Classification of Danube Delta boundaries by using machine learning algorithms on co-registered Sentinel-1 and Sentinel-2 data

Mobina Keymasi; Omid Ghozatlou; Andrei Anghel; Mihai Datcu

doi:10.1117/12.2654024

2 March 2023 Classification of Danube Delta boundaries by using machine learning algorithms on co-registered Sentinel-1 and Sentinel-2 data

Mobina Keymasi, Omid Ghozatlou, Andrei Anghel, Mihai Datcu

Author Affiliations +

Proceedings Volume 12493, Advanced Topics in Optoelectronics, Microelectronics, and Nanotechnologies XI; 124931B (2023) https://doi.org/10.1117/12.2654024
Event: Advanced Topics in Optoelectronics, Microelectronics and Nanotechnologies 2022, 2022, Constanta, Romania

Abstract

Remote sensing image scene classification is a contentious research area, particularly in difficult-to-classify regions. The Danube delta is a constantly changing and difficult to categorize region. Machine learning methods have recently been used for scene classification because of their beneficial results. For many remote sensing applications, co-registration of Multi Spectral Images (MS) and Synthetic Aperture Radar (SAR) data is crucial. This paper focuses on both supervised and unsupervised novel machine learning methods, such as t-SNE, k-means, and SVM, applied to co-registered Sentinel-1 and Sentinel-2 data of the Danube delta. The outcome demonstrates that Sentinel-1 vertical-vertical (VV) is a better band for data training since it exhibits more details, and the learned SVM classifier using t-SNE can be applied to other days with a respectable level of accuracy.

Citation Download Citation

Mobina Keymasi, Omid Ghozatlou, Andrei Anghel, and Mihai Datcu "Classification of Danube Delta boundaries by using machine learning algorithms on co-registered Sentinel-1 and Sentinel-2 data", Proc. SPIE 12493, Advanced Topics in Optoelectronics, Microelectronics, and Nanotechnologies XI, 124931B (2 March 2023); https://doi.org/10.1117/12.2654024

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KEYWORDS

Infrared radiation

RGB color model

Remote sensing

Vegetation

Feature extraction

Synthetic aperture radar

Machine learning

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