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    Accessibility Analysis of Medical Facilities based on Multiple Transportation Modes of Network Map
    GUO Chenchen, LIANG Juanzhu
    Journal of Geo-information Science    2022, 24 (3): 483-494.   DOI: 10.12082/dqxxkx.2022.210260
    Abstract1111)   HTML197)    PDF (6509KB)(491)      

    Owing to the rapid advent of urbanization and the increasing demand for medical services by residents, the pressure on medical services in densely populated areas is surging. The analysis of the accessibility of medical service facilities is of primordial importance. In this study, the medical data was garnered from the Fuzhou Municipal Health Commission, and the crawler technology was used to yield the number of residential households to estimate the population. By use of the Baidu map to obtain the real time road condition information of the peak and non-peak time periods, the access time under the optimal route from the community residential districts to the hospital based on the real-time road condition was calculated, and the time zones of medical services were drawn. The accessibility of general hospitals in the main urban area of Fuzhou was analyzed using the two-step mobile (Ga-2SFCA) search method boosted by the Gaussian distance attenuation function, considering factors such as the travel mode, searching time threshold, and travel peak hours. The results yielded show that: (1) By integrating Baidu Map API into Ga-2SFCA model, multivariate and fine-grained analysis of accessibility was implemented, leading to the accurate measurement of urban medical service supply and demand; (2) The time cost of public transportation at different periods was less affected by traffic congestion, and reaching tertiary hospitals was faster. Under the premise of advocating green transportation, this mode of public transportation was recommended for medical treatment; (3) Under different conditions, the accessibility of medical facilities depended on the space of residential differentiation characteristics significantly, on the whole presenting a "single center" and "diminishing layer coil" distribution. High accessibility of residential areas was mainly distributed in urban core areas, and the lower level of accessibility settlement distribution was in the peripheral urban areas. However, other factors can also influence accessibility, such as the time threshold. The accessibility level of medical services markedly differed with the transportation mode, and the accessibility of medical services was significantly higher along the subway. The choice of off-peak travel time can effectively improve the level of medical service; (4) Due to the layout of urban expressways, the spatial distribution of medical accessibility in driving mode was consistent with that of roads, presenting a "loop level" pattern. However, the spatial distribution of accessibility under the public transport mode was affected by the urban bus microcirculation system, displaying the trait of "axial expansion." The method used in this paper provides a new scientific method for refined measurement and analysis of the accessibility of medical service facilities.

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    Forty Years' Progress and Challenges of Remote Sensing in National Land Survey
    SHU Mi, DU Shihong
    Journal of Geo-information Science    2022, 24 (4): 597-616.   DOI: 10.12082/dqxxkx.2022.210512
    Abstract1031)   HTML76)    PDF (4871KB)(288)      

    The national land survey is a major component of evaluating national conditions and strength. Its main purpose is to master the detailed national land use status and natural resource changes. It is of great significance to cultivated land protection and sustainable social and economic development. With the development of remote sensing technology, investigating the status, quantity, and distribution of land resources has always been the focus of remote sensing applications. This article reviews the application of remote sensing in national land survey over the past four decades. Until now, remote sensing technology has shown broad prospects in national land survey. However, the remote sensing information extraction in national land survey still mainly relies on visual interpretation and is not automated enough. In recent years, the remote sensing data tend to have the characteristics of high-resolution, large-scale, multi-temporal, and multi-sensor. However, the existing automated information extraction technology does not fully integrate those characteristics, hindering the application in national land survey. This article first introduces the relevant progress in national land survey from four aspects: feature extraction using very-high-resolution images, samples acquisition from large-scale images, transfer learning in multi-temporal/multi-sensors images, and multi-source heterogeneous data fusion. Then, four challenges in the existing remote sensing information extraction technology in the national land survey are summarized: ① Image feature is the key to image classification. There are questions on how to define and select features. In addition, high-resolution images put forward higher requirements for advanced feature extraction; ② Remote sensing data in the national land survey are usually large in scale, and there are inter-class imbalance and intra-class diversity. Therefore, it is a challenge to obtain sufficient, balanced, and diverse sample sets from such complex data set; ③ Generally, the efficiency of sample collection cannot catch up with the accumulation speed of remote sensing data, thus the labeled samples are relatively small compared with the data. For multi-sensor/multi-temporal imagery, how to realize land use classification in a low-cost and timely manner is a question worth considering; ④ There is a semantic gap between land cover and land use. Since remote sensing images mainly reflect land cover information, how to properly introduce semantic information to bridge the semantic gap and realize land use classification is a problem. Finally, the future development and application of remote sensing technology in national land survey are prospected, such as transformation from visual interpretation to artificial intelligence technology, accuracy and consistency assessment of remote sensing classification products in land survey, crowdsourcing methods for large-scale land use production, and update of large-scale land use data.

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    Research Progress of the Application of Geo-information Science and Technology in Territorial Spatial Planning
    XIE Hualin, WEN Jiaming, CHEN Qianru, HE Yafen
    Journal of Geo-information Science    2022, 24 (2): 202-219.   DOI: 10.12082/dqxxkx.2022.210317
    Abstract1011)   HTML63)    PDF (1876KB)(379)      

    Territorial spatial planning is the spatial blueprint of high-quality social and economic development. With the rapid development of geo-information science and technology, geo-information science and tech- nology has changed the way of territorial spatial planning. Its powerful capability in data acquisition, analysis, prediction, and management provides support in data, method, and platform for territorial spatial planning, thus enabling territorial spatial planning to be more scientific, operable, and forward-looking. Based on literature review, summary, and comparative analysis, this study analyzes the technical requirements of territorial spatial planning compilation, implementation, supervision, public participation, and intelligent transformation, and systematically expounded the application of geo-information science and technology in territorial spatial planning. This study expounds the contributions of geo-information science on China's territorial spatial planning from the following three aspects: (1) Geospatial data, remote sensing data, and socio-economic big data provide data basis for territorial spatial planning; (2) Geographic Information System (GIS) analysis method, geographic simulation method, and artificial intelligence method provide method support for territorial spatial planning; (3) The application of GIS platform, cloud computing, and urban intelligent platform promotes the intelligent transformation of territorial spatial planning. This study also points out shortages of different technologies. However, there are still some problems that need to be further explored: (1) The generation of socio-economic big data and its application scenarios in territorial spatial planning are concentrated in urban space; (2) Both traditional and modern technologies in territorial spatial planning have advantages and disadvantages. These technologies need to be effectively integrated to prepare more scientific territorial spatial planning; (3) The construction of territorial spatial planning platform has not been organically combined with the construction of City Information Modeling (CIM) and other intelligent society platforms, there is a huge space for mining in the future. According to the maturity of its application in territorial spatial planning, these technologies can be divided into mature technology and promising technology. With the promulgation of territorial spatial planning at all levels and types and the initial establishment of Chinese territorial spatial planning system in 2021, attention should be paid to the application of intelligent planning methods in agricultural space and ecological space, technical system construction of intelligent territorial spatial planning, and the improvement of territorial spatial planning intellectualization.

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    Journal of Geo-information Science    2022, 24 (9): 1645-1646.  
    Abstract635)   HTML5)    PDF (481KB)(4)      
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    Location Selection and Prediction of SexyTea Store in Changsha City based on Multi-source Spatial Data and Random Forest Model
    HUANG Qin, YANG Bo, XU Xinchuang, HAO Hanzhou, LIANG Lili, WANG Min
    Journal of Geo-information Science    2022, 24 (4): 723-737.   DOI: 10.12082/dqxxkx.2022.210478
    Abstract561)   HTML61)    PDF (6410KB)(176)      

    SexyTea, as a local milk tea brand in China, combines traditional Chinese tea culture with fashion elements and incorporates a strong Chinese style, making it a must-drink milk tea drink for tourists who visit Changsha. Exploring its spatial distribution and evaluating the suitability of its store location is of great practical significance for optimizing store layout, promoting economic development, and improving tourism service level. This article is based on the API of AMAP to crawl the SexyTea POI in Changsha City, and the spatial pattern is analyzed using the average nearest neighbor index, geographic concentration index, unbalanced index, standard deviation ellipse, kernel density estimation, and other methods. We integrate multi-source heterogeneous spatial data to select a series of factors that affect its spatial distribution and use the random forest model to evaluate the suitability of the store layout. The analysis results show that: ① The spatial distribution of SexyTea in Changsha is agglomerated as a whole (ANN=0.558, G=40.283), clustered around the city's core business clusters, forming a spatial pattern of "one super-multi-core"; ② The average test accuracy after optimization of the random forest model is 92.18%, and the OOB test accuracy is 93.45%. The evaluation results can accurately reflect the suitability and spatial distribution heterogeneity of the SexyTea store in Changsha City; ③ SexyTea location suitability results show that the suitability probability in the core business clusters of Changsha City is generally high, and there is an obvious high-value agglomeration phenomenon, which is in line with Friedman's "center-periphery" theory. If the business clusters are stratified into centers of different levels, the service functions and scope of influence provided by them will be affected by the attenuation of spatial distance, and the spatial distribution conforms to the Tobler's First Law of Geography; ④ The ranking result of feature importance shows that competitive environment, transportation location, and socio-economic development have the greatest contribution to the model. This is complementary to the minimum difference criterion emphasizing agglomeration effect and traditional commercial location strategy emphasizing location selection. Therefore, such factors can be considered when selecting store locations. The methods and conclusions of this research that integrate multi-source spatial data and use data mining technology to solve the location problem can provide reference for the location and spatial layout of SexyTea stores.

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    Division and Feature Analysis of Nanchang Urban Center Isochrone Maps based on Traffic Big Data
    LIU Linlin, ZHENG Bohong, LUO Chen
    Journal of Geo-information Science    2022, 24 (2): 220-234.   DOI: 10.12082/dqxxkx.2022.210372
    Abstract525)   HTML39)    PDF (16424KB)(315)      

    For the current territory development planning in China, the Ministry of Natural Resources has put forward a method to evaluate the accessibility of urban centers based on isochrone maps. The use of dynamic traffic data in isochrone maps studies is becoming more and more recurrent, but comparative analyses between dynamic and static data are still rare. In this paper, Nanchang city is taken as a case study to generate the urban center isochrone maps using static and dynamic traffic data. The city is divided into 500 m×500 m grids, with each grid center point representing a given destination while Bayi Square and Greenland Central Square are set as origins. Using the above origins and destinations, the dynamic data were obtained daily from the Baidu open map platform at 15:00 and at 18:00 over nine days-time (Saturday-next Sunday). Subsequently, the confusion matrix and Kappa coefficient are used to test the consistency between the isochrone maps generated by the two datasets. The results suggest that most of Nanchang urban central areas are within a 60 min-circle and most of Nanchang's urban areas are within a 120 min-circle, when taking Bayi Square or Greenland Central Square as the origin. The isochrone maps generated by the static data has just a fair consistency with those generated by the dynamic data at evening peak time on workdays. Within the urban central areas, the isochrone maps generated by the static data have reached a substantial consistency with those generated by the dynamic data at off-peak time on workdays, indicating that the static data is more suitable for evaluating the urban center accessibility at off-peak time on workdays. Besides, the dynamic data can display the temporal characteristics of the isochrone maps. The isochrone maps of the dynamic data at 4 time-points show that the urban center accessibility at 15:00 on workdays is significantly better than others. But the proportions of isochrone surfaces to the total urban areas are found to increase with the drivetime, and their growth curves are in accordance with the trend of the Logistic curve. The key time nodes of each growth curve can provide more targeted division thresholds for isochrone maps. This research highlights the accuracy of the isochrone maps generated by the dynamic data and explores the applicability of the static data. The research also shows that using the key time nodes of the Logistic curve contributes to a more reasonable subdivision of the isochrone map.

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    Harbor Detection based on Multi-Source Data and Semantic Modeling of Ship Stop Trajectory
    YAN Zhaojin, YANG Hui
    Journal of Geo-information Science    2022, 24 (9): 1662-1675.   DOI: 10.12082/dqxxkx.2022.210471
    Abstract485)   HTML8)    PDF (9641KB)(22)      

    Harbor detection is the top priority of maritime ship supervision, and the ship activity information acquired by Automatic Identification System (AIS) can provide high temporal and spatial accuracy of ship activity information for harbor detection. In order to explore the application of AIS data in harbor detection, a harbor detection method based on multi-source data and semantic modeling of ship stop trajectory is proposed. Firstly, the semantic model of ship stop trajectory is constructed through data mining and semantic information enhancement to identify ship stop trajectory in the harbor area. Secondly, a classification model based on random forest is established to classify ship berthing trajectories and ship anchoring trajectories, and then harbor berths and anchorages are extracted by using spatial step-by-step merging method. Finally, the data of ship berthing trajectories, roads, coastline, bathymetry, and land use and land cover data are integrated to identify harbor objects considering situational-domain knowledge. Based on over 83 million AIS trajectory records of 96,790 ships in 2017, the proposed method is applied to detect harbor object in the South China Sea study area. The experimental results show that the overall classification accuracy of ship stop behavior is 0.9477 and the Kappa coefficient is 0.8948. 447 harbor areas in the South China Sea study area are extracted, and the overlay verification results with Google Earth images show that the extraction results are all located within the real harbor images. In addition, compared with the 24 harbor locations in the South China Sea region contained in the Natural Earth dataset, the integrity of the extraction results is greatly enhanced. Therefore, the harbor detection method based on multi-source data and semantic modeling of ship stop trajectory has high accuracy and completeness for harbor detection. Meanwhile, the harbor areas extracted by this method can provide target areas for harbor identification based on remote sensing images, thus improving the efficiency of dynamic identification of harbor object in a large region or even globally.

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    Delimitation of Urban Development Boundary and Construction of Space Control System from the Perspective of Territorial Spatial Planning
    CHEN Ting, XU Weiming, WU Sheng, LIU Jie
    Journal of Geo-information Science    2022, 24 (2): 263-279.   DOI: 10.12082/dqxxkx.2022.210552
    Abstract452)   HTML25)    PDF (25960KB)(341)      

    Under the background of territorial spatial planning in the new period, delimiting the urban development boundary scientifically and reasonably and establishing a sound territorial space use control system are important measures to guide all kinds of territorial space development and protection. Taking Fuzhou City as an example, this paper constructs a global multi-dimensional territorial space control system. Management and control constraints are embedded in the future land use pattern simulation. At the same time, considering the regional spatial heterogeneity and spatial-temporal dependence, this paper designs the Spatial-temporal Cellular Automata (ST-CA) model which integrates geographical partition strategy, deep learning technology, and the functional module of FLUS model to delimit the urban development boundary. Based on the existing achievements, this study integrates three zones and three lines to carry out the application research of spatial management and control under the thinking of "combination of planning and control". The results show that: (1) The ST-CA model considering regional spatial heterogeneity and spatial-temporal dependence can effectively improve the accuracy of land use change simulation and achieve a more realistic and accurate geographical simulation process. The overall accuracy of the model increased from 95.95% to 98.34%; (2) Control constraints are embedded in the process of geographical simulation, which can guide the rational layout and controllable scale of urban, agricultural, and ecological spaces. Delimitation of urban development boundary based on simulation results can effectively avoid occupation on protected land; (3) The future simulation results combined with the control early warning value show that the urban expansion situation in the main urban area and surrounding districts and counties of Fuzhou City is relatively severe. In the future, it is urgent to reasonably regulate the territorial space pattern of Fuzhou City; (4) The characteristics of boundary change trend show that the delimitation results are consistent with the long-term development planning of Fuzhou City, which is in line with regional development demands. The territorial space pattern presents a multi-axis development trend. The research results can provide scientific planning for the development and protection of territorial space and practical reference for territorial space control and optimization in Fuzhou City.

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    Vegetation Data and Classification in Pan-Arctic Terrestrial Regions: Retrospective and Perspective
    XUE Shouye, XU Haiyan, GAN Zipeng, LIANG Bingyan, CHONG Biying, WANG Li, ZHANG Bo, LI Xiaoming, LI Lisha, MAO Nan, LIU Guimin, WU Xiaodong
    Journal of Geo-information Science    2022, 24 (3): 421-436.   DOI: 10.12082/dqxxkx.2022.210311
    Abstract353)   HTML9)    PDF (2812KB)(70)      

    Pan-Arctic area belongs to the high latitudes, and the vegetation in Pan-Arctic mainly belongs to the temperature-limited ecosystem, and thus the vegetation is sensitive to global warming. A vegetation atlas with high accuracy is the scientific basis for the study of response of vegetation to climate change and its driving mechanisms. However, there is a large room for improvement of vegetation type classification in the Pan-Arctic regions. For a better knowledge of the current status, history, and future trends in the vegetation mapping, we comprehensively reviewed the data resources, approaches, and methods of vegetation type classification in the Pan-Arctic region. Overall, the field survey of vegetation began in the 1920s, and there have been some land cover type data at the regional scale. However, there are still many challenges for Pan-Arctic vegetation type mapping, which can be attributed to several reasons such as differences in field survey data, standards for the land cover type classification, and the heterogeneities in tundra ecosystem, and differences in mapping methods and difficulties of optimizing algorithm. In the future work, more attentions should be paid to standard classification rules, and standard dataset preparation and integration, which will benefit the development of new methods for vegetation type mapping in the Pan-Arctic area.

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    A Fine-scale Study on Spatio-temporal Patterns of Metro Commuter Flows under Rainfall Events in Shanghai
    HUANG Sheng, LI Weijiang, ZHU Mengru, LIU Zhen
    Journal of Geo-information Science    2022, 24 (2): 249-262.   DOI: 10.12082/dqxxkx.2022.210373
    Abstract346)   HTML39)    PDF (14124KB)(282)      

    In the context of global climate change, extreme precipitation events are becoming more frequent and have an increasing impact on urban commutes. In this study, based on hourly rainfall data and metro OD passenger flow data, we use a prophet time-series model to forecast the regular values of commuting flow under rainfall events, and quantitatively assess the spatial-temporal changes of commuting flow caused by rainfall at station and OD levels. Our results show that (1) the commuting flow generally tends to decrease with increasing hourly rainfall. The fluctuation of commuting flow varies from one type of station to another. Rainfall can delay commuting departure time and lead to surge in metro flow in certain times. The higher the commuting demand for a station, the more its flow fluctuates. Flow fluctuation due to rainfall varies in different time periods. 7:00 and 17:00 show high fluctuation with more flexibility in commuting departure time, while 8:00—9:00 and 18:00—19:00 show high rigidity; (2) Rainfall can induce a significant increase in short commuting flow of less than 15 minutes, averaging to around 7.3%. In contrast, the impact on medium and long commuting flow is modest, with an overall decrease of 1.3%. Of the OD flows across various functional zones, fluctuation from residential to industrial stations is most notable during the morning commute, while less so from commercial to residential stations during the evening commute. Most of the departure stations of rainfall-sensitive metro lines during the morning commute are located around large residential areas, and around large industrial parks and commercial centers during the evening commute. Flow fluctuation in the evening commute is lower than that in the morning commute. Although total commuting flow is not significantly affected by rainfall, its surge in certain local regions and times should be highlighted. Our methodology and results will help to quantify the impact of rainfall on metro commutes and provide a basis for spatialized transport coping strategies.

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    Establishing Fundamental Geographic Framework for the Comprehensive Maritimes Atlas Oriented to Sea and Land Integration
    HUANG Lina, YANG Liuduozi, YAO Xiangyu, HOU Mengying, REN Fu
    Journal of Geo-information Science    2022, 24 (9): 1647-1661.   DOI: 10.12082/dqxxkx.2022.220081
    Abstract346)   HTML9)    PDF (6287KB)(45)      

    The design and compilation of comprehensive maritime atlas integrating sea and land information serve the national development initiative of "building a marine community with shared future", it is also an important thrust to promote the culture fusion and friendly cooperation between marine and land areas. Therefore, it has attracted widespread attention in the field of cartography. This paper firstly discusses the special characteristics of marine-land integrated atlas through the comparative analysis with nautical charts and land atlas, referring to the thematic topic, map scale, map projection, and geographic subdivision. Then it proposes a top-level design of fundamental geographic framework for the comprehensive maritime atlas from the perspective of marine and land combination, including both the content system and construction strategy. Next, taking "Maritime Atlas of the World" as an instance, the paper puts forward the specific establishment of fundamental geographic framework in details: (1) the coordinate system of WGS84 should be used for medium and small scale maps, while the CGCS2000 should be used for large scale maps; (2) according to the map thematic and content, cartographic area, and deformation needs, mapping units can use various projections such as qual difference latitude parallel polyconic projection, Mercator projection, Goode projection, and so on; (3) six types of geographic base maps are adopted, i.e. typical reginal map, land map, sea map, navigation area map, and port map, their contents are generated in series by further selection and simplification; (4) all the mapping units should be arranged to the north, and map layouts are various with flexible geographic subdivision and map subdivision. The “Maritime Atlas of the world” complication practice shows that this proposed fundamental geographic framework can well support the integration of marine and land information into a cohesive coordinative manner.

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    A Distributed Geospatial Simulation Framework for Massive Spatial Agent-Based Modeling
    ZENG Mengxiong, HUA Yixin, ZHANG Zheng, ZHANG Jiangshui, YANG Zhenkai, WEI Yuanyuan
    Journal of Geo-information Science    2022, 24 (5): 815-826.   DOI: 10.12082/dqxxkx.2022.220001
    Abstract323)   HTML9)    PDF (4059KB)(64)      

    Geospatial simulation based on agent-based modeling is an effective method to recognize and understand dynamic geographic phenomena. As the scale and complexity of geospatial simulation continues to increase, the challenges in model computation increase. Distributed parallel simulation could be used to solve the complex simulation issue of large-scale agents. However, the existing research on building parallel simulation system based on agent modeling/simulation software is not suitable for modeling of spatial agent with high-mobility and behavioral interaction with others, and real-time visualization of simulation process. To solve this problem, this paper proposes a distributed geospatial simulation framework, namely DGSimF, for massive dynamic spatial agent modeling, which supports real-time representation and analysis of the simulation process. A simple but efficient spatial modeling agent for spatial-temporal data is designed, which supports the modeling of integrated geoscience models directly based on agent behavior, adopts the time differentiation method to coordinate the execution of the behavior of each computing node, supports distributed computation in the way of "task parallel" to improve the simulation performance, and constructs a Virtual Geographic Environment (VGE) based on three-dimensional earth rendering engine to support real-time visualization of intermediate simulation results. Finally, the experiments based on the "Red vs. Blue" case are carried out, and the simulation performance with different computation cost and different number of clients is analyzed. The results show that DGSimF can provide an effective platform for massive spatial agent simulation of spatio-temporal feature change and behavior interaction. By expanding the computing nodes, the pressure of complex simulation calculation can be effectively alleviated. Meanwhile, the simulation performance of the proposed framework is high, and the parallel efficiency remains above 0.7 in these experiments.

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    Urban Comprehensive Vitality Evaluation and Influencing Factors Analysis Considering Population Agglomeration and Emotional Intensity
    LIANG Lifeng, ZENG Wenxia, SONG Yuexiang, SHAO Zhenfeng, LIU Xiujuan
    Journal of Geo-information Science    2022, 24 (10): 1854-1866.   DOI: 10.12082/dqxxkx.2022.220027
    Abstract318)   HTML3)    PDF (8364KB)(17)      

    The scientific and quantitative evaluation of urban vitality can provide an important basis for urban planning and urban coordinated development. Existing studies on urban vitality and urban planning both focus on the characteristics of people's activities, without considering the psychological feelings of urban residents. In view of the current situation that residents' emotions are easily ignored in research, this study selects Baidu heat map to measure the intensity of population agglomeration intensity and uses the emotional analysis results of micro-blog text data to measure emotional intensity. Using the TOPSIS model to calculate the comprehensive vitality of the city, a comprehensive vitality evaluation framework considering population agglomeration and emotional intensity is proposed. This study selects eight influencing factors from three dimensions: urban physical environment, economic environment, and ecological environment, including road accessibility, land use mix, the density of POI, building density, nighttime light intensity, salary level, housing price level, and vegetation coverage. The influence of the eight influencing factors on the spatial heterogeneity of urban vitality is further explored by the GeoDetector model. This study shows that: (1) The comprehensive vitality evaluation method integrating population agglomeration intensity and emotional intensity proposed in this study can better reflect the spatial differentiation pattern of urban vitality. The effectiveness of this proposed framework for evaluating urban comprehensive vitality is verified by the analysis results of the typical sampling regions; (2) Among the eight influencing factors, the density of POI has the greatest influence on urban comprehensive vitality, while the influence of vegetation coverage on urban comprehensive vitality is the weakest. However, the interaction between vegetation coverage and other factors has the most significant impact on the spatial heterogeneity of urban vitality. It shows that the vegetation coverage factor does not directly act on the spatial heterogeneity of urban vitality but indirectly affects the spatial differentiation of urban comprehensive vitality by coupling the road accessibility, density of POI, and building density.

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    Research on Route of Mountain Flood Disaster Avoidance based on Equivalent Distance Algorithm
    ZHANG Chaoqin, XUE Fengchang, CHEN Xiaojuan, LI Ting, HAN Yu, JIANG Jian, TANG Weigan
    Journal of Geo-information Science    2022, 24 (5): 864-874.   DOI: 10.12082/dqxxkx.2022.210628
    Abstract296)   HTML8)    PDF (16380KB)(152)      

    The ability of disaster prevention and mitigation in mountainous and rural areas is weak. Mountain flood disasters have strong suddenness, and the response time of disaster avoidance is short, which are likely to cause casualties. Reasonable design of avoidance routes can help reduce losses caused by disasters. Based on GIS, this paper designs disaster avoidance routes in Tianbaizhi Village, Xingtai City, in the Hebei Province. The Digital Elevation Model (DEM) and orthophoto of the research area are obtained through Unmanned Aerial Vehicle (UAV) photogrammetry. Factors that influence disaster avoidance route planning including slope, cost distance, and function of cost path are used to calculate the initial avoidance route in the mountainous areas. The area where the mountain flood ditch is located and the area with a large slope are used as the interrupted area of the disaster avoidance route. The existing mountain roads are fully considered and rationally used to optimize the final disaster avoidance route. Based on the distance and average slope of the disaster avoidance route, the disaster avoidance route obtained by this method is quantitatively compared with the original disaster avoidance route. The result shows that (1) Among the 20 long-distance disaster avoidance routes designed, this method shortens the length of 18 routes, reduces the average slope of 10 routes, and controls the increase of the average slope of the other 8 routes within 2°; (2) Compared with the original route, the maximum length of each route can be shortened by 329.74 m, and the average slope only increases by 0.68°. The disaster avoidance distance is shortened by adding a small amount of average slope, which improves the disaster avoidance efficiency; (3) The length of remaining two routes increases by 15.21 m and 9.57 m, respectively, resulting in an average slope reduction of 8.43° and 1.43°. The average slope of the routes is reduced by adding a small amount of distance, which improves the safety of disaster avoidance routes; (4) The southern part of Tianbaizhi Village is close to the disaster avoidance point, and the avoidance of disasters is relatively difficult. In contrast, the northern part of Tianbaizhi Village has a longer route to the disaster avoidance point. The longest distance is 1210.02 m, and the difficulty of disaster avoidance is greater. The optimized disaster avoidance path has been separated from the barrier area with large slope, and the degree of overlap between disaster avoidance path and the mountain flood ditch is greatly reduced. The method proposed in this study provides a sufficient scientific basis for relevant decision-makers.

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    VCS Optimization Method of Vatti Algorithm for Polygon Overlay and Parallelization Using GPU
    ZHANG Zhikun, FAN Junfu, XU Shaobo, CHEN Zheng
    Journal of Geo-information Science    2022, 24 (3): 437-447.   DOI: 10.12082/dqxxkx.2022.210409
    Abstract293)   HTML14)    PDF (3596KB)(78)      

    Vatti algorithm is one of the widely used vector polygon clipping algorithms. In the process of intersection calculation based on the construction of scanning beams, the data structure of binary tree and recursive calculation method lead to an obvious increase in time consumption when dealing with polygons with plenty of vertices. The calculation efficiency of the algorithm is significantly affected by the boundary vertex number of the overlapping polygons. Aiming at the efficiency improvement of the time-consuming scanning beam construction process of Vatti algorithm, this paper proposes an optimization approach based on polygon boundary vertex pre-sorting method, which is named VCS (Vertex Coordinate Pre-Sorting) method, and realizes a fine-grained level parallel Vatti algorithm on GPU device based on CUDA. The VCS method replaces the original binary tree data structure of Vatti algorithm with a double linked list, and obtains an obvious efficiency improvement on polygon boundary vertex information searching process with a smaller additional storage space. In GPU environment, the bitonic sorting method is used to sort the elements of polygon boundary vertex array in parallel and filter out the valid values, which overcomes the defect of low efficiency caused by the original algorithm using binary tree data structure. Experimental results show that the improved algorithm presents higher efficiency with the same calculation accuracy as the original algorithm. When the number of polygon vertices is 920 000 and the number of threads in each thread block is 32, compared with the serial algorithm which builds scan beams using CPU, the VCS optimization method with GPU-based parallel polygon clipping algorithm obtains a relative acceleration ratio of 39.6 times, and the efficiency of vector polygon superposition analysis algorithm is improved by 4.9 times overall.

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    Usage Patterns Identification and Flow Prediction of Bike-sharing System based on Multiscale Spatiotemporal Clustering
    JIANG Xiao, BAI Lubin, LOU Xiayin, LI Mei, LIU Hui
    Journal of Geo-information Science    2022, 24 (6): 1047-1060.   DOI: 10.12082/dqxxkx.2022.210691
    Abstract292)   HTML15)    PDF (5434KB)(74)      

    At present, China government and bike-sharing companies mostly use electronic fence parking stations to manage the shared bicycles normatively. Electric fence parking stations for free-floating bike-sharing are predetermined 'virtual fences' to guide users to park bikes in designated zones and regulate inappropriate parking behaviors. However, due to the randomness and uncertainty of the inflow and outflow of bicycles at a single parking station, the scheduling of bicycles based on an independent parking station is hard to realize. Therefore, it is necessary to group fence stations into clusters and implement regional management. In this paper, we proposed a network clustering algorithm based on spatiotemporal constraints, which comprehensively considered spatial factors (location and geographical environment of the parking stations) and temporal factors (historical bike-sharing system orders) as the clustering partition basis, and this algorithm can realize the multi-scale groups division of parking stations only by setting a distance threshold. We chose Xiamen Island as the research region. Using the distance thresholds of 3000 m and 700 m respectively, we carried out clustering experiments on the electronic fence parking stations in the whole Xiamen Island and its Wushipu block. The results showed that this algorithm can not only gather the parking stations with similar temporal and spatial characteristics into the same group, but also make the shared bike flow mainly concentrated in the streets within each group, which is convenient for regional management. Then, we mined the characteristics of shared bikes among the partitioned groups, which can effectively identify and locate hot areas for shared bikes. The results showed that subway stations, office buildings, parks, hospitals, shopping malls, and residential areas had a greater impact on the usage pattern of shared bikes. In particular, it is necessary to focus on the accumulation of shared bikes near office buildings, shopping malls, hospitals, and subway stations, and the shortage of bicycles near the residential areas, parks, and factories during the morning rush hours. Finally, we used the Long Short Time Memory network (LSTM) to predict the orders of shared bikes. The results showed that 84% of the groups had a prediction accuracy of more than 85%, and the average of the overall prediction accuracy was 91.301%, which can meet the needs of bike-sharing system scheduling. Our research provides scientific suggestions for relevant departments to arrange electronic fence parking stations, and the LSTM model has high accuracy in predicting bicycle flow, which is effective in reducing the scheduling cost of bike-sharing system and improve the management efficiency.

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    Constructing Index for the Assessment of Urban Residential Land Efficiency Using Location-Based Big Data
    YUAN Yuan, MAO Lei, LI Hongqing, ZHAO Xiaofeng
    Journal of Geo-information Science    2022, 24 (2): 235-248.   DOI: 10.12082/dqxxkx.2022.210239
    Abstract281)   HTML21)    PDF (24660KB)(254)      

    Information empowerment to the territorial spatial planning has become a hot research field in the new era. However, research on territorial utilization evaluation using big data integration remains to be explored. The purpose of this paper is to carry out an empirical study on the efficiency assessment of residential land use in new urban area employing Tencent location-based big data. Assessment index of residential land use efficiency in each residential area have been proposed, supported by integration of multi-source geospatial data, to reveal the differences in land use efficiency among different residential areas in Changzhou city. The results show that, firstly, population size of hourly particle statistics within the residential area fluctuates periodically, reaching peak value at 21:00 generally, which is in line with the routine of daily going out and returning home for urban residents. There are also expected differences in population agglomeration degree and population size among residential buildings with different capacity rates. Secondly, the 29 residential areas are divided into five groups by year of construction, 1980s, 1990s, 2000s, 2010—2015, and post-2015. The average population size of efficiency index of group 1980s, 1990s, 2000s, 2010—2015, and post-2015 are 1.74, 2.45, 2.31, 0.95, and 0.91 per 100 m2, respectively. Index values of residential areas built before 2010 are significantly higher than those built after 2010. Furthermore, residential areas built after 2010 are lower than the average level (population size of 2.06 per 100 m2in year 2018) of the entire urban residential areas. Thirdly, it is suggested that lower results of efficiency index is not fully equal to poor level of intensive land use. The main reasons of diverse land use efficiency of residential areas constructed in different periods include the growth periodicity of new urban area development in Changzhou city, and urban residents' desire for better living environment to enhance their quality of habitation. Research shows that location-based big data, as a source of population data with high solution, could reflect the temporal and spatial characteristics of resident aggregations objectively. Index constructed to assess urban residential land efficiency using location-based big data is both innovative and scientific, which could provide a new way for the analysis of high-quality land space utilization. In conclusion, regularity recognition of behavior characteristics from urban residents can provide support for spatial policy formulation during the urbanization process based on "putting people first" policy in China. What's more, new data sources, represented by location-based big data in this paper, will play an important role in decision-making mechanism of territorial spatial planning.

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    A Remote Sensing Image Classification Method based on Deep Transitive Transfer Learning
    LIN Yu, ZHAO Quanhua, LI Yu
    Journal of Geo-information Science    2022, 24 (3): 495-507.   DOI: 10.12082/dqxxkx.2022.210428
    Abstract281)   HTML4)    PDF (10263KB)(64)      

    In the practical task of remote sensing image classification, the biggest problem with the use of deep neural network method is the lack of sufficient labeled samples. How to use fewer labeled samples to achieve higher accuracy of remote sensing image classification is a problem that needs to be solved at present. ImageNet is the largest image recognition dataset in the world, the model trained on it has rich underlying features. Fine-tuning the ImageNet pre-training model is the most common transfer learning method, which can make use of the rich underlying features to improve the classification accuracy. However, there is a big difference between ImageNet image features and remote sensing image features, and the improvement of classification effect is limited. In order to solve the above problems, a remote sensing image classification method based on deep transitive transfer learning combined with deep neural network is proposed in this paper. This method constructs an intermediate domain using the open-source remote sensing scene recognition datasets as the data source and uses ImageNet pre-training weight as the source domain and remote sensing images to be classified as the target domain for transfer learning to improve remote sensing image classification accuracy. First, based on ImageNet pre-training VGG16 network, the fully connected layer is replaced by the global average pooling layer in order to speed up the weight update of convolutional layer, and the GAP-VGG16 is constructed. The intermediate domain dataset is used for training the ImageNet pre-training GAP-VGG16 to obtain the weight. Then, based on the SegNet, the T-SegNet is designed by adding the convolutional layer into the SegNet to further extract the obtained weight. Finally, the obtained weight is transferred to T-SegNet, and the remote sensing image classification is achieved by training the target domain dataset. In this paper, the Aerial Image Dataset and UC Merced Land-Use Dataset are selected as the data sources of the intermediate domain dataset, and the ZY-3 Panjin area image is selected as the target domain image, 50% and 25% of the training samples are selected for the experiment. The experimental results show that using 50% and 25% of the training samples, the Kappa coefficient of the classification results using the proposed method in this paper is increased by 0.0459 and 0.0545, respectively compared to SegNet, and is increased by 0.0377 and 0.0346, respectively compared to ImageNet pre-training SegNet. For classes with a smaller number of samples, the classification accuracy of the method in this paper is improved more significantly.

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    Topographic Change Detection that Considers the Spatial Autocorrelation of DEM Errors
    DAI Wen, CHEN Kai, WANG Chun, LI Min, TAO Yu
    Journal of Geo-information Science    2022, 24 (12): 2297-2308.   DOI: 10.12082/dqxxkx.2022.220209
    Abstract281)   HTML0)    PDF (17640KB)(0)      

    Traditional topographic change detection methods often ignore the spatial autocorrelation of DEM errors. To solve this problem, a topographic change detection method that considers the spatial autocorrelation of DEM errors is proposed in this paper. Firstly, the DEM of Difference (DoD) is obtained from two original DEMs, and the spatial distribution of DEM errors is evaluated by the Monte Carlo method. Secondly, based on spatially distributed DEM errors, DoD errors are calculated by error propagation and their spatial autocorrelation degree is analyzed using the semi-variance function. Finally, topographic changes (erosion, deposition, and net changes) are calculated based on the spatial autocorrelation analysis and significance detection. The results in four small catchments show that the elevation errors of UAV-photogrammetry DEM are spatially autocorrelated, which can be simulated by the Monte Carlo method. The use of spatially distributed error instead of RMSE for topographic change detection effectively reduces the sensitivity of the detection results to the significance threshold. When the significance threshold is increased from 68% to 95%, the loss of observations using the spatially distributed error is 5.39%~6.75% lower than that using the RMSE. The proposed method can be effectively used in the fields of surface deformation monitoring, erosion monitoring, sediment transport assessment, and so on.

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    Review on the Research Progress of Boundary Delineation Methods of the Loess Plateau Landforms
    DING Xiaohua, WANG Cheng, XI Junjie, WANG Zhao, YUE Chengyu, ZHANG Qingfeng
    Journal of Geo-information Science    2022, 24 (7): 1219-1233.   DOI: 10.12082/dqxxkx.2022.210837
    Abstract280)   HTML15)    PDF (5004KB)(70)      

    The most direct and effective way to distinguish geographical entities is to delineate their boundaries. At present, the delineation of the geomorphic boundary of the Loess Plateau is mostly based on classification boundaries and natural division boundaries. Based on different data sources and their expressions, this article reviews the previous research progress on the demarcation of the natural geographic boundary of loess landform types and summarizes the connotation of loess landforms boundary from morphological genetic geomorphic classification, digital geomorphic classification, and other classification systems. The advantages and disadvantages of quantitative description based on natural language and digital environment are analyzed. Besides, we sort out the quantitative identification and classification methods of the Loess Plateau landform types based on digital terrain analysis. Furthermore, we discuss and prospect the geomorphic boundaries from three aspects: (1) the relationship between the determination of the landform boundary and the classification system; (2) the reference of the delineation of the landform boundary; (3) the scale effect of the landform boundary. This review summarizes the background of the relevant theoretical studies on loess geomorphic regionalization and provides the theoretical basis and support for local practical work.

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    Spatial-temporal Equilibrium Analysis and Attraction Area Optimization of Dockless Sharing Bicycles Connected to Subway Stations
    KUANG Jiaheng, WU Qunyong
    Journal of Geo-information Science    2022, 24 (7): 1337-1348.   DOI: 10.12082/dqxxkx.2022.210775
    Abstract280)   HTML41)    PDF (5931KB)(63)      

    Dockless sharing bicycles are one of the most effective options for connecting to the subway. However, the uneven spatial-temporal distribution of sharing bicycles has caused great inconvenience to users and managers, especially during the morning peak period, which will greatly reduce the operating efficiency of a transportation system. Therefore, studying the characteristics of spatial-temporal distribution of dockless sharing bicycles used to connect to the subway has certain significance for improving the commuting efficiency during the morning peak period. In order to understand the spatial-temporal characteristics of feeder metro riding, this paper takes Xiamen city as the experimental area, takes the riding of feeder metro stations during the morning peak as the main research object, proposes a new method to establish the attraction area of metro stations based on travel OD, and proposes a bicycle clustering method considering metro stations based on travel characteristics. This article also analyzes the overall travel balance of each subway station during the morning rush hour from the perspective of mathematical statistics, tide ratio statistics, and the point of attraction area, and analyzes the spatial-temporal balance of cycling around subway stations at different times during the morning rush hour. Through analysis, the similarities and differences of the balance of each subway station under three perspectives are obtained. The results show that: ①According to the characteristics of the tide ratio, the connection function of the subway station for cycling can be divided into 4 categories: the start type, balanced type, arrival type, and not suitable for connecting to the subway type, reflecting the overall connection characteristics of each subway station; ②The attraction area of the subway station connecting to the riding is different from the characteristics of the tide ratio, and its main influencing factors are the geographic location of the subway station and the surrounding land use type; ③ For the analysis results of the spatial-temporal balance, the tide ratio has no significant impact on the spatial-temporal balance level, and the major influencing factor is the surrounding land use type. The analysis results can reflect the difference in the operation of sharing bicycles that connect to the surrounding subway stations during the morning rush hours in Xiamen and the efficiency of connecting to the subway, so as to support the scheduling and supervision of key areas of bicycle sharing companies.

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    Spatialization of Carbon Emissions in Guangzhou City by Combining Luojia1-01 Nighttime Light and Urban Functional Zoning Data
    LU Yifan, LIANG Yingran, LU Siyan, XIAO Yue, HE Xiaoyu, LIN Jinyao
    Journal of Geo-information Science    2022, 24 (6): 1176-1188.   DOI: 10.12082/dqxxkx.2022.210610
    Abstract279)   HTML26)    PDF (5789KB)(78)      

    A reasonable spatialization of urban carbon emissions is an important prerequisite for formulating clear carbon emission reduction policies. However, previous studies relied heavily on the nighttime light data with coarse spatial resolution and did not consider the huge differences of carbon emissions between various industry sectors. Therefore, the corresponding results cannot accurately reflect the spatial distribution of carbon emissions. To solve the disadvantages of previous methods, this study proposed a more reasonable method for the spatialization of carbon emissions. Firstly, three statistical models were used to estimate the carbon emissions of various industry sectors for Guangzhou in 2019. Next, the spatial distribution of carbon emissions was simulated based on the combined use of Luojia1-01 nighttime light and urban functional zoning data. Based on the spatialization result, both the global and local spatial autocorrelation analyses were carried out to reveal the spatial characteristics of carbon emissions in Guangzhou. Finally, the random forest model was used to investigate the socio-economic driving factors behind the carbon emissions in Guangzhou. The results are summarized as follows: (1) Although the carbon emissions of Guangzhou increased slowly after 2011, the total emission volume still reached 83.12 million tons in 2019, in which the transportation sector played a dominant role; (2) Compared with the commonly-used ODIAC (1 km), EDGAR (10 km) carbon emission products and the carbon emission spatialization results based on NPP-VIIRS (500 m), the result generated by high resolution (130 m) nighttime light and urban functional zoning data can more accurately characterize the spatial differences of carbon emissions; (3) There was a significant positive global spatial autocorrelation of carbon emissions in Guangzhou, resulting in highly concentration areas of secondary and tertiary sectors; (4) The main influencing factors for the secondary sector's carbon emissions were public budget revenue, GDP of the secondary sector, public budget expenditure, and fixed asset investment. In comparison, the major contributors to the tertiary sector's emissions were retail sales of consumer goods, GDP of the tertiary sector, GDP per district, and population. In summary, this study carefully considers the differences in industry structure, and then utilizes the high-resolution nighttime light data to investigate the distribution pattern of carbon emissions. The results will be helpful for policy-makers to formulate reasonable carbon emission reduction and industrial optimization strategies.

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    YOLOv5 based on Aircraft Type Detection from Remotely Sensed Optical Images
    LONG Yican, LEI Rong, DONG Yang, LI Dongzi, ZHAO Chenchen
    Journal of Geo-information Science    2022, 24 (3): 572-582.   DOI: 10.12082/dqxxkx.2022.210369
    Abstract274)   HTML10)    PDF (8122KB)(66)      

    Automatic detection of aircrafts plays an important role in airport monitoring and intelligence analysis. Currently, there are various and mature methods for aircraft detection, but the aircraft type detection is still facing many problems, such as the use of unpublicized self-made datasets, the difficulty to reproduce experiment, and the inability to verify generalization ability. Therefore, detecting aircraft type quickly and accurately is still a hotspot in the field of remote sensing image analysis. The traditional detection methods are complicated in processes, poor in robustness and generalization, and cannot detect the specific type of aircrafts. In recent years, deep learning methods have been widely applied in the field of computer vision. Compared with the two-stage algorithm, YOLO, as a one-stage algorithm, rejects the steps of multiple regression, includes only a convolution network, and regards the detection problem as the regression problem of image classification and candidate box parameters. However, multi-layer convolution and pooling may weaken or completely lose aircraft features, making it challenging to extract practical features. Meanwhile, remote sensing images are susceptible to light conditions, seasonal changes, cloud occlusion, noise, and other factors, which makes the detection task harder. In order to solve these problems, this paper firstly used the MTARSI dataset to screen samples and then collected aircraft images from open-source methods such as Google Earth using random rotation, changed brightness, added noise, and other methods to form a new aircraft type detection dataset. Secondly, multi-scale adjustment and training were carried out based on YOLOv5. Finally, an across-dataset was used to identify the aircraft in the optical remote sensing images, which could verify the model’s generalization ability. The experimental results show that the method can accurately and effectively detect the number, location, and type of aircraft in the optical remote sensing images and has strong robustness and generalization ability. The accuracy of type detection reached 82.12% in the across-dataset, which can provide technical support for intelligent aircraft semantic analysis and on-board application research.

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    Research on the Evolution of Global LNG Maritime Transportation Network and Trade Condition of China
    MEI Qiang, HU Qinyou, LIU Xiliang, ZHAO Ruina, YANG Chun, WANG Peng, QI Yuling, YANG Yang, YUAN Qirui
    Journal of Geo-information Science    2022, 24 (9): 1701-1716.   DOI: 10.12082/dqxxkx.2022.220021
    Abstract265)   HTML3)    PDF (8754KB)(14)      

    With the proposal of "carbon peak" and "carbon neutralization", Liquefied Natural Gas (LNG) has gradually garnered the attention of energy market as a clean and low-carbon energy. In this context, it is of great significance to analyze the evolution mode of the LNG maritime transport network, so as to master the dynamic of global energy pattern and the status of China's import trade. In this paper, the evolution trend of the global LNG maritime transport network from 2018 to 2020 is explored based on the ship trajectory data and complex network theory. Meanwhile, according to China's trade status, LNG import sources, distribution of main import ports, and the inflow status of the top three import ports in China are analyzed. The results show that: (1) From 2018 to 2020, the global LNG maritime transport network expanded with a “scale-free” characteristic. The "breadth" and "depth" of node connections in the backbone network are increasing, and there is a risk that global LNG trade will become monopolistic; (2) The countries along the "Belt and Road Initiative" actively participated in trade. The numbers of import ports and import voyages in Central and North America, South and Southeast Asia have significantly increased, and in particular, Sabetta and Bonny ranked the top eight globally according to their export volume; (3) The average shortest path length of the network is increasing year by year from 2018 to 2020, and the new mode of "transshipment port" business is gradually emerging. By 2020, 21 transshipment ports have participated in LNG trade, and the United States occupies the dominant position in global transshipment; (4) In recent three years, China's LNG import scale has developed rapidly, and the flow direction of the maritime transport network tends to be diversified. However, Australia is still the main LNG source for China. In terms of import volume, the ports of Tianjin, Shenzhen, and Yung'an rank the top three in China, and the pressure to reduce carbon emissions has prompted the economically developed regions to build terminals and increase imports.

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    Construction of Semantic Information Model for Aerospace Cooperation Earth Observation
    LU Wanjie, LIU Wei, NIU Chaoyang, XIE Limin, LV Liang
    Journal of Geo-information Science    2022, 24 (8): 1421-1431.   DOI: 10.12082/dqxxkx.2022.220036
    Abstract264)   HTML18)    PDF (3923KB)(42)      

    Earth observation technology is an important tool to obtain geospatial information and has now entered the stage of multi-platform and multi-sensor. Obtaining information and knowledge through the semantic modeling of aerospace cooperation earth observation is one of the important methods for the execution and planning of earth observation missions. To monitor the platform operation of aerospace cooperation earth observation and extract information and knowledge to serve the earth observation, a semantic model for aerospace cooperation earth observation is proposed. Firstly, the basic description of the domain ontology for aerospace cooperation earth observation platform is established, which can assist the clarification of research contents. Secondly, considering the correlation between different earth observation platforms and starting from the aspects of platform, sensor, time, and space, the domain ontology for aerospace cooperation earth observation platform is constructed based on Basic Formal Ontology, which is described by using six tuples. Thirdly, based on the modeling of spatiotemporal relationships and sensor objects, the cooperation observation rules for typical applications are formulated according to typical application requirements, to serve the evaluation and decision-making of aerospace cooperation earth observation tasks. Then, the semantic descriptions of spatiotemporal relationships are constructed, and the comprehensive semantic description of aerospace cooperation earth observation is realized by combining the semantic description of static and dynamic scenarios. Finally, in order to verify the domain ontology and semantic description for aerospace cooperation earth observation platform, based on the micro-service architecture and 3-dimension visualization framework, the service experimental system is built to verify the effectiveness of proposed models and methods, which takes Zhengzhou, the provincial capital of Henan, as an example. The aero-based and space-based earth observation platforms are used by the service experimental system to carry out the observation tasks, and the activities of aerospace cooperation earth observation are displayed in real time. Based on the cooperation observation rules, recommendations for the selection of the earth observation platform are given. Results show that the proposed models and methods can effectively represent and display the semantic information of operation status and task performance of aerospace cooperation earth observation, which can be used for mission planning and decision-making of earth observation. In follow-up research, a more refined semantic information model of aerospace cooperation earth observation will be constructed to support more complex earth observation scenarios. At the same time, the construction of cooperative observation rules under different application scenarios will be fully considered, and more accurate and detailed information will be provided for earth observation activities by reasoning.

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    Topographic Retrieval of the Tidal Flats in the Yangtze Estuary based on the Dynamic Tidal Submergence
    ZHANG Min, WU Wenting, WANG Xiaoqin, SUN Yu
    Journal of Geo-information Science    2022, 24 (3): 583-596.   DOI: 10.12082/dqxxkx.2022.210429
    Abstract261)   HTML4)    PDF (10915KB)(199)      

    Tidal flats are important transitional zones between terrestrial and marine ecosystems and have complicated ecological processes and essential ecosystem services. Tidal flats are highly dynamic under the influences of land-sea interactions and anthropogenic activities. Limited by the accessibility, it is difficult to map the tidal flat using traditional survey. To solve the difficulty in obtaining tidal flat elevation data, a tidal flat elevation inversion model suitable for large-scale with high accuracy is needed. In this study, we proposed an algorithm incorporating tidal submergence and time-series Remote Sensing (RS) data to map the topography of tidal flats. We used Chongming Dongtan as an example and further extended the results to the whole Yangtze Estuary. Firstly, the K-means++ clustering was employed to extract the inundation extent of tidal. Then, the frequency of tidal inundation of each pixel was calculated from the time series RS data. Finally, the tidal flat topography was retrieved based on the regional tidal frequency. All available Sentinel-2 and Landsat-8 images from 2016 to 2020 were used to build the time-series dynamic of tidal flats to map the topography. Verified by the in-situ data, the results showed that the total accuracy and F1-score of the inundation extent extraction of the tidal flats were 97.73% and 0.98, respectively. The average absolute error of elevation inversion was 0.15 m. The accuracy of tidal flat elevation was positively correlated with the number of available images. The total area of tidal flats was 346.93 km2 with an elevation range of 1.00~3.84 m. The tidal flats in the Yangtze Estuary were mainly distributed in Chongming Dongtan, Jiuduansha, Hengsha Dongtan, Nanhui Biantan, and Tuanjiesha. Among them, Nanhui beach had the largest area (107.44 km2), while Chongming east beach had the largest elevation difference (2.84 m). The distribution status of tidal flat was mainly affected by sediment hydrodynamics, vegetation, and human engineering activities. Compared with the existing dataset, our results showed a more robust capacity in the inundation extent extraction of tidal flats. With the increasing number of effective observations and tidal level information from time-series RS images in coastal areas, the extraction accuracy of tidal flat information could be further improved. The proposed algorithm has a great potential in rapid mapping of tidal flat topography and is of great significance for the dynamic monitoring and management of tidal flat resources.

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    Location Advantage of Inland River Ports in the Yangtze River Economic Belt based on Multi-Source Data
    ZOU Xinchen, MU Fengyun, WANG Junxiu, CHEN Jiankun, TIAN Tian
    Journal of Geo-information Science    2022, 24 (9): 1717-1729.   DOI: 10.12082/dqxxkx.2022.220448
    Abstract252)   HTML4)    PDF (6650KB)(21)      

    Inland river ports are important nodes of inland river shipping links. Evaluation of the regional advantage of inland river ports is of great significance for port infrastructure construction in the Yangtze River Economic Belt. Taking the inland ports along the Yangtze River in 2021 as the research object, the original model is improved by using multi-source data and combining three indicators within the radiation range of inland ports on the Yangtze River. The AHP-EWM model is used to calculate the location advantage of 28 ports along the Yangtze River in the Yangtze River economic belt. Results show that: (1) except Chongqing and Wuhan, the density of traffic network in the port radiation range beyond Jiangsu province is relatively low. From the perspective of the influence of traffic networks, its distribution is relatively balanced, and the value is relatively similar. The influence of the spatial distribution of urban economics is disordered; (2) The spatial pattern of freight ports in the Yangtze River Economic Belt is characterized by "three centers, one cluster" according to their regional advantages and spatial distribution; (3) By dividing inland ports at the provincial level along the Yangtze River, it is found that the regional difference of dominance between the three ports in Jiangxi Province is the smallest, and the overall degree of dominance is also low. The result of Anhui Province is similar to Jiangxi Province. The overall degree of dominance of ports in Jiangsu Province is high with a small regional difference. The regional dominance of ports in Hubei Province has the largest difference, indicating that there might be issues such as unbalanced infrastructure construction that needs to be improved in future. The research results can provide guidance for infrastructure construction, road traffic planning, and port site selection of various ports in the Yangtze River Economic Belt, and help open up the "last kilometer" of railway and high-grade highway access to ports.

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    Review and Perspective for Resources and Environmental Information Development and Service along the Economic Corridors of the "Belt and Road" Initiative
    WANG Juanle, WEI Haishuo, YAN Xinrong, ZHANG Min, HAN Xuehua
    Journal of Geo-information Science    2022, 24 (6): 1019-1033.   DOI: 10.12082/dqxxkx.2022.210306
    Abstract250)   HTML12)    PDF (7810KB)(65)      

    The "Belt and Road" is a major international cooperation initiative proposed by China to adapt to current development needs. It has six economic corridors as its core pillars. The region of interest spans the three continents of Asia, Europe, and Africa, involving a large number of countries with varied regional geographical conditions and complex resources and environment backgrounds. Determination of resources and environmental information along the routes in a systematic and comprehensive manner will play a crucial role in decision-making support for promoting the scientific implementation of the Belt and Road Initiative. Considering the complex background of geographical resources, the environment, and the diverse international cooperation needs, the exploitation and utilization of resources and environmental information along the “Belt and Road” face several opportunities and challenges. This paper proposes a Spatial Information Service System for the Belt and Road Initiative, which is oriented toward collaborative innovation. Two technical routes, top to bottom and bottom to top, are used to demonstrate the overall framework of information acquisition and utilization, and generation of information services for decision support. The progress on resources and environmental information development and services in the six economic corridors is reviewed, including resources and environment patterns and their spatiotemporal evolution, monitoring and evaluation of the United Nations Sustainable Development Goals(SDGs), key technology application in disaster risk reduction knowledge service, resources and environmental information integration and sharing, and the effect of COVID-19 on economic and social development, which can provide a reasonable foundation and reference for the establishment of a comprehensive system for "Belt and Road" resource, environment, and spatial information service. Finally, the development trends and the main directions for potential research and cooperation are highlighted, including strengthening the comprehensive collection and service capabilities of basic resource and environmental data, providing further contributions to data and methods on SDGs target monitoring and evaluation in China, integrating the entire chain of data, information, and knowledge of disaster risk reduction applications, promoting the integration and sharing of resource and environmental data with harmonized standards, and promoting the construction and application of collaborative innovation platforms involving multiple parties. The research would provide a reference for promoting the development and utilization of synchronous data resources, information integration and sharing, and the construction of collaborative innovation application environment of the "Belt and Road" economic corridor, thus, promoting decision-making support for the sustainable development of the "Belt and Road" Initiative.

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    Accessibility of Beijing Dual Hub Airports from the Perspective of Residential Travel
    HUANG Jie, SHI Wenqian, CHEN Yu
    Journal of Geo-information Science    2022, 24 (5): 914-924.   DOI: 10.12082/dqxxkx.2022.210515
    Abstract243)   HTML10)    PDF (5283KB)(60)      

    For a city with dual hub airports, the relationship between two airports is important for its integrated transport system. Since 2019 Beijing has been a city with dual hub airports, namely Beijing Capital International Airport (PEK, hereinafter referred as “Capital Airport”) and Beijing Daxing International Airport (PKX, hereinafter referred as “Daxing Airport”). Based on the Gaode Map API, which can obtain real-time data precisely, this paper obtains real-travel-time data in both auto mode and public transport mode. It investigates the accessibility spatial pattern of two airports under the two travel modes from the perspective of residential travel so that we can offer suggestions on the integration development of “civil aviation-urban transportation” system. The results show that: ① The use of Daxing Airport has effectively improved the spatial accessibility to airports in Beijing, especially from the south area, making civil aviation service in Beijing tend to be a “north-south equilibrium”. The coverage of the two airports is complementary in 0.5-hour service area by driving and 1 hour service area by public transport, which effectively improves the efficiency of aviation service in Beijing. ② In Beijing, accessibility by auto is higher than that by public transport and accessibility from Capital Airport is higher than Daxing Airport in both travel modes. Under the auto mode, the two airports begin to compete in the coverage within 1 hour journeys. For public transport mode, there is competition within 1.5 hour. ③ Under the public transport mode, the service area and population of the two airports in Beijing need to be improved, as the two airports only serve 1.4% of urban area and 7% of total population in Beijing. So it is important to construct 1 hour service area for residents to access the airports. ④ In the view of intra-urban transfer, accessibility from train stations to the Capital Airport is higher than that of Daxing Airport. Hence, accessibility between Daxing Airport and train stations should be enhanced to support the integration of aviation and high-speed rail travel. Last, we offer suggestions in order to promote the effective integration of airport and urban traffic system in double hub airport cities.

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    Spatio-temporal Changes of Vegetation in the Yellow River Basin and Related Effect of Landform based on GEE
    WANG Xiaolei, SHI Shouhai
    Journal of Geo-information Science    2022, 24 (6): 1087-1098.   DOI: 10.12082/dqxxkx.2022.210685
    Abstract242)   HTML19)    PDF (7282KB)(81)      

    The Yellow River Basin serves as an ecological barrier in the eastern plain of China. Analyzing the spatiotemporal change of vegetation cover in Yellow River Basin and its topographic effects is helpful for ecological environment management. In this study, we first calculated the annual Fractional Vegetation Cover (FVC) of the Yellow River Basin for 1990—2020 through the GEE cloud computing platform using pixel binary model and Landsat images. Then, the spatiotemporal trend of FVC was obtained through Theil-Sen Median trend analysis and Mann-Kendall test. Finally, the topographic effects on FVC was quantified based on Digital Elevation Model (DEM) data (i.e., SRTM Plus) through ArcGIS. The results show that: (1) the FVC in the Yellow River Basin presented a spatial distribution of low in the northwest and high in the southeast. Low-level FVC values accounted for 45% of the entire basin area, which were mainly concentrated in the arid and semi-arid areas in the northwest; (2) the vegetation coverage in the middle of the basin was improved significantly, which accounted for 57.07% of the entire region. The degradation trend of the northwest and west region was stronger than that in other regions of the Yellow River Basin; (3) the vegetation coverage was significantly affected by the topography. High-level FVC occurred in regions where the slope was greater than 40° and the elevation was between -31~637 m. The vegetation recovery was good within the range of slope of 8~18° and elevation of 1852~2414 m. The results can provide scientific support for the ecological environment protection and high-quality development of the Yellow River Basin.

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