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

Bitte benutzen Sie diese Kennung, um auf die Ressource zu verweisen:
Open Access logo originally created by the Public Library of Science (PLoS)
Titel: Mapping Lower Saxony’s salt marshes using temporal metrics of multi-sensor satellite data
Autor(en): Stückemann, Kim-Jana
Waske, Björn
ORCID des Autors:
Zusammenfassung: 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.
Bibliografische Angaben: 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.
Schlagworte: Salt marshes; Spectral-temporal metrics; Multi-sensor; Sentinel-2; Sentinel-1; Landsat 8
Erscheinungsdatum: 24-Nov-2022
Lizenzbezeichnung: Attribution 4.0 International
URL der Lizenz:
Publikationstyp: Einzelbeitrag in einer wissenschaftlichen Zeitschrift [Article]
Enthalten in den Sammlungen:FB06 - Hochschulschriften

Dateien zu dieser Ressource:
Datei Beschreibung GrößeFormat 
Stueckemann_Waske_IJAEOG_2022.pdfArticle12,18 MBAdobe PDF

Diese Ressource wurde unter folgender Copyright-Bestimmung veröffentlicht: Lizenz von Creative Commons Creative Commons