The point-radius method for georeferencing locality descriptions and calculating associated uncertainty

Abstract

Natural history museums store millions of specimens of geological, biological, and cultural entities. Data related to these objects are in increasing demand for investigations of biodiversity and its relationship to the environment and anthropogenic disturbance. A major barrier to the use of these data in GIS is that collecting localities have typically been recorded as textual descriptions, without geographic coordinates. We describe a method for georeferencing locality descriptions that accounts for the idiosyncrasies, sources of uncertainty, and practical maintenance requirements encountered when working with natural history collections. Each locality is described as a circle, with a point to mark the position most closely described by the locality description, and a radius to describe the maximum distance from that point within which the locality is expected to occur. The calculation of the radius takes into account aspects of the precision and specificity of the locality description, as well as the map scale, datum, precision and accuracy of the sources used to determine coordinates. This method minimizes the subjectivity involved in the georeferencing process. The resulting georeferences are consistent, reproducible, and allow for the use of uncertainty in analyses that use these data.

Ecology and Geography of Human Monkeypox Case Occurrences Across Africa

“…nga.mil/geonames/GNS/index), and electronic data published with the Rand McNally New Millennium World Atlas (Rand McNally and Company, 1988). The Mammal Networked Information System (MaNIS) point-radius georeferencing method was used to assess spatial uncertainty in the geographic referencing of each occurrence point to account for the spatial extent of the named place, uncertainty of directions, and uncertainty of distances (Wieczorek et al, 2004). We restricted our analyses to sites that could be georeferenced with a spatial precision finer than 10 km.…”

“…The previous analysis used 156 occurrences but did not filter case occurrences based on spatial precision-as such, occurrences may have been included that referred to broader regions or that were nebulous regarding precise location; this imprecision can produce overly broad estimates of ecologic niches (Levine et al, 2007). The point-radius method we employed considers a ''locality'' as a geographic point combined with a radius that encompasses any associated uncertainties (Wieczorek et al, 2004). This approach has recently been recommended for broader application to reporting of disease occurrence (Peterson, 2008b).…”

“…Models based on simple environmental data sets may be overly general and lacking detail, owing to the broad interpolation and smoothing inherent in the process of generating the climate coverages (Nakazawa et al, 2007). Refinements such as filtering occurrence localities based on spatial precision can avoid imprecision resulting from an uncertain geolocation (Wieczorek et al, 2004;Peterson, 2008b). As ecologic niche modeling continues to evolve as a tool in spatial epidemiology and public health, focused studies evaluating these points may prove useful.…”

The value of georeferenced collection records for predicting patterns of mosquito species richness and endemism in the Neotropics

“…The database could be improved by including estimates of georeference error, e.g. by the point-radius method (Wieczorek et al, 2004). Almost 9000 mosquito records in the original MIMP database lacked a georeference but could be added with new software (e.g.…”

Diversity and distribution of type specimens deposited in the Invertebrate section of the Museum of Zoology QCAZ, Quito, Ecuador

“…Before the widespread use of geographic information systems (GIS) products such as global positioning systems (GPS) and electronic gazetteers in the mid 1990's, most biological collections in the Museum did not have specifi c or complete geographic coordinates. We increased the number of known locations by submitting the label data information to a strict protocol of geo-referencing (Wieczorek et al 2004). We divided the locality information from data labels into nine categories (Wieczorek et al 2004).…”