Authors: Patrick D. Hagge*, Arkansas Tech University
Topics: Historical Geography, Geographic Information Science and Systems, Agricultural Geography
Keywords: historical GIS, agriculture, cotton, US South, Arkansas, history, GIS
Session Type: Paper
Start / End Time: 8:00 AM / 9:40 AM
Room: Galerie 1, Marriott, 2nd Floor
Presentation File: No File Uploaded
The growing academic subfield of historical GIS (HGIS) allows for effective spatial representation of historical data. However, many HGIS approaches of the recent past are either focused on hyperlocalized places that allow for data collection and analysis over a small areal region, or “data-overload” locations that are easily described by quantitative data that were often tabulated by government entities. By contrast, studies of historical rural agriculture (particularly tenant farming) face problems of data that are privately-held, incomplete, or aggregated. The families residing on and around the cotton farms of Tucker, Arkansas in the early-to-mid-Twentieth Century are emblematic of these potential HGIS pitfalls. Throughout the twentieth century, while enormous economic restructuring occurred, much of the population and land shifts occurred beyond the reach of formal governmental documents. In addition, HGIS has only been used sporadically in studies of the cotton plantation South. An application of HGIS towards cotton plantation landscapes generally and Tucker specifically result in two research questions. First, how did the spatial configurations of farms and populations in and around Tucker evolve during the twentieth century? Second, how can HGIS better deal with multi-source data (public and private) typically seen in rural agriculture? Public documents (manuscript US Census records, land records) combine with private data to add deep spatial context to an era of transformation in the rural South. While this research illuminates the spatial history of Tucker, Arkansas, it also allows for greater assessment and understanding of HGIS applications in studies of cotton agriculture.