Krzepek, Katrin ; Günther, Anke ; Huth, Vytas ; Jansen, Florian ; Iwaszczuk, Dorota
Hrsg.: IEEE (2024)
The Influence of Vegetation on Sentinel-1 Intensity Time Series Using NDVI and in-Situ Data in Peatlands: A Case Study.
IGARSS 2024. Athens, Greece (07.07.2024-12.07.2024)
doi: 10.1109/IGARSS53475.2024.10642399
Konferenzveröffentlichung, Bibliographie
Kurzbeschreibung (Abstract)
Surface roughness and dielectric properties affect the synthetic aperture radar (SAR) signal. For this reason, SAR time series can be used to measure soil moisture or identify vegetation cycles. Moisture and vegetation are key factors that influence several ecological processes in peatland ecosystems. This case study deals with the influence of vegetation on the SAR signal in two study areas and its reduction in order to increase the correlation between SAR signal and water table depth (WTD). One drained and one rewetted peatland serve as study areas. The measured data SAR, WTD and two vegetation parameters (normalized difference vegetation index (NDVI) and Greeness) are represented by empirically fitted sine functions. By subtracting the NDVI fit from the SAR fit, an increase in the Pearson correlation coefficient from 0.55 to 0.88 can be achieved for the drained peatland in our case study.
| Typ des Eintrags: | Konferenzveröffentlichung |
|---|---|
| Erschienen: | 2024 |
| Autor(en): | Krzepek, Katrin ; Günther, Anke ; Huth, Vytas ; Jansen, Florian ; Iwaszczuk, Dorota |
| Art des Eintrags: | Bibliographie |
| Titel: | The Influence of Vegetation on Sentinel-1 Intensity Time Series Using NDVI and in-Situ Data in Peatlands: A Case Study |
| Sprache: | Englisch |
| Publikationsjahr: | 2024 |
| Ort: | New York, NY |
| Verlag: | IEEE |
| Buchtitel: | IGARSS 2024 - 2024 IEEE International Geoscience and Remote Sensing Symposium |
| Veranstaltungstitel: | IGARSS 2024 |
| Veranstaltungsort: | Athens, Greece |
| Veranstaltungsdatum: | 07.07.2024-12.07.2024 |
| DOI: | 10.1109/IGARSS53475.2024.10642399 |
| Kurzbeschreibung (Abstract): | Surface roughness and dielectric properties affect the synthetic aperture radar (SAR) signal. For this reason, SAR time series can be used to measure soil moisture or identify vegetation cycles. Moisture and vegetation are key factors that influence several ecological processes in peatland ecosystems. This case study deals with the influence of vegetation on the SAR signal in two study areas and its reduction in order to increase the correlation between SAR signal and water table depth (WTD). One drained and one rewetted peatland serve as study areas. The measured data SAR, WTD and two vegetation parameters (normalized difference vegetation index (NDVI) and Greeness) are represented by empirically fitted sine functions. By subtracting the NDVI fit from the SAR fit, an increase in the Pearson correlation coefficient from 0.55 to 0.88 can be achieved for the drained peatland in our case study. |
| Freie Schlagworte: | Synthetic Aperture Radar, Peatlands, Water Table Depth, Vegetation, Curve Fitting |
| Fachbereich(e)/-gebiet(e): | 13 Fachbereich Bau- und Umweltingenieurwissenschaften 13 Fachbereich Bau- und Umweltingenieurwissenschaften > Institut für Geodäsie 13 Fachbereich Bau- und Umweltingenieurwissenschaften > Institut für Geodäsie > Fernerkundung und Bildanalyse |
| Hinterlegungsdatum: | 10 Sep 2024 06:39 |
| Letzte Änderung: | 10 Sep 2024 06:39 |
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