GEOLOGIC MAPS IN A GOOGLE FUSION TABLE ENVIRONMENT: A CASE STUDY IN NEW YORK

The goal of this project was to create, color, organize and share geologic maps in a Google Fusion Table. There are several advantages to using Google products. One, the data reside on Google servers; two, the Fusion Table app provides a means of organizing, analyzing and visualizing the data; and three, these resources make the geologic data easily accessible, shareable and free. Geologic data for New York State has been published by the New York State Museum, both in printed maps and in GIS format. While this data is available to the public, there has not been an easy way to visualize and analyze the data. We present here the steps required to move geologic data from the native format (shapefile) into the Fusion Table, and then offer suggestions on the use of the database functionality in the app.

The first step in getting the shapefiles into a Fusion Table is to translate the shapefile into a Keyhole Markup Language file (kml). We tried several methods of file conversion, and found that ShapeEscape, a free online app service, performed the format conversion with fewest errors. Custom and New York State standard color tables based on different material types were then constructed in a spreadsheet and merged with the Fusion Table. Within the Fusion Table, each row corresponds to a point, line or area feature, with additional columns providing information about the feature, such as rock age, type, onscreen color, etc. We tried to retain all of the original attributes of the data while merging in new information such as New York State rock type descriptions and graphical attributes for each of the specific material types. We present our results in working with the bedrock and surficial geology maps of New York State. The maps are available online, in a clickable, searchable, filterable, tabular, downloadable and graphical format. Clicking on the map pulls up an information window, which provides a significant amount of visual functionality to the map. Geolocated photographs, for instance, can be added to the window, along with rock descriptions or other attributes in the table. The data can readily be filtered by rock age, or rock type. We think the ensemble of functions in the Fusion Table can lead to exciting virtual fields for exploration and data dissemination, especially for geoscience educators.