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    20 July 2022, Volume 51 Issue 7
    Academician Forum
    Review and prospect in change detection of multi-temporal remote sensing images
    ZHANG Zuxun, JIANG Huiwei, PANG Shiyan, HU Xiangyun
    2022, 51(7):  1091-1107.  doi:10.11947/j.AGCS.2022.20220070
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    Change detection (CD), as one of the hot spots in the field of photogrammetry and remote sensing, is a technology branch with important research value in artificial intelligence (AI) systems. The rapid development and deep integration of the two subjects have made it possible to automatic and intelligent process the massive, complex and diverse remote sensing datasets. It has been widely used in many areas, such as resources monitoring, urban planning, disaster assessment, etc. With the development of the remote sensing and computing power, change detection is also evolving. This paper mainly analyzes and summarizes the current change detection methods from the perspectives of geometry and semantics. We focus on the utilization of geometric information and the feature fusion method of deep neural networks. Furthermore, the paper provides a summary of open datasets derived from different sensors, along with information related to change detection. Finally, we point out the challenges of the change detection and the future trends of the area are summarized and prospected.
    Pan-map representation in ICT era
    GUO Renzhong, CHEN Yebin, MA Ding, ZHAO Zhigang, YING Shen
    2022, 51(7):  1108-1113.  doi:10.11947/j.AGCS.2022.20220140
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    The advancements of information and communication technology (ICT) offer us great freedom to creating maps or geographic representations. Such a cartographic renaissance facilitates the development of Pan-map theory. The present study analyzes systematically the evolution of map definition and clarifies promptly the concept of Pan-map. By unifying conventional standard maps and other creative map forms-map-likes-within the Pan-map theoretical framework, the study proposes a classification system that includes standard maps, realistic maps, and idealistic maps and discusses how these map categories, together with their styles and continuous transitions, contribute to Pan-map visualization.
    Progress and evolution of contemporary GNSS
    TAN Shusen, ZHANG Tianqiao
    2022, 51(7):  1114-1118.  doi:10.11947/j.AGCS.2022.20220138
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    It has been nearly half a century since the United States and the Soviet Union proposed the construction of GPS and GLONASS respectively. Over the past half century, GNSS has profoundly changed the military struggle, economy, society and daily life of mankind. In order to meet the future progress of human civilization and the new needs of the intelligent era, GNSS still needs further innovation and evolution. This paper systematically summarizes the development progress and enlightenment of contemporary GNSS, studies the direction of GNSS deep transformation needed in the intelligent era, and puts forward the scheme of GNSS transformation and development, which can be used as a reference for GNSS designers and builders.
    Progress in deformation modeling of an SNREI Earth
    SUN Heping, ZHOU Jiangcun, XU Jianqiao
    2022, 51(7):  1119-1129.  doi:10.11947/j.AGCS.2022.20220105
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    Acquiring the characteristics of the Earth's deformation induced by the internal and external forces is the key to recognizing the Earth's internal structure and dynamic processes. Observing and investigating the global and regional deformation is one of the important tasks for constructing and maintaining a high precision space-time reference. This paper introduces in details the main progress in the theoretical modeling of the Earth's deformation. The emphases are on the loading effects of the atmosphere, oceans, land water and heat, as well as the deformation caused by seismic dislocation. The main points involve the fundamental theory of (heat) elastic deformation, the efficient methods to the solution and the difficulties in the computation, as well as the solving strategies to these difficulties. Finally, on the basis of the elastic deformation, we prospect the requirements and potential applications of the Earth's deformation theories under the background that the accuracies of the instruments are more and more improved and human's activities intensively affect the global environment.
    Technical connotation and research agenda of natural resources spatio-temporal information
    CHEN Jun, WU Hao, LIU Wanzeng, SHAN Weidong, ZHANG Jun, ZHAO Pengjun
    2022, 51(7):  1130-1140.  doi:10.11947/j.AGCS.2022.20210643
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    Talking with the spatio-temporal information, judging in three-dimensional space and making decisions based on scientific facts are not only the main initiative to improve natural resources management and build a modern governance system, but also a formidable challenge for the surveying and mapping technology domain. Therefore, we should strengthen the technological innovation of spatio-temporal information, promote its deep integration with natural resources business, build a new generation of natural resources spatio-temporal information technology system, provide high-quality spatio-temporal information, carry out high-level spatio-temporal analysis and implement a high-level of spatial-temporal empowerment. This paper analyzes the main technical needs of natural resources management for spatio-temporal information, discusses the technical connotation of natural resources spatio-temporal information, proposes the general development of "comprehensive dynamic perception, systematic accurate cognition, and domain-wide intelligent control" as the main line, and outlooks the future research direction.
    Research framework of remote sensing monitoring and real-time diagnosis of earth surface anomalies
    WANG Qiao
    2022, 51(7):  1141-1152.  doi:10.11947/j.AGCS.2022.20220124
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    Due to the abruptness, diversity, randomness and complexity of all kinds of earth surface anomalies caused by natural and human factors, the time-effectiveness of traditional satellite remote sensing is seriously lagging behind the actual needs of earth surface anomaly warning and emergency treatment. Real-time and intelligent remote sensing monitoring of earth surface anomalies has become an important strategic demand for high-quality social and economic development in China in the new era, and also a major technical challenge for the development of remote sensing science. Based on the analysis of the technical challenges and the necessity of research on the real-time remote sensing monitoring of earth surface anomalies, this paper focuses on solving the scientific problems behind the technical bottleneck of "not being able to see, not being able to see clearly and not being able to see quickly" in remote sensing monitoring of earth surface anomalies. From a new perspective of the trinity of satellite, payload and application, a series of new ideas on real-time monitoring of surface anomalies by the integration of "communication-navigation-remote sensing", on-orbit processing and satellite-earth reciprocal feeding machine learning have been put forward. A research framework for real-time remote sensing monitoring of earth surface anomalies is proposed, which consists of remote sensing response characteristics and semantic characterization of earth surface anomalies, adaptive real-time remote sensing monitoring of large dynamic range, real-time remote sensing detection in orbit, and real-time generation and expression of remote sensing early warning knowledge, these studies provide a scientific scheme for in-depth research on the mechanism and method of real-time monitoring of earth surface anomalies by remote sensing, and provide a the technical system framework for realizing real-time service of remote sensing monitoring and early warning products for earth surface anomalies up to the user's mobile terminal.
    The development and prospect of China's space earth observation technology
    JIANG Bitao
    2022, 51(7):  1153-1159.  doi:10.11947/j.AGCS.2022.20220199
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    After more than 50 years of development, China's space earth observation technology has made great strides from scratch and from weak to strong, and it has been widely used in such fields as economic construction, national defense security and so on. At present, the internet of things, big data, cloud computing, artificial intelligence and other technology have rapidly developed, space observation technology is undergoing profound changes. In order to grasp the technological development context and promote the high-quality development of China's space earth observation field during the 14th Five-year Plan period, the development history of China's space earth observation technology is systematically summarized. The opportunities and challenges facing China's space earth observation technology are analyzed from the aspects of international competition, domestic demand and technological innovation, and the development direction of the construction of giant constellations and massive data processing and intelligence fusion application and other technologies are prospected.
    Geodesy and Navigation
    Fusing acoustic ranges and inertial sensors using a data and model dual-driven approach
    CHEN Ruizhi, QIAN Long, NIU Xiaoguang, XU Shihao, CHEN Liang, QIU Chao
    2022, 51(7):  1160-1171.  doi:10.11947/j.AGCS.2022.20220169
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    BDS started providing services worldwide since 2020. It can offer centimeter level positioning service when an open sky is available. BDS is now making a step further to become a more ubiquitous, integrated and intelligent system. At the meantime, high precise indoor positioning techniques are still under developments. Among these techniques, Apple has adapted the ultra-wideband (UWB) technique to iPhone and tried to push this technique to mass-market. While other new positioning techniques such as 5G, acoustic ranging, WiFi round-trip-time (RTT) and bluetooth (BT) angle of arrive (AoA) which support pervasive smartphones are alse competitive. For indoor positioning, it is still facing the challenges of low accuracy, high cost, small signal coverage and limited capability of generalization. Fusing multiple positioning sources method is one of the important approaches to solve these problems. Especially the fusing combination of low-cost inertial positioning source and high-accuracy radio frequency/acoustic positioning source has practical applicable value at present. Pedestrian dead reckoning (PDR) positioning source based on inertial sensors has advantage of the capability to alleviate error accumulation in double integration. However, it is still facing difficulties because of the complex of smartphone holding poses and the diversity of sensor hardware performance. Furthermore, this step-wise approach also limits the position update rate to less than 2 Hz. In order to develop a low-cost, high-precision and wide-coverage indoor positioning solution, a new approach of fusing acoustic ranges and inertial sensors by using a data and model dual-driven method is proposed in this paper. The data driven PDR solution part is developed based on a neural network, it is a deep learning approach by training a network to learn the velocity vector using the inertial measurements as input. The learned velocity vector is then used to propagate the PDR trajectory, which is further integrated with the high precise acoustic ranging measurements by an extended Kalman filter(EKF) in the model driven part. The proposed solution can offer a positioning accuracy of 0.23 meters at a position update rate of 20 Hz.
    Recent progresses and future prospectives of ground-based GNSS water vapor sounding
    ZHANG Kefei, LI Haobo, WANG Xiaoming, ZHU Dantong, HE Qimin, LI Longjiang, HU Andong, ZHENG Nanshan, LI Huaizhan
    2022, 51(7):  1172-1191.  doi:10.11947/j.AGCS.2022.20220149
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    Water vapor is one of the most important parameters that can be used to investigate extreme weather events and climatic phenomena. Effective monitoring and analyses of the water vapor content are of great significance for forecasting various types of meteorological disaster events and analyses of climatic changes. Ground-based GNSS, as a relatively newly emerged atmospheric sounding technique, has been widely applied to the sounding of atmospheric water vapor. The performance of the ground-based GNSS water vapor sounding technique has experienced unprecedented developments with the substantial strengthened richness of multi-frequency and multi-mode as well as its global operation ability and wide-spread ground-based infrastructures. All these offer strong data support and a great opportunity to advance our knowledge and an in-depth understanding of climate change and extreme weather events. The primary purpose of this paper is to synthesize and to review the current status and developments of the ground-based GNSS water vapor sounding technique. First, recent primary progresses and significant achievements in the retrieval of various types of atmospheric parameters using the ground-based GNSS technique are comprehensively summarized. Then, the theory, technical feature and major advancement of the GNSS-derived atmospheric products in the applications of climate analyses and extreme weather forecasting are presented. Finally, the challenges, opportunities and future prospectives in terms of the technique and its innovative applications of national and international significance are provided.
    Analysis on 3D crustal deformation of Qinghai-Tibet Plateau and its surrounding areas based on block model
    DANG Yamin, YANG Qiang, WANG Wei, LIANG Yuke
    2022, 51(7):  1192-1205.  doi:10.11947/j.AGCS.2022.20220123
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    2020 height measurement of Mount Qomolangma has obtained rich GNSS monitoring data of Qinghai-Tibet Plateau and its surrounding areas. This paper collected the long-term observation data of GNSS from CMONOC and Nepal CORS network, got the 3D velocity field of GNSS for more than 20 years, and used GRACE model to eliminate the influence of non-tectonic load deformation and improve the accuracy of vertical velocity field. Then, it studied the characteristics of crustal movement and tectonic deformation of the Qinghai-Tibet Plateau from many aspects such as crustal movement, block movement and strain, block relative movement through the block model. The results show that the crustal deformation of the Qinghai-Tibet Plateau has obvious zoning characteristics. The north-south contraction is mainly manifested in the Lasa block, the east-west extension is mainly manifested in the Bayankala block, and the Qiangtang block has no obvious horizontal compression, but the crustal uplift rate is the largest, and the horizontal area tends to expand. The results of this paper can support the crustal thickening theory of the Qinghai-Tibet Plateau.
    Real-time wide-area precise positioning and precise timing service system
    SHI Chuang, GU Shengfeng, LOU Yidong, ZHENG Fu, SONG Wei, ZHANG Dong, MAO Feiyu
    2022, 51(7):  1206-1214.  doi:10.11947/j.AGCS.2022.20220153
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    Wide-area real-time accurate positioning and timing service has become a hotspot in the field of GNSS. At present, domestic and foreign scholars have carried out a lot of valuable research on the model and algorithm. The method of data processing and service system construction for real-time wide-area precise positioning (WPP) and wide-area precise timing (WPT) is investigated in this paper. Various clock datums, including the quasi-stable datum of satellite clocks, the quasi-stable datum of station atomic clocks, and the datum of standard time, are proposed for the constraint on clock estimation solution by introducing stations that are linked to external atomic frequency standard or the source of standard time (UTC/BDT) in the solution. Also, the impact of clock datum on PPP, precise point timing (PPT) is analyzed. In this paper, the real-time products of the satellite orbit, clock errors, phase biases and ionospheric delays, as well as the real-time tracking station data, are utilized to verify the products reliability of the system and the performance of terminal positioning and timing service. The results of the real-time products indicate that the average RMS of radial orbit errors is 1.8 cm and 6.7 cm, and the average STD of clock errors is about 0.05 ns and better than 0.1 ns for GPS and BDS-3, respectively; the accuracy of ionospheric delays is 0.74 TECU and 1.03 TECU for GPS and BDS-2, respectively. Based on the above products, PPP/PPP-RTK and PPT/PPT-RTK services that meet real-time positioning of centimeter-level and one-way timing better than 0.5 ns are realized. It takes about 12 min to reach the positioning accuracy under 5 cm for the horizontal component in the GPS+BDS-2 PPP-RTK solution.
    Corrections of solid earth tide and ocean tide for measurement of deflection of the vertical
    GUO Jinyun, JIN Xin, BIAN Shaofeng, CHANG Xiaotao
    2022, 51(7):  1215-1224.  doi:10.11947/j.AGCS.2022.20220104
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    The deflection of the vertical (DOV) is the basic data for geodesy and geophysics. The solid earth tide and ocean tide are important factors affecting the precision of DOV measurement.The correction of the solid earth tide mainly includes the direct effect of celestial tidal-generating potential on the DOV, and the indirect effect of additional gravitational potential caused by solid earth deformation.Based on the spherical harmonic expansion theory of the gravitational field, this paper deduces the correction formulae of the solid earth tide and ocean tide for DOV measurement. Using JPL DE421 ephemeris model and EOT11A tide model, the DOV corrections on 19570 GNSS stations all over the world were calculated, and their temporal and spatial variations were then analyzed. The corrections of tidal-generating potentials of solar and lunar and its additional gravitational potentials, and ocean tide for the meridian and prime vertical components of DOV are given bythe examples. The updated precision of DOV measurement can reach the level of 0.1″, however, the DOV corrections of the solid earth tide and the ocean tide account for about 17% of the first-class astronomical accuracy (0.3″) in China. It must be taken into account the corrections of solid earth tide and ocean tide in the applications of precise DOV.
    GNSS undifferenced and uncombined data processing and PPP-RTK high-precision positioning
    YUAN Yunbin, HOU Pengyu, ZHANG Baocheng
    2022, 51(7):  1225-1238.  doi:10.11947/j.AGCS.2022.20220134
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    This work discusses the origins, features, and applications of GNSS differenced and combined data processing methods. After pointing out some limits of the differenced and combined methods under the background of multi-frequency and multi-GNSS, we summarize the advantages of the undifferenced and uncombined data processing method and introduce the rank-deficiency elimination strategy that is used to construct full-rank undifferenced and uncombined models. Based on this strategy, we systematically formulate a class of undifferenced and uncombined integer ambiguity resolution-enabled precise point positioning (PPP-RTK) functional models, including code-plus-phase and phase-only categories. Both categories impose different constraints on ionospheric delays and yield three variants, including ionosphere-weighted, ionosphere-float, and ionosphere-fixed variants. All variants consider both code and frequency division multiple access signals. Finally, we evaluate the undifferenced and uncombined PPP-RTK performance by conducting boat-borne, airborne, and tractor-borne positioning experiments. Results show that, for three cases, the time to first fix is less than 10 s, the ambiguity success rate is higher than 96%, the horizontal positioning accuracy is better than 2 cm, and the vertical positioning accuracy is better than 5 cm. For Galileo+GPS+BDS triple-system tractor-borne positioning, the performance of phase-only PPP-RTK is comparable to that of code-plus-phase PPP-RTK. Compared to Galileo+GPS dual-system positioning, triple-system positioning decreases the time to first fix from several hundreds of seconds to several seconds, improves the ambiguity success rate from approximately 85% to better than 99%, and improves the positioning accuracy by approximately 30%.
    Parameters estimation and applications from single- to five-frequency multi-GNSS precise point positioning
    JIN Shuanggen, WANG Qisheng, SHI Qiqi
    2022, 51(7):  1239-1248.  doi:10.11947/j.AGCS.2022.20220129
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    Global navigation satellite system (GNSS) has been developed into the era of multi-frequency multi-GNSS, particularly four global navigation satellite systems including China's BeiDou navigation satellite system (BDS) with broadcasting more than ten frequencies of all-day and all-time observation information about pseudo-range, phase and Doppler. Multi-frequency multi-GNSS provides users more observations with more combination choices and new opportunities for the applications of precise positioning, navigation and timing (PNT), such as high precision location-based services, geodesy, space weather and disaster monitoring. However, the multi-frequency and multi-GNSS brings numerous questions and challenges, e.g. the combination models and system bias of GNSS precise point positioning (PPP) as well as atmospheric delay estimation. This paper presents multi-GNSS PPP models from single- to five-frequency observations. The PPP performance, receiver clock difference, tropospheric delay, satellite and receiver hardware delay, and inter-frequency bias are estimated and assessed from single- to five-frequency multi-GNSS observations. The latest advances on GNSS PPP applications are presented, including GNSS meteorology, ionospheric modeling, time-frequency transfer, structure health and earthquake monitoring as well as their related applications. The results show that the multi-frequency multi-GNSS has greatly improved the accuracy and reliability of PPP in parameters estimation, which has an important application value. Finally, the application prospective and outlook of multi-frequency multi-GNSS PPP are given and discussed.
    A new vehicle motion constraint model with parameter autonomous learning and analysis on inertial drift error suppression
    ZHANG Xiaohong, ZHOU Yuhui, ZHU Feng, HU Haojie
    2022, 51(7):  1249-1258.  doi:10.11947/j.AGCS.2022.20220141
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    Accurate, continuous and reliable location information is the basic condition for in-vehicle navigation applications. Under the premise of not adding other sensors, integrating GNSS, MEMS, on-board CAN sensors and vehicle motion constraint information is the most practical and low-cost vehicle multi-fusion navigation scheme. In the vehicle motion constraints, reasonable configuration of the relevant parameters is the key to making the constraints work fully. Thus, focusing on the vehicle non-integrity constraints, this article uses multiple regression and deep learning methods to build a new vehicle motion constraint model with parameter autonomous learning. Moreover, a new idea of directly learning lateral/vertical velocity parameters in the observation domain is proposed, which has better constraint effect than the old variance domain parameter adjustment method. The experiments show that compared with the traditional method of adjusting parameters in the variance domain, the new model with parameter autonomous learning in the observation domain has a significant improvement in accuracy. The inertial estimation error using the multivariate regression models is reduced by 69.6%~81.2% in the horizontal position, while the use of deep learning is reduced by 60.0%~77.3%. At the same time, the horizontal relative positioning accuracy is improved by 75.2% and 65.0% respectively, the new model can effectively improve the maintenance ability of vehicle positioning accuracy when GNSS failure.
    Progress and thoughts on establishment of geodetic coordinate frame
    JIANG Weiping, LI Zhao, WEI Na, LIU Jingnan
    2022, 51(7):  1259-1270.  doi:10.11947/j.AGCS.2022.20220232
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    Coordinate frame is the basis for describing the Earth's shape and its variation, as well as geospatial information. It is also a key geospatial information infrastructure to expand human activities and promote social development. With development of space geodetic observation technologies together with integration of earth science and related disciplines, establishment of global and regional coordinate frame based on space geodetic techniques has become the main task of geodesy field at present, while the goal of building coordinate frame with 1 millimeter (mm) level prove to be both the disciplinary goal and great challenge for international geodesy community of the 21st century. Taking the most widely used International Terrestrial Reference Frame (ITRF) with perfect theory and the highest accuracy as an example, this paper firstly describes the method of establishing coordinate frame based on space geodetic technologies. Secondly, the latest progress and limitations of recent global/regional coordinate frames are illustrated. Finally, ideas for several key issues aiming at establishing the 1 mm level coordinate frame are proposed.
    Review of GNSS precise orbit determination: status, challenges, and opportunities
    LI Xingxing, ZHANG Wei, YUAN Yongqiang, ZHANG Keke, WU Jiaqi, LOU Jiaqing, LI Jie, ZHENG Hongjie
    2022, 51(7):  1271-1293.  doi:10.11947/j.AGCS.2022.20220173
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    Precise orbit of GNSS satellites is the foundation and prerequisite of GNSS high-precision applications, and the technology of GNSS precise orbit determination (POD) has always been the research focus and hotspot in the field of satellite navigation. This paper firstly introduces the general situation of GNSS constellation and tracking data. The key issues in the construction of the function model, dynamic model and stochastic model in GNSS POD are sorted out. The research progress of GNSS precise orbit determination with the augmentation of low earth orbit (LEO) onboard data and inter satellite link (ISL) data is concluded. Then, from the application point of view, the basic status of current GNSS precision orbit products is summarized, followed by the orbit accuracy evaluation. Finally, the challenges of GNSS precise orbit determination in the rapid solution of massive GNSS network, the data fusion of multi-level observations, the refinement of solar radiation pressure (SRP) models, and the high-precision real-time POD are discussed. The opportunities brought by the development of LEO constellation, optical clock, and laser link in GNSS POD are also prospected.
    The causes of contemporary sea level rise over recent two decades: progress and challenge
    XU Tianhe, MU Dapeng, YAN Haoming, GUO Jinyun, YIN Peng
    2022, 51(7):  1294-1305.  doi:10.11947/j.AGCS.2022.20220091
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    Revealing the cause of global mean sea level (GMSL) rise helps to advance the knowledge of current climate change, and make adaptive planning. Space geodesy technique along with Argo float greatly improves the investigation of the cause of sea level rise on global and regional scales. These observations serve as important supplements to model output that usually fail to capture long-term trend, in addition to providing independent verifications, they also help to understand the drivers of sea level change on long-term and interannual scales. This paper reviews the achievements and progresses in the cause of sea level change, with a particular focus on discussing the contributions of mass variations over global land area. Observations suggests that, over recent two decades, 65% GMSL rise is caused by ocean mass increase due to mass loss in polar ice sheet and mountain glacier, and land hydrology. The remaining GMSL rise is induced by ocean thermal expansion. Given that global warming is expected to continue, both ice mass loss and ocean thermal expansion are associated with acceleration, which results in accelerated GMSL rise. These results have important implications for understanding climate change and projecting future GMSL rise. Except for presenting the major achievements, we also highlight some challenges that confront the study of the cause of GMSL rise, for example:①Observations are not able to close the sea level budget at local scales. ②The discrepancy of GMSL budget increases significantly after 2016.
    Photogrammetry and Remote Sensing
    Real-time forecast of urban flood in China: past, present and future
    LIN Hui, WU Xianyu, PAN Jiayi, ZOU Haibo
    2022, 51(7):  1306-1316.  doi:10.11947/j.AGCS.2022.20220144
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    Global climate change and rapid urbanization had broken the original balance of urban precipitation, catchment and drainage, and worsened the urban flood problem in China, resulting in huge loss of life and property. Therefore, it is urgent to explore accurate and efficient urban flood forecasting approaches to strengthen urban flood prediction and mitigate impacts of this disaster.However, the complexity of urban meteorological and hydrological processes makes the study of real-time urban flood prediction face many challenges.Based on detailed reviews, this paper summarizes the main causes of frequent urban flooding in China, and elucidates progress in data and models for real-time urban flood prediction, with descriptions of existing problems and challenges, and future developments.
    Data-driven multi-source remote sensing data fusion: progress and challenges
    ZHANG Liangpei, HE Jiang, YANG Qianqian, XIAO Yi, YUAN Qiangqiang
    2022, 51(7):  1317-1337.  doi:10.11947/j.AGCS.2022.20220171
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    Multi-source remote sensing data fusion is an important technology to generate seamless observation data of large scene with a high temporal-spatial-spectral resolution, which breaks through the limitation of single sensor observation and realize the complementary utilization of multi-platform and multi-mode observation data. With the improvement of artificial intelligence theory and technology, data-driven multi-source remote sensing data fusion has been widely favored by researchers. However, the inherent low physical interpretability and weak generalization ability of data-driven algorithms have impeded its further development in multi-source remote sensing data fusion. Therefore, this paper systematically summarizes the researches of homogeneous remote sensing data fusion, heterogeneous remote sensing data fusion and point-surface fusion through three sections, and analyzes the trend of each fusion problem. Finally, this paper discusses the challenges faced by data-driven fusion algorithm, and points out some feasible future directions of multi-source remote sensing data fusion, which provides some suggestions for researchers in this field.
    Application and prospect of the integration of InSAR and BDS/GNSS for land surface deformation monitoring
    HE Xiufeng, GAO Zhuang, XIAO Ruya, LUO Haibin, JIA Dongzhen, ZHANG Zhetao
    2022, 51(7):  1338-1355.  doi:10.11947/j.AGCS.2022.20220148
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    As flourishing space geodesy technologies, InSAR and BeiDou/GNSS have advantages in land surface deformation monitoring. By applying the two tools to carry out integrated measurements, their complementarity can be fully exploited to achieve the unification of high temporal resolution of BeiDou/GNSS and high spatial resolution of InSAR. This paper firstly introduces the basic principles of InSAR and BeiDou/GNSS for land surface deformation monitoring, focusing on the theoretical development of InSAR in the past two decades. Secondly, the latest progress of InSAR and BeiDou/GNSS integration and data fusion are reviewed. Then, the key issues and challenges faced by the land surface deformation monitoring applications are summarised. Finally, the future outlook of the deformation monitoring method integrating InSAR and BeiDou/GNSS is discussed.
    Progresses and possible frontiers in the study on seismic applications of multi-frequency and multi-polarization passive microwave remote sensing
    WU Lixin, QI Yuan, MAO Wenfei, LIU Shanjun, DING Yifan, JING Feng, SHEN Xuhui
    2022, 51(7):  1356-1371.  doi:10.11947/j.AGCS.2022.20220131
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    Passive microwave remote sensing satellites are capable of observing the Earth surface in mode of multi-frequency and multi-polarization, and its all-weather and high sensitivity characteristics satisfy the requirements of monitoring on and analyzing to crustal activity and earthquake. In recent years, remote sensing monitoring and analysis of thermal anomalies in the process of earthquake preparation and occurrence have been widely concerned. In this paper, the state-of-the-art of multi-frequency and multi-polarized passive microwave satellite remote sensing for earthquake monitoring and seismic anomaly detection are reviewed in terms of the development of satellite-borne passive microwave sensors and the earthquake application of passive microwave remote sensing. The deficiencies and achievements of the selection of microwave radiation data, the method of abnormity analysis, the elimination of gross error, and the cognition of info-physics are discussed. The recent progresses of passive microwave remote sensing in seismicity research are summarized, and the scientific logic and synergic chain of passive microwave satellite remote sensing with multi-frequency and multi-polarization on seismic monitoring and anomaly identification are presented. Moreover, two possible frontiers of the interdisciplinary of remote sensing and geophysics, i.e., the reliable identification of seismic anomaly from microwave radiation and the embedded info-physics of microwave remote sensing on the alteration of crust stress field, are pointed out. The related critical issues on the fundamental laboratory experiment of remote sensing rock mechanics and the synergic analysis of seismic remote sensing, which need to be solved urgently, are discussed. Finally, the authors suggest that multidisciplinary union, intersection and fusion are indispensable for further deepening the development of science and technology of seismicity remote sensing.
    Key issues of InSAR system designment based on satellite formation
    LOU Liangsheng, MIAO Jian, CHEN Junli, LIU Zhiming, ZHANG Xiaowei, ZHANG Hao
    2022, 51(7):  1372-1385.  doi:10.11947/j.AGCS.2022.20220110
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    The space-based InSAR system can be used in all-weather, all-day, and with high degree of data processing automation, which can measure the global digital surface models and acquire radar orthophotos in a short time, making it a promising system with broad development prospects. This paper firstly introduced the InSAR measurement method and the error transformation model which may affect the product accuracy, and expounded the InSAR system based on satellite formation. Then, by considering the two aspects of obtaining interference data and ensuring accuracy, it is proposed that without considering SAR technology, the main key technologies of satellite formation InSAR system design include:system coherence, baseline selection, satellite formation configuration, cooperative mode of two satellites, product precision control, et al. On the basis of summarizing the key technologies of satellites, this paper analyzes the performance and core indicators involved in these key technologies, and proposes the elements to be concerned about in the design.
    Establishment and application of China civil optical satellite surveying and mapping products
    TANG Xinming, WANG Hongyan
    2022, 51(7):  1386-1397.  doi:10.11947/j.AGCS.2022.20220181
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    With more than a decade development, civil optical satellite surveying and mapping and its applications in China have made great progress. In this paper, we systematically summarizes the general situation of technical parameters and data acquisition of China's civil optical satellites in-orbit, especially stereo surveying and mapping satellites.Based on the introduction of satellite surveying and mapping product processing and system construction, we summarize the applications of satellite surveying and mapping technology and its products, and conclude with the forward to the development of surveying and mapping satellites and satellite surveying and mapping applications during the 14th Five Year Plan period.
    Geo-cognitive models and methods for intelligent interpretation of remotely sensed big data
    ZHANG Bing, YANG Xiaomei, GAO Lianru, MENG Yu, SUN Xian, XIAO Chenchao, NI Li
    2022, 51(7):  1398-1415.  doi:10.11947/j.AGCS.2022.20220279
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    With the explosive growth of remotely sensed data and computing power, and the breakthrough of intelligent analysis algorithms, there is an urgent need to improve the capabilities to match in remotely sensed big data processing and analysis. Aiming at the crucial problems of coupling association and cross fusion of remotely sensed big data intelligent processing and geographical cognition in complex scenes, this paper analyzes the characteristics and relationships between remotely sensed big data and geographical science, puts forward the idea of building deep network of multimodal knowledge fusion and intelligent interpretation of remotely sensed data for geographical cartography, and establishes the framework of remotely sensed big data intelligent processing and application system. A general high-resolution remote sensing intelligent processing system for technology development and an intelligent application platform for industry applications are proposed, respectively, in order to boost the technological innovations and engineering applications of intelligent interpretation using remotely sensed big data.
    Technical progress of space-air-ground collaborative monitoring of landslide
    XU Qiang, ZHU Xing, LI Weile, DONG Xiujun, DAI Keren, JIANG Yanan, LU Huiyan, GUO Chen
    2022, 51(7):  1416-1436.  doi:10.11947/j.AGCS.2022.20220320
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    Landslide disaster is one of the natural disasters with the highest frequency, largest distribution, and highest losses worldwide, endangering human life and property as well as important engineering facilities. Scientific monitoring is one of the most significant measures for monitoring and early warning of landslide, as well as active prevention. Landslide monitoring has gradually evolved from traditional manual ground monitoring on specific site to multi-dimensional collaborative monitoring after years of technical research and integration of high-resolution optical remote sensing, satellite InSAR, UAV photogrammetry, wireless sensor network (WSN), and other new technology methods, allowing China to achieve remarkable results in geological disaster risk identification, monitoring, and early warning. Based on a professional understanding of the landslide occurrence mechanism and deformation damage process, this paper summarizes the most recent research progress in landslide monitoring technology in China from the three-dimensional perspectives of spaceborne (optical remote sensing and InSAR), airborne (UAV photogrammetry), and ground-based (global satellite navigation system, crack-meter, and other ground surface and internal monitoring of slope), analyzes, and discusses the technical advantages and disadvantages. The technical advantages and applicability of each in engineering practice are analyzed and discussed, and a new cooperative monitoring mode for the entire process of landslide deformation and damage is proposed, providing a new paradigm of thinking and experience guidance for the scientific prevention of landslide disasters.
    A review of developments in the theory and technology of three-dimensional reconstruction in digital aerial photogrammetry
    ZHANG Li, LIU Yuxuan, SUN Yangjie, LAN Chaozhen, AI Haibin, FAN Zhongli
    2022, 51(7):  1437-1457.  doi:10.11947/j.AGCS.2022.20220130
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    As one of the essential branches of photogrammetry, aerial photogrammetry has made significant progresses in the past decades. The emergence of various new working modes,such as oblique aerial photography and UAV photogrammetry, has brought new challenges to traditional aerial photogrammetry and has spawned many new solutions. In addition, new theories and techniques in computer vision technology and deep learning technology in artificial intelligence are continuously integrated into aerial photogrammetry, promoting the development of aerial photogrammetry in the direction of intelligence and automation. Therefore, modern aerial photogrammetry is already the product of the fusion of multiple sensors, the combination of various data acquisition methods, and the intersection of computer vision and machine learning technologies in traditional photogrammetry and artificial intelligence technologies. Three-dimensional reconstruction is the core problem of aerial photogrammetry. This paper expounds on the problems existing in modern aerial photogrammetry, summarizes and discusses the current research status from four aspects:corresponding tie points extraction of aerial images; block adjustment; image dense matching; and singleton modeling. And finally this paper gives the mainstream aerial image photogrammetry processing framework at home and abroad.
    Partial geoscience parameters inversion from InSAR observation
    LI Zhiwei, XU Wenbin, HU Jun, FENG Guangcai, YANG Zefa, LI Jia, ZHANG Heng, CHEN Qi, ZHU Jianjun, WANG Qijie, ZHAO Rong, DUAN Meng
    2022, 51(7):  1458-1475.  doi:10.11947/j.AGCS.2022.20220156
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    Natural factors or human activities can alter the stress of earth surface or its interior part, which generally causes disaster events. Obtaining the key geoscience paramters of disaster events and their developing progress is essential for us to accurately understand the disaster progress, scientifically interpret the disaster mechanism, and properly formulate acting strategy. InSAR is widely used in the parameter inversion of disaster events and their developing progress caused by natural factors or human activities. This paper firstly introduces the development of InSAR satellites and the basic principles of InSAR surface deformation monitoring. Subsequently, the research status of InSAR geoscience parameter inversion in various disaster-causing events is summarized, including earthquake, volcanic activity, groundwater extraction, mining, permafrost freezing and thawing, glacier movement, and underground fluid migration, etc. Finally, we conclude the main challenges and issues of InSAR geoscience parameter inversion.
    3D geospatial information extraction of urban objects for smart surveying and mapping
    YANG Bisheng, CHEN Chi, DONG Zhen
    2022, 51(7):  1476-1484.  doi:10.11947/j.AGCS.2022.20220183
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    3D spatial-temporal information is indispensable for the major national needs of new infrastructure construction, digital twin cities, natural resource management and monitoring. The rapid development of surveying and mapping equipment is beneficial to improve the convenience of point cloud and image acquisition, providing a new technical means for smart surveying and mapping. However, how to intelligently extract 3D spatial-temporal information from point cloud and image is still facing challenges. Surrounding the core of the smart surveying and mapping, this paper focuses on the key technologies and research progress of point cloud location accuracy improvement, point cloud and panoramic image fusion, component-level urban objects extraction, software development and practice.
    Interferometric synthetic aperture radar for deformation mapping: opportunities, challenges and the outlook
    LI Zhenhong, ZHU Wu, YU Chen, ZHANG Qin, ZHNAG Chenglong, LIU Zhenjiang, ZHANG Xuesong, CHEN Bo, DU Jiantao, SONG Chuang, HAN Bingquan, ZHOU Jiawei
    2022, 51(7):  1485-1519.  doi:10.11947/j.AGCS.2022.20220224
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    With frequent launches of synthetic aperture radar (SAR) satellites, interferometric SAR (InSAR) technology has been presented with unprecedented opportunities along with many new challenges for deformation mapping. In this paper, we concisely demonstrate the current development of SAR satellites and the principle of the InSAR technique, and then systematically review the advantages and disadvantages of a set of advanced InSAR techniques including InSAR stacking, small baseline subset InSAR (SBAS-InSAR), persistent scatterer InSAR (PS-InSAR),distributed scatterer InSAR (DS-InSAR) and split-bandwidth interferometry (SBI).On this basis, major challenges currently hampering InSAR applications (e.g., coherent loss, atmospheric distrubence, phase unwrapping errors, geometric distortions and multi-dimensional surface displacements) are investigated and their corresponding possible solutions are discussed. Then, we review the current status, particularly their limitations, of various typical InSAR applications under different scenarios such as earthquakes, volcanoes, landslides, ground subsidence, glaciers, infrastructure displacement monitoring, and atmospheric water vapour mapping. Finally, we present the outlook of InSAR, suggesting that with the continuous development of higher spatial resolution, higher temporal resolution and smaller SAR satellites, InSAR shall be applied to a number of new applications that cannot be achieved by traditional methods, bringing greater inspiration to the development of InSAR in China.
    Cartography and Geoinformation
    Advance and future development of the multi-scale spatial data linkage updating
    ZHANG Xinchang, HE Xianjin, SUN Ying, HUANG Jianfeng, ZHANG Zhiqiang
    2022, 51(7):  1520-1535.  doi:10.11947/j.AGCS.2022.20220095
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    Multi-scale spatial database is an important basis for administrative decision-making and planning at all levels of national economic construction, and also plays a key role in smart city and national defense construction. The current situation of data is related to the operation efficiency of database, and multi-scale spatial data linkage updating provides important technical support.With the development of artificial intelligence, geospatial big data and comprehensive intelligence of maps, many achievements have been made in the linkage updating of spatial data, though it also faces many challenges. Firstly, the research progress of linkage updating is described in terms of updating strategy, matching method, change information detection and updating information transmission of multi-scale spatial data. Secondly, the application of artificial intelligence technology in each stage of the linkage updating process is analyzed. Finally, combining with automatic maps generalization and the background of geospatial big data, the development trend of linkage updating in multi-scale spatial data is discussed.
    Advances in cartography from the perspective of Maslow's hierarchy of needs
    LI Zhilin, LAN Tian, TI Peng, XU Zhu
    2022, 51(7):  1536-1543.  doi:10.11947/j.AGCS.2022.20220170
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    As the most significant carrier of spatial information, map carries the demand of human being for obtaining spatial information and accompanies human being transforming human civilization from primitive society to agricultural society, industrial society and information society. Studying the advance in cartography is helpful not only to understand the evolution of human civilization but also to outlook at the future development of cartography. Existing studies tend to divide the history of cartography into several development stages by time or time plus a typical event. Such partitioning system cannot comprehensively reflect the close relationship between cartography and the process of human civilization.Therefore, this article examines the advance in cartography from the perspective of human needs, i.e., based on Maslow's hierarchy of needs in human life, and puts forward an outlook for the future of cartography.
    Recent advance and challenge in geospatial big data mining
    LIU Yaolin, LIU Qiliang, DENG Min, SHI Yan
    2022, 51(7):  1544-1560.  doi:10.11947/j.AGCS.2022.20220068
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    In the era of big data, geospatial big data provide new opportunities for understanding complex human-land relationships. Data mining is essential for revealing valuable spatio-temporal patterns (e.g., clusters, outliers, association rules, etc.) hidden in geospatial big data. Geospatial big data has some unique characteristics, e.g., fine spatio-temporal granularity, wide spatio-temporal scope, rich information on human-land relationships, high spatio-temporal bias, and low spatio-temporal precision. Geospatial big data requires specially designed data mining methods given its unique characteristics. In this study, we first analyzed the relationships between spatial data mining and geospatial big data mining, then reviewed recent advances in geospatial big data mining, and finally summarized the challenges and further research directions of geospatial big data mining. This review is expected to provide some valuable reference for the improvement of theories and methods of geospatial big data mining.
    Research on consistency processing of multi-source geospatial data
    SUN Qun, WEN Bowei, CHEN Xin
    2022, 51(7):  1561-1574.  doi:10.11947/j.AGCS.2022.20220151
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    The processing and application of multi-source geospatial data have been widely concerned recently. The consistency processing of multi-source geospatial data is a significant technology to eliminate the problems amang multi-source, heterogeneous, muti-temporal and multi-scale geospatial data, as well as a major way to produce and update geospatial data. In this paper, the main causes of inconsistency in multi-source geospatial data are firstly discussed, then the research progress of consistency processing is overviewed and evaluated from 3 aspects, namely geometric, semantic and spatial-relation. Based on the analysis above, a series of tough problems to be solved are expounded, where the future research priorities are put forward sequentially.
    Research progress and prospect of digital depth model constructing technology
    PENG Rencan, DONG Jian, JIA Shuaidong, TANG Lulu, WANG Fang
    2022, 51(7):  1575-1587.  doi:10.11947/j.AGCS.2022.20220142
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    Depth is the basic element that reflects the undulating shape of the submarine topography, and it is an important reference for human beings to understand and utilize the ocean and make scientific decisions.Digital depth model is a digital representation of submarine topography fluctuations using discrete depth data. The digital depth model constructing technology is closely related to the quality, characteristics and application fields,which directly determines the reliability and accuracy of the representation of the submarine topography,and will have an important impact on the safety of ship navigation and other related applications,has always been the core content of the scientific research of hydrographic and cartographers as well as the production practice of marine surveying and mapping geographic information products.On the basis of summarizing the conceptual connotation of digital depth model, combined with the current status of digital depth model constructing technology at home and abroad, this paper focuses on the research progress and achievements of digital depth model in navigational and non-navigational fields, and the future development direction of digital depth model constructing technology is prospected.
    A survey of the research progress in automated generalization of submarine terrain data
    WU Fang, DU Jiawei, WU Fanghua
    2022, 51(7):  1588-1605.  doi:10.11947/j.AGCS.2022.20220119
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    The submarine terrain data influences human cognition, exploration and utilization of the ocean largely. The generalization of submarine terrain data is one of the key researches of nautical chart generalization and oceanographic spatial data processing. Usually, the generalization of submarine terrain data belongs to map generalization. However, influenced by many factors, such as historical origin, disciplinary system, application target and so on, the generalization of submarine terrain data is often regarded as a relatively independent and special research content in map generalization. In this paper, the specificities of submarine terrain data generalization are explained at first. Furthermore, the development of submarine terrain data generalization is summarized from three aspects, i.e., the data enrichments, implementation methods and quality evaluations of submarine terrain data generalization. And then, three common use cases of submarine terrain data generalization are given. Finally, the development trend of submarine terrain data generalization is further discussed based on its content deficiency, technique upgrading and application prospect.
    Research progress and trend of intelligent interpretation for natural resources features
    ZHANG Jixian, GU Haiyan, YANG Yi, ZHANG He, LI Haitao, HAN Wenli, SHEN Jing
    2022, 51(7):  1606-1617.  doi:10.11947/j.AGCS.2022.20220109
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    Interpretation of natural resources features is the most basic, most widely used, most involved, and most technically difficult task in survey and monitoring work. It faces many challenges such as application understanding, accurate interpretation, and fine interpretation. Starting from the application scenarios of natural resource survey and monitoring, firstly, this article elaborates its research progress from three aspects:scene-features coupling interpretation mode, semantic understanding expression cognition, and human-computer collaborative interpretation methods. Then, it discusses six key research directions and basic ideas, including scene-feature coupling interpretation, knowledge-driven semantic understanding, human-machine collaborative intelligent interpretation, indoor and outdoor integrated and 3D environment interpretation, quantitative inversion of key parameters, high-confidence quality control and authenticity verification. Finally, summaries are given. This paper aims to provide some ideas for the research on intelligent interpretation of natural resources survey and monitoring features, and promote the solution of bottlenecks that plague the application of remote sensing image automatic interpretation methods in natural resource survey and monitoring applications.
    A review of web-based ubiquitous geospatial information discovery and integration technology
    LIU Jiping, WANG Yong, HU Yanzhu, LUO An, CHE Xianghong, LI Pengpeng, CAO Yuanhui
    2022, 51(7):  1618-1628.  doi:10.11947/j.AGCS.2022.20220102
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    There are many technical difficulties to discover and integrate geospatial information from web-based data considering its the ubiquitousness, diverse forms and structures. In this review, we first analyze the classification and characteristics of web-based ubiquitous geospatial information, upon which we systematically investigate the current progress of the discovery and integration technology. Here, the development status of discovery technology are summarized from four aspects of fast and accurate service discovery, deep network data collection with high coverage, location information extraction from unstructured text, and spatial semantic extraction of associated images. Subsequently, we analyze and explore the development trends of integration technology application to the matching and association of heterogeneous geometric data, address standardization, semantic alignment of homonymy entities, geographic entity relationships construction. Finally, we prospect the application of web-based ubiquitous geospatial information discovery and integration technology in many aspects such as open geospatial data network, urban governance and emergency management, network monitoring and geospatial intelligence.
    Network and graph-based SpaceTimeAI: conception, method and applications
    CHENG Tao, ZHANG Yang, James Haworth
    2022, 51(7):  1629-1639.  doi:10.11947/j.AGCS.2022.20220236
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    SpaceTimeAI and GeoAI are currently a hot topic, which apply the latest algorithms in computer science, such as deep learning. Although deep learning algorithms have been successfully applied in raster data processing due to their natural applicability to image processing, their applications in other spatial and space-time data types are still immature. This paper sets up the proposition of using the network (& graph)-based framework as a generic spatial structure to present space-time processes that are usually represented by the point, polyline, and polygon. We illustrate network and graph-based SpaceTimeAI, from graph-based deep learning for prediction, to clustering and optimisation. These demonstrate the advantages of the network (graph)-based SpaceTimeAI in the applications of transport & mobility, crime & policing, and public health.
    An interpretation and representation of scale concept in geo-information sciences
    AI Tinghua, ZHANG Xiang
    2022, 51(7):  1640-1652.  doi:10.11947/j.AGCS.2022.20220143
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    This study reviews issues of scale concept, scale effect and scaling transformation in geo-information sciences. A 3×3 matrix model is presented to jointly represent scale intension and extension, as well as the exploration of 9 sub-concepts of scale branches. Based on the interaction between sub-scale concepts, the study examines the dependence between scale broadness and granularity, the consistent change rules of temporal-spatial granularity and semantic-spatial granularity. Due to the importance of spatial relationship in spatial analysis and reasoning, three relationship granularities on topological, direction and distance geometry are discussed with corresponding computation methods. After the complete interpretation of scale concepts in Geo-information sciences, the paper offers the future works on scale question including the formalization of scale concept, no-change of scale questions and role of scaling transformation in spatial knowledge acquisition.
    Current status and prospects of research for volunteered geographic information
    FAN Hongchao, KONG Gefei, YANG Anran
    2022, 51(7):  1653-1668.  doi:10.11947/j.AGCS.2022.20220192
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    In comparison with the classic GIS, volunteered geographic information (VGI) reveals differently in data acquisition. It allows internet users to contribute geographic information data in different forms using the techniques of Web2.0. In the recent 20 years, VGI is getting more popular in research and applications as an important data source. In this paper, we did a literature study on articles related to VGI to show the development and the state of art of VGI. On this base, we discussed challenges and opportunities of the VGI in the future. In particular, suggestions have been made for VGI development in China.