ANALIZA SATELITSKIH SNIMAKA PRIMENOM PYTHON BIBLIOTEKA I METODA SPEKTRALNE MEŠAVINE

Sebastijan Ristić

doi:10.24867/32KG04Ristic

Geodesy Engineering

Vol. 40 No. 11 (2025): Proceedings of the Faculty of Technical Sciences

ANALYSIS OF SATELLITE IMAGES USING PYTHON LIBRARIES AND SPECTRAL MIXTURE METHODS

Sebastijan Ristić

32KG04Ristic.pdf (Serbian)

DOI:: https://doi.org/10.24867/32KG04Ristic
Submitted: November 10, 2025
Published: 2026-03-09

Abstract

The paper presents an analysis of spectral mixture models (SMA) on satellite images from the Sentinel-2 platform, aimed at classifying crop types in specific area of Bačka district. The processing of the images was carried out using Python programming language and its libraries.

References

[1] SentinelHub, https://custom-scripts.sentinel-hub.com/custom-scripts/sentinel-2/bands/ (pristupljeno 19.09.2023.)
[2] Andreas C. Muller, Sarah Guido, "Introduction to Machine Learning with Python" 1st edition, Доступно на: https://www.nrigroupindia.com/e-book/Introduction%20to%20Machine%20Learning%20with%20Python%20(%20PDFDrive.com%20)-min.pdf, 5-7, (pristupljeno 17.09.2023.)
[3] Јоhn A. Richards, Remote Sensing Digital Image Analysis – Fifth edition; Berlin – Heiderberg, 2013, 424-426

[1] [1] SentinelHub, https://custom-scripts.sentinel-hub.com/custom-scripts/sentinel-2/bands/ (pristupljeno 19.09.2023.)

[2] [2] Andreas C. Muller, Sarah Guido, "Introduction to Machine Learning with Python" 1st edition, Доступно на: https://www.nrigroupindia.com/e-book/Introduction%20to%20Machine%20Learning%20with%20Python%20(%20PDFDrive.com%20)-min.pdf, 5-7, (pristupljeno 17.09.2023.)

[3] [3] Јоhn A. Richards, Remote Sensing Digital Image Analysis – Fifth edition; Berlin – Heiderberg, 2013, 424-426