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The Linbeiken area is located in the village of Pingding, Taiwan. Since the Mindulle and Aere Typhoons in 2004, and as a result of the landslide triggered by the continuous heavy rainfall on 9 June 2006, there has been a persistent collapse of side slopes in the area. This paper describes the equipment that was installed to collect on-site topographic and hydrological information in the Linbeiken area upstream of the Pingding River and to monitor changes in the landslide area, as well as the measurements that were collected during the 2008 Typhoon Sinlaku. A case study of a landslide in Pingding, Taiwan was used to monitor the accurate coordinate changes in the potential landslide areas during typhoons. The goal of this study was to establish warning indexes, and to strengthen the software and hardware at the local disaster response center in the hope of gaining a full idea of the surface movement in landslide areas in future flood seasons. This is important for boosting the preparedness to adapt to landslide hazards, for improving disaster warnings, and for reporting efficiently to better protect the lives and property of local residents. The results show that the landslide disaster monitoring and warning system in Taiwan, as applied during Typhoon Sinlaku in 2008, is both effective and comprehensive.

Forest fires constitute a major environmental problem in tropical countries, especially in the context of climate change and increasing human populations. This paper aims to identify the causes of frequent forest fires in Son La Province, a fire-prone and forested mountainous region in northwest Vietnam, with a view to constructing a forest fire-related database with multiple layers of natural, social and economic information, extracted largely on the basis of Landsat 7 images. The assessment followed an expert systems approach, applying multi-criteria analysis (MCA) with an analytical hierarchy process (AHP) to determine the weights of the individual parameters related to forest fires. A multi-indicator function with nine parameters was constructed to establish a forest fire risk map at a scale of 1:100,000 for use at the provincial level. The results were verified through regression analysis, yielding R2 = 0.86. A real-time early warning system for forest fire areas has been developed for practical use by the relevant government authorities to provide more effective forest fire prevention planning for Son La Province.

Climate change has been impacting strongly on economic sectors, facilities, people and wealth. Developing sustainable disaster prevention and mitigation technologies in the context of climate change is a long-term and urgent task of all levels, sectors and localities. Based on the analysis of scientific findings on the evolution of some major climatic factors (temperature and rainfall), sea level rise and the impact of these factors on the sectors of the sector Quang Ninh Tourism. At the same time, assessing the impact of climate change on all sectors, form the basis for new proposals for high-tech applications. Keywords Climate change; Disaster; Disaster prevention; Disaster mitigation; Quang Ninh; Quang Ninh flooding DOI: https://doi.org/10.23953/cloud.ijarsg.373

In regular convolutional neural networks (CNN), fully-connected layers act as classifiers to estimate the probabilities for each instance in classification tasks. The accuracy of CNNs can be improved by replacing fully connected layers with gradient boosting algorithms. In this regard, this study investigates three robust classifiers, namely XGBoost, LightGBM, and Catboost, in combination with a CNN for a land cover study in Hanoi, Vietnam. The experiments were implemented using SPOT7 imagery through (1) image segmentation and extraction of features, including spectral information and spatial metrics, (2) normalization of attribute values and generation of graphs, and (3) using graphs as the input dataset to the investigated models for classifying six land cover classes, namely House, Bare land, Vegetation, Water, Impervious Surface, and Shadow. The results show that CNN-based XGBoost (Overall accuracy = 0.8905), LightGBM (0.8956), and CatBoost (0.8956) outperform the other methods used for comparison. It can be seen that the combination of object-based image analysis and CNN-based gradient boosting algorithms significantly improves classification accuracies and can be considered as alternative methods for land cover analysis.

The Bridge Health Monitoring (BHM) system has become crucial for long-span bridge structures. This study aims to assess the bridge deck movement based-on GPS time series data and environmental data obtained from BHM system. The correlation and regression analysis are utilized to find out the pairwise relationship between the bridge deck movement in all directions and environmental factors as well as traffic load. The result shows the highest correlations in bridge deck vertical movements, the symmetrical oscillation in different parts of bridge deck and it also reveals the impact of air temperature change, wind velocity and traffic vehicle on bridge deck movement in all directions.

With the development of mobile mapping systems, point cloud is becoming an important data type to build the three-dimensional geospatial information. In particular, some recent applications such as robot navigation, self-driving drones/vehicles, and construction robotics need three-dimensional high-definition maps within cm-level accuracy to make a decision of action by themselves. These maps are based on point cloud data from three-dimensional surveys of geographic features on the Earth by laser scanning and photogrammetry. Point clouds provide a flexible and accurate geometric information for reconstructing 3D shapes of not only indoor but also outdoor features. However, it expends time on creating a map due to many manual operations of processing. In this paper, we design an interoperable framework of semantic annotation for point cloud data. Semantic annotation of point cloud is the process of attaching conceptual label information such as cars, buildings, desks, or people to each point in a set of data. This process takes first priority to create training data set for machine learning and deep learning tasks. An efficient annotation tool for 3D point cloud data is crucial to improve the quality of deep learning models and getting better results in deep learning would be helpful to reduce the manual processing. Even though there are already a number of tools, they are usually standalone and tightly coupled systems. This is likely to lead to a problem of limited interoperability of data and process between systems. This paper introduces a resource-oriented design for the annotation framework of point cloud data on the Web with the ability of quick adaptation of various machine learning techniques.

In recent years, as information technologies have been widely adopted, more countries have focused attention on the intelligentization of cities. In 2012, the United Nations listed “Smart City” as one of the progress indicators of a country. The original development of smart cities emphasized technology-based demands, but gradually promoted people-oriented needs, especially on issues related to living and environment, such as public safety, transportation, environmental sustainability and health care. The most important concern is to provide effective solutions to local problems. Spatial information has become wider and more diversified with the rapid development of high technologies, such as ICT, IoT and big data applications. It plays an important role in the planning of smart cities and smart homeland. Municipal governance such as traffic control, environment monitoring, disaster prevention information is based on geographic information system (GIS). The resources, information and data of cities can be spatially visualized. The spatially visualized information are not only texts and data, but integrated, coherent and spatially effective information which can identify and explore correlation and development trends in urban information. In view of this, the government uses smart homeland as the core to explain development and planning of smart city and smart village, and in consideration of the unique geographical characteristics of Taiwan and the importance of spatial resources management and strategy, promotes development of spatial information technologies and application of the technologies to smart homeland. On the basis of smart homeland concept, this study discusses key points of promotional strategies and action plans of the cities in Taiwan, and from the perspective of spatial information, explores and analyzes how to integrate spatial information technologies into urban governance, disaster prevention traffic and tourism under Taiwan's strategies for smart homeland information development. It can help the county and city governments to propose the smart city development strategies, improve government governance, promote regional economic growth, satisfy people's demands and promote the sustainable development of smart cities.

The aim of this study was to develop an online collaborative map to enable researchers to locate, explore, and share cancer data.This 2-scale (global and country-level) cancer map adopts a database-driven model, which was implemented using the Google Map Application Programming Interface (API) and asynchronous JavaScript and XML (AJAX) technology. Seven visualization techniques were used to present data. Data on worldwide cancer mortality between 1950 and 2013 were taken from the International Agency for Research on Cancer (IARC) database. Incidence data were from the IARC CI5plus database. Survival data were from the IARC SURVCAN study. Prevalence data between 1990 and 2017 were from the Institute for Health Metrics and Evaluation's (IHME) catalog while demographic data were from the World Bank Data Catalog. Cancer data for Taiwan between 1991 and 2016 were obtained from the Department of Health and Welfare. This study used visualization techniques that included: a choropleth map to display the prevalence of cancer; a tornado diagram to show the age-standardized mortality rates of all cancers among men and women in 2013; a treemap to show a ranking of cancer mortality data; a sunburst chart to show mortality rates of all cancers by gender; a line chart to show mortality trends for all cancers; a bar chart to show mortality and incidence rates and a heatmap to show variations in cancer across different countries.The world cancer map generated by this study can be accessed at http://worldmap.csmu-liawyp.tw. Country-level mortality data are presented as crude and age-standardized rates.We used visualization methodologies and constructed an easily maintainable web-based user interface with cancer data from administrative regions in 150 countries. This serves as a platform that allows researchers to manage and disseminate cancer data.

There are many factors in various aspects that affect spatial data sharing (SDS), such as organization, personnel, legal system, data use, technique, motives, cost, fairness, power balance and data standards. Early research had mostly dealt with personal experience, which lacked holistic thinking and resolving. In recent years, researchers who believed SDS as a social phenomenon began study using Social Network Analysis and observed the role played by organizational networks during the process of SDS to explain how organizational networks affected SDS. While there exist few studies on SDS between units and persons within an organization, and past research lacked effective methods of message gathering and filtering from the targeted organizations, this study proposed the empirical method and dimensions, unlike before, to understand and promote SDS from various aspects. After observation on organizational process of SDS over a long period, this article gathered empirical data on the behaviours of SDS in Tai...

In recent years, the rapid development of remote sensing technology has proliferated high-quality images that occupy larger and larger storage spaces. Video has become widespread for environmental observation. Hence, digital data is growing exponentially, and geographic information systems must determine how to manage and process images and video effectively. Researchers cannot limit themselves to desktop PCs due to computational and storage limits. The aim of this article was to propose and implement an architectural design for a novel cloud computing platform based on two Web Coverage Service and Web Map Service interfaces from the Open Geospatial Consortium (OGC), cloud storage from Hadoop Distributed File System (HDFS), and image processing from MapReduce. Results are presented on tablet computers (Asus transformer pad) and websites. Within this framework, we implemented image management as well as simple WebGIS and created an experiment in read/write performance with four kinds of data sets (normal d...

Using GIS in the classroom enhance students’ computer skills and explore the range of knowledge. The paper highlights GIS integration on e-learning platform and introduces a variety of abundant educational resources. This research project will demonstrate tools for e-learning environment and delivers some case studies for learning interaction from Central Taiwan Universities. Feng Chia University (FCU) obtained a remarkable academic project subsidized by Ministry of Education and developed e-learning platform for excellence in teaching/learning programs among Central Taiwan’s universities. The aim of the project is to integrate the educational resources of 13 universities in central Taiwan. FCU is serving as the hub of Center University. To overcome the problem of distance, e-platforms have been established to create experiences with collaboration enhanced learning. The e-platforms provide coordination of web service access among the educational community and deliver GIS educational resources. Most of GIS related courses cover the development of GIS, principles of cartography, spatial data analysis and overlaying, terrain analysis, buffer analysis, 3D GIS application, Remote Sensing, GPS technology, and WebGIS, MobileGIS, ArcGIS manipulation. In each GIS case study, students have been taught to know geographic meaning, collect spatial data and then use ArcGIS software to analyze spatial data. On one of e-Learning platforms provide lesson plans and presentation slides. Students can learn Arc GIS online. As they analyze spatial data, they can connect to GIS hub to get data they need including satellite images, aerial photos, and vector data. Moreover, e-learning platforms provide solutions and resources. Different levels of image scales have been integrated into the systems. Multi-scale spatial development and analyses in Central Taiwan integrate academic research resources among CTTLRC partners. Thus, establish decision-making support mechanism in teaching and learning. Accelerate communication, cooperation and sharing among academic units

During nuclear accidents, when radioactive materials spread into the environment, the people in the affected areas should evacuate immediately. However, few information systems are available regarding escape guidelines for nuclear accidents. Therefore, this study constructs escape guidelines on mobile phones. This application is called Mobile Escape Guidelines (MEG) and adopts two techniques. One technique is the geographical information that offers multiple representations; the other is the augmented reality that provides semi-realistic information services. When this study tested the mobile escape guidelines, the results showed that this application was capable of identifying the correct locations of users, showing the escape routes, filtering geographical layers, and rapidly generating the relief reports. Users could evacuate from nuclear accident sites easily, even without relief personnel, since using slim devices to access the mobile escape guidelines is convenient. Overall, this study is a useful reference for a nuclear accident emergency response.

When radiological accidents occur, radioactive material may spread into the atmosphere, causing large-scale and long-term contamination. To diminish the effects of such accidents, researchers from many countries have investigated training programs in emergency response to radiological accidents, especially in the wake of several serious radiological accidents. Although many training programs have been proposed, this study identifies two problems: the lack of effective data representation and the lack of complete training records. Therefore, by considering various requirements for relief and evacuation work at radiological accident sites, it integrates four-dimensional geographical information and mobile techniques to construct a training platform for radiological accident emergency response. During training, groups of participants learn to respond to simulated radiological accident scenarios. Moreover, participants can use the training platform to review and discuss training details. Judging by the results, the training platform has not only increased the effectiveness of training programs, but also complied with standard operating procedures for radiological accident emergency response in Taiwan. In conclusion, this study could serve as a useful reference for similar studies and applications.

Mazu, a protective sea God, has been worshipped by residents of Taiwan and southeast coast of mainland China as well as overseas Chinese around the globe for hundreds of years. The number of people around the world under her influence of religious belief and moral culture can reach up hundreds of million. Every year in lunar March, the over- one-week long Mazu patrol and pilgrimage held by Jenn Lann Temple in Dajia County of Taiwan attracts millions of pilgrims and tourists around the world to participate in one of the biggest religious events in the world. To keep track of the entire patrol and pilgrimage, Jenn Lann Temple has been cooperating with GIS Research Center, Feng-Chia University since 2008, setting up a GPS receiver, a digital camera, and 4 video recorders on Mazu’s palanquin. Both real-time position of the palanquin and live videos on the scene along the way of pilgrimage were published on the Internet, providing pilgrims, tourists and viewers around the world with an open access to observe the entire event. This paper details this initiative of introducing spatial technology to large cultural events. The study collects the historic tracks of Mazu’s palanquin during the pilgrimage from 2008 to 2010, analyzes their spatial-temporal attributes, and elicits several interesting facts behind the figures and maps. It also explores how spatial technologies can help organize large-scale events and even accelerate the dissemination of culture.

The analysis, measurement, and computation of remote sensing images often require an enhanced supervised classification technique to develop an efficient spatial decision support system. Rice is a crop of global importance, which has drawn a great interest in using remote sensing techniques for evaluating its production. Ancillary information is widely used to improve the classification accuracy of satellite images. However, few of these studies questioned the importance and strategies of using this ancillary information. The enhanced decision support system in our study has two stages. In the first stage, the images are obtained from the remote sensing technique and the ancillary information is employed to increase the accuracy of classification. In the second stage, it is decided to construct an efficiently supervised classifier, which is used to evaluate the ancillary information. Back-propagation neural network (BPN) with extended delta bar delta (EDBD) algorithm is incorporated into our decision support classifier system. This classifier renders two crucial contributions: (1) the EDBD algorithm accelerates the convergence speed of the learning process and (2) the relative importance (RI) on each band of ancillary information is evaluated rationally.

To enhance the efficiency of surfing the Internet, an integrated platform for real estate agency-based on service-oriented architecture (SOA) is established. It employs the concept of search engine and loads the information provided previously by each real estate agency to this platform. Due to the different types of data structure from each real estate agency website, the standard format must be defined for integrating the information. In this paper, the standard is defined by XML and is used to integrate heterogeneous database. This standard format includes the data fields that are required by the agency websites. It is processed in the platform which is expandable by receiving information from other sources in the future. In consideration of the copyright regulation, the agents are allowed to login and to share specific information on this platform in order to increase the transaction rate. The system also includes a Google Map engine for GIS service that marks the spatial location as the users send the requests. It helps the users to find the demanded housing information and to retrieve the nearby geographic location in a very short time.

Nowadays, the administration and execution of disaster monitoring in Taiwan are able to achieve the goal of overall monitoring with the assistance of various tools and technology distributed in different organizations. Examples of information and technology include the data collected by monitoring stations, existing database and spatial data warehouse, precipitation information provided by the Central Weather Bureau (CWB), results of site investigation, Remotely Piloted Vehicle (RPV) airscape images, aerial photos, satellite images, and etc. Therefore, in order to facilitate tasks of disaster monitoring, heterogeneous data needs to be integrated via a consistent communication interface. The use of grids was proposed to solve the problems in heterogeneity, distribution, and efficiency triggered by networking. Information worth sharing is uploaded to a platform which can publish and register data and control the flow of information; users then access the platform to search and fetch valuable information and value-added applications. On the platform, all of the heterogeneous and distributed data is encrypted, decrypted, monitored, and hence interchangeable according to international standards. Because the employment of grid computing does not require large-scale modifications of existing systems, grids designed for different purposes are being developed. Our research adopts the emerging grid technology to create a grid-based disaster management mechanism. Taking disaster relief distribution as an example, we optimize the stockpile distribution and delivery routes by utilizing Sensor GRID and Application GRID and by combining the interpretation given by real-time traffic information systems. Our study will further the government's abilities to manage disasters, and substantially strengthen the cooperation and communication between the government and academic units.

Landslides during earthquakes have led to severe casualties and have resulted in damaged structures and facilities. The goal of the present study is to analyze the landslide problems in a remote area—Shei-Pa National Park in Taiwan. Spatial information techniques (Remote Sensing and Geographic Information System) with an innovative data mining technique, Discrete Rough Set (DRS) method, are incorporated to our study for analyzing landslides, their distribution, and classification. The present study provides how to find (1) the most representative data of landslide samples from the existing database, (2) the core attributes of the target categories: Normalized Difference Vegetation Index (NDVI) and Vegetation Index (VI), and (3) the thresholds (segment points) of each attribute on the target categories. A conventional approach, C4.5 Decision Tree Analysis, is used as a comparison. The methodology discussed in this study is of help to the analysis of landslide problems and thus facilitates the informed decision-making process.

Owing to the rapid developments in the field of Geographic Information Systems and Remote Sensing techniques, various images sources have been widely available to identify ground changes information. Those commonly used multi-scale images provide the sources from macro to micro information and can be served as basic analysis platform in landslide monitoring and land use classification. Taiwan has a unique and vulnerable geological condition with potential disasters easily triggered by landslide occurrence due to typhoon and heavy precipitation each summer season. In order to identify and analyze those landslide information temporary and spatially, this research integrate satellite images, aerial survey data from aviation photography and LIDAR, and remotely controlled helicopter techniques to set up a diverse information network. Satellite images can fulfill the need for large area environmental inventory and land use classification. Digital Terrain Model generated by LIDAR and aerial photos can b...

Debris flow, one of the most active hydrological processes, brings about a great loss of life and properties in the Chen Yu Lan River area, Nan-Tou County, Taiwan. The goal of this study is to manage and monitor the debris flows in a vast area. Thus, the strategy is to collect hydraulical and in-situ data easily and quickly through our spatial information system. Then, a novel Data Mining technique will be developed to find a rule-based knowledge system of debris flow. The entire study can be divided into two parts. In the first part, using spatial information the debris flow image is extracted from the outbreak area. The system provides precise positional information pertaining to the debris flow events. Attributes such as effective watershed area, Normalized Difference Vegetation Index (NDVI), and slope are automatically obtained from the system. In the second part of this study, K -mean theory is used to classify the observed hydraulical and in-situ data into different categories. Then, the ‘Effective Rough Set’ method is successfully used to analyze the factors influencing the debris flow phenomenon and delivers rational knowledge rules. The contribution of this study is presented that NDVI, slope and effective watershed area are the major factors influencing debris flow in the study area. The knowledge rules can provide better understanding on the elevation of high potential debris catchments.

Changes in land can involve pressing and complex problems that urban areas need to resolve. Construction of a land use or land cover mechanism is an essential way of dealing with those problems. Based upon the difficulties that occur in investigations of land use, this study will focus on the development of a spatial knowledge database. The major function of a spatial knowledge database is to integrate spectral, GIS, aerial photos, and DEM information. In this study data from a series of periods for SPOT‐HRV XS images (1993, 1996, 1998) were collected. A decision‐tree concept was built into the image‐classification database to resolve the uncertainty of images in urban areas. The aim of this study is to provide an objective solution for efficiently classifying images in urban areas.

Since 2003, the Taichung Jazz Festival has become one of the major annual events regularly held in Taichung City. The number of tourists and the tourism business opportunities brought by this festival has been increasing year by year, even reaching more than 1 million participating tourists/times ever since 2015. In terms of traditional assessment methods for great events, we used to obtain analytic information such as visitor satisfaction or the number of people through questionnaires. However, different levels of issues concerned by tourists cannot be easily understood through standardized questionnaires. Due to the popularization of online platforms and smart phones, people tend to voluntarily provide some information when they are participating in an activity. Such coordinated information is namely "Volunteered geographic information" (VGI), ex. "check-in" created by anyone. People can show their positive and negative messages by expressing their words about certain places (food, landscape, etc.), which can can make up for the shortcomings of traditional questionnaires. In this study, through the API provided by Facebook and by writing a web crawler program, we downloaded a total of 46,260 comments/messages written by people during the period of the Jazz Festival. Then, by means of Chinese word segmentation and through keywords, statistical analyses were conducted on two indicators shown by these tourists regarding the Jazz Festival: 1. Satisfaction about this event: To analyze people's positive and negative evaluations of the handling of this event, as well as their feelings; 2. Suggestions for event improvements: To analyze all aspects of concrete problems and suggestions for improvements proposed by people for this event. In this study, through collecting VGI data and constructing unstructured information analysis methods, explorations were made, concerning people's intuitive feeling about Jazz Festival from a mass perspective. In addition, comparisons and analyses against traditional questionnaires were conducted. Therefore, the findings of this study can serve as a reference for future leisure activity surveys combined with VGI data analyses.

This paper proposes a service integration model of service component architecture (SCA) that follows Service Oriented Architecture principles applied in services of Geographic Information Systems (GIS). GIS integrates the different types of data to bring a broader, more comprehensive view to decision makers. We have successfully integrated SCA in the domain of vending machines in the past. Readily, we focus on using this architecture to integrate related services of GIS, substantially reduce the duplication of development, publish service of disaster reduction quickly, and provide users with a completely new experiential usage in GIS domain. Meanwhile, we also address many components that can be integrated with system scaling up in GIS, such as environmental monitoring, remote-sensing image's processing, Map services, location-based services, and so on. Therefore, we use cloud computing to solve these discussed issues. Finally, this paper implements a SCA-based Rainfall Information Application that composes web service from third party, employs GIS interpolation computation by IDW, and runs the cloud-based service by MapReduce programming model easily. The results of this study can increase development speed, reduce unnecessary work and time consuming, and make the system more stable and scalable in GIS.

In recent years, due to the rapid development of remote sensing technology, a single high-quality image will occupy larger storage space, and video has become so widespread in the usage of environmental observation and record. Hence, digital data is growing exponentially, and how to manage them and make image processing more effectively is a key issue in Geographic Information System. Additionally, the limitation of hardware resource and time-consuming images' processing is a bottleneck to cope with such big data by commercial software in single PC. The aim of this paper is to propose a framework based on some standards of the interface (WCS, WMS, and WPS) from Open Geospatial Consortium (OGC), cloud storage from HDFS, and image processing from MapReduce. Within this framework, we implement image management as well as simple WebGIS and test a read/write performance under four kinds of data sets (Normal Distribution, Skew to Left, Skew to Right, and Peak in Left and Right). The results reveal write/read performance of HDFS are outperform than the local file system in the situation of larger files (most files range in size from 8 MB to 10 MB) and a large number of threads (threads equal to 40 or 50).

Spatial data sharing is fundamental to the promotion of spatial data infrastructure. Data sharing is affected by diverse and complex factors, which have been studied largely by the approach of observing organizational development. Quantitative messages and qualitative descriptions have been obtained through gathering of organizational messages from short-term surveys with massive questionnaires or through relatively in-depth case studies. But the stability of research results has been affected by the questionnaire contents, the appropriateness of responding subjects chosen, how thorough the understanding of organizational operation was and the timing of investigation, as well as the judgment of the correctness of the information gathered. Given little research having investigated the messages about the subjects by long-term observation, this article takes the approach of direct, in-depth involvement and long-term observation on the organizational process of spatial data sharing to gather the first-hand and consistent data of Taichung City Government's n development on spatial data over the span of 17 years. Preliminary analysis of the factors affecting spatial data sharing is made by empirical research. Also, the complexity of spatial data sharing is explained from the multiple, interactive dimensions of Balanced Scorecard. The present research presents to verify, based on empirical data, that the dimension of influence of regulation enforcement is a direct and crucial factor, with part of the findings echoing to other previous research. The present research is hoped to understand, based on the materials of unprecedented, long-term empirical research, the real causes of the influences on spatial data sharing and to explain it.

This paper explores the application of virtual reality techniques to rail transit systems from the design and training perspective. This paper presents virtual environments for interactive 3D visualization of a rail transit station. It also describes the design and implementation of some 3D models, which offer a good level of user-interaction and animation within a common rail transit system. The virtual environments for interactive 3D visualization are modeled using Virtual Reality Modeling Language (VRML), a web standard for creating virtual worlds. Two basic categories of models are discussed in the paper. The static 3D models, which are used for planning and design purposes, are based on the object-oriented approach. The dynamic models, which are used for simulation and driver-training purposes, are based on the event-driven approach. Even though a standalone VR application is not capable of a higher level of interaction or animation, using SCRIPT nodes, JavaScript can be embedded in the program to provide additional functionalities. JavaScripting can be used ingeniously to manipulate and control some of the key animation and interpolation nodes to provide powerful functionalities within the VR world. This paper integrates the script programming language with virtual reality and elucidates simulations that can be employed for driver training purposes. By employing these visualization and simulation techniques, designers, engineers, planners, and decision-makers can assess the plan beforehand. The virtual worlds serve as immensely useful tools during the design process by helping the designers to position themselves in photo-realistic 3D immersive environments wherefrom the actual scenario can be viewed and modifications made accordingly.