Web-Based Visualization of Marine Environment Data

Transcription

1 Web-Based Visualization of Marine Environment Data HE Yawen 1,2,3,*, Su Fenzhen 2, Du Yunyan 2 Xiao Rulin 2,3 1 Yantai Institute of Coastal Zone Research, CAS, Yantai , China 2 Institute of Geographic Sciences and Natural Resources Research, CAS, Beijing , China 3 Graduate School of Chinese Academy of Sciences, Beijing, , China *heyw@lreis.ac.cn Abstract As the long-term marine survey and research, especially with the development of new marine environment monitoring technologies, prodigious amounts of complex marine environment data keep continued and rapid growth. This paper recommends an integrative visualization solution to those data, to enhance the visual display of data and data archives, and to develop a joint use of those distributed data from different organizations or communities. Following this strategy, after the analysis of web services technologies and the concept definition of marine information gird, this paper focuses on the spatiotemporal visualization method and proposes a process-oriented spatiotemporal visualization method. It also provides an original visualization architecture which is integrative and based on the explored technologies. Then it shows how the marine environment data are organized based on the spatiotemporal visualization method, and how the organized data are represented for use with web services and stored in a reusable fashion. Finally, the prototype system for the marine environment data of the South China Sea provides visualization of Argo floats, sea surface temperature fields, sea current fields, salinity, in-situ investigation data and ocean stations. The integration visualization architecture is illustrated on the prototype system which highlights the processoriented temporal visualization method, which proves the good effect of the architecture and the method promoted by this work. Keywords-Marine environment data; Web Services; Marine information grid; Spatio-temporal visualization; Process-oriented; Integration I. INTRODUCTION The spatial information visualization is the specific application of computer visualization technology, and for the sake of furthering exploratory of the principle of spatial information through the visual effect in a virtual geographical environment [1-2]. China is a large marine country, hundreds of state and local organizations have expressed a need for products and services that integrate a variety of data into decision support tools (especially, web-based visualization tools), and research institutes have repeated called for additional research, data, information, tool, methods to aid their contingency planning and recovery efforts [3]. Therefore, it is crucial to provide efficient integration and visualization means of marine environment data that locate on distributed data centers in the marine business routine [4-6]. However, the integration and visualization of marine environment data face two major problems: first, barriers to organize and store the data caused by distribution. Second, multi-source, heterogeneity and the efficient integration method of distributed resources is still far from being achieved [7-8]. Moreover, visualization and integration cannot be implemented on single machine, often performed on super-computers, and the results of these tasks are usually analyzed by a design team consisting of several members [9-10]. Based on this point, this paper proposes a process-oriented spatio-temporal visualization method, and then elaborates on the integrative visualization architecture for marine environment data, and at last, a prototype system is developed to demonstrate the method and architecture. II. VISUALIZATION METHOD With the rapid development of detecting and observing technologies, the amount of the marine environment data keeps continued and rapid growth, and these data generate multidimensional data fields including huge and complicated information. However, the visualization and analysis of those data face two barriers. Firstly, discrete data collected from the marine observation projects and field data calculated by the marine models are too abstract to intuitively represent marine characteristics. Secondly, the oceanographic process is 3- dimensional space and featured as multi-attribute, boundary uncertainty, time-spatial unity and dynamic tendency. So the oceanographic process-oriented organization and expression of marine environment data are the precondition of the marine environment data visualization and analysis. Object model is used to organize and express the discrete characteristics, and field model is used to represent continuous phenomena in GIS, so as marine domain, the field model is used to represent wave, temperature, salinity, density, current, chlorophyll and other marine phenomena. The object model is used to represent coastline, submarine obstacle, fishing ground and other marine entities. In addition, the field-object model is used to represent thermal layer (such as temperature thermal layer, salinity thermal layer, density thermal layer and acoustic thermal layer), eddy (such as cold eddy and warm eddy), frontal surface, water mass, and other marine phenomena. There are a lot of previous visualization researches based on these expression models [11-16]. This study was granted from the Main Direction Program of the Knowledge Innovation of Chinese Academy of Sciences (Grant Nos. KZCX1- YW-12-04) and the National High Technology Research and Development Program of China (863 Program) (Grant Nos. 2009AA12Z148)

2 The spatial-dimensional based visualization method can be divided into two parts: 2D visualization and 3D visualization. In the former method, we can use point, line, surface and other symbols to represent the concerned entities and their components, and use the size of the symbol to represent the value of the entity. The latter method reflects the different values of various surfaces by chrome and gray. In marine domain, the 2D visualization mainly includes 2D scalar quantity field data visualization and 2D vector field data visualization. The visualization of 2D scalar quantity field data ((such as temperature, salinity and density, which have attribute value, but have no direction)) is realized by the chrome/gray visualization method. In addition, the geometry-graphic visualization method is mainly for 2D vector field data (such as chlorophyll, sea level pressure, sea surface temperature contour, ocean current). The study of marine phenomena not only focuses on the spatip-temporal distribution characteristics of sea surface, but also on this level of sea subsurface. So the 3D visualization of marine environment data is very important too. The 3D visualization, which is similar to 2D visualization, includes 3D scalar quantity field data visualization and 3D vector field data visualization. The profile reconstruction method and 3D iso-surface method are the major visualization methods for 3D scalar quantity field data, which are more complicated than the visualization methods of 2D scalar quantity field data. Firstly, some profiles are extracted at different depth from 3D data volume. Secondly, each of the extracted profiles is represented by the 2D scalar quantity data visualization method. The 3D vector field data are mainly used to represent the continuous characteristics in marine environment, and the changes of each spatial point in the 3D vector field are represented by the visualization method of 2D vector field data. Ocean current field is a typical 3D vector field, the changes of each spatial point in the ocean current field can be visualized by arrow with size and direction. However, it looks like disorderly that mass arrows are assembled together into a whole, so the visualization for 3D vector field data has not been solved perfected till now. The oceanographic processes are a concentrated and high information-based objects, moreover, are featured as multiattribute, boundary uncertainty, time-spatial unity and dynamic tendency. In order to understand the vary law of those objects in a period of time, recording their behavior at a certain moment, modeling and predicting their conditions of the future, studying the relationship between processes and conditions, and the spatiotemporal visualization of oceanographic processes are all very necessary. Thanks to the spatio-temporal visualization, point processes, line processes and surface processes with their attributes can be represented based on the time dimension using the visual and graphic fashion, so we can see the temporal and spatial distribution characteristics of marine environment data. This paper proposes the process-oriented spatio-temporal visualization method, which includes the point process visualization method, the line process visualization method and the surface process visualization method. 1) The point process visualization method is mainly for point objects, which can not only be points in space, but also be generalized spatial regions. This method mainly uses process curve to represent the different values of point objects on the time dimension, in the process curve system the vertical axis is the value and the horizontal axis is time, the value change through time is represented by the curve. 2) The line process visualization method is mainly for line objects, which can be straight lines and curves (such as horizontal line, vertical line) located on different direction and pressure. This method represents the various value of each point on the line through time, and it includes two ways: a) In the 3D coordinate system, using different color on a line to express the different value. b) In the 2D coordinate system, there are two means. (a) Static method. In the 2D coordinate system, the horizontal axis is time and the vertical axis is the length of the line segment, and the color and saturation represent the variety of value. (b) Dynamic method. In the 2D coordination system, the horizontal axis is the length of the line segment and the vertical axis is the value, each line in this system represents the value variety at one time, so we can set an interval for all the lines to display in order of time. 3) The surface process visualization method is mainly for surface objects (such as horizontal plane, vertical plane and inclined plane). In this method, colors represent the value of each spatial point on the plane, corresponds to different time, there will be many planes, so we can set an interval for all the planes to display in order of time. III. RELATIVE TECHNOLOGIES AND INTEGRATIVE ARCHITECTURE This section gives an overview of web services and marine information grid, then, we present specific requirements of the integrative architecture for marine environment data and propose our solutions that satisfy those requirements. A. Marine Information Grid Based on the previous research on web services and gird (for a review of early work in this area see[17-19]), this paper proposes the definition of marine information gird: it aims to provide seamless and scalable access to wide-area distributed marine resources, and enables the sharing, selection, and aggregation of a wide variety of geographically distributed computational resources (such as supercomputers, compute clusters, storage systems, data sources, instruments, people) and presents them as a single, unified resource for solving large-scale compute and data intensive computing applications (e.g., spatio-

3 temporal visualization of marine environment data, online analysis of the visualized marine environment data). In a previous article [20], according to the characters of marine environment data, a service-oriented architecture of marine information grid is put forward, and it has three layers, namely resource layer, service layer and application layer. to access the different marine environment data services. Additionally, as the marine environment data have to be represented by the spatio-temporal visualization method, those data have to be organized based on the process-oriented method. In order to facilitate the service registration, the architecture provides a service registration center base on UDDI (Universal Description Discovery and Integration). IV. PROTOTYPE SYSTEM AND RESULTS Application layer Figure 1. The architecture of marine information grid Resource layer mainly includes marine information (e.g. multi-format marine environment data, marine environment database) and computational resources (such as supercomputers, compute clusters, storage systems, data sources, visualization instruments, people). Service layer (middle-business logic tiger) functions as a link between the resource layer and the application layer. Moreover, it provides the unified interface to register, publish marine environment data based on web services and provides an appropriate agent to implement an abstract web service. The application layer is the service consumer that can communicate with the resource layer to find the marine environment data services and the computational resources, and can display services on a specified view or a normal browser. B. The Integrative Architecture Huge volume, distribution, multi-source, heterogeneity problems are the specific properties of marine environment data. Because of huge volume and distribution of data, it is almost impossible to efficiently transmit them to web clients. This paper proposes an integrative architecture which can solve the problems triggered by various techniques. The architecture is the running structure of marine information grid, which decides the stability and extensibility of the whole system. The integrative architecture is a 3-tiered architecture, the core components of the architecture are the process-oriented marine environment data organization and GIS server (Server Object Manager (SOM) and Server Object Container (SOC)). As the architecture aims at web services usage, GIS server has to be able A. Data Preparation and Services Implementation In this paper, the South China Sea is selected as the study area, and table 1 is the experimental data list. TABLE I. OVERVIEW OF THE EXPERIMENTAL DATA Name Time range Format Provider Geographical data None IMG IGSNRR, CAS Floats data NetCDF USGODAE Vector field data None NetCDF IGSNRR,CAS Scalar quantity field data 2006 HDF NASA For international recommendations of the web services, the integrative architecture uses ESRI s ArcGIS Server to provide interactive Web Mapping services in order to easily provide marine environment data on web browser. Here, we take the sea surface temperature field data as an example to illustrate how to implement the web services. Firstly, in order to accommodate the spatio-temporal visualization method, the marine environment data must be pre-processed and organized oriented process. Secondly, the managed data set is transformed into GIS data format (geodatabase). Thirdly, the transformed data is packed to web services. The descriptions of all the marine environment data services can be published to service registration center, and then all web services clients can use the operation of query to search the service description, and last use service description to bind with service provider and invoke service. B. Prototype System Design and Implementation Figure 2 is the deployment diagram of the prototype system, which consists of three web services nodes, a web services registration center and an integrative visualization service platform. Node 1 (provides web services of sea surface temperature field data and Argo data), node 2 (provides web services of sea current field data), node 3 (provide web services of other data) and the integrative visualization service platform are arranged in the institute of geographical sciences and natural resources research Chinese academy of science. The web services registration center is arranged in the Northeastern University. All the nodes are connected between each other, and the data nodes are not only the service providers, but also the service requesters, they utilize ArcGIS Server 9.3 for serving data services, IIS web server 6.0 as the HTTP proxy.

4 Figure 2. he prototype system component/ deployment diagram C. Visualization Results The visualization results of the prototype system include two aspects: 1) spatial-dimensional based visualization for float data, marine in-situ investigation data, scalar quantity field data and vector field data; 2) process-oriented temporal visualization for Argo float data, marine in-situ investigation data and sea surface temperature field data. Figure 3 and Figure 4 are the process-oriented visualization of sea surface temperature field data (provieded by IGSNRR, CAS, in South China Sea ( E, N)). Figure 3. The line process-oriented spatio-temporal visualization of sea surface temperature field data; this display shows the 2D visualization result of this data (A), the step 1 (B) to set the time range, the step 2 (C) to draw a line on the map, and the line process-oriented visualization result.

5 Figure 4. The surface process-oriented spatio-temporal visualization of sea surface temperature field data; this display shows the 2D visualization result of this data (A), the step 1 (B) to set the time range, the step 2 (C) to draw a polygon on the map, and the surface process-oriented dynamic visualization result (D). V. CONCULSION This paper presents techniques for integrative visualization of marine environment data (multi-dimensional space visualization method and process-oriented spatio-temporal visualization method). During the implementation we got a lot of insights into the web services and marine information grid. As a first contribution, this paper proposes a process-oriented spatio-temporal visualization method. Second, the integrative visualization architecture is outlined and illustrated using the prototype system. The prototype system provides visualization of Argo floats, sea surface temperature fields, sea current fields, salinity, and in-situ investigation data. Moreover, it becomes a wonderful education tool for the public learn about ocean. There are still plenty of open problems relating to 3D visualization of vector field data based on the process-oriented spatio-temporal visualization method. For instance, it is so disordered when all the features on different pressure are assembled together. We plan to address the above issue in the future by continuously extending the prototype system. Furthermore, the spatial analysis based on the web-based visualization method will be studied in a further stage of the research. REFERENCES [1] L. Deren, W. Yandong, Z. Qing, and G. Jianya, "Data model and visualization of 3D city landscape based on integrated databases," Geo- Spatial Information Science, vol. 2, pp [2] G. Jian-hua and L. Hui, "Perspective on Geo-visualization," Journal of Remote Science, vol. 3, pp [3] F. Su, C. Zhou, V. Lyne, Y. Du, and W. Shi, "A data-mining approach to determine the spatio-temporal relationship between environmental factors and fish distribution," Ecological Modelling, vol. 174, pp [4] D. J. Wright, "Coastal mapping and charting," Geospatial Solutions, vol. 14, p. 20. [5] S. U. Fen-zhen, "1, ZHOU Cheng-hu~ 1, YANG Xiao-mei~ 1, DU Yunyan~ 1, LUO Jian-cheng~ 1, ZHANG Tian-yu~ 1 (1. Institute of Geography Science and Resource Research, Chinese Academy of Sciences, Beijing100101, China); Definition and structure of marine geographic information system [J]," Acta Oceanologica Sinica, vol. 6,. [6] L. D. Ren, X. Y. Zhu and J. Y. Gong, "From Digital Map to Spatial Information Multi-grid A Thought of Spatial Information Multi-grid Theory," Geomatics and Information Science of Wuhan University, vol. 28, pp [7] T. Dimmestol and A. Lucas, "Integrating GIS with ocean models to simulate and visualize spills," in The 4th Scandinavian research conference on GIS, Helsinki, Finland, 1992, pp [8] N. Regnauld, "Improving efficiency for developing automatic generalisation solutions," in Joint ISPRS Workshop on Multiple Representation and Interoperability of Spatial Data, [9] J. Wood, H. Wright and K. Brodlie, "Collaborative visualization," in Proceedings of the 8th conference on Visualization'97, [10] K. W. Brodlie, D. A. Duce, J. R. Gallop, J. Walton, and J. D. Wood, "Distributed and collaborative visualization," in Computer Graphics Forum, 2004, pp [11] D. A. Lane, "UFAT: a particle tracer for time-dependent flow fields," in Proceedings of the conference on Visualization'94, 1994, p [12] N. Max, R. Crawfis and C. Grant, "Visualizing 3D velocity fields near contour surfaces," in Proceedings of the conference on Visualization'94, 1994, p. 255.

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