Abstract

AbstractGeographic information systems (GIS) methods, combined with airborne remote sensing, enable collection of complex spatial datasets across broad regional areas. This article explores the use of GIS techniques for fast collection, processing and analysis of pedestrian survey data. This approach is used at Tell Abu Shusha, a multiperiod site in the Jezreel Valley of northern Israel. Surface survey of this tell and the surrounding region, conducted by the Jezreel Valley Regional Project during 2017, documented extensive visible remains of settlement features as well as the ruins of the Ottoman era village of Abu Shusha. Using this data, the potential for existing spatial analytical techniques to be modified and improved through modern processing capabilities is shown. Kolmogorov–Smirnov nonparametric tests, pure locational (k‐means) and unconstrained clustering methods were applied to the field walking survey data, showing evidence of feature clustering at multiple scales as well as environmental patterning in where features are located. Results demonstrate that these approaches increase the speed and accuracy of pedestrian survey data collection and that the modification of these analytical techniques makes them more robust than before, allowing for the identification of meaningful large‐scale spatial patterns.

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