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Understanding the long-term development of an irrigation network using a sinuosity-based automatic classification of waterways

Boon, Maddy; Motta, Davide; Massa, Michele; Wainwright, John; Lawrence, Dan; Ayala, Gianna

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Authors

Maddy Boon

Davide Motta

Michele Massa

Gianna Ayala



Abstract

This study investigates the use of planform sinuosity as a metric to produce an automatic classification of waterways in the pre-modern and present-day irrigation networks in the Konya Plain in south-central Türkiye. Results show that such automatic classification may replace a time-consuming manual classification or provide a preliminary classification for subsequent manual refinement, depending on the number of classification categories used, the distribution of sinuosity across the network, and the degree of human modification. They also show that sinuosity thresholds for classification are area- and time-specific. Sinuosity is then used to quantify and interpret network changes in planform alignment and expansion and to identify long-term trends and areas of landscape modification. Results reveal a general pattern of decreasing sinuosity over time in the Konya Plain, indicating a continual human intervention, with areas where the present-day network was built upon the old Ottoman system. The methods presented in this investigation may be applicable to other studies of irrigation-network evolution and impact on landscape and can be used in conjunction with archeological and historical analysis.

Citation

Boon, M., Motta, D., Massa, M., Wainwright, J., Lawrence, D., & Ayala, G. (online). Understanding the long-term development of an irrigation network using a sinuosity-based automatic classification of waterways. Holocene, https://doi.org/10.1177/09596836241285795

Journal Article Type Article
Acceptance Date Sep 1, 2024
Online Publication Date Oct 17, 2024
Deposit Date Oct 18, 2024
Publicly Available Date Oct 18, 2024
Journal The Holocene
Print ISSN 0959-6836
Electronic ISSN 1477-0911
Publisher SAGE Publications
Peer Reviewed Peer Reviewed
DOI https://doi.org/10.1177/09596836241285795
Public URL https://durham-repository.worktribe.com/output/2971361

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