network roundly.

With the development of Global Navigation Satellite Systems (GNSS), geodetic GNSS receivers have been utilized to monitor sea levels using GNSS-Interferometry Reflectometry (GNSS-IR) technology. The multi-mode, multi-frequency signals of GPS, GLONASS, Galileo, and Beidou can be used for GNSS-IR sea level retrieval, but combining these retrievals remains problematic. To address this issue, a GNSS-IR sea level retrieval combination system has been developed, which begins by analyzing error sources in GNSS-IR sea level retrieval and establishing and solving the GNSS-IR retrieval equation. This paper focuses on two key points: time window selection and equation stability. The stability of the retrieval combination equations is determined by the condition number of the coefficient matrix within the time window. The impact of ill-conditioned coefficient matrices on the retrieval results is demonstrated using an extreme case of SNR data with only ascending or descending trajectories. After determining the time window and removing ill-conditioned equations, the multi-mode, multi-frequency GNSS-IR retrieval is performed. Results from three International GNSS Service (IGS) stations show that the combination method produces high-precision, high-resolution, and high-reliability sea level retrieval combination sequences.

Total Electron Content (TEC) and electron density enhancement were observed on the day before 17 March 2015 great storm in the China Region. Observations from ground- and space-based instruments are used to investigate the temporal and spatial evolution of the pre-storm enhancement. TEC enhancement was observed from 24°N to 30°N after 10:00 UT at 105°E, 110°E and 115°E longitudes on March 16. The maximum magnitude of TEC enhancement was more than 10 TECU and the maximal relative TEC enhancement exceeded 30%. Compared with geomagnetic quiet days, the electron density of Equatorial Ionization Anomaly (EIA) northern peak from Swarm A/C satellites on March 16 was larger and at higher latitudes. NmF2 enhanced during 11:30—21:00 UT at Shaoyang Station and increased by 200% at ~16:00 UT. However, TEC and electron density enhancement were not accompanied by a significant change of hmF2. Most research has excluded some potential mechanisms as the main driving factors for storm-time density enhancements by establishing observational constraints. In this paper, we observed pre-storm enhancement in electron density at different altitudes and Equatorial Electrojet (EEJ) strength results derived from ground magnetometers observations suggest an enhanced eastward electric field from the E region probably played a significant role in this event.

The exploration of building detection plays an important role in urban planning, smart city and military. Aiming at the problem of high overlapping ratio of detection frames for dense building detection in high resolution remote sensing images, we present an effective YOLOv3 framework, corner regression-based YOLOv3 (Correg-YOLOv3), to localize dense building accurately. This improved YOLOv3 algorithm establishes a vertex regression mechanism and an additional loss item about building vertex offsets relative to the center point of bounding box. By extending output dimensions, the trained model is able to output the rectangular bounding boxes and the building vertices meanwhile. Finally, we evaluate the performance of the Correg-YOLOv3 on our self-produced data set and provide a comparative analysis qualitatively and quantitatively. The experimental results achieve high performance in precision (96.45%), recall rate (95.75%), F1 score (96.10%) and average precision (98.05%), which were 2.73%, 5.4%, 4.1% and 4.73% higher than that of YOLOv3. Therefore, our proposed algorithm effectively tackles the problem of dense building detection in high resolution images.

GF-14 satellite is a new generation of sub-meter stereo surveying and mapping satellite in China, carrying dual-line array stereo mapping cameras to achieve 1:10000 scale topographic mapping without Ground Control Points (GCPs). In fact, space-based high-precision mapping without GCPs is a challenging task that depends on the close cooperation of several payloads and links, of which on-orbit geometric calibration is one of the most critical links. In this paper, the on-orbit geometric calibration of the dual-line array cameras of GF-14 satellite was performed using the control points collected in the high-precision digital calibration field, and the calibration parameters of the dual-line array cameras were solved as a whole by alternate iterations of forward and backward intersection. On this basis, the location accuracy of the stereo images using the calibration parameters was preliminarily evaluated by using several test fields around the world. The evaluation result shows that the direct forward intersection accuracy of GF-14 satellite images without GCPs after on-orbit geometric calibration reaches 2.34 meters (RMS) in plane and 1.97 meters (RMS) in elevation.

Coastal subsidence monitoring typically employs Global Navigation Satellite System (GNSS) positioning technology. This method provides information only about subsidence below the station base. Sediments in coastal areas tend to accumulate quickly, and subsidence can change significantly due to compaction and alluvium. Therefore, monitoring subsidence above the base is essential to obtain overall coastal subsidence. A new technology called GNSS-Interferometric Reflectometry (GNSS-IR) has been recently developed, which can utilize multipath effects to monitor reflector height. Since the base of the GNSS station is deep and the base length remains constant, the height changes measured by the GNSS-IR technology can reflect subsidence above the base. Accordingly, this paper employs GNSS-IR technology to measure subsidence changes above the base. Additionally, GNSS positioning technology is used to obtain subsidence changes below the base, and the overall subsidence change is then calculated using both GNSS-IR and GNSS positioning technology. The Mississippi River Delta, known for its significant sediment thickness, was selected as the study area, and data from FSHS, GRIS, and MSIN stations was analyzed. The results demonstrate that GNSS-IR can be used to measure the subsidence rate above the base, and the corrected overall subsidence rate is equivalent to the relative sea level rise rate.

At present, GNSS-Acoustic (GNSS-A) combined technology is widely used in positioning for seafloor geodetic stations. Based on Sound Velocity Profiles (SVPs) data, the equal gradient acoustic ray-tracing method is applied in high-precision position inversion. However, because of the discreteness of the SVPs used in the forementioned method, it ignores the continuous variation of sound velocity structure in time domain, which worsens the positioning accuracy. In this study, the time-domain variation of Sound Speed Structure (SSS) has been considered, and the cubic B-spline function is applied to characterize the perturbed sound velocity. Based on the ray-tracing theory, an inversion model of “stepwise iteration & progressive corrections” for both positioning and sound speed information is proposed, which conducts the gradual correction of seafloor geodetic station coordinates and disturbed sound velocity. The practical data was used to test the effectiveness of our method. The results show that the Root Mean Square (RMS) errors of the residual values of the traditional methods without sound velocity correction, based on quadratic polynomial correction and based on cubic B-spline function correction are 1.43ms, 0.44ms and 0.21ms, respectively. The inversion model with sound velocity correction can effectively eliminate the systematic error caused by the change of SSS, and significantly improve the positioning accuracy of the seafloor geodetic stations.