Cemetery Mapping and Digital Data Analysis: A Case Study in Minnesota, USA


  •  Maureen L. Schmidt    
  •  Fei Yuan    
  •  Woo Jang    

Abstract

This study examines how geospatial technologies can be used in the aid of local-level cemetery management with limited resources using a case study in Woodland Hills Memorial Park Cemetery, Minnesota, USA. The hard-copy records in a handwritten ledger were manually transferred into an Excel table. The spatial data of the gravesites were collected using a Trimble Geo 7X unit with a Zephyr antenna and a Laser Rangefinder sensor over the summer of 2017. A geodatabase was constructed by joining the Excel table with the GPS data in GIS. A procedure was also developed to map the spatial distributions of plots and analyze the demographic data. It was demonstrated that a very high locational accuracy could be achieved based on carefully designed GPS data collection strategies. In addition, the data analysis results revealed that there were 12,190 plots in total, approximately half of which were still available for purchase. Among the 5,906 inhabitants buried at the Woodland Hills, many were ethnically German and Scandinavian, of whom 9.7% were veterans and nearly half were from the Greatest Generation (born between 1901 and 1927). The birth, death, and age distributions are significantly different between the nonveteran and veteran groups. Clustered patterns were identified for the filled plots and all the Generation categories. Such results will be beneficial to local cemetery managers to plan for further development as well as to future historians or individuals interested in the local culture and history. The proposed methods can greatly facilitate local-level cemetery data collection, mapping, query, and analysis.


This work is licensed under a Creative Commons Attribution 4.0 License.
  • ISSN(Print): 1916-9779
  • ISSN(Online): 1916-9787
  • Started: 2009
  • Frequency: semiannual

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Google-based Impact Factor (2018): 11.90

h-index (January 2018): 17

i10-index (January 2018): 36

h5-index (January 2018): 13

h5-median(January 2018): 15

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