Spatial Information Grid Research Articles

An Occupancy Information Grid Model for Path Planning of Intelligent Robots

Commonly used robot map models include occupancy grid maps, topological maps, and semantic maps. Among these, an occupancy grid map is mainly represented as a quadrilateral grid. This paper proposes an occupancy information grid for intelligent robots by exploiting the advantages of the occupancy grid map and spatial information grid. In terms of geometric structure, a regular hexagonal grid is used instead of a regular quadrilateral grid. In terms of attribute structure, the single obstacle attribute is replaced by the grid terrain characteristics, grid element attributes, and grid edge attributes. Thus, the occupancy information grid model is transformed into a new data structure describing the spatial environment, and it can be effectively applied to map construction and path planning of intelligent robots. For the map construction application of intelligent robots, this paper describes the basic process of laser sensor-based grid model construction. For the path planning application of intelligent robots, this paper extends the A* algorithm based on a regular hexagonal grid. Additionally, map construction and path planning applications for intelligent robots are experimentally verified. Several experimental results were obtained. First, the experimental results confirmed the theoretical conclusion that the minimum sampling density of the hexagonal structure was 13.4% lower than that of the quadrilateral structure. Second, the regular hexagonal grid is clearly more advantageous in describing environmental scenes, which can ameliorate the "undercompleteness" phenomenon. Third, there were large differences in the planning paths based on two types of grids, as shown by the fact that the distance of the planning paths obtained by the regular hexagonal grid was reduced by at least 10.8% and at most 15.6% compared with the regular quadrilateral grid.

A balanced decomposition approach to real-time visualization of large vector maps in CyberGIS

With the dramatic development of spatial data infrastructure, CyberGIS has become significant for geospatial data sharing. Due to the large number of concurrent users and large volume of vector data, CyberGIS faces a great challenge in how to improve performance. The real-time visualization of vector maps is themost common function in CyberGIS applications, and it is time-consuming especially when the data volume becomes large. So, how to improve the efficiency of visualization of large vector maps is still a significant research direction for GIScience scientists. In this research, we review the existing three optimization strategies, and determine that the third category strategy (i.e., parallel optimization) is appropriate for the real-time visualization of large vector maps. One of the key issues of parallel optimization is how to decompose the real-time visualization tasks into balanced sub tasks while taking into consideration the spatial heterogeneous characteristics. We put forward some rules that the decomposition should conform to, and design a real-time visualization framework for large vector maps. We focus on a balanced decomposition approach that can assure efficiency and effectiveness. Considering the spatial heterogeneous characteristic of vector data, we use a "horizontal grid, verticalmultistage" approach to construct a spatial point distribution information grid. The load balancer analyzes the spatial characteristics of the map requests and decomposes the real-time viewshed into multiple balanced sub viewsheds. Then, all the sub viewsheds are distributed to multiple server nodes to be executed in parallel, so as to improve the realtime visualization efficiency of large vector maps. A group of experiments have been conducted by us. The analysis results demonstrate that the approach proposed in this research has the ability of balanced decomposition, and it is efficient and effective for all geometry types of vector data.

Design & implementation of distributed spatial computing node based on WPS

Currently, the research work of SIG (Spatial Information Grid) technology mostly emphasizes on the spatial data sharing in grid environment, while the importance of spatial computing resources is ignored. In order to implement the sharing and cooperation of spatial computing resources in grid environment, this paper does a systematical research of the key technologies to construct Spatial Computing Node based on the WPS (Web Processing Service) specification by OGC (Open Geospatial Consortium). And a framework of Spatial Computing Node is designed according to the features of spatial computing resources. Finally, a prototype of Spatial Computing Node is implemented and the relevant verification work under the environment is completed.

Dynamic identification of one-way road state based on floating car data

The identification of one-way road state can provide relevant information of road network to the public timely and accurately,improve the efficiency of public travel,and enhance the service level of dynamic traffic information.This paper presented a dynamic identification algorithm of one-way road state based on Floating Car Data(FCD).Firstly the line feature information of maps was got,and the matching of spatial information grid with the traffic roads was pretreated to achieve fast matching for massive FCD;Then statistical characteristics of FCD direction information was analyzed to filter dual-threshold information and direction information;Finally one-way road state information was got dynamically.The actual road network tests show the algorithm can identify one-way road state information effectively.

An On-Demand Approach to Build Reusable, Fast-Responding Spatial Data Services

Many applications for global climate change research heavily rely on analyzing geospatial data collaboratively and always accompanying with complex computational algorithms. It is desirable to study a flexible and efficient approach for easy interoperation among heterogeneous datasets and computation models, thus providing quick responses for decision making. Early research on services-based mechanisms can ensure interoperability of geo-data resources and interoperability of geo-processing sources, but cannot ensure interoperability of both geo-data resources and geo-processing sources simultaneously due to their different characteristics on service deployment and management. An important issue is to find a way to keep diversity of data sources and maintain advantages of various geo-processing algorithms whereas data resources and processing sources can be chained together at a certain level of granularity. To address this need, we propose Data Service Entity Node (DSEN) to take the spatial data sources and geo-processing function as isomorphic service in a uniform manner based on service clustering method. We have applied our on-demand data service model to China Spatial Information Grid (SIG) test-bed and report a case study of flood monitoring application. The result shows our advantages and powerful capabilities by running two algorithms and process models for water extraction in an efficient way. The proposed on-demand approach can be used to build reusable spatial data service and respond quickly, and dynamically support different requirements of targeted applications.

THE SEMANTIC RETRIEVAL OF SPATIAL DATA SERVICE BASED ON ONTOLOGY IN SIG

Abstract. The research of SIG (Spatial Information Grid) mainly solves the problem of how to connect different computing resources, so that users can use all the resources in the Grid transparently and seamlessly. In SIG, spatial data service is described in some kinds of specifications, which use different meta-information of each kind of services. This kind of standardization cannot resolve the problem of semantic heterogeneity, which may limit user to obtain the required resources. This paper tries to solve two kinds of semantic heterogeneities (name heterogeneity and structure heterogeneity) in spatial data service retrieval based on ontology, and also, based on the hierarchical subsumption relationship among concept in ontology, the query words can be extended and more resource can be matched and found for user. These applications of ontology in spatial data resource retrieval can help to improve the capability of keyword matching, and find more related resources.

The Research on Flood Character Grid Base on GIS

Flood character grid is the most important part of the spatial information grid, which is used in the research of the model for flood disaster loss assessment. The implement of it's processing including: (1)Create a polygon class which has elevation, the depth of flood, the speed of flood current, the pollution degree of flood field in Personal Geodatabase; (2)Determining the size of grid and set the size of polygon element according with its size;(3)Import the attribute value to correspond field;(4)Use ArcEngine and C# programming implement it. The application example results show that the speed of use personal Geodatabase to create polygon class is very fast and use the data of DEM can extract the elevation attribute effectively, it can provide the basic data for the loss assessment of the flood disaster consequently.

PRS-BASED INFORMATION EXTRACTION OF OBJECTS IN REMOTE SENSING IMAGE

The point resource system is a new needs-oriented method for information processing. In PRS, points can have different scales and resolutions, which is a reflection of the real world based on the synthesized description of the object. With this useful tool, we can process large quantities of remote sensing data more quickly and accurately. The performance of the point resource system in image processing is described. To meet the demand of information extraction in the spatial information grid, a model is built which includes image point modeling, knowledge point modeling and object point modeling. A full procedure of objects extraction with PRS is shown in this paper.

Spatial Information Grid Services Based on WSRF and Their Management

Spatial Information Grid Services Based on WSRF and Their Management

The Data Transmission Network and Computing Environment of Spatial Information Grid

Studied the foundation of SIG (Spatial Information Grid) computing environment, this article first designed a data transmission network which is based on SIG. And then, it described the topological structure and communication link of data transmission network. Next, it discussed the status quo of spatial computing resources and the resources deployment of spatial information grid which made a support to the finding and calling of resources. Finally, it studied the resources finding and sharing of spatial information grid in VO (Visual Organization) and the VO form in SIG. It then proposed the resources finding mechanism and the sharing process.

Application of Spatial Information Grid in the Field of Chinese Materia Medica Resource Inventory

There are two main problems in the field of Chinese materia medica resources.One is that the data of Chinese materia medica resources cannot be shared by different users,and the other is that they cannot be used for special purposes,because the data come from different sources during resource inventory.The paper introduces the technology that can be used in the field of Chinese materia medica resource inventory-spatial information grid.The paper mainly discusses the application of spatial information grid in the field of Chinese materia medica resources,including the features and concept of spatial information grid,the division of the spatial information grid in the field of Chinese materia medica resource inventory,the way to set up the attributes of grid,the way to obtain and update the data of grid,and for what the spatial information grid can be used in the field of Chinese materia medica resource inventory,with the hope of finding a new way to realize the digitalization of Chinese materia medica resources,and help to share and use the data of Chinese materia medica resource inventory.

The Optimization of Remote Spatial Join Queries on Spatial Information Grid

The Optimization of Remote Spatial Join Queries on Spatial Information Grid

Preliminary study of Grid computing for remotely sensed information

Observing the world‐wide concentration and distribution of ozone is important for monitoring the evolution of the ozone layer, to derive the amount of UV, to provide ozone and UV forecasts and to improve weather forecasting. Monitoring ozone is the primary function of the Global Ozone Monitoring Experiment. Each day, space missions download, from space to ground, many raw images that are stored in ground stations located all over the world. How to process this data resource in real time — or almost real time — and effectively share spatial information among the remote sensing community is a pressing task. Grid computing can provide access to a globally distributed computing environment via authentication, authorization, negotiation and security. It can create a computational environment handling many PetaBytes of geographically distributed data, tens of thousands of heterogeneous computing resources and thousands of simultaneous users from many research institutions. It can provide a powerful tool for sharing both remote sensing data and processing middleware. This paper introduces the concept of grid computing, followed by its applications for atmospheric ozone retrieval. The special remote sensing data analysis note for the Spatial Information Grid (SIG) is addressed in detail. A series of remotely sensed image processing middleware is shown. Experience shows that near‐real‐time products, such as maps of ozone, from the processing and analysis of remotely sensed data are possible.

On Generalized and Specialized Spatial Information Grid

On Generalized and Specialized Spatial Information Grid

A visual information system and its use in urban planning

This research is based on a visual information system. Information about visual— aesthetic relationships in space is taken from panoramic photographs. These photographs are taken from the intersections of the spatial information grid. Views are inventoried and evaluated, and information is transferred into grid cells and thence into a computer data bank. Thus we can process and simulate different visual phenomena and optimise future visual impact. Changes in the environment can be simultaneously tested on photographs and through computer outputs. In the present research, this basic visual information is broadened into the field of sociology, through questionnaires about public opinion. That is, visual information is measured according to values given by the public about the visual environment. Thus we incorporated the whole feedback loop — visual inventory—public evaluation—computer optimisation—testing on photographs. With such information we have tested various visual relationships, such as visual absorption of the countryside, visual dynamics, interactions and changes in databank. The crucial parts of the research are location criteria for different land-uses to give an optimal visual impact: housing, working places, centres, recreation areas, preserved land, traffic- and communal infrastructures. Each experiment consisted of several tests with computer outputs, photosimulations and interpretations. Computer- printed information was applied to photographs. In the research we have also completely documented computer programs. Their most important roles are lists, averages, extreme values, frequencies and graphical outputs in plotter or printer (SYMAP) techniques.