Environmental Information for Intelligent Decisions

• Published in: Intelligent Environments pp. 245 - 258
• Main Authors: Kaye, Patricia, Noble, Stewart, Slater, Wayne
• Format: Book Chapter
• Language: English
• Published: The Netherlands North-Holland 1997; Elsevier Science & Technology
• Subjects: Computer science; GEOGRAPHY; Highway & traffic engineering
• ISBN: 0444823328; 9780444823328
• DOI: 10.1016/B978-044482332-8/50018-4

Environmental issues are undermining the entire energy base of industrial society, threatening the quality of human life, and the very survival of the human species. Computing and communications systems enable one to better visualize and understand the complex environment. A “virtual ecosystem” is being created, in which people can explore alternative scenarios and consider the environmental outcomes of their decisions. Sustainable management of the environment is the goal, so that the environmental impacts of human activities are minimized. Intelligent decisions, based on the most expert knowledge available, are the cornerstone of such ecologically sustainable development. Effective solutions to environmental problems require a proactive and dynamic decision-making process that draws together interested parties to protect, restore and manage ecosystems, conserve biodiversity, and pursue sustainable development. Most of the existing information is isolated, available to only a few. These islands of expert data can be drawn together and made available to those who need it by using the distributed database technology. The technologies that enable visualization of the landscape are geographic information systems, satellite-image analysis, and spatial modeling algorithms. The use of spatial analysis allows relationships to be explored on scales varying from local to continental to global. Spatial modeling techniques allow the exploration of complex relationships between data objects. Access to information is being provided through cyberspace, an environment inhabited by knowledge existing in electronic form. This chapter presents Australia's Environmental Resources Information Network (ERIN) as a case study to illustrate how remotely sensed and ground based monitoring data can be combined with spatial, demographic, and biological information.