The Structure and Technology of Structuring Marine Areas Using Remote Sensing Data in Semi-Arid Conditions

Authors

  • Denis Krivoguz 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

DOI:

https://doi.org/10.7225/toms.v13.n01.w10

Keywords:

Remote sensing, Marine, Areas, Bare ground, Spectral indices, Ground cover

Abstract

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.

 

Published

2024-02-20

How to Cite

Krivoguz, D., Bespalova , L., Chernyi, S., Zhilenkov, A., Silkin, A., Goryachev, I. and Daragan, P. (2024) “The Structure and Technology of Structuring Marine Areas Using Remote Sensing Data in Semi-Arid Conditions”, Transactions on Maritime Science. Split, Croatia, 13(1). doi: 10.7225/toms.v13.n01.w10.
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