Web cellular automata: a forest fire modeling approach and prototype tool

by: Publication: Cartography and Geographic Information Science

Rapid advances in computer processing and visualization capabilities, coupled with the decreasing costs of personal computers, have allowed a wider end-user group to access advanced GIS, spatial modeling, and visualization technologies. Consequently, the development of and on GIS-based applications environmental models standalone desktop computers and workstations within small networks has become an established practice for small businesses, consulting companies, governments, and academics. However these standalone applications and models suffer from many limitations that include platform dependence, limited end-user access, and inefficient data and information dissemination.

The use of Internet technology can overcome many limitations of stand-alone GIS applications and environmental models (A1-Sabhan et al. 2003). The Internet is an interconnected system of net works linking computers around the globe, regardless of geographic location. Internet technology has evolved rapidly during the last decade, and the Internet and world wide web (WWW) are now firmly recognized as effective means of exchanging geospatial data (Rohrer and Swing 1997; Doyle et al. 1998).

GIS applications on the Internet can be traced back to the second half of the 1990s. Internet GIS is a network-based GIS utilizing both the wired and wireless Internet to provide access to remote geospatial data and geo-processing tools (Peng 1999). The structure is based on a client/ server arrangement with functions for presentation, program logic, and database management distributed between the client and server computers. The world wide web is a networking and an information-sharing application based on the HTTP protocol that extends the Internet framework. Most Internet GIS applications use the web to exchange data, perform limited spatial analysis, and visualize results. Hence, the term Web-based GIS or Web GIS is often used for this kind of GIS extension (Peng and Tsou 2003).

Deploying GIS applications on the Internet is more advantageous than using stand-alone applications (Xie and Yapa 2006; Bellasio and Bianconi 2005; Al-Sabhan et al. 2003). Models on the Internet can be accessed by multiple users at different geographical locations, thus leading to increased involvement of stakeholders in the decision-making process. This in turn allows further communication and collaboration in decision-making (Dragicevic and Balram 2004; Mustajoki et al. 2004; Li 2006). Remote databases can be accessed in different geographical locations as well as in real time. Data security and integrity can be maintained more efficiently on data servers, by specifying varying degrees of permission for different users. Moreover, there is no need for specific GIS or modeling software on the client copotin, thereby allowing application and database upgrades and debugging from a central location. By providing a consistent and user-friendly interface with essential tools and functionality for the specific application, the end-user is more focused on the tasks and goals for solving the problem. Furthermore, GIS applications and models are not dependent on a specific hardware or operating system platform; an Internet connection and web browser are the only prerequisites for accessibility.

There exists a wide range of proprietary Web GIS software that is engrained within the GIS user and developer community. Examples software include Autodesk�s MapGuide (Autodesk, Inc. 2007), ESRI�s ArcIMS (ESRI 2007), ER Mapper�s Image Web Server (ER Mapper 2007), GE SmallWorld�s Internet Application Server (GE Energy 2007), Intergraph�s Geomedia Web Map (Intergraph 2007) and MapInfo�s MapXtreme (MapInfo 2007). Traditional Web GIS has been mainly limited to web mapping applications that serve static maps as raster images as well as more interactive vector-based thematic maps. Specifically, the functionality of Web GIS software technology is limited to common tasks such as pan and zoom, geo-coding and buffering, spatial queries, and feature extraction. Hence, more advanced GIS analysis functionality and spatio-temporal modeling capabilities are not yet fully established as mainstream Web GIS technologies.

In parallel with the increased use of web-based GIS, the past decade has seen more active research on web-based spatial modeling and spatial decision support systems (SDSS). Increasingly, researchers are now making their spatial models accessible over the web, with examples including: oil spill modeling (Xie and Yapa 2006), simulation of industrial accidents and atmospheric dispersion (Bellasio and Bianconi 2005), land evaluation for agricultural soil protection (De la Rosa et al. 2004), exploratory data analysis of river water quality parameters (Halls 2003), management of urban soils (Hossack et al. 2004), river systems (Chang and Chang 2002), watersheds (Choi et al. 2005; Huang and Worboys 2001), hydrological land-use change impact assessment (Choi et al. 2005), flood prediction (Al-Sabhan et al. 2003), floodplain management (Stigumaran et al. 2000), livestock grazing (Mohtar et al. 2000), and soil contaminant transport (Zeng et al. 2002).

There are several challenges related to implementing models that can handle spatial and temporal components of the change process over the web. The computational load between client and server must be balanced for optimal performance. There must be sustained bidirectional communication between the client and server during the modeling process so as to update the displayed results at each time step (Huang 2003). As well, the lack of temporal GIS capabilities is an ongoing challenge facing web-based modeling efforts because the integration of Web GIS and dynamic models still needs to be adequately addressed.

Given the advantages of deploying spatial models over the web, one application area that can particularly benefit from the new web functionalities is natural hazard/disaster management and response, where both rapid information dissemination of real time data and collaborative decision making are of paramount importance (USGS 2007). Forest fire is one such natural hazard. Forest fires serve an integral role in maintaining the health and diversity of many forest ecosystems (Johnson and Miyanishi 2001), but they may also have negative socio-economic impacts linked to public health, safety, property, and resource depletion.

There are many fire models and decision support systems in existence or in continuous development (Pastor et al. 2003; Andrews and Queen 2001). Accessing these models and decision support tools over the web can provide valuable assistance to fire management agencies and stakeholders involved in making more effective management decisions in real time. Important benefits include the prevention of loss of life and property, as well as reducing the adverse effects on natural resources.

Deployments of fire-related applications over the web such as forest fire risk mapping (CFS 2007), real-time and forecast weather (Rocky Mountain Research Station 2007), hot spot detection (MODIS 2007), and burnt area mapping (NorthTree Fire International 2007) have been reported in the literature. However, the challenges associated with extending spatio-temporal fire simulation models over the web has not been adequately addressed (Eklund 2001). In this study, we argue that making such simulation capability accessible over the web (especially using a thin client web interface) can be of immense value for fire disaster management and evacuation. Fire managers and decision makers can use PDAs or handheld computers at any place with an Internet connection (e.g., fire base station) and can run simulations of the progress of fire, based on the most up to date data

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One Response to Web cellular automata: a forest fire modeling approach and prototype tool

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