Izvorni znanstveni članak
https://doi.org/10.7225/toms.v13.n01.w10
The Structure and Technology of Structuring Marine Areas Using Remote Sensing Data in Semi-Arid Conditions
Denis Krivoguz
orcid.org/0000-0001-5702-3260
; Southern Federal University, Rostov-on-Don, Russia
Liudmila Bespalova
; Southern Federal University, Rostov-on-Don, Russia
Sergei Chernyi
; Saint Petersburg State Marine Technical University, Saint-Petersburg, Russia
Anton Zhilenkov
; Saint Petersburg State Marine Technical University, Saint-Petersburg, Russia
Artem Silkin
; Saint Petersburg State Marine Technical University, Saint-Petersburg, Russia
Ivan Goryachev
; Saint Petersburg State Marine Technical University, Saint-Petersburg, Russia
Pavel Daragan
; Saint Petersburg State Marine Technical University, Saint-Petersburg, Russia
Sažetak
Correctly distinguishing urbanized marine areas from bare ground is becoming increasingly important in the context of urbanization and environmental management. This study explores the feasibility of using spectral indices to distinguish urbanized marine areas from bare ground with similar spectral signatures. The Landsat-8 data were analyzed and different spectral indices were calculated and tested for their effectiveness in identifying urban areas. The results show that the Normalized Difference Built-up Index (NDBI) and the Vegetation Blending Unit (VBU) have promising potential for distinguishing urban areas from bare ground. The identification of category boundaries based on the distribution of minimum and maximum values of different spectral indices allows a clear delineation of urbanized areas. This study highlights the usefulness of spectral indices in extracting urbanized marine areas from remote sensing data and has practical implications for urban planners, decision makers, and stakeholders involved in urban planning, land use management, and environmental protection. However, caution is needed to avoid misclassification, and careful selection of appropriate indices is crucial to achieve correct classification results.
Ključne riječi
Remote sensing; Marine; Areas; Bare ground; Spectral indices; Ground cover
Hrčak ID:
316751
URI
Datum izdavanja:
20.4.2024.
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