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CAG - computer-aid-georeferencing, or rapid sharing, restructuring and presentation of environmental data using remote-server georeferencing for the GE clients. Educational and scientific implications.

We suggest a method of using external public servers for rearranging, restructuring and rapid sharing of environmental data for the purpose of quick presentations in numerous GE clients. The method allows to add new philosophy for the presentation (publication) of the data (mostly static) stored in the public domain (e.g., Blue Marble, Visible Earth, etc). - The new approach is generated by publishing freely accessible spreadsheets which contain enough information and links to the data. Due to the fact that most of the large depositories of the data on the environmental monitoring have rather simple net address system as well as simple hierarchy mostly based on the date and type of the data, it is possible to develop the http-based link to the file which contains the data. Publication of new data on the server is recorded by a simple entering a new address into a cell in the spreadsheet. At the moment we use the EditGrid system as a spreadsheet platform. The generation of kml-codes is achieved on the basis of XML data and XSLT procedures. Since the EditGrid environment supports fetch and similar commands, it is possible to create smart-adaptive KML generation on the fly based on the data streams from RSS and XML sources.

The previous GIS-based methods could combine hi-definition data combined from various sources, but large-scale comparisons of dynamic processes have been usually out of reach of the technology. The suggested method allows unlimited number of GE clients to view, review and compare dynamic and static process of previously un-combinable sources, and on unprecedent scales. The ease of automated or computer-assisted georeferencing has already led to translation about 3000 raster public domain imagery, point and linear data sources into GE-language. In addition the suggested method allows a user to create rapid animations to demonstrate dynamic processes; roducts of high demand in education, meteorology, volcanology and potentially in a number of industries. In general it is possible to state that the new approach, which we have tested on numerous projects, saves times and energy in creating huge amounts of georeferenced data of various kinds, and thus provided an excellent tools for education and science.