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Knowledge-guided intelligent recognition of the scale for fragmented raster topographic maps REN Jiaxin, LIU Wanzeng, CHEN Jun, ZHANG Lan, TAO Yuan, ZHU Xiuli, ZHAO Tingting, LI Ran, ZHAI Xi, WANG Haiqing, ZHOU Xiaoguang, HOU Dongyang, WANG Yong Acta Geodaetica et Cartographica Sinica    2024, 53 (1): 146-157.   DOI: 10.11947/j.AGCS.2024.20230005 Abstract （228）   HTML （97）    PDF（pc） （16874KB）（382）       Knowledge map    Save Determining the topographic map scale is a critical basis for assessing the degree of confidentiality of topographic maps. In this study, we propose a solution to the challenge of estimating the scale of fragmented raster topographic maps by leveraging a priori knowledge of scale-related features, constructing an expert knowledge image pyramid dataset (EKIPD) under guided expert knowledge, and applying deep convolutional neural network algorithms to create a hybrid intelligent model that synergistically combines knowledge, data, and algorithm. The EKIPD dataset captures a representative sample distribution of fragmented topographic maps of varying sizes, which enables us to statistically determine the optimal recognition size (ORS) for sub-map recognition. The ORS then serves as a stepping threshold to partition the topographic maps into recognizable sub-maps. Each sub-map is independently processed through the model to obtain individual predictions, which are subsequently integrated to infer the map scale. Experimental validation shows that this method achieves an accuracy of approximately 97%, demonstrating its efficacy. Reference | Related Articles | Metrics

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The progress and trend of cartography and geographic information engineering in China (2019—2023) SUN Qun, REN Fu, LONG Yi, CHEN Xin, XU Gencai, LIU Jianjun, ZHOU Zhao Acta Geodaetica et Cartographica Sinica    2024, 53 (3): 399-412.   DOI: 10.11947/j.AGCS.2024.20230562 Abstract （144）   HTML （37）    PDF（pc） （12949KB）（242）       Knowledge map    Save Based on the development of cartography and geographic information technology in China since 2019, this report summarizes the achievement in theories of cartography, digital cartography and press techniques, updating of China's National Fundamental Geographic Information Database, geographic information technology and industrial development, geographic information applications and services, atlas compiling and publishing, and the new online map. Finally, the report offers some prospects for the developing trend of cartography and geographic information engineering in China. Reference | Related Articles | Metrics

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Automatic Analysis and Mining of Remote Sensing Big Data LI Deren, ZHANG Liangpei, XIA Guisong Acta Geodaetica et Cartographica Sinica    2014, 43 (12): 1211-1216.   DOI: 10.13485/j.cnki.11-2089.2014.0187 Abstract （4625）   HTML    PDF（pc） （1314KB）（11033）       Knowledge map    Save With the diversification of the imaging methods and the growing categories, quantity, and observation frequency of remote sensing data, the ability of land-cover observation has reached an unprecedented level, which means a new era of big data in remote sensing is coming. However, the existing methods and processing techniques cannot fulfill the need of the big data application in remote sensing. Thus, to develop the automatic analysis and mining theory and techniques for remote sensing big data is among the most advanced international research areas. This paper investigates and analyses the domestic and overseas research status and progress around this field and points out its key problems and developing trends. Reference | Related Articles | Metrics

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Research on deep learning models for hyperspectral image classification PU Shengliang Acta Geodaetica et Cartographica Sinica    2023, 52 (1): 172-172.   DOI: 10.11947/j.AGCS.2023.20210203 Abstract （250）   HTML （19）    PDF（pc） （729KB）（707）       Knowledge map    Save Related Articles | Metrics

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GNSS ultra-rapid orbit and clock offset estimation method with the aid of the constraint of BDS-3 onboard clock HU Chao, WANG Qianxin Acta Geodaetica et Cartographica Sinica    2024, 53 (3): 413-424.   DOI: 10.11947/j.AGCS.2024.20230168 Abstract （133）   HTML （18）    PDF（pc） （12929KB）（108）       Knowledge map    Save The high-stability BDS-3 onboard clock is one of the significant advanced technologies of BDS, which is underutilized in GNSS data processing. To solve the precision restriction of GNSS ultra-rapid orbit and clock offset parameters under the strict timeliness limitation, GNSS ultra-rapid orbit and clock offset estimation method with the aid of the constraint of BDS-3 onboard clock is proposed in this research. Firstly, based on the correlation GNSS clock offset and orbit, the GNSS orbit determination model is constructed with the consideration of BDS-3 onboard clock parameter. Secondly, impacts of onboard clock constraints on GNSS orbit determination are analyzed by taking BDS-3 precise clock offsets as example in experiments. Thirdly, to overcome the influence of the prediction clock offset and selected constraints on GNSS ultra-rapid orbit determination, the synchronously processed method of BDS-3 clock modelling and GNSS ultra-rapid orbit estimation is proposed. According to the experimental results, it is indicated that the accuracy of BDS-3 and GPS orbit and clock offsets can be respectively improved with 27.5%, 5.1% and 20.2%, 5.2%, under the optimal constraint on BDS-3 onboard clock. Meanwhile, compared with the traditional epoch-wise white noise strategy of GNSS clock parameter, the proposed one-step processing method for BDS-3 satellite clock modeling and GNSS ultra-rapid orbit determination can respectively improve the accuracy of GNSS ultra-rapid clock offset and orbit up to 4.8% and 34.2%, where the millimeter-level orbit accuracy improvements can be obtained. Therefore, the proposed GNSS ultra-rapid orbit and clock offset estimation method based on BDS-3 clock offset constraints can effectively utilize the information of BDS-3 highly stable onboard clock information, and realize the accuracy improvement of GNSS ultra-rapid orbit and clock offsets. Reference | Related Articles | Metrics

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Research Progress and Methods of InSAR for Deformation Monitoring ZHU Jianjun, LI Zhiwei, HU Jun Acta Geodaetica et Cartographica Sinica    2017, 46 (10): 1717-1733.   DOI: 10.11947/j.AGCS.2017.20170350 Abstract （4758）   HTML    PDF（pc） （1654KB）（9154）       Knowledge map    Save Deformation monitoring is one of the most mature applications of space-borne InSAR technique. Firstly, we introduce the basic principle of InSAR in the monitoring of deformation and the current SAR satellites. The deformation monitoring methods of InSAR are then classified into the groups of D-InSAR, PS-InSAR, SBAS-InSAR, DS-InSAR and MAI, which are analyzed in the aspects of technical features and application scopes. Subsequently, we analyze the research progress and deficiencies of InSAR in the investigation of urban, mining area, earthquake, volcano, infrastructure, glacier, permafrost and landslide. Finally, some advanced academic problems such as deformation monitoring in multi-demension and low coherence area, atmospheric and orbital errors mitigation, and accuracy assessment are concluded. Reference | Related Articles | Metrics

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GPS trajectory agglomeration and refined road network extraction WU Qunyong, WU Zufei, ZHANG Liangpan Acta Geodaetica et Cartographica Sinica    2019, 48 (4): 502-511.   DOI: 10.11947/j.AGCS.2019.20180256 Abstract （1999）   HTML    PDF（pc） （4008KB）（1962）       Knowledge map    Save Aiming at the shortcomings of low-accuracy in the use of GPS data to extract bidirection a roads and intersections, this paper proposes a trajectory agglomeration and refined roads extraction method that takes into account the position and travel direction to extracts refined road network. First,we remove the discrete and abnormal trajectory points from the original trajectory and insert the trajectory points into the trajectory segments by a certain step size, in order to improve the extraction accuracy of the intersection network.Second,we introduce the driving direction angle to express the driving direction of the vehicle at the track point, obtain its similar trajectory points set by considering the position and direction of the track point, calculate the offset distance of each track point in turn, and complete the track aggregation by iteratively offsetting the track points.Finally, we eliminate the track points that have not been successfully gathered, and use the Grid digitization method to extract the road network that can reflect the fine steering relationship of the roads from the trajectory data after gather. The trajectory agglomeration and road network extraction experiments were carried out with GPS data of Fuzhou taxis. The experimental results show that this method can effectively gather the GPS trajectories according to the direction of vehicle travel and the extracted road network is bidirectional roads, and can finely reflect the steering relationship of the roads at the intersections. Reference | Related Articles | Metrics

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A distributed GNSS/SINS/odometer resilient fusion navigation method for land vehicle MU Mengxue, ZHAO Long Acta Geodaetica et Cartographica Sinica    2024, 53 (3): 425-434.   DOI: 10.11947/j.AGCS.2024.20220349 Abstract （75）   HTML （7）    PDF（pc） （8885KB）（96）       Knowledge map    Save To improve the fault-tolerance of a low-cost land vehicle navigation system in the complex environment, this paper proposes a distributed GNSS/SINS/odometer resilient fusion method based on the suboptimal gain fusion algorithm. First, a velocity compensation model for each odometer on four wheels is established according to the Ackermann steering geometry, which improves the accuracy of forward and lateral velocity measurement at the inertial measurement unit center. Then, a fault detection and classification criteria based on Chi-square test statistics is designed to make full use of the available observation information. Last, a resilient adjustment model for the stochastic model and information sharing factors (ISF) are proposed to mitigate the influence of abnormal observation from the sensor layer and the decision layer respectively and realize the resilient fusion of multi-source information. A real car test is carried out to verify the effectiveness of the distributed GNSS/SINS/odometer resilient fusion method. The experiment results demonstrate that the proposed method can effectively reduce the impact of subsystem faults on the global state estimation and improve the fault tolerance performance of the system in complex environments. Moreover, compared with the traditional federated Kalman filtering (FKF), the SGF algorithm can achieve the equivalent accuracy with significant computational efficiency improvement, which is conducive to the practical engineering application of multi-source information resilient fusion. Reference | Related Articles | Metrics

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Development status and trends of Imaging Geodesy LI Zhenhong, ZHU Wu, YU Chen, ZHANG Qin, YANG Yuanxi Acta Geodaetica et Cartographica Sinica    2023, 52 (11): 1805-1834.   DOI: 10.11947/j.AGCS.2023.20230003 Abstract （396）   HTML （75）    PDF（pc） （19962KB）（1024）       Knowledge map    Save The utilization of remote sensing satellites has led to a significant increase in the use of imagery for acquiring Earth-related data. These satellites offer high observational accuracy and spatio-temporal resolutions, making them valuable tools for obtaining geodetic parameters, such as the shape and size of our planet. This advancement has not only propelled the field of Geodesy but has also given rise to a new discipline known as Imaging Geodesy. Imaging Geodesy has become an interdisciplinary science of Geodesy, Remote Sensing, Photogrammetry and Computer Vision, and has played an important role in the fields of disaster reduction, environmental protection and new energy development. In this paper, the development, definition, key technologies, main contents and development trends of Imaging Geodesy are summarized. With the development of remote sensing satellites and corresponding image processing technologies, the developmental history of Imaging Geodesy can be divided into four stages, i.e. beginning, leaping, in-depth innovation, and comprehensive application. According to the locations of its research objects, Imaging Geodesy's research contents include: observing the Earth's atmosphere, monitoring the Earth's surface, and determining the physical structure of the Earth's interior. To illustrate the practical applications of Imaging Geodesy, five scenarios are presented: generation of digital elevation models, monitoring of atmospheric water vapor, detection and monitoring of active landslides, investigation of earthquake cycles and monitoring of soil moisture. One major challenge of Imaging Geodesy is how to fuse and process the big data from multiple sources in near real time. It is believed that this paper would assist geodesy scholars in better understanding Imaging Geodesy, enabling them to integrate this emerging field into their teaching and research and to contribute to national strategies and project developments. Reference | Related Articles | Metrics

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Progress, Challenges and Perspectives of 3D LiDAR Point Cloud Processing YANG Bisheng, LIANG Fuxun, HUANG Ronggang Acta Geodaetica et Cartographica Sinica    2017, 46 (10): 1509-1516.   DOI: 10.11947/j.AGCS.2017.20170351 Abstract （4170）   HTML    PDF（pc） （1579KB）（9471）       Knowledge map    Save 3D LiDAR can perform an intensive sampling of the earth surface in a direct way, and yield the 3D point cloud that contains numerous and scattered points with the coordinates ( X, Y, Z) and attributes (e.g., intensity). As the vital 3D geospatial data for description of the world in the digital era, 3D point cloud plays an important role not only in earth science researches but also in national requirements (e.g., global change analysis, global mapping, and smart city). Inspired by sensor technologies and national requirements, 3D LiDAR has got great progresses in hardware, data processing and applications, and is facing new challenges. Following the history of 3D LiDAR, this paper first reviews the status of 3D LiDAR system, and introduces the development of key technologies in data processing. Then the typical applications of 3D LiDAR in surveying and other related fields are listed, and current challenges in point cloud processing are concluded. Finally, some future perspectives are presented. Reference | Related Articles | Metrics

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Preliminary verification of dual-satellite tandem altimetry on board SUN Zhongmiao, ZHAI Zhenhe, GUAN Bin, RUAN Rengui, HUANG Lingyong Acta Geodaetica et Cartographica Sinica    2024, 53 (2): 207-216.   DOI: 10.11947/j.AGCS.2024.20230264 Abstract （181）   HTML （19）    PDF（pc） （7787KB）（187）       Knowledge map    Save The classic method to derive gravity field from satellite altimetry is first to calculate the deflection of the vertical using the sea surface height difference (SSHD), and then further to calculate the marine gravity anomaly and the marine geoid height, et al. Obviously, improving the measurement accuracy of SSHD can directly improve the inversion accuracy of ocean gravity field. The dual-satellite tandem altimetry principle is proposed in the paper. By designing the orbit of dual-satellite, the cross orbit distance (i.e. resolution) between the sub-satellite points of the dual-satellite can be reached about 1 arcmin. The dual-satellite simultaneously measure the SSHD along their orbital direction and in the cross orbital direction. At this time, the radial error of the orbit is showed as the relative orbital radial error between dual-satellite or between single satellite observation epochs, and the corrections related to atmospheric propagation and geophysical effects are approximately equal for dual-satellite with a ground orbit spacing of only 1 arcmin, and are rarely reflected in the SSHD. Therefore, the accuracy of SSHD will be significantly improved compared to that of the traditional single satellite condition. Using the actual observation data from our twin altimetry satellites A, B, the difference error between the relative orbit radial error and the eight corrections in the SSHD was preliminarily verified. The results show that for the calibration stage with a distance of about 25 km between sub-satellite points, the difference errors of corrections such as dry troposphere, wet troposphere, ionosphere, solid tide, polar tide, and reverse atmospheric pressure are all on the order of 5 mm. There are residual errors of approximately 1 cm and 2 cm in the difference in tidal correction and sea state deviation, respectively. For the sub-satellite point spacing of about 2 km in the business orbit, the relative orbital radial error is about 3 mm,and except for the residual error of about 0.52 cm in the sea state deviation difference, the difference error of other corrections is less than 0.05 cm and can be completely ignored. Reference | Related Articles | Metrics

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Research progress of geodesy in China (2019—2023) DANG Yamin, JIANG Tao, YANG Yuanxi, SUN Heping, JIANG Weiping, ZHU Jianjun, XUE Shuqiang, ZHANG Xiaohong, YU Baoguo, LUO Zhicai, LI Xingxing, XIAO Yun, ZHANG Chuanyin, ZHANG Baocheng, LI Zishen, FENG Wei, REN Xia, WANG Hu Acta Geodaetica et Cartographica Sinica    2023, 52 (9): 1419-1436.   DOI: 10.11947/j.AGCS.2023.20230343 Abstract （792）   HTML （112）    PDF（pc） （1294KB）（1365）       Knowledge map    Save From July 11 to 20, 2023, the 28th International Union of Geodesy and Geophysics (IUGG) general assembly was held in Berlin, Germany. According to the tradition of IUGG, the Chinese National Committee for International Association of Geodesy (CNC-IAG) organized dozens of domestic institutions to compile the “2019—2023 China National Report on Geodesy”, which summarized the research progress of various branches of geodesy in China from 2019 to 2023. This article summarizes the overall progress of China's geodetic discipline in recent years, focusing on representative progress in six research directions including reference frame, comprehensive PNT and resilient PNT, gravity field and vertical datum, precise GNSS products, multi-source sensor integrated navigation, and marine geodesy. Moreover, in light of the development trends of international geodesy and related interdisciplinary disciplines, several suggestions are proposed for the future development of geodesy in China. Reference | Related Articles | Metrics

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A coupled DeepLab and Transformer approach for fine classification of crop cultivation types in remote sensing LIN Yunhao, WANG Yanjun, LI Shaochun, CAI Hengfan Acta Geodaetica et Cartographica Sinica    2024, 53 (2): 353-366.   DOI: 10.11947/j.AGCS.2024.20220692 Abstract （153）   HTML （12）    PDF（pc） （15707KB）（142）       Knowledge map    Save How to accurately monitor the planting of different types of complex farmland crops by remote sensing is the key to the realization of agricultural area survey and crop yield estimation in the area of smart rural agriculture. In the current pixel level semantic segmentation of crop planting in high-resolution images, the deep convolution neural network is difficult to take into account the spatial multi-scale global features and local details, which leads to problems such as blurring boundary contours between various farmland plots and low internal integrity of the same farmland area. In view of these shortcomings, this paper designs and proposes a dual branch parallel feature fusion network (FDTNet) that couples DeepLabv3+and Transformer encoders to achieve fine remote sensing monitoring of crop planting. Firstly, DeepLabv3+and Transformer are embedded in FDTNet in parallel to capture the local and global features of farmland image respectively. Secondly, the coupled attention fusion module (CAFM) is used to effectively fuse the characteristics of the two features. Then, in the decoder stage, the convolutional block attention module (CBAM) is applied to enhance the weight of the effective features of the convolutional layer. Finally, the progressive multi-level feature fusion strategy is adopted to fully fuse the effective features in the encoder and deco-der, and output the feature map to achieve high-precision classification and recognition of late rice, middle rice, lotus root field, vegetable field and greenhouse. In order to verify the effectiveness of FDTNet network model in high-resolution crop classification application, this paper selects different high-resolution Yuhu dataset and Zhejiang dataset and experimental results of mIoU reach 74.7% and 81.4%, respectively. The mIoU of FDTNet can be 2.2% and 3.6% respectively higher than the existing deep learning methods, such as UNet, DeepLabv3, DeepLabv3+, ResT and Res-Swin. The results show that FDTNet has better classification performance than the compared methods in two types of farmland scenes, which have single texture and large sample size, or multiple texture and small sample size. The proposed FDTNet has a comprehensive ability to extract effective features of multiple category crops. Reference | Related Articles | Metrics

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Deep learning algorithm for feature matching of cross modality remote sensing images LAN Chaozhen, LU Wanjie, YU Junming, XU Qing Acta Geodaetica et Cartographica Sinica    2021, 50 (2): 189-202.   DOI: 10.11947/j.AGCS.2021.20200048 Abstract （3271）   HTML （236）    PDF（pc） （25649KB）（3256）       Knowledge map    Save Focusing on the problem of difficulty in matching due to the differences in imaging modality, time phases, and resolutions of cross modality remote sensing images, a new deep learning feature matching method named CMM-Net is proposed. First, a convolutional neural network is used to extract high-dimensional feature maps of the cross modality remote sensing images. The key points are selected according to the conditions that both the channel maximum and local maximum are met, and the 512-dimensional descriptors in corresponding location are extracted on the feature map to complete the feature extraction. In the matching stage, after completing the fast-nearest neighbor searching, in order to solve the problem of lots of mismatched points, a purification algorithm with dynamic adaptive Euclidean distance and RANSAC constraints is proposed to ensure that the mismatches are effectively eliminated while retaining the correct matches. The algorithm was tested using multiple sets of cross modality remote sensing images and compared with other algorithms. The results show that the proposed algorithm has the ability to extract similar scale invariant features in cross modality images, and has strong adaptability and robustness. Reference | Related Articles | Metrics

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Status analysis and research of sample database for intelligent interpretation of remote sensing image GONG Jianya, XU Yue, HU Xiangyun, JIANG Liangcun, ZHANG Mi Acta Geodaetica et Cartographica Sinica    2021, 50 (8): 1013-1022.   DOI: 10.11947/j.AGCS.2021.20210085 Abstract （1295）   HTML （125）    PDF（pc） （1747KB）（2404）       Knowledge map    Save The rapid development of earth observation projects in China has obtained a large volume of multi-source (multi-type sensors, multi-temporal, multi-scale) remote sensing data. But the capability of intelligent remote sensing image processing lags behind data acquisition. In recent years, people have significantly improved the effectiveness of image feature extraction with deep learning networks. But limited number and variety of sample data is not enough for processing the multi-source remote sensing images. This paper analyzed existing sample datasets and proposed a method for constructing a sample database for intelligent remote sensing image interpretation, including the data model, classification system, data organization, as well as the Internet-based platform for collaborative sample collection and sharing. Reference | Related Articles | Metrics

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Geographic Knowledge Graph Building Extracted from Multi-sourced Heterogeneous Data JIANG Bingchuan, WAN Gang, XU Jian, LI Feng, WEN Huiqi Acta Geodaetica et Cartographica Sinica    2018, 47 (8): 1051-1061.   DOI: 10.11947/j.AGCS.2018.20180113 Abstract （2657）   HTML    PDF（pc） （2571KB）（4322）       Knowledge map    Save 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. Reference | Related Articles | Metrics

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An InSAR phase unwrapping method based on R2AU-Net HE Yi, YANG Wang, ZHU Qing Acta Geodaetica et Cartographica Sinica    2024, 53 (3): 435-449.   DOI: 10.11947/j.AGCS.2024.20230305 Abstract （70）   HTML （4）    PDF（pc） （17203KB）（69）       Knowledge map    Save The accuracy of terrain elevation or surface deformation retrieval relies heavily on the quality of InSAR phase unwrapping. Conventional phase unwrapping techniques, rooted in non-machine learning models (such as path-following or minimum norm), face challenges in producing accurate unwrapping outcomes within areas of low coherence or high phase gradients (dense interference fringes). Deep neural network models offer distinct advantages in nonlinear representation and feature expression, widely employed in digital image processing research, wherein InSAR phase unwrapping parallels image regression.This paper presents an InSAR phase unwrapping approach utilizing the R2AU-net. Initially, pairs of wrapped and unwrapped phases are simulated through mathematical fractal methods, circumventing inherent errors and artifacts introduced by integrating external DEMs into the phase. This approach maintains terrain feature diversity and complexity while providing the requisite dataset for model training. Subsequently, the R2AU-net phase unwrapping model, built upon the foundational U-net model, incorporates attention mechanisms to augment the model's convolutional feature selection capacity, thereby improving unwrapping performance in regions of low coherence or dense striping. The utilization of recurrent residual convolutional structures addresses the vanishing gradient issue, enhancing the model's feature representation capability.Ultimately, experimental analyses are conducted using both simulated and real data. The results demonstrate that the proposed R2AU-net phase unwrapping model effectively retains terrain elevation or real surface deformation information, thereby bolstering the reliability of unwrapping outcomes. In terms of performance, it surpasses established methods such as the Goldstein branch-cut method, SNAPHU method, as well as CNN and U-Net phase unwrapping models. Reference | Related Articles | Metrics

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Concepts of Comprehensive PNT and Related Key Technologies YANG Yuanxi Acta Geodaetica et Cartographica Sinica    2016, 45 (5): 505-510.   DOI: 10.11947/j.AGCS.2016.20160127 Abstract （3132）   HTML    PDF（pc） （1232KB）（3490）       Knowledge map    Save The core idea of comprehensive positioning, navigation and time (PNT) is the technique that uses all the available resources to provide PNT services in the whole area, including inside and outside door, air, space, under water and underground, which does not solely rely on the GNSS. The definition and basic concepts of the comprehensive PNT are presented. The possible signal sources are listed. The core technologies related to the comprehensive PNT are analyzed, including the integration of the multiple sensors and adaptive data fusion for multiple PNT signals. It is emphasized that the information of the comprehensive PNT should be from "multiple sources based on different physical principles", the control system should be operated by voluntary users based on cloud platform, the user terminals or sensors should be "deeply integrated" and the PNT information should be "adaptively fused" and serve mode might be based on cloud platform. The comprehensive PNT system should meet the robust availability, continuity, high accuracy and reliability with unified geodetic datum and time datum. Reference | Related Articles | Metrics

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An Overview on Data Mining of Nighttime Light Remote Sensing LI Deren, LI Xi Acta Geodaetica et Cartographica Sinica    2015, 44 (6): 591-601.   DOI: 10.11947/j.AGCS.2015.20150149 Abstract （3670）   HTML    PDF（pc） （1051KB）（6422）       Knowledge map    Save When observing the Earth from above at night, it is clear that the human settlement and major economic regions emit glorious light. At cloud-free nights, some remote sensing satellites can record visible radiance source, including city light, fishing boat light and fire, and these nighttime cloud-free images are remotely sensed nighttime light images. Different from daytime remote sensing, nighttime light remote sensing provides a unique perspective on human social activities, thus it has been widely used for spatial data mining of socioeconomic domains. Historically, researches on nighttime light remote sensing mostly focus on urban land cover and urban expansion mapping using DMSP/OLS imagery, but the nighttime light images are not the unique remote sensing source to do these works. Through decades of development of nighttime light product, the nighttime light remote sensing application has been extended to numerous interesting and scientific study domains such as econometrics, poverty estimation, light pollution, fishery and armed conflict. Among the application cases, it is surprising to see the Gross Domestic Production (GDP) data can be corrected using the nighttime light data, and it is interesting to see mechanism of several diseases can be revealed by nighttime light images, while nighttime light are the unique remote sensing source to do the above works. As the nighttime light remote sensing has numerous applications, it is important to summarize the application of nighttime light remote sensing and its data mining fields. This paper introduced major satellite platform and sensors for observing nighttime light at first. Consequently, the paper summarized the progress of nighttime light remote sensing data mining in socioeconomic parameter estimation, urbanization monitoring, important event evaluation, environmental and healthy effects, fishery dynamic mapping, epidemiological research and natural gas flaring monitoring. Finally, future trends of nighttime light remote sensing and its data mining have been proposed from four aspects including new data source, knowledge discovery, in-situ observation, and national/global geographic conditions monitoring. Reference | Related Articles | Metrics

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Cartography：its past, present and future WANG Jiayao, WU Fang, YAN Haowen Acta Geodaetica et Cartographica Sinica    2022, 51 (6): 829-842.   DOI: 10.11947/j.AGCS.2022.20210661 Abstract （1186）   HTML （96）    PDF（pc） （1445KB）（1170）       Knowledge map    Save Currently, cartography, as well as other disciplines such as geography, is at a time of great revolution. While cartography is making progress continuously, various "trend of thoughts" and "points of view" appear, such as "is cartography marginalized?" and "where should cartography go?" These arise great concerns in the circles of both academy and industry of geoinformation. To answer the questions, firstly, this paper briefly introduces the development history of cartography, including reviewing the three times of rise in the history of cartography. It is not forgetting the past that can go to the future successfully. A review of the history of cartography is for the purpose of making cartography walk to the future better. Secondly, the achievements of contemporary cartography are analyzed, including the discipline systems of cartography, new minds, new thoughts and new methods in cartography, intelligent map generalization and cascade renewal of multiscale maps, social influences of maps, and inexhaustible driving forces of cartography development. It is to know present that can start a good future. Finally, to play the leading role of cartographic philosophy in innovative development of cartography, the paper addresses the development of cartography promoted by artificial intelligence and the achievements in visualization of spatio-temporal big data and visual design. It deems that cartography will certainly develop at an integrated direction of both high differentiation and high synthetization, and the rerise of cartography is the great trend of the time. Reference | Related Articles | Metrics