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Integrating Older Survey Data into Modern Research Paradigms: Identifying and Correcting Spatial Error in “Legacy” Datasets

  • Isaac I. T. Ullah (a1)

Abstract

The data from older archaeological surveys are incredibly important resources, often containing our only information about sites that have been destroyed or that are now inaccessible. These surveys occurred before the advent of GPS technology, however, so their spatial accuracy is often uncertain. Many types of locational errors accumulate in such “legacy” datasets, so using them in modern GIS-based spatial analyses is frequently problematic. Many of the sources of error can be identified and quantified, however, and systematic and random errors (derived mainly from Cartesian, rounding, and human error) can largely be mitigated by scanning the original field maps, georectifying the maps to trusted imagery, and then digitizing sites directly. The remaining “mislocation” errors derive from difficulty identifying locations in the field. The original survey notes may contain clues about mislocation error, but it is impossible to mitigate these errors without re-recording site locations with more accurate survey instruments. Instead, I advocate the use of GIS-based models to estimate the influence of specific surveying practices on site location accuracy. These models can provide a standardized, quantifiable measure of mislocation error in a legacy dataset, which can help guide its use in modern GIS analyses that require accurate site locations.

Los datos de prospecciones arqueológicas antiguas son recursos de una enorme importancia, pues contienen a menudo la única información disponible sobre yacimientos que han sido destruidos, o que resultan inaccesibles en la actualidad. Sin embargo, estas prospecciones tuvieron lugar antes de la llegada de la tecnología GPS, por lo que su precisión espacial es a menudo incierta. Los tipos de errores de localización que se acumulan en este tipo de datos “heredados” son numerosos, por lo que su uso en análisis espaciales modernos basados en SIG es, con frecuencia, problemático. No obstante, muchas de las causas de estos errores pueden ser identificadas y cuantificadas y, tanto los errores sistemáticos como aleatorios (derivados principalmente del Cartesiano, el redondeo y los errores humanos), pueden ser mitigados en gran medida por medio del escaneo de los mapas de campo originales, su georrectificado a partir de imágenes de confianza, y la posterior digitalización de los sitios. Los restantes “errores de ubicación” tienen su origen en la dificultad a la hora de situar los puntos en el campo. Los diarios y anotaciones originales de las prospecciones pueden contener pistas sobre dichos errores de ubicación, pero resulta imposible mitigar su efecto sin volver a registrar las ubicaciones de los yacimientos con instrumentos más precisos. En su lugar, yo abogo por el uso de modelos basados en SIG para estimar la influencia de determinados métodos específicos de exploración en la precisión de la localización de los sitios. Estos modelos pueden proporcionar una medida estandarizada, cuantificable de los errores de ubicación en un conjunto de datos heredado, lo que puede ayudar a guiar su uso en los análisis modernos de SIG, que requieren ubicaciones exactas de los yacimientos.

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Integrating Older Survey Data into Modern Research Paradigms: Identifying and Correcting Spatial Error in “Legacy” Datasets

  • Isaac I. T. Ullah (a1)

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