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An object‐based approach to support the automatic delineation of magnetic anomalies
Author(s) -
Hegyi Alexandru,
Vernica MiljaMiroslav,
Drăguţ Lucian
Publication year - 2019
Publication title -
archaeological prospection
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.785
H-Index - 38
eISSN - 1099-0763
pISSN - 1075-2196
DOI - 10.1002/arp.1752
Subject(s) - magnetometer , magnetic anomaly , software , computer science , scale (ratio) , segmentation , object (grammar) , magnetic survey , geology , geophysics , identification (biology) , process (computing) , artificial intelligence , algorithm , pattern recognition (psychology) , magnetic field , data mining , physics , geography , cartography , programming language , botany , quantum mechanics , biology
Abstract The intensive use of geophysics in archaeological investigations demands new ways of fast and meaningful data interpretation. With the increasing size and complexity of magnetometer data, manual identification and delineation of magnetic anomalies becomes a time‐consuming activity. In this respect, our study introduces a new approach to automate this laborious procedure, implemented as a ready‐to‐use tool within the eCognition® software. The approach relies on a multiresolution segmentation (MRS) algorithm, which is applied on a single layer containing magnetic values. Magnetic anomalies are automatically identified and delineated at three levels of scale. Magnetic anomalies are thus classified as potential archaeological features. The degree of departure from a normal distribution is adjustable at 0.5 and 1 standard deviation (SD), respectively. The approach was tested on magnetometer images of a buried medieval village in the west of Romania. The data were acquired along parallel profiles covering six squares of 100 m × 100 m each. We have deliberately selected this magnetic map because it is not the top in terms of magnetic results and it provides staggers (due to data acquisition in 100 m grids) to show that if this algorithm works on this magnetic map, it will work defiantly on those where archaeological structures/anomalies are even more regulated. The tested scenes indicated accurate results, displaying positive‐ and negative‐valued magnetic anomalies with levels of detail almost similar to manually delineated anomalies. Our approach is simple to apply. Being implemented as a customized process for the eCognition® software, the tool attached to the article repository has a significant potential to support interpretation of any type of image obtained through geophysical measurements and we consider it an aid for large‐scale surveys.