Detecting Urban Changes in Coastal Areas using SAR Amplitude Data

Monitoring urban expansion in coastal zones is critical for sustainable development and environmental protection. Synthetic Aperture Radar (SAR) data from the Sentinel-1 mission offers reliable, all-weather, and day-and-night imaging capabilities well-suited for this task. This study presents a workflow based on ESA’s SNAP toolbox for detecting urbanization-related changes in coastal areas using amplitude analysis of Sentinel-1 VV-polarized imagery. The methodology is demonstrated on a case study of the Opatija-Ičići coastal region in Croatia, with results validated through optical imagery. As a supplementary tool, a lightweight Python-based method is proposed for simplified differencing and fast visualization using KMZ overlays in Google Earth. While not a replacement for SNAP’s processing capabilities, this method enables quicker analysis and greater accessibility by allowing users to perform change detection without relying on specialized software. Together, these approaches highlight the potential of Sentinel-1 SAR data for operational urban change detection in sensitive coastal environments.

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Publication Details

Published
2025-09-15
DOI
https://doi.org/10.1109/elmar66948.2025.11193985
Primary Topic
Remote Sensing and Land Use
Type
article
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article

Detecting Urban Changes in Coastal Areas using SAR Amplitude Data

Dario Bojanjac, Filip Turčinović, Karla Sever, Marko Bosiljevac
Remote Sensing and Land Use
article

Detecting Urban Changes in Coastal Areas using SAR Amplitude Data

Dario Bojanjac, Filip Turčinović, Karla Sever, Marko Bosiljevac
article en

Abstract

Monitoring urban expansion in coastal zones is critical for sustainable development and environmental protection. Synthetic Aperture Radar (SAR) data from the Sentinel-1 mission offers reliable, all-weather, and day-and-night imaging capabilities well-suited for this task. This study presents a workflow based on ESA’s SNAP toolbox for detecting urbanization-related changes in coastal areas using amplitude analysis of Sentinel-1 VV-polarized imagery. The methodology is demonstrated on a case study of the Opatija-Ičići coastal region in Croatia, with results validated through optical imagery. As a supplementary tool, a lightweight Python-based method is proposed for simplified differencing and fast visualization using KMZ overlays in Google Earth. While not a replacement for SNAP’s processing capabilities, this method enables quicker analysis and greater accessibility by allowing users to perform change detection without relying on specialized software. Together, these approaches highlight the potential of Sentinel-1 SAR data for operational urban change detection in sensitive coastal environments.

University of Zagreb (HR)
Openalex Percentile: Top 66%
Remote Sensing and Land Use
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