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In this paper, a 1'×1' bathymetry model BAT_WHU2020 in the range of 75°S—70°N is constructed by using the latest version of the global gravity anomaly model derived from the multi-source satellite altimetry data and the shipboard depths. The accuracy of the model is analyzed and evaluated based on ship depths, existing models and multibeam soundings. The standard deviation of the difference between the proposed model and the ship depths in China Sea and its adjacent areas (104°E—160°E, 0°N—50°N) is about 70 m, which is equivalent to the accuracy of SIO V19.1 model, superior to ETOPO1, DTU10, GEBCO_08 model, and about 30% higher than the accuracy of BAT_VGG model published before, which shows that the method in this paper is reliable, and the data processing is accurate and the accuracy is high. The standard deviation of the differences between BAT_WHU2020 model and ship depths is about 50~65 m globally, and the ratio of the difference within ±200 m is greater than 95%. It is showed that the accuracy of BAT_WHU2020 model is equivalent to SIO V19.1, better than ETOPO1, DTU10, GEBCO_08 model, and improved about 27%~36% from the BAT_VGG model. Comparing to SIO V19.1 model, the standard deviation of the model differences is about 90~110 m, about 90% of the grid differences is within 200 m, and about 95% is within 300 m . Finally, the effects of crustal isostasy and high order terms in the Parker's formula on the accuracy of the results, the accuracy of the model compared to multibeam soundings, and the spatial resolution are discussed. It indicates that the spatial resolution of BAT_WHU2020 model is about 10~18 km, and the relative accuracy is about 5%~6% around the Mariana trench and Macquarie ridge.

The construction of the voxel model is an important part of computer ionospheric tomography (CIT) method. It will no doubt affect the accuracy of the CIT method. However, most existing researches focus on how to improve the image’s accuracy via inversion algorithm and few of them are concerned with the grid construction solution. This paper intends to improve accuracy by making some optimization on the voxel model. Some preliminary experiments were first carried out to explore the relationship between the accuracy of the image and its corresponding resolution. Then, based on the findings, a new CIT method, which is to improve the accuracy of the tomographic image of the interesting area at the price of reducing the resolution of the non-interesting area, was proposed. After that, some further experiments were taken to validate the new method. After comparing various accuracy indicators, such as root mean square error (RMSE), absolute mean error (MAE), 68% percentile, 95% percentile and stand deviation, the new method is showed to be better than the one that is not using the method proposed in this paper. According to our experiments, the new method is able to decrease RMSE/MAE of the tomographic image by 15% to 40%.

Aiming at the problem that the three-dimensional coordinate solution precision is influenced by the non-linear error, a method of combining multi-image forward intersection with single hidden layer BP neural network is proposed in this paper. The steps are: ①In order to obtain the initial value of the three dimensional coordinates with higher accuracy, the external parameters of the camera are optimized by constructing the Lagrange equation about the world coordinates under the constraint of known real world coordinates of the sample point. ②The single hidden layer BP neural network is trained by using the calculated 3D coordinate and the real 3D coordinate as input and output parameters, respectively. ③The initial three-dimensional coordinate is corrected by brought into the model. Experiments show that: ①In the environmental field of view of the test device, the proposed method outperforms the space intersection, the sparse bundle adjustment and the other classic neural network methods, the maximum deviation is 0.492 7 mm. ②Compared with other classic neural network methods, the network structure of this paper is 3-6-3, the structure is simple and the calculation efficiency is high.

In order to obtain the accurate SAR orthophoto over wide area, it is necessary to modify the geometric parameters for each of the SAR images. However, it is time consuming and laborious to correct each of the SAR images over wide area, which seriously decreased the efficiency of SAR image analysis. Therefore, a wide-area joint geometric calibration method is proposed in this paper. Firstly, the independent system-level calibration parameter is calculated using several SAR images on the basis of R-D model. Secondly, the influence of atmospheric delay component is removed from the system-level calibration parameters. Then, the optimal system-level calibration parameters are obtained based on the least squares adjustment principle. Finally, the other SAR images are corrected using the optimal system-level calibration parameters.In this paper, 32 scenes of GF-3 SAR images covering the central and eastern part of China are used for joint geometric calibration. The positioning error of the calibrated SAR images is less than 9 m. The experimental results show that the accuracy of geometric calibration for GF-3 SAR images can be improved by the proposed approach, and thus the effectiveness and feasibility of the proposed approach is demonstrated.

Multipath effect is related to the observational environment of stations, and cannot be eliminated or mitigated by differential algorithm. It is a major factor affecting accuracy and reliability in GPS signal processing. This paper proposes a method to mitigate the multipath effect—MHGM (Multi-point Hemispherical Grid Model). The method divides the hemisphere centered on each station into a grid, and estimates the multipath error at the station based on parametrization of the grid points, which can be applied to different kinds of hardware and software system of GPS data processing and observation environment. The experimental results in this paper show that, MHGM multipath error modeling based on data from observations made improvements in the mean RMS of double-differenced observation residuals averaging about 71.3%, an average increase of 26.9% compared with the traditional sidereal filtering method, the positioning results of 1.7 mm in level and 3.0 mm in altitude are obtained for static observation using real-time kinematic relative positioning mode. MHGM proposed in this paper also can used to assess orientation of error sources around the station, giving guidance which may assist in the physical elimination of sources of multipath error.

The definition and connotation of ubiquitous surveying and mapping are given at first. The differences from the traditional surveying and mapping are analyzed and presented. Since the Internet enables convenient interaction of information between people, the most significant progress of ubiquitous mapping in the Internet age is to meet diverse demands about relations between human beings and the society, as well as human beings and the environment, which means that human beings have become the mapping target. At the same time, ubiquitous mapping also focuses on the dynamic perception of environmental changes, the perception and cognition and corresponding services of the relationship between human beings and the environment. This paper indicates that the Internet cannot meet the demands of coordinated perception to physical world or the coordinated management neither the control of remote wide area due to the virtuality of its position and the too low network time standard. Therefore, the Internet and the Internet of Things shall advance towards the ubiquitous network with the capability of perceiving accurate space-time position. This paper discuss that the ubiquitous network is a perceptive network with space-time characteristics of “Any Time and Any Where” with the evolution of the Internet and the Internet of Things, and is evolving towards “Any Thing and Any Service” with the expansion of the intelligent demands. Currently, only the global satellite navigation system including Beidou, namely GNSS technology, is able to provide the ubiquitous network with space-time position perception and management and control capability in wide area and the global scale. Supported by ubiquitous network, ubiquitous mapping is developing with the characteristics of real-time and accurate space-time perception and control, to realize the perception, cognition, and regulation of land, sea and air network integration, indoor and outdoor integration, and the integration of human beings into physical world and virtual network world as well. As a result, the ubiquitous network will also be the key information infrastructure in the intelligent age. To understand the demands of ubiquitous mapping in the intelligent age, this paper combs through the definition of intelligence, wisdom and artificial intelligence from the perspective of natural intelligence and space-time position. The fundamental, key and coordinated role of ubiquitous mapping is discussed based on the four hot research directions of the new-generation artificial intelligence, including the cross-border integration, human-machine coordination, open collective intelligence and autonomous control, and its application to military, engineering, real-time and high-precision mapping as well as the earthquake early warning. At last, this paper sheds light on the vision of future application trend of ubiquitous mapping to new fields in the intelligent age, such as ubiquitous mapping of the virtual space, construction of digital twin virtual human, and “space and time sovereignty” to national security.

Based on multi-structures convolutional neural networks, this paper proposes an urban expansion cellular automata model (MSCNN-CA) considering the multi-scale neighborhood information to explore the problem of traditional cellular automata (CA) models merely accounting for a single pixel's factors while mining the urban development suitability. This paper took the main urban zone of Wuhan and Pudong New District of Shanghai as examples to simulate the urban expansion process of the two study areas from 2005 to 2015. The experimental results show that, compared with two traditional CA models (LR, ANN), the three single-structure CNN-CA models constructed in this paper have different degrees of improvement in Kappa coefficient, FoM coefficient, hit rate (h) and miss rate (m). In particular, the FoM coefficient is increased by 23.3%~29.4% in the main urban zone of Wuhan and 20.3%~28.5% in Pudong New District of Shanghai. In addition, compared with the three single-structure CNN-CA models, the MSCNN-CA model is also improved in various indicators. Such as, the FoM coefficient is increased by 0.8%~4.8% in the main urban zone of Wuhan and 2.8%~7.8% in Pudong New District of Shanghai. The two study areas' simulation results show that, compared with the traditional CA models, the urban expansion cellular automata model based on multi-structures convolutional neural network (MSCNN-CA) can effectively improve the accuracy of urban expansion simulation and more realistically reflect the evolution process of urban expansion. Besides, both the stability and the accuracy of the MSCNN-CA model are improved comparing with the single-structure convolutional neural network CA model.

In recent years, the time transfer method based on precise point positioning (PPP) shows a superior performance in terms of accuracy and coverage, which has made it become one of the most popular GNSS time transfer methods. As the timeliness of wide-area differential products improves, real-time PPP time transfer has been applied to the study of precise timing. On the basis of PPP time transfer, this paper introduces a wide-area precise timing(WPT) system based on BeiDou satellite navigation system (BDS). We applied real-time PPP time transfer, time-frequency control and hardware delay calibration technology in this system, which could ensure that users can obtain accurate, stable and traceable time in real time.The WPT system consisted of time service platform and terminal. The platform introduced high-accuracy time as the reference time of the system. At the same time, it provided real-time wide-area differential correction data. The terminal obtained the difference between the local clock and the system time based on PPP method. Then steering clock technology was used to realize time synchronization between terminal and system. In order to verify the real-time timing performance of the system, this paper conducted performance testing and evaluation in zero baseline, short baseline and wide-area environments. The experimental results show that the accuracy of time synchronization in the condition of zero baseline and short baseline is better than 0.5 ns. And timing accuracy in a single day is better than 1 ns in a single day, which provide a reference for the development of precision timing technology based on BeiDou system.

The traditional data acquisition, processing and application mode of satellite remote sensing system can't meet the application requirements of satellite remote sensing image popularization and real-time, and it is urgent to develop intelligent remote sensing satellite system to solve the problem of on-orbit processing and intelligent service of remote sensing image. This paper first expounded the development of intelligent remote sensing satellite, and introduced the characteristics of intelligent remote sensing satellite. Then the article gave a detailed introduction to the intelligent remote sensing satellite on-orbit processing architecture, service mode and key algorithms involved in on-orbit processing. Finally, the paper explored the service scenario and service mode of Luojia-3-01 satellite based on the design and development of Luojia-3-01,and prospected the development of intelligent remote sensing satellite under the background of 5G, 6G, and artificial intelligence era.

Satellite remote sensing has played a critical role in the quantitative retrieval of atmospheric PM2.5, which can be attributed to its advantages of wide spatiotemporal coverage and low cost. This paper reviews the progress of remote sensing mapping of atmospheric PM2.5. First, the atmospheric PM2.5 remote sensing retrieval methods are summarized, and the applicable conditions and limitations of the validation approaches for atmospheric PM2.5 remote sensing retrieval are analyzed. Second, this paper summarizes the bias correction of satellite retrieved PM2.5 synthesis product and the missing information reconstruction of satellite retrieved PM2.5. Finally, the prospective directions of remote sensing mapping of atmospheric PM2.5 are discussed.

City sensing and decision-making are the primary prerequisites for the realization of urban intelligence. In view of the current research progress, this paper reviewed the urban comprehensive sensing based on the integrated satellite-airborne-ground sensor web, the management and analysis of urban spatio-temporal big data, and the intelligent decision-making and focusing service for multi-level users. Meanwhile, this paper compares and analyzes the current urban spatio-temporal information platforms and their applications in smart cities. On this basis, it puts forward three challenges faced by the sensing and management of smart cities in the future, including the highly fused physical sensing and social sensing, highly intelligent city management and analytical capability, and highly confident decision based on cyber-physical system.

Spatial-temporal clustering algorithm is the basic research topic of geographic spatial-temporal big data mining. In view of the problem that traditional CFSFDP clustering algorithm cannot be applied in spatio-temporal data mining, this paper proposes a spatio-temporal constraint algorithm called ST-CFSFDP(spatial-temporal clustering by fast search and find of density peaks). ST-CFSFDP adds time constraint on the basis of CFSFDP algorithm, and modifies the calculation strategy of sample attribute value, which not only solves the problem of multi-density peak of single cluster set in the original algorithm, but also can distinguish and identify clusters at the same location and at different times. In this paper, the simulated spatiotemporal data and real indoor location trajectory data were used for the experiment, the results show that the ST-CFSFDP algorithm has a recognition rate of 82.4% at a time threshold of 90 s and a distance threshold of 5 m,which is better than the classic ST-DBCSAN, ST-OPTICS and ST-AGNES algorithm increased by 5.2%, 4.2%, and 7.6%, respectively.

In this paper the graphic generalization of roads is transformed into linear graphic simplification based on mesh model when the navigation data precision is decreased. A progressive collaborative graphic generalization method for roads in the navigation data is proposed based on the mesh model, which can ensure that the single road and road networks after generalization are similar to the original high-precision data in spatial directional relationship. In the process of data handling, the navigational requirements are applied to constrain the progressive graphic simplification of the road. Besides, characteristics of road shape and the spatial direction relationship at the intersection of roads are maintained while visualizations of the roads in navigation is taken into consideration. The algorithm proposed in this paper has been verified with navigation data in actual production, which proves the method is both effective and practical.

This paper takes autonomous driving and driverless as the research object, discusses and defines intelligent high-precision map. In this paper, intelligent high-precision map is considered as a key link of future travel, and a carrier of real-time perception of traffic resources in the entire space-time range, and the criterion for the operation and control of the whole process of the vehicle. As a new form of map, intelligent high-precision map has distinctive features in terms of cartography theory and application requirements compared with traditional navigation electronic maps. In order to promote the development of research and application of intelligent high-precision map, it is necessary to analyze and discuss its key features and problems. This paper proposes the information transmission model from the cartography theory; combines the wheeled robot's control flow from practical application, proposes the data logic structure of intelligent high-precision map, and analyzes its application in autonomous driving; summarizes the computing mode of "crowdsourcing+edge-cloud collaborative computing", and carries out key technical analysis on how to improve the quality of crowdsourced data; analyzes the effective application scenarios of intelligent high-precision map in the future; Finally, presents some thoughts and suggestions for the future development of this field.

Mapping function errors are usually not taken into consideration, when space geodetic data observed by VLBI, GNSS and some other techniques are utilized to estimate troposphere delay, which could, however, probably bring non-ignorable errors to solutions. After analyzing the variation of mapping function errors with elevation angles based on several-year meteorological data, this paper constructed a model of this error and then proposed a two-step estimation method of troposphere delay with consideration of mapping function errors. The experimental results indicate that the method puted forward by this paper could reduce the slant path delay residuals efficiently and improve the estimation accuracy of wet tropospheric delay to some extent.

Weighted mean temperature is a critical parameter in GNSS technology to retrieve precipitable water vapor (PWV). It is convenient to obtain high-accuracy Tm estimation near surface utilizing Bevis formula and surface temperature. However, some researches pointed out that the Bevis formula has large uncertainties in high-altitude regions. This paper researches the applicability of Bevis formula at different height levels and finds that the Bevis formula has relatively high precision when the altitude is low, while with altitude increasing, the precision decreases gradually. To solve the problem, this paper studies the relationship between Tm and atmospheric temperature of the near-earth space range (the height range between 0~10 km) and finds that they have high correlation on a global scale. Accordingly, this paper builds a global weighted mean temperature model based on near-earth atmospheric temperature. Validation results of the model show that this model can provide high-accuracy Tm estimation at any height level in the near-earth space range.

The fast convergence without initial value dependence is the key of large angle relative directional solution. Therefore, a hybrid conjugate gradient algorithm is proposed in this paper. The concrete process is:① stochastic hill climbing(SHC) algorithm is used to make random disturbance to the given initial value of the relative directional element, and the new value to guarantee the optimization direction is generated; ② In local optimization, super-linear convergent conjugate gradient method is used to replace the steepest descent method in relative orientation to improve its convergence rate; ③ The global convergence condition is that the calculation error is less than the prescribed limit error. The comparison experiment shows that the method proposed in this paper is independent of initial value, has higher accuracy and fewer iterations.

For the determination of the smoothing factor (also known as the regularization parameter) in the co-seismic slip distribution inversion, the compromise curve between the model roughness and the data fitting residual is generally used to determine (in order to distinguish the method proposed in this paper, the method is called "L curve" according to its shape). Based on the L-curve, the eclectic intersection curve as a new method are proposed to determine the smoothing factor in this paper. The results of the simulated experiment show that the inversion accuracy of the parameters of the seismic slip distribution with the smoothing factor determined by the eclectic intersection curve method is better than that of the L curve method. Moreover, the eclectic intersection curve method and the L curve method are used to determine the smoothing factor of L'Aquila and Taiwan Meinong earthquake slip distribution inversion respectively, and the inversion results are compared and analyzed. The analysis results show that the L'Aquila and Meinong of Taiwan actual earthquake slip distribution results are in the range of other scholars at home and abroad, and compared with the L curve method, the eclectic intersection curve method has advantages of high computation efficiency, no need to depend on data fitting degree and more appropriate of smoothing factor and so on.

The research and modeling of nonlinear variations of GPS stations coordinates are effective ways to weaken nonlinear motion of the stations. However,due to the diversity and complexity of nonlinear variations of stations' coordinates,the theoretical correction model contained multiple mechanisms has not been established to weaken the nonlinear motion of GPS stations.In this paper,global distribution regularity of annual terms of vertical coordinates of stations was discovered based on the measured vertical coordinates residuals of nearly 500 GPS stations,two statistical correction models of annual variations based on measured data were respectively constructed for the northern and southern hemispheres.The experiments show that the statistical correction model proposed in this paper can weaken 30%~50% vertical coordinate residuals of most GPS stations in the world.

Traffic plays a vital role in people's life and social economy.Vehicle speed detection is an important part of intelligent transportation system.This paper focus on the vehicle speed detection based on multi-source data from autonomous unmanned aerial vehicle (UAV).Firstly,we build a multi-source data acquisition system on UAV for visible image and thermal infrared image.Secondly,we utilize "You only look once" (YOLO),which is a deep learning framework for vehicle detection.Finally,we track the vehicle based on Kalman filter and calculated the vehicle speed according to the result of vehicle tracking.This paper adopts the UAV platform to increase the flexibility.While the use of multi-source data improves the accuracy of the vehicle detection and tracks the vehicle in different illumination.The result of experiments shows that the strategy is effective and robust,which provides an efficient and flexible monitoring mode for traffic management department.

Airborne gravimetry is an effective technology to obtain the Earth's gravity field information of land and offing area in high precision and resolution quickly.Downward continuation is one of the key steps in airborne gravimetry data processing,and the quality of continuation results directly influence the further application of surveying data.Based on numerical analysis of the continuation models of traditional least squares method,improved least squares method and Tikhonov regularization method,and according to the basic characteristics of spherical harmonic function,the continuation models of Poisson integral iteration method and improved Poisson integral iteration method were proposed and deduced.For the testing area in this paper,the surveyed airborne and terrestrial gravimetry data prove that the precision of the new continuation models of Poisson integral iteration method and improved Poisson integral iteration method are equal.Compared with the continuation models of traditional least squares method and improved least squares method,of which the precision are improved about 15.26 mGal and 0.21 mGal,respectively.The precision of new continuation models are inferior to Tikhonov regularization method about 0.13 mGal.Therefore,the new continuation models proposed in this paper can not only be used to amend the ill-posed problem of the continuation model introduced by traditional Poisson integral discretization formula,but also be used to suppress the ill-posed problem of the continuation model itself.Therefore,the research achievements can be applied directly in the data processing of our country's airborne scalar and vector gravimetry.

Uncertainty often exists in the process of measurement data acquiring,which affects the reliability and validity of parameter estimation.Based on uncertain mixed adjustment model,this paper applies the adjustment criterion,minimizing the sum of squares of random error and squares of uncertainty error,to study a new iteration algorithm to solve the adjustment model under the bound constrain of uncertainty.By the example,the estimation results of proposed method are compared with that of another relative method.The results show that the parameter calculation method presented in this paper is effective and feasible.Meanwhile,the method has satisfied applicability when the uncertainty is large.

The existing three-dimensional (3D) visualization of flood disaster scenes has problems such as weak immersion and lack of mobility.This paper combines mobile virtual reality (VR) with 3D visualization of flood disaster scenes,and proposes a construction optimization and interaction method for flood disaster scenes based on mobile VR.Firstly,a mobile VR scene construction scheme under a plugin-free B/S architecture is proposed.Second,certain key technologies for scene optimization are discussed,including diverse modes of scene data organization,optimization control of scene data volume and adaptive scheduling of mobile scenes.Finally,some interaction and analysis schemes based on gaze,such as scene roaming exploration and interactive flood information query,are designed.A test platform was developed and a case experiment analysis was carried out.The experiment results demonstrate that the flood disaster scene constructed by the methods addressed in this paper can be displayed smoothly and explored interactively on smart phones.

As a new generation of geographic language,virtual geographic environments(VGE) needs to construct the virtual geographic knowledge engineering through the analysis and excavation of multi-sourced heterogeneous spatio-temporal data.Through the transformation about "data-information-knowledge-wisdom",it can promote the rapid conversion and integration of geographic knowledge for intelligent VGE system,which may provide a theoretical and technical support for intelligent processing of geographic information and intelligent service of geographic knowledge.Knowledge graph plays the role of a bridge between artificial intelligence and knowledge engineering for VGE system.This paper firstly reviewed the research status in knowledge graph and geographic knowledge graph from the domestic and abroad perspectives.Then,the construction process of geographic knowledge graph is proposed.Furthermore,the key technologies of geographic knowledge graph are discussed in depth.Finally,the application direction of geographic knowledge graph is discussed and stated.The study of geographic knowledge graph in this paper may help to realize the knowledgization of geographic information and promote the intelligent service level for VGE system.

This paper focuses on machine learning in intelligent photogrammetry:the elevation difference fitting neural network method.The limitations of observation technologies and processing methods lead to the lack of global high-accuracy seamless DEMs,which further restrict DEMs’ application in the fields of hydrology,geology,meteorology,military and other applications.In this paper,we propose a multi-source DEM fusion method using the neural network model trained based on elevation difference.The proposed method is employed to generate a high-quality seamless DEM dataset blending SRTM1,ASTER GDEM v2,and ICESat GLAS.At first,the ICESat GLAS data were filtered according to the relevant parameters and the elevation differences with DEMs.The threshold of elevation difference adaptively varied with terrain slope to remove the abnormal points effectively.The neural network was then applied to learn the error distribution of ASTER GDEM v2,using the ICESat GLAS data as the control points.We constructed the network input composed of slope information,latitude and longitude coordinates,while the elevation difference of ICESat GLAS and ASTER GDEM v2 were set as the target output.The corrected ASTER GDEM v2 results can be obtained by adding the predicted output to the original elevation values.At last,the corrected ASTER GDEM v2 values were utilized to fill the voids of SRTM1,where the vertical bias between the datasets were dealt with TIN delta surface method to blend the seamless DEM.Randomly selected data were used for actual experiments,and the proposed model was evaluated by comparing with other methods and DEM datasets through quantitative evaluation and visual discrimination.Experiment results show that the proposed method has lower value of RMSE than compared methods both in void or the whole area,which can effectively overcome the influence of outliers in ASTER GDEM v2,and generate seamless DEM.

This paper is the third part of the three dimensional digital photogrammetry intelligent conformation under the machine vision parameter:the direct 3D imaging mechanism of the light field and the 3D intelligent conformation benchmark of digital photogrammetry.In this paper,the moving object’s capture takes 3-3-2 information processing as the starting point,the basic principle of using biological compound eye three-dimensional imaging,however,because the traditional bionic vision by the hardware constraints,this paper obtained the theory based on bionic compound eye 3-3-2 information,the use of a new generation of micro lens array light field camera technology,put forward a method of extracting depth information of the scene to single light field images,and its application to absolute depth measurement.The light field image an important characteristic is that the intensity and direction of different light information recording into the camera,this paper proposes the use of light information for multi depth focusing,the focusing points in different levels of cost calculation,determine the object image plane,finally construct the depth map object point based on the location of the imaging plane.Compared with the traditional light depth estimation,the depth map obtained by this method can greatly improve the resolution,and does not depend on the number of micro lens in the light field.In order to verify the effectiveness of the proposed method,this paper will compare the depth calculation using the algorithm proposed in this paper and the existing depth information algorithm.

In this paper,one of the key elements of intelligent data processing in digital photogrammetry is discussed based on machine vision:efficient management technology of massive point cloud,an improved algorithm for hash mapping 3D data on GPU is proposed.The algorithm can efficiently perform dynamic insertion,update and indexing of data without the limitation of data scale.We applied the algorithm to TSDF (truncated signed distance field) algorithm for point cloud fusion,which can reduce the noise of single frame and the data registration error between different frames in a very efficient way.Currently,most of the data structures of point cloud fusion algorithms are regular or hierarchical grid data structures,so the object bounding boxes should be specified in advance.Moreover,the hierarchical data structure is complex and hard to parallelization.Therefore,the requirements of dynamic scalability,updating and indexing data of real-time 3D reconstruction cannot be satisfied.This paper exploited hash map to manage 3D data.At the same time,the current active region could be estimated with sensor motion to exchange data between host and GPU,keeping low memory utilization of GPU.In the experiments on different levels of graphics cards(GTX960,GTX1050,GTX1060),the algorithm can satisfy the real-time frame rate requirements(60 fps,2.11×105 points per frame),so it meets the requirement of efficient management of 3D point cloud data in three-dimensional imaging.

This paper focuses on intelligent photogrammetry deep learning:deep residual method.Salient object detection aims at identifying the visually interesting object regions that are consistent with human perception.Multispectral remote sensing images provide rich radiometric information in revealing the physical properties of the observed objects,therefore promise a great potential in salient object detection tasks.Conventional salient object detection methods often employ handcrafted features to predict saliency by evaluating the pixel-wise or superpixel-wise similarity.With the recent emergence of deep learning based approaches,in particular,fully convolutional neural networks,there has been profound progress in visual saliency detection.However,this success has not been extended to multispectral remote sensing images,and existing multispectral salient object detection methods are still mainly based on handcrafted features,essentially due to the difficulties in image acquisition and labeling.In this paper,we propose a novel deep residual network based on a top-down model,which is trained in an end-to-end manner to tackle the above issues in multispectral salient object detection.Our model effectively exploits the saliency cues at different levels of the deep residual network.To overcome the limited availability of remote sensing images in training of our deep residual network,we also introduce a new spectral image reconstruction model that can generate multispectral images from RGB images.Our extensive experimental evaluations using both multispectral and RGB salient object detection datasets demonstrate a significant performance improvement of more than 10% compared with the state-of-the-art methods.

Accuracy is a key factor in high-resolution remote sensing and photogrammetry.The factors that affect accuracy are imaging system errors and data processing errors.Because of the complexity of aerial camera system errors,this paper focuses on the design of digital aerial camera system,to reduce the system error and provide data procession fundamentally.There are many kinds of digital aerial camera system at present,but lacking a unified physical model,which causes the system to be built in multi-camera and multi-rigid model.Such system is complex,costly,and difficult to describe,and is easily affected by factors such as vibration and temperature,so the installed accuracy can only reach millimeter level.For this reason,this paper proposes the unified physical structure of digital aerial camera,which imitates the theory of out-of-field multi-CCD,in-field multi-CCD,and once-imaging and twice-imaging digital camera systems.Considering this,the spatial-temporal representation of the variable baseline-height ratio is established.From the variable baseline-height ratio,we can link the opto-mechanical spatial parameters with the elevation accuracy,so that to achieve connection between the surface elevation with opto-mechanical structural parameter; further designing the twice-imaging digital camera prototype system and the wideband limb imaging spectrometer,which provides prototype for transformation from the current multi-rigid,one-time imaging aerial camera to single rigid structure.Our research has laid a theoretical foundation and prototype references for the construction and industrialization of digital aerial system.

This paper focuses on the time efficiency for machine vision and intelligent photogrammetry,especially high accuracy on-board real-time cloud detection method.With the development of technology,the data acquisition ability is growing continuously and the volume of raw data is increasing explosively.Meanwhile,because of the higher requirement of data accuracy,the computation load is also become heavier.This situation makes time efficiency extremely important.Moreover,the cloud cover rate of optical satellite imagery is up to approximately 50%,which is seriously restricting the applications of on-board intelligent photogrammetry services.To meet the on-board cloud detection requirements and offer valid input data to subsequent processing,this paper presents a stream-computing based high accuracy on-board real-time cloud detection solution which follows the “bottom-up” understanding strategy of machine vision and uses multiple embedded GPU with significant potential to be applied on-board.Without external memory,the data parallel pipeline system based on multiple processing modules of this solution could afford the “stream-in,processing,stream-out” real-time stream computing.In experiments,images of GF-2 satellite are used to validate the accuracy and performance of this approach,and the experimental results show that this solution could not only bring up cloud detection accuracy,but also match the on-board real-time processing requirements.

This paper tackles imaging system pose tracking and model refinement,one of the fundamental work for 3D photogrammetry.The researches belong to the videometrics,an interdiscipline which combines computer vision,digital image processing,photogrammetry and optical measurement.Related works are summarized briefly in this paper.We study the problems of pose tracking for target with 3D model.For the target with accurate 3D model,line model based pose tracking methods are proposed for target with rich line features.Experimental results indicate that the proposed methods track the target pose accurately.Normal distance iterative reweighted least squares and distance image iterative least squares methods are proposed to process more general targets.This paper adopts bound adjustment to tackle pose tracking in image sequence for target with inaccurate 3D line model.The proposed method optimizes model line parameters and pose parameters simultaneously.The model line orientation,position and mean angle error,mean position error of pose are 0.3°,3.5 mm and 0.12°,20.1 mm in simulation experiments of satellite pose tracking.Line features are used to track target pose with unknown 3D model through image sequence.The model line parameters and pose parameters are optimized under the framework of SFM.In simulation experiments,the reconstructed line orientation,position error and mean angle error,mean position error of pose are 0.4°,7.5 mm and 0.16°,23.5 mm.

This paper deals with the massive point cloud segmentation processing technology on the basis of machine vision,which is the second essential factor for the intelligent data processing of three dimensional conformation in digital photogrammetry.In this paper,multi-model fitting method is used to segment the point cloud according to the spatial distribution and spatial geometric structure of point clouds by fitting the point cloud into different geometric primitives models.Because point cloud usually possesses large amount of 3D points,which are uneven distributed over various complex structures,this paper proposes a point cloud segmentation method based on multi-model fitting.Firstly,the pre-segmentation of point cloud is conducted by using the clustering method based on density distribution.And then the follow fitting and segmentation are carried out by using the multi-model fitting method based on split and merging.For the plane and the arc surface,this paper uses different fitting methods,and finally realizing the indoor dense point cloud segmentation.The experimental results show that this method can achieve the automatic segmentation of the point cloud without setting the number of models in advance.Compared with the existing point cloud segmentation methods,this method has obvious advantages in segmentation effect and time cost,and can achieve higher segmentation accuracy.After processed by method proposed in this paper,the point cloud even with large-scale and complex structures can often be segmented into 3D geometric elements with finer and accurate model parameters,which can give rise to an accurate 3D conformation.

ZY-3 01 and ZY-3 02 satellites, as important remote sensing stereoscopic mapping satellites in China, undertake the tasks of production of geographic products, land resource investigation and so on. Precision orbit determination(POD) is a prerequisite for the success of ZY-3 01 and ZY-3 02 missions. Dual-frequency GPS receiver and SLR reflector manufactured by China play significant roles in POD and independent orbits checkout. Although PCO priori values were obtained before satellites launched,by PCO estimation in-flight, this paper analyses the feasibility of PCO in different directions and finds ZY-3 01 and ZY-3 02 SLR RMS checkouts are improved 0.331 mm,0.399 mm respectively. Further, this paper estimates PCV models of ZY-3 01 and ZY-3 02 spaceborne GPS antennas using direct approach and residual approach and their PCV models can reach[-15 mm 15 mm]. Through the use of PCV models(10°×10°), ZY-3 01 orbits SLR checkouts are improved 2.143 mm (direct approach), 1.628 mm (residual approach), orbit accuracy in 3D of overlapping arcs are improved 11.377 mm (direct approach),13.903 mm (residual approach), ZY-3 02 orbits SLR checkouts are improved 0.727 mm (direct approach),0.692 mm (residual approach), orbit accuracy in 3D of overlapping arcs are improved 1.736 mm (direct approach),1.548 mm(residual approach).The effect of PCV model resolution (10°×10°,5°×5°,2°×2°) on POD is further discussed in this paper. After comprehensive consideration of computational efficiency, storage space, increase amplitude and other factors, 5°×5° PCV model by residual approach is the best choice.

Exploring automatic point cloud classification method is of great importance to 3D modeling,city land classification,DEM mapping and etc.To overcome the problem that extracting geometric feature for point cloud classification involved neighbor structure meets the challenge that the optimal neighbor scale parameter,high data dimension and complex computation,lacking efficient feature importance analysis and feature selection strategy,this paper proposed a point cloud classification and dimension reduction method based on random forest.After analyzing the characteristic of elevation,intensity and echo of laser points,this paper extracted a total of 6 feature types like normalized height feature,height statistic feature,surface metric feature,spatial distribution feature,echo feature,intensity feature,then built a multi-scale feature parameter from them.Finally,a supervised classification was conducted using a random forest algorithm to optimal the feature set and choose the best feature set to classify the point cloud.Results indicate that,the overall accuracy of the proposed method is 94.3% (Kappa coefficient is 0.922).The proposed method got an improvement in the overall accuracy when compared with no feature selection strategy and SVM classification strategy; The feature importance analysis indicates that the normalized height is the most important feature for the classification.

Aiming at the problems of uncertain fitting function,incomplete filtering effects and some soundings unreasonable exclusion by applying tendency surface filtering algorithm in multi-beam bathymetric data,the paper brought forward the concept of natural neighboring points influence field,which means the minimum local area of an arbitrary point in scattered soundings,and erects an improved algorithm of tendency surface filtering based on natural neighboring points influence field. Firstly,the paper analyzed the local approximate surface of the natural neighboring points influence field,and constructed the unified surface fitting function in the specific local coordinate system for natural neighboring points influence field. Secondly,by using the unified surface fitting function,the iterative tendency surface filtering method has been erected to filter gross error data affecting the judgment of the normal points step by step. At last,according to the different continuity of the boundary point on the mutation terrain within the neighborhood adjacent terrain,a judgment criterion to the boundary point is established to reserve the boundary point. Some experiments were completed to prove the validity of the algorithm. The experiments show that the improved algorithm can adapt to the submarine topographies of varied complexities,eliminate the gross error points in the multi-beam bathymetric data and preserve the normal and special points of actual submarine topography. Therefore,the precision of submarine topography expression is significantly improved.

Node importance has significant influence on the calculation of shortest path of large-scale road network. A shortest path estimation method based on node importance is proposed in this paper that is suitable for large-scale network. This method integrates the criteria importance though intercrieria correlation (CRITIC) method with complex network theory, with a view to evaluate nodes importance. By combining the restriction strategy to realize network division, the effective simplification of large-scale road network and shortest path estimation are realized through the construction of hierarchical network. The results show that this method can be used to distribute the center nodes evenly, and make little difference in the size of the subnetwork. As the constraint parameter increases, the numbers of nodes and edges reduced gradually, and the query accuracy reached 1.026. Compared with single index and unlimited parameters methods, this paper significantly reduces the size of the network and obtains a high accuracy on the approximate calculation of the shortest path. These will provide a new way of thinking for approximate analysis of large-scale complex networks.

Terrestrial 3D laser scanning is one of principal methods to get the geometric information of object surface,and the integrity of the scanned object is a basic requirement in data acquisition. In order to solve the missing point cloud problem due to the scanning dead angle caused by confined working space,this paper proposes a method using ordinary plane mirror to obtain laser scanning data for non-direct viewing area according to the plane mirror reflection principle,analyzes the influence mechanism of the ordinary plane mirror on the propagation path and distance of laser beam,deduces the coordinate equation of the object point corresponding to the image point reflected by ordinary plane mirror in laser scanning. Given the laser scanning characteristic,this paper introduces a mirror reflection system included target balls and ordinary plane mirror,and expounds the system construction,system calibration and constructing method of system coordinate system. The feasibility and precision of the method are verified by experiments.

In general,ionosphere-free model and uncombined model are applied for GNSS precise point positioning (PPP).This paper detailed analyzes the correlation of different parameters of each model,and deducevarious PPP functional model by means of parameterization methods.And uncombined PPP with ionospheric parameter constrains i.e.ionosphere-weighted model can fasten PPP convergence effectively.This paper takes advantage of GPS-only and GPS and BDS combination dataset as example for positioning in different PPP models.In the perspective of positioning accuracy and convergence time,positioning performance are detailed analyzed in both static PPP and simulated dynamic PPP modes.The results demonstrate that GPS-only has the similar accuracy with GPS+BDS combination,and both ionosphere-free model and uncombined model static PPP can achieve the positioning accuracy of millimeter to centimeter level,while the horizontal positioning accuracy of dynamic PPP is superior to 3 cm and the vertical positioning accuracy is superior to 5 cm.In terms of convergence time,ionosphere-free model is superior to uncombined model,and the convergence time of ionosphere-weighted model is the shortest.Compared to the ionosphere-free model,the ionosphere-weighted model can decrease about 15% convergence time,while it can decrease about 34% convergence time compared to the uncombined model in the dynamic positioning.

Because of the lack of relationships between matching line and adjacent lines in the process of individual line matching, and the weak reliability of the individual line descriptor facing on discontinue texture, this paper presents a reliable line matching algorithm for stereo images with topological relationship. The algorithm firstly generates grouped line pairs from lines extracted from the reference image and searching image according to the basic topological relationships such as distance and angle between the lines. Then it takes the grouped line pairs as matching primitives, and matches these grouped line pairs by using epipolar constraint, homography constraint, quadrant constraint and gray correlation constraint of irregular triangle in order. And finally, it resolves the corresponding line pairs into two pairs of corresponding individual lines, and obtains one to one matching results after the post-processing of integrating, fitting, and checking. This paper adopts digital aerial images and close-range images with typical texture features to deal with the parameter analysis and line matching, and the experiment results demonstrate that the proposed algorithm in this paper can obtain reliable line matching results.

Web-based geographic information service is the important manner for public service of geographic information in the information age. In January 2011, the National Administration of Surveying, Mapping and Geoinformation released the National Geo-information Service Platform "Tianditu", which effectively promoted the sharing and extensive application of the distributed geographic information resources around the country. This paper introduced the construction background, key technologies, and application effect of "Tianditu". And further efforts were discussed in the end of the paper.

Spatial information generalization is a major issue in spatial information processing. This paper reviews the research development of cartographic generalization in generalization knowledge category and acquiring, operator and algorithm, quality evaluation and process modeling and controlling. The paper analyzes cartographic generalization in the background of big data, and puts forward that the cartographic generalization should revise the research object, the concept and the method.

This paper briefly reviewed the history of seafloor terrain measuring technology,and then detailed the introduced sonar bathymetry based on vessel,airborne laser bathymetry,integrated measurement for coastal topography and three inversion methods for seafloor terrain.That entirely presents the current situation of stereoscopic,efficient,high-accuracy and high-resolution of seafloor topography acquirement.Finally,combined with the future requirements,this paper summarized the core job and development trend in future seafloor terrain measuring field,which includes developing more portable multi-beam system with ultra-wide coverage,high accuracy and resolution,researching more efficient correction model of sound velocity effects,smoothing of bathymetry data and expression of submarine topography.Meanwhile,automatic ship measurement will be an important task mode.Also airborne laser survey,seafloor topography inversion from sonar image and deep-towing measurement has enormous potential in development.

This paper systematically summarizes the research and development of technology and product since the launch of the ZY-3 surveying and mapping satellite,as well as the data application.Based on the introduction about satellite system technical parameters,this paper describes the processing methods about radiation correction,attitude post-processing,geometric calibration and imaging geometric model,and introduces the project realization in the past 5 years.The application of the data is summarized and analyzed,and the development prospect of the mapping satellite is briefly expected.

With the impetus of ICT, cartography faces the unprecedented challenges. The paper discusses the problems and changes of cartography facing the digital technology, analyzes the constraints of traditional cartography that are mainly delimited by 2D physical paper map. Diverseness of modern cartography shows various map products, and the paper illustrates the digital freedom in information space of modern cartography from eight aspects, including physical reality VS virtual reality, paper map VS digital map, superficial visualization VS inner visualization and so on. Modern cartography encounters the new development opportunities and fresh demands in digital era, and it's necessary to extend the framework of cartography and to assimilate newly sprouted things to promote the rejuvenation of cartography.

The paper discusses differences between China Geodetic Coordinate System 2000 (CGCS2000) and later updated ITRF versions, such as ITRF2014, in terms of technical implementation and maintenance. With progress of space geodetic technology, also the development of the BeiDou navigation satellite system, especially third generation of BDS with signal global coverage in the future, it is possible for us to establish a global millimeter-level reference frame based on space geodetic technology including BDS. The millimeter reference frame implementation concerns two factors:① The variation of geocenter motion estimation; ② the site nonlinear motion modeling. In this paper, the geocentric inversion methods are discussed and compared among results derived from various technical methods. Our nonlinear site movement modeling focuses on singular spectrum analysis method, which is of apparent advantages over earth physical effect modeling. All presented in the paper expected to provide reference to our future CGCS2000 maintenance.

Since the concept was proposed at the beginning of last century, cartography generalization has been gradually changed from full manual operation mode to computer automation mode after decades of improvement and development. However, the level of map automation is still relatively low until now. So, this paper puts forward an integrated representation of geographical model for entity and symbol on the basic of innovative model units and spatial relation model. Then the automatic methods of topological compensation for model entity and cartography compensation for model symbolization are established, we want to explore a solution to solve the worldwide problem of automatic cartography generalization. Finally, this paper look into the future and developmental direction of automatic cartography generalization.

Recently, detailed underwater target detection and imaging sonar technology has become a research hotpot with the urgent need of marine research. Multibeam synthetic aperture sonar technology has been proposed combining the both technological advantages in this paper, owing to the emphatically analyses of the technology trends of multibeam bathymetric sonar and synthetic aperture sonar. The research progress in the key technologies of multibeam synthetic aperture sonar has been discussed in this paper, the effectiveness of multibeam synthetic aperture sonar detection mechanism is preliminary verified by the experiments. The potential that the multibeam synthetic aperture technique can effectively enhance the underwater target resolution has aslo been proved through the contrast experiment.

Influenced by the growing popularity of smart phones and the rapid development of open science, remote sensing is being developed and applied more by general public than by trained professionals. This trend is mainly embodied in the democratized data collection, democratized data processing and democratized data usage. This paper discusses and analyzes the three aforementioned characteristics, introduces some recent representative work and progress. It also lists numerous international open data processing tools, including photogrammetry processing, laser scanning processing, machine learning, and spatial information management. In addition, the article makes a detailed description of the benefits of open data, and lists a number of global data programs and experimental data sets for scientific research. At the end of this paper, it is pointed out that the democratization of remote sensing will not only produce great economic benefits, but also bring about great social benefits, and finally change the landscape of industry and the life style of people.

Combining service-computing technology with domain requirements is one of the important development directions of geographic information under Internet+, which provides highly efficient technical means for information sharing and collaborative services. Using GlobeLand 30 as an example, this paper analyzes the basic problems of integrating land cover information processing and service computing, introduces the latest research progress in domain service modeling, online computing method and dynamic service technology, and the GlobeLand 30 information service platform. The paper also discusses the further development directions of GlobeLand 30 domain service computing.

The unification of the global height datum is a key problem to be solved for geodesy after the unification of global geodetic coordination system and three-dimension spatial datum, and the basis of global spatial information sharing and exchange. In this paper, the theoretical and practical problems of vertical datum offset between the regional height datum and the global height datum are studied. Based on the classical theory of the height system in physical geodesy, the definition of the height datum vertical offset is given, and the rigorous formulas for calculating the vertical offset are derived. The formulas can be used to deduce the three methods of the height datum vertical offset determination. On that basis, the influences of different reference system and reference ellipsoid parameters on the calculation of the vertical offset are analyzed. The results show that the reference system and the ellipsoid parameter conversion are very necessary. At the same time, the height anomaly differences method needs to consider the degree zero correction caused by the inconsistency between gravity potential of the global height datum and the one computed by the model. Based on potential difference approach and the height anomaly difference method, the vertical offset between the China 1985 national height datum and the global height datum corresponding to the normal gravity potential U0 of GRS80, WGS-84 and CGCS2000 reference ellipsoidal from the 152 GPS/leveling points near the origin of Qingdao height origin and the EGM2008, EIGEN-6C4 and SGG-UGM-1 model. The regional datum is 23.1 cm lower than the global datum based on EIGEN-6C4 and WGS-84. When the Gauss-Listing geoid (mean sea surface) is selected as the global height datum, the China 1985 national height datum is 21.0 cm higher than the global height datum. The results also show that there are still large differences among the accuracies of the current gravity field models on these GPS/Levelling points around Qingdao, which will lead to big differences in estimating the vertical datum offset between the China 1985 national height datum and the global height datum with respect to different selected data sets. Therefore, the accuracy and reliability of the current global gravity field models needs to be further improved if they were used for the height datum vertical offset determination. The theoretical and practical results of this paper could be used for the realization of the unification of the regional height datum and the global height datum.