HPSIN: a new hybrid P2P spatial indexing network

Geographic information system （GIS） is increasingly managing very large sets of data, hence a centralized data index may not always provide the most scalable solution. Recently, the peer to peer （P2P） networks have become very popular for sharing information in a totally decentralized manner. In this paper, a new hybrid P2P spatial indexing network （HPSIN） is proposed, which combines distributed quad-tree with distributed Hash table （DHT） based Chord network to maintain both query efficiency and system load balance. In addition, a simple theoretical model based on opened queueing network for HPSIN is established. Assuming each peer as M/M/1 queueing processor in the model, fundamental characteristics of the system is captured, and expression of average query delay is obtained in close form. The theoretical analysis and numerical computing results show that there exists an optimum point of tradeoff between efficiency and load balance. By setting a proper value of start index level ls for different network scale and query rate, HPSIN will achieve the minimum overall query delay, therefore, can adapt to different P2P application environments.

DAPR-tree: a distributed spatial data indexing scheme with data access patterns to support Digital Earth initiatives

This paper proposes a novel data indexing scheme,the distributed access pattern R-tree(DAPR-tree),for spatial data retrieval in a distributed computing environment.As compared to traditional distributed indexing schemes,the DAPR-tree introduces the data access patterns during the indexing utilization stage so that a more balanced indexing structure can be provided for spatial applications(e.g.Digital Earth data warehouse).In this new indexing scheme,(a)an indexing penalty matrix is proposed by considering the balance of data number,topology and access load between different indexing nodes;(b)an‘access possibility’element is integrated to a classic‘Master-Client’structure for a distributed indexing environment;and(c)indexing algorithm for the DAPR-tree is provided for index implementations.By using a duplication of official GEOSS Clearinghouse system as a case study,the DAPR-tree was evaluated in a number of scenarios.The results show that our indexing schemes generally outperform(around 9%)traditional distributed indices with the utilization of data access patterns.Finally,we discuss the applicability of the DARP-tree and document DARP-tree shortcomings to encourage researchers pursuing related topics in Big Data indexing for Digital Earth and other geospatial initiatives.

Research on Tourism Agglomeration: A Case Study of Hainan Province, China

On the basis of analyzing yearly data and spatial relationships between tourism spots, star hotels and travel agencies of Hainan Province, and comparing all the methods of measuring industrial spatial agglomeration, this paper chose Hefindahl index, Location Quotient, nearest neighbor index, spatial connection index and geographic concentration index to measure Hainan tourism agglomeration. By applying these methods, total tourism agglomeration, agglomeration of tourism factors and regional agglomeration differences were studied. The results showed that the overall agglomeration increases as time flows, and the eastern part is the most agglomerated, the west takes the second, with the middle ranking the least. The large-scale agglomeration regions are Sanya and Haikou. The influencing factors of Hainan tourism spatial agglomeration were concluded as tourism resource endowment, industrial attributes, geographic conditions, governmental policies and the overall economic development level, etc. In addition, the paper proposed tourism spatial agglomeration modes of Hainan Province at various spatial scales.

Web-based visualization of spatial objects in 3DGIS

Adaptive rendering large and complex spatial data has become an important research issue in a 3DGIS application. In order to transmit the data to the client efficiently, this paper proposes a node-layer data model to manage the 3D scene. Because the large spatial data and limited network bandwidth are the main bottlenecks of web-based 3DGIS, a client/server architecture including progressive transmission methods and multiresolution representations, together with the spatial index, are developed to improve the performance. All this makes the application quite scalable. Experimental results reveal that the application works appropriately.

Sample indexed spatial orthogonal frequency division multiplexing

Optical spatial modulation （OSM） is a multiple-transmitter technique that can provide higher data rates with low system complexity as compared with single-input single-output systems. Orthogonal frequency division multiplexing （OFDM） is widely implemented to achieve better spectral efficiency in wireless channels. Asymmetrically clipped optical OFDM （O-OFDM） and DC-biased O-OFDM are two well-known O-OFDM techniques suitable for intensity-modulation direct-detection optical systems. In this work, sample indexed spatial OFDM （SIS-OFDM） is proposed to combine OSM and O-OFDM in a novel way and achieve significant per- formance gain. By assigning time-domain samples of the O-OFDM transmit symbol to different transmitters, SIS-OFDM achieves much better spectral efficiency and reduces computational complexity at the transmitter as compared with previous work that combines OSM with O-OFDM in the frequency domain. We also consider the impact of optical source biasing on overall performance, and the relative performance of imaging receiver （ImR） versus non-imaging receiver （NImR） design for our proposed SIS-OFDM technique. Results indicate that for an Ntx x Nrx multiple-input multiple-output configuration where Nix = N = 4, SIS-OFDM using ImR can achieve up to 135 dB of signal-to-noise ratio gain over comparable system using a NImR. Also, using Nc number of O-OFDM subcarriers provides up to Nsc × log2（Ntx） additional bits per symbol of spectral efficiency over technioues that combine OSM and O-OFDM in the freollencv domain.

Efficient Data Access for Location-Dependent Spatial Queries

When the mobile environment consists of light-weight devices, the loss of network connectivity and scarce resources, e.g., low battery power and limited memory, become primary issues of concern in order to efficiently support portable wireless devices. In this paper, we propose an index-based peer-to-peer data access method that uses a new Hierarchical Location-Based Sequential （HLBS） index. We then propose a novel distributed Nearest First Broadcast （NFB） algorithm. Both HLBS and NFB are specifically designed for mobile peer-to-peer service in wireless broadcast environments. The system has a lower response time, because the client only contacts a qualified service provider by accessing the HLBS and quickly retrieves the data to answer the query by using NFB. HLBS and NFB design the index for spatial objects according to the positions of individual clients and transfer the index in the order arranged so that the spatial query can be processed even after the user tunes the partial index. Hence, this design can support rapid and energy-efficient service. A performance evaluation is conducted to compare the proposed algorithms with algorithms based on R-tree and Hilbert-curve air indexes. The results show that the proposed data dissemination algorithm with the HLBS index is scalable and energy efficient in both range queries and nearest neighbor queries.

A spatial multi-scale integer coding method and its application to three-dimensional model organization

With the rapid development of digital earth,smart city,and digital twin technology,the demands of three-dimensional model data’s application is getting higher and higher.These data tend to be multi-objectification,multi-type,multi-scale,complex spatial relationship,and large amount,which brings great challenges to the efficient organization of them.This paper mainly studies the organization of three-dimensional model data,and the main contributions are as follows:1)A integer coding method of three dimensional multi-scale grid is proposed,which can reduce the four-dimensional(spatial dimension and scale dimension)space into one-dimensional,and has better space and scale clustering characteristics by comparing with various types of grid coding.2)The binary algebra calculation method is proposed to realize the basic spatial relationship calculation of three-dimensional grid,which has higher spatial relationship computing ability than 3D-Geohash method;3)The multi-scale integer coding method is applied to the data organization of three-dimensional city model,and the experiment results show that:it is more efficient and stable than the threedimensional R-tree index and Geohash coding method in the establishment of index and the query of three dimensional space.

Area and shape distortions in open-source discrete global grid systems

A Discrete Global Grid System(DGGS)is a type of spatial reference system that tessellates the globe into many individual,evenly spaced,and well-aligned cells to encode location and,thus,can serve as a basis for data cube construction.This facilitates integration and aggregation of multi-resolution data from various sources to rapidly calculate spatial statistics.We calculated normalized area and compactness for cell geometries from 5 open-source DGGS implementations-Uber H3,Google S2,RiskAware OpenEAGGR,rHEALPix by Landcare Research New Zealand,and DGGRID by Southern Oregon University-to evaluate their suitability for a global-level statistical data cube.We conclude that the rHEALPix and OpenEAGGR and DGGRID ISEA-based DGGS definitions are most suitable for global statistics because they have the strongest guarantee of equal area preservation-where each cell covers almost exactly the same area on the globe.Uber H3 has the smallest shape distortions,but Uber H3 and Google S2 have the largest variations in cell area.However,they provide more mature software library functionalities.DGGRID provides excellent functionality to construct grids with desired geometric properties but as the only implementation does not provide functions for traversal and navigation within a grid after its construction.

宁杭城市多时空尺度居住空间分异与比较研究

Residential segregation is a dual process of socio-spatial differentiation in residents and spatio-temporal heterogeneity in dwelling.However,most of the existing studies are established from the single perspective of urban residents based on demographic data,which is difficult to reveal the dynamics and complex spatial reconstruction within and between cities.With the characteristics of both stability and timeliness,the rapidly changing housing market is one of the processes and results of socio-spatial reconfiguration,and it is undoubtedly a better lens to observe residential segregation.This paper adopts methods such as multi-group segregation index,multi-scalar segregation profiles,and decomposition of segregation index,with Nanjing and Hangzhou as case cities,and establishes multi-scalar segregation profiles and comparative models based on three geographical scales of census tract,block and grid,and different residential types.A quantitative study was conducted on the degree and pattern of multi-scalar residential segregation in Nanjing and Hangzhou from 2009 to 2018.The paper found that the spatial segregation index is an improvement of the non-spatial segregation index.There are differences between Nanjing and Hangzhou in the evolution process of residential segregation.Nanjing has a higher degree of spatial differentiation as a whole,among which spatial components have a more significant impact.

Indices of Congested Areas and Contributions of Customers to Congestions in Radial Distribution Networks

Congestions are becoming a significant issue with an increasing number of occurrences in distribution networks due to the growing penetration of distributed generation and the expected development of electric mobility.Fair congestion management(CM)policies and prices require proper indices of congested areas and contributions of customer to congestions.This paper presents spatial and temporal indices for rapidly recognizing the seriousness of congestions from the perspectives of both magnitude violation and duration to prioritize the affected areas where CM procedures should be primarily activated.Besides,indices are presented which describe the contributions of customers to the congestions.Simulation tests on IEEE 123-bus and Australian 23-bus low-voltage distribution test feeders illustrate the calculation and capabilities of the proposed indices in balanced and unbalanced systems.