HistoryForge (<ext-link ext-link-type="uri" xlink:href="https://historyforge.net">https://historyforge.net</ext-link>) is a web application that combines information from U.S. Census records, historical maps, and other records in an interactive framework of human and spatial relationships that illustrate what communities looked like and how they evolved over time. It generates an environment that invites a study of local history at the levels of neighborhood, family, and individual. HistoryForge is being developed using open source software so that any community can adopt it to explore their own local history and add archival material. This paper will describe the project's development, growing potential for enriching records with archival material, and its current implementation in four different communities. The rapid development of the last year has been supported by a two-year grant from the Public Engagement with Historical Records from the National Historical Publications and Records Commission of the National Archives.
The paper will focus on a project at Kent State University using a local oral history digital collection. The project displays the potential of how the application of an additional layer of geospatial information into an existing digital collection can improve user access and provide alternate methods to browse material (geographically). Transcriptions from the May 4 oral history collection at Kent State University were analyzed and tagged at any point there was a mention of one of the location points of interest. A new website was created where oral histories could be browsed using a historical map from the time period (spring 1970). This paper will outline the project and provide some initial steps for other institutions to begin such a project.
Abstract This article describes automatic road boundary extraction from a high resolution true orthoimage using the Ribbon Snakes algorithm. We assume the existence of prior information for the rough range of road widths in the scenes and road centerline data. Previous works on road boundary extraction have been focused on rural areas, using the same approach. Applying the Ribbon Snakes algorithm to an urban area, we encounter multiple-local-minima problem due to cars and lane markings. We overcome this problem by repeating the optimization of the Ribbon Snakes model at different widths. With the existing road centerlines, fixed width Ribbon Snakes (FXWRS) is applied and its total energy after optimization is stored. After changing the road width, FXWRS is reapplied and the total energy is again stored. By comparing the total energies for each of the road widths, we determine the optimum width that produces the least total energy. Applying FXWRS with the optimum width and road centerline, refined road boundaries are obtained. We show the feasibility of this approach by comparing results with ground truth.