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Currently, vector map encryption algorithms predominantly rely on symmetric key encryption, which poses significant risks due to potential key leakage. On the other hand, existing asymmetric encryption algorithms, although offering enhanced key security, require the conversion of data into integer form before encryption, which can compromise the precision and accuracy of the original vector map data. To address these issues, this paper introduces a novel asymmetric lossless encryption algorithm for vector maps based on the RSA algorithm. The proposed algorithm begins by dynamically selecting the integer part of the coordinate values from the vector map. These selected values are then encrypted asymmetrically using RSA, ensuring both security and data integrity. To further enhance the encryption process, SHA-512 is employed to generate a key for a chaotic system. This chaotic system is subsequently used to reorganize the point coordinates of the already encrypted vector map, achieving a one-map, one-ciphertext encryption model. Experimental results demonstrate that the proposed algorithm is capable of encrypting and lossless decrypting various types of vector maps without any data distortion. Furthermore, the algorithm is versatile and can be applied to other types of geospatial data, including 3D point clouds and oblique photography 3D models, making it a robust solution for a wide range of geospatial encryption needs. [ABSTRACT FROM AUTHOR]

To address the challenges of effectively managing and professionally utilizing massive geospatial data in the railway surveying process, this paper presented an automated management and publishing method based on the ERDAS APOLLO spatial GIS engine. By integrating the characteristics of data at various stages of railway surveying, a standardized process for data organization, storage, processing, and sharing was established. A method for collecting and verifying railway geospatial metadata was developed, enabling rapid data entry and attribute acquisition for railway geospatial information. A system architecture with separate data, service, and application layers was designed in a B/ S (Browser/ Server) mode for the distribution and display of multi-source geospatial information. Utilizing Asp. Net, Vue. js, and the Cesium mapping framework. A railway multi-source geospatial data management system was developed in a front-end and backend separated architecture, achieving unified data management and shared application. A survey project with a total data volume exceeding 600 GB was selected as a case study to verify the system's capabilities in data management, checking, verification, and visualization. The research indicates that the automated data management and service publishing process significantly reduce the costs associated with data storage, processing, and maintenance. The integrated map and attribute approach enhances the efficiency of data retrieval and increases the value of data utilization, effectively serving the application needs of the railway design profession for geospatial information data. [ABSTRACT FROM AUTHOR]

Geographic grid coding is a very important and basic work in efficiently managing, analyzing and querying massive geospatial location data and providing information services. GeoHash, Google S2 and Uber H3 are three commonly used geographic grid coding methods in commercial applications. This paper starts from the basic concepts of geographic coding and its evolution process, and introduces the geographic grids involved in the current geographic coding and the current geographic grid coding methods, then explains the three geographic grid coding methods from the aspects of algorithm overview, coding mode, coding level and its corresponding spatial scope, and finally conducts a comparative analysis from the aspects of ortho-polyhedral selection, dissecting units, filling curves, coding level, neighbor query and neighbor distance type, and the advantages and disadvantages of algorithm application, so as to explore the application value and prospect of the three methods in depth, which can provide a reference for the research and application based on the geographic location of large-scale data. [ABSTRACT FROM AUTHOR]

The data-driven research paradigm brings a strong demand for training data sharing in geospatial artificial intelligence (GeoAI). The training data content and organization from different GeoAI applications are diverse. A unified information model will lay the foundation for GeoAI training data sharing and interoperability. By analyzing the common features and core attributes of different GeoAI training data, an information model for training data was proposed, and the training data quality elements and evaluation methods were explored. The results provide a reference for development of GeoAI training data stores and sharing services. [ABSTRACT FROM AUTHOR]

Satellite photogrammetry is an important way to obtain geospatial information of the earth, and it is also an effective way to solve the mapping issue for difficult areas in the world. The development process of optical surveying and mapping satellites are briefly summarized, and the optical surveying and mapping satellites of China are introduced in detail. After years of technological development, the results of optical photogrammetry satellites in China can meet the accuracy requirements of 1∶50 000 and 1∶10 000 scale surveying and mapping products. And the development status of optical surveying and mapping satellites are summarized, and the future development trends of surveying and mapping satellites are proposed, including on-board intelligent detection and storage, on-board and ground data intelligent processing, and multi-satellite network collaborative detection. With the support of global high-precision basic information data, the future photogrammetry satellites will be developed in the direction of an integrated, ubiquitous and intelligent type to improve the guarantee capability of surveying and mapping products. [ABSTRACT FROM AUTHOR]

Copyright of Geography & Geographic Information Science is the property of Geography & Geo-Information Science Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Bulletin of Soil & Water Conservation is the property of Bulletin of Soil & Water Conservation Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

【Objective】The intersection of big data and research on ‘three rural’ issues has created a research field with great potential. By combing the research results in this field, this paper has an in-depth understanding of its research focus and future direction, in order to provide some support for related research.【Method】 The paper used the methods of literature analysis and summary and induction to summarize and discussed the application of big data in the research of ‘three rural issues’ from three aspects: Research on agricultural issues, research on rural issues and research on farmers’ issues.【Result】With the popularization of communication infrastructure, big data such as internet usage data, communication sensor equipment data, geospatial data, organization management and operation data have been applied to the research of ‘three rural’ issues in China. At present, the application of big data in the research of ‘three rural’ in China has been constantly enriched. In the research of agricultural problems, big data has been applied to all links of agricultural production and operation, such as agricultural production monitoring and output improvement, and agricultural product market trend prediction. In the research on rural issues, the application of big data mainly focused on depicting the current situation of rural development, especially the evaluation of rural spatial environment, which can find a large number of rural spatial structures and systems driven by actual social and economic activities. In the research on farmers’ problems, the problem areas applied by big data mainly include the identification of farmers’ spatio-temporal behavior laws and the wealth and well-being of farmers reflected by them. High coverage data reflecting individual behavior, such as mobile phone use and signaling positioning data, has been the main data sources for such research.【Conclusion】The application of big data in the research of ‘three rural’ issues in China shows great development prospects in the development of agricultural industry, farmers’ lives and spatial planning, but there are also challenges in the aspects of data source and quality, method design, integration of traditional governance experience, etc. [ABSTRACT FROM AUTHOR]

The contradictions between land production, living, and ecological functions have gradually emerged, as industrialization and urbanization continue to advance. It is necessary to accurately allocate and coordinate the functions of land development and protection for the reasonable distribution of human activities in sustainable agriculture. This study aims to explore the spatiotemporal characteristics of trade-offs/synergies in the land use functions and the influencing factors. Taking Hangzhou City of China as an example, an attempt was made to evaluate the land production, living and ecological functions at the fine scale from 2000 to 2018 using the multi-source data and a series of geospatial models. Then, the correlation analysis was used to reveal the trade-offs/synergies of land use functions at the global and grid scales. The influencing factors of land use function trade-offs/synergies were also identified by the linear regression model. The results showed that: (1) The living function showed a trade-off relationship with the production and ecological function between 2000 and 2018, whereas the trade-off intensity of production and living functions was stronger than that of living and ecological functions. Production and ecological functions were established to determine a synergistic relationship during the study period. There was a trend of increasing first and then decreasing in the trade-off relationship between production and living functions, where the trade-offs of living and ecological functions gradually weakened. The interactive relationship between production and ecological functions was shifted from a synergistic relationship in 2000-2005 to a trade-off relationship in 2015-2018. (2) Spatially, the production-living function was dominated by strong trade-off and production-weakening trade-off, where the trade-off intensity tended to weaken from the east to the west and from the central to the periphery. The areas with a synergy state were located in the low-altitude mountain of central and western Hangzhou. The production-ecological function presented a mixed pattern of trade-off and synergy areas in space. The trade-off areas accounted for about 31%, with the weak trade-off and production-weakening trade-offs, mainly distributed in northern and eastern Hangzhou. The synergy areas occupied about 38%, with the weak synergy and simultaneous improving synergy, mainly distributed in the western and southern Hangzhou. The living-ecological function was dominated by the weak trade-off and ecology-weakening trade-off. The trade-off area accounts for 14%, where the trade-off intensity showed a trend of high in the east and low in the west, gradually decreasing from the center to the edge. The synergy relationship was dominated by weak synergy and simultaneous weakening synergy, the synergy areas accounted for 8%, mainly scattered in the outer suburbs. (3) Natural conditions and geographical location posed significant negative effects on the trade-offs/synergies in production-living and living-ecological functions, whereas there were significant positive effects on production-ecological function trade-offs/synergies. The urbanization-induced land conversion and the increase of land-use intensity further aggravated the trade-offs in land use functions. Therefore, there were different trade-offs/synergies in the land use functions at global and grid scales. The overall characteristics and local differences can be fully considered in the decision-making on land use function, according to the local conditions. [ABSTRACT FROM AUTHOR]

Objectives: In the era of big data, geospatial information resources are constantly increasing. However, the current knowledge bases are difficult to take into account the semantic knowledge as well as to retrieve geospatial data quickly. Therefore, it is urgent to introduce ontology technology to improve the access speed of geospatial data on the basis of semantic knowledge so as to accurately obtain the information needed by users. Methods: We propose a fast retrieval method that takes into account the semantic knowledge of geospatial data based on ontology. Firstly, a semantic knowledge base is constructed through encoding rules of generic place name, geospatial data and Baidu encyclopedia open source data. Secondly, we design some query rewrite rules and mapping methods between semantic knowledge and spatial data-base. So that we can construct retrieval statements based on place names automatically. Results: The feasibility of the fast retrieval method is verified through the application of an example and the comparative analysis of efficiency and quality. Conclusions: Based on the semantic information of geospatial data, we can automatically construct the structured query language(SQL) retrieval statement only by geographical entity name, reduce the user's dependence on data storage method and SQL grammar rules, and effectively improve the retrieval efficiency and intelligence of the system. [ABSTRACT FROM AUTHOR]

Copyright of Remote Sensing for Natural Resources is the property of Remote Sensing for Natural Resources Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Objectives: Geospatial data and computing plays an important role in the era of big data and artificial intelligence(AI), and provides a dimension of social studies in term of ontological, methodological, and epistemologs aspects. Methods: This interview invited some influential scholars from the fields of sociology, geo ⁃informatics, computing science and expressed their views on how spatial and geo ⁃ computing can be intergrated in computational social science. Results: Geospatial studies and social science share a very basic research objective which focuses on heterogeneity, and spatial big data provides an unprecedented paradigm for social studies. Also, challenges were raised on building a therotical framework, data availiablity, computing issues, and related concerns on ethics. Conclusions: To solve the challenges, it requires the closer collaboration among social science, geo⁃science, and computer science. We wish this discussion could inspire the related studies and provide a blueprint for both geospatial and social computing. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Central China Normal University is the property of Huazhong Normal University and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Hydrographic Surveying & Charting / Haiyang Cehui is the property of Hydrographic Surveying & Charting Editorial Board and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Journal of Remote Sensing is the property of Editorial Office of Journal of Remote Sensing & Science Publishing Co. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Crowdsource geospatial data is one kind of open geographic data collected by the public. A wealth of spatial information and knowledge are hidden in crowdsource geospatial data. Check⁃in data is one of the representative crowdsource geospatial data. Most existing work on spatial ⁃ textual objects, such as evaluating the similarity of two spatial⁃textual objects in spatial keyword query, considers that spatial simi⁃ larity and text similarity are independent of each other. According to the first law of geography: Everything is connected; the closer two objects are, the stronger their connection is. We explore the correlation be⁃ tween spatial information and textual information in the real check ⁃in data scrawled from the location based social networks. After data preprocess and geographic mapping, we computed the textual attribute values in each region. Then, we use the exploratory spatial analysis to analyze the global spatial autocorrelation and local spatial autocorrelation in different the spatial scales, that is different states in United States and the two cities such as New York and Los Angeles, respectively. The results show that different textual attri⁃ butes in different regions have different global spatial autocorrelation; the results obtained from the local au⁃ tocorrelation analysis show the phenomenon that the textual attributes get together. Both the above results provide the basis for research on the assumption that “the texts are similar in the near space”. Further⁃ more, the conclusion can help departments or enterprises to make reasonable decisions. [ABSTRACT FROM AUTHOR]

By combining geo-computing tasks and spatial-temporal data resources with specific business logic, users can deal with complex geographic problems in specific domains. Traditional geo-computing processes require manual participation if complex iterations are built. Scientific workflows support automated process to assist researchers in geo-computing and knowledge discovery. A method for complicated geospatial flow processing based on scientific workflow is proposed. Firstly, exist open source scientific workflow management systems are compared. Subsequently, the core problems of geo-computing processes are analyzed: Heterogeneous multi-source data access, the description of complex computing, the scalability of computing, and the interaction and sharing of data analysis processes. The complex geo-computing flow processing method supported by scientific workflow is put forward, which can combine the data dependencies between complicated applications. Based on Swift’s excellent capabilities in process structure, dispatchable resource types, and fault tolerance levels, geospatial flow can control the sequence of different parts to be completed under the constraints of time, storage and resources. Therefore, spatial-temporal data can be searched, moved, analyzed, processed and visualized. Finally, a housing site selection case based on this method is presented to show the feasibility [ABSTRACT FROM AUTHOR]

HBase as a NoSQL database has been adopted as a solution for storing and managing huge datasets in many applications. However, it does not provide direct support for storing spatial data. In view of this, we present a data management system called GS - Phoenix for big geospatial data. GS - Phoenix builds on two open-source projects, Phoenix and HBase. While geospatial data being inserted into GS-Phoenix, it automatically generates a spatial index based on space filling curve in the form of primary keys of data table or a secondary index. By taking advantage of the spatial index, GS-Phoenix achieves several basic spatial query operations including rectangular range query, non-regular area query and k nearest neighbor (kNN) query which are all essential primitives for realizing complex spatial queries. GS - Phoenix employs the user - defined functions and server-side sorting mechanisms to impose most spatial filtering tasks on the server side in query processing, effectively reducing the computing burden of the client. GS -Phoenix also leverages a query optimization method based on spatial distribution statistics, which further improves the efficiency of spatial query. Experimental results show that GS-Phoenix deployed over a small scale cluster can sustain an I/O throughput of over 170 000 data insertions per second, while serving spatial range queries and kNN queries with response times as low as hundreds of milliseconds. The experiments demonstrate that GS - Phoenix is applicable to a wide spectrum of geospatial position related applications which demand high insertion throughput and real time spatial queries. [ABSTRACT FROM AUTHOR]

Vector is an important type of geospatial data, discretization is an important link for its fusion with raster data, and the generation of the discrete line is the basic problem. In view of the shortcomings of discrete line generation algorithm of triangular grid, this paper proposes a mathematical model for establishing the equivalent triangle grid discrete line mathematical model by means of the weak duality hexagonal grid and solving it by dimensionality reduction. Firstly, according to the weak duality relationship between the triangular grids and the hexagonal grids, an equivalent triangular grid discrete line model is established based on the hexagonal grids. Then, using the dimension reduction method, the two‐dimensional discrete line model is equivalently transformed into a one‐dimensional closed path solution. Finally, a discrete triangle conversion generation algorithm for planar triangular grids is designed and implemented. The experimental results show that the proposed algorithm is ingenious and rigorous in theory and beneficial to the programming. The operation efficiency is about 9‐10 times of the similar algorithms, with a better result. This algorithm can be applied to vector data in real‐time grid transformation, terrain modeling, spatial analysis, simulation and other fields,with broad application prospects. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Central China Normal University is the property of Huazhong Normal University and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Geospatial big data has been widely applied to distinguish urban functions. Especially, the research of functional hierarchy is of profound significance in understanding the structural characteristics and distributional forms of urban functions thoroughly, but related studies are still vacant. Therefore? this study depicts human mobility patterns based on time-series taxi trajectory data and point of interests (POIs) data, and identifies urban functional properties and spatial structures through combining dynamic time warping and K-MEDOIDS clustering algorithm. The results show that the urban functions in the central area of Guangzhou possess obvious hierarchical characteristics. With the refinement of hierarchies, the functional properties are developed from the dual-structure of working-living into the triple-structure of working-living-entertainment gradually. Moreover, the spatial structure is consistent with the ring-shaped structure, and its urban functions are gradually transformed from the living-entertainment function at outer rings into the commercial-entertainment function at central rings，and present different tendencies at different rings. This study provides efficient references for urban planners to understand the property changes and structural characteristics of urban functions. [ABSTRACT FROM AUTHOR]

The growth of massive distributed geospatial data and complex geoprocessing services makes asynchronous geoprocessing a research hotspot in the geospatial domain. Meanwhile, the Open Geospatial Consortium (OGC) provides a series of standards and specifications to advance interoperability between geospatial Web services. Most are based on synchronous protocols that cannot satisfy more complex geoprocessing tasks, especially those in the Sensor Web environment. This paper presents an interoperable approach for asynchronous geoprocessing services that leverages Web processing services (WPSs) and Web notification services (WNSs) to support asynchronous invocation. We analyze the general asynchronous communication patterns in message transfer and invocation available in a service oriented architecture. Compared to existing poll-based approaches, the paper adopts a push pattern for asynchronous notification, and at the same time makes user requests standard-compatible. The push pattern was implemented using WNS. An asynchronous adapter for WPS services, combined with a WNS, is used for augmenting existing synchronous WPS services with asynchrony. The approach is compatible with existing WPS specifications, thus still follows the interoperable service standards in the geospatial domain. A service prototype was designed and implemented, and performance tests are discussed. [ABSTRACT FROM AUTHOR]

In order to solve the efficiency problem in vector map visualization with the traditional vector map visualization model, and to improve the capability of parallel processing for vector maps, a new approach for parallel visualization of vector maps is proposed, based on vector data spatial distribution information. This research focuses on the principles related to the collection, retrieval and analysis of vector data spatial distribution information. A workflow for decomposition and parallel processing are elaborated in this paper. Eventually, when all of the computing resources in a server cluster are sufficiently utilized, the parallel visualization of vector data can be realized. Simulation results demonstrate that the new approach proposed in this paper can improve the capability of a map server cluster, to meet the needs of massive concurrent users. [ABSTRACT FROM AUTHOR]

Currently the satellites ground systems provides single business, which lead to lack the ability of shared and collaboration. For solving these problems, this paper proposed a new satellites ground systems' architecture. It firstly studied the subsystems' service based on OGC service standards; then made a whole new satellites ground systems' architecture. At the end, it implemented a prototype of the ground systems. [ABSTRACT FROM AUTHOR]