However, when the Shape Method was applied to six case studies by considering the reference object shape, the uncertainty areas were reduced considerably (by up to 99.5% of the uncertain area generated by the Point-Radius Method). From 2005–2010, 1,271 of 1,356 Yosemite Search and Rescue YOSAR incidents (93.7%) could be georeferenced using the Point-Radius Method, with a mean uncertainty radius = 560  51 m and mean uncertainty area of 3.60  0.840 km2. Incorporating uncertainty measurements into a spatial database allows for more appropriate analyses of spatial dependence and the spatial distri- bution of incidents. This study implemented two established approaches for georeferencing incidents, the ‘Point-Radius’ and ‘Shape’ methods. incidents they must be georeferenced from textual descriptions. However, one major challenge for evaluating SAR in a spatial context is the lack of explicitly spatial data (addresses or coordinates) for historic. Once incidents are georeferenced they can be spatially queried and ana- lyzed. The Search and Rescue (SAR) of individuals who become lost, injured, or stranded in wilderness presents a unique and worthwhile spatiotemporal challenge to inves- tigate. Investigations of the geocoded output datasets revealed a projected improvement in match rates when combining the two road centerline datasets into a hybrid reference dataset. Comparative statistics between the two reference datasets were created for analysis. A Geographic Information System (GIS) geocoded records from source address datasets representing multiple test areas with two competing spatial reference datasets of road centerlines. Research conducted in this project examined the improvements in geocoding match rates when combining two updated multiple road centerline datasets. GIS users run the risk of producing unsatisfactory geocoding match rates due to discrepancies in the source data, reference data, or both. Spatial data of customers or test subjects are often obtained through address geocoding. The validity of all geographic analysis is directly related to the accuracy of all geographic datasets representing real-world phenomena involved within a given study.

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