Mapping Lower Saxony’s salt marshes using temporal metrics of multi-sensor satellite data

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https://doi.org/10.48693/321
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Title: Mapping Lower Saxony’s salt marshes using temporal metrics of multi-sensor satellite data
Authors: Stückemann, Kim-Jana
Waske, Björn
ORCID of the author: https://orcid.org/0000-0002-2586-3748
Abstract: Salt marshes act as an important natural buffer in terms of coastal protection in the light of the rising sea level. Due to weather events like extreme storms the extent of salt marshes changes. Hence, it is of great importance to regularly monitor these changes, especially for managing interventions and reporting their ecological status in the frame of environmental policies, like Natura 2000. In this study, the potential of freely available sallite imagery is investigated and a methodological approach suggested to map superior salt marsh types (pioneer zone, lower and upper salt marshes) for supporting regular monitoring compliances. Therefore, (spectral-)temporal metrics of optical Sentinel-2 (S2) and Landsat 8 as well as SAR Sentinel-1 were calculated and used in different classification setups. The classifications were performed using a basic Random Forest classifier. A detailed accuracy assessment shows the impact of different datasets on the overall accuracy. The best result was achieved using S2 data, which led to an overall accuracy of 90.3 %. The combination of optical and SAR data, on the other hand, did not increase the classification accuracy. Overall, the freely available datasets and the proposed method proof useful and are considered well suited for monitoring salt marshes.
Citations: Stückemann, K.-J., & Waske, B. (2022): Mapping Lower Saxony’s salt marshes using temporal metrics of multi-sensor satellite data. International Journal of Applied Earth Observation and Geoinformation, 115, 103123.
URL: https://doi.org/10.48693/321
https://osnadocs.ub.uni-osnabrueck.de/handle/ds-202305048960
Subject Keywords: Salt marshes; Spectral-temporal metrics; Multi-sensor; Sentinel-2; Sentinel-1; Landsat 8
Issue Date: 24-Nov-2022
License name: Attribution 4.0 International
License url: http://creativecommons.org/licenses/by/4.0/
Type of publication: Einzelbeitrag in einer wissenschaftlichen Zeitschrift [Article]
Appears in Collections:FB06 - Hochschulschriften
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