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Buławka, Nazarij; Orengo, Hector A.; Lumbreras Ruiz, Felipe; Berganzo-Besga, Iban; Gupta, Ekta, 2025, "Traces of ancient irrigation in central Iraq detected using deep learning model", https://doi.org/10.58132/MY8CCL, Dane Badawcze UW, V1
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The dataset consists of predicted levees between Babylon and Uruk, utilising the Swin UNETR 48-band deep learning model with multitemporal multisource satellite data. The data used in the study were assembled from multitemporal Landsat 5, Sentinel-1 SAR, Sentinel-2 multispectral imagery, and the TanDEM-X 30 Edited DSM, combined with vegetation and moisture indices, PCA reductions of seasonal variability, and Multi-Scale Relief Model (MSRM) outputs. The post-processing included the morphological operations, such as filtering by size and closing. The results of the model after post-processing enabled it to achieve a precision of 0.5118 and a recall of 0.5908 at the pixel level.
The dataset is supplemented with the results of training and the final version of the model.
irrigation, Mesopotamia, Iraq, canal, Deep learning (Machine learning), deep learning, deep learning model
CC BY - Creative Commons Attribution 4.0
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