Publication Details

Category Text Publication
Reference Category Journals
DOI 10.3390/rs16152798
Licence creative commons licence
Title (Primary) Exploring spatial aggregations and temporal windows for water quality match-up analysis using Sentinel-2 MSI and Sentinel-3 OLCI data
Author Schröder, T.; Schmidt, S.I. ORCID logo ; Kutzner, R.D.; Bernert, H.; Stelzer, K.; Friese, K. ORCID logo ; Rinke, K.
Source Titel Remote Sensing
Year 2024
Department SEEFO
Volume 16
Issue 15
Page From art. 2798
Language englisch
Topic T5 Future Landscapes
T4 Coastal System
Supplements https://www.mdpi.com/article/10.3390/rs16152798/s1
Keywords validation; match-up; water quality; inland waters; satellite data
Abstract Effective monitoring and management of inland waterbodies depend on reliable assessments of water quality through remote sensing technologies. Match-up analysis plays a significant role in investigating the comparability between in situ and remote sensing data of physical and biogeochemical variables. By exploring different spatial aggregations and temporal windows, we aimed to identify which configurations are most effective and which are less effective for the assessment of remotely sensed water quality data within the context of governmental monitoring programs. Therefore, in this study, remote sensing data products, including the variables of Secchi depth, chlorophyll-a, and turbidity, derived from the Copernicus satellites Sentinel-2 and Sentinel-3, were compared with in situ laboratory data from >100 waterbodies (lakes and reservoirs) in Germany, covering a period of 5 years (2016–2020). Processing was carried out using two different processing schemes, CyanoAlert from Brockmann Consult GmbH and eoapp AQUA from EOMAP GmbH & Co. KG, in order to analyze the influence of different processors on the results. To investigate appropriate spatial aggregations and time windows for validation (the match-up approach), we performed a statistical comparison of different spatial aggregations (1 pixel; 3 × 3, 5 × 5, and 15 × 15 macropixels; and averaging over the whole waterbody) and time windows (same day, ±1 day, and ±5 days). The results show that waterbody-wide values achieved similar accuracies and biases compared with the macropixel variants, despite the large differences in spatial aggregation and spatial variability. An expansion of the temporal window to up to ±5 days did not impair the agreement between the in situ and remote sensing data for most target variables and sensor–processor combinations, while resulting in a marked rise in the number of matches.
Persistent UFZ Identifier https://www.ufz.de/index.php?en=20939&ufzPublicationIdentifier=29212
Schröder, T., Schmidt, S.I., Kutzner, R.D., Bernert, H., Stelzer, K., Friese, K., Rinke, K. (2024):
Exploring spatial aggregations and temporal windows for water quality match-up analysis using Sentinel-2 MSI and Sentinel-3 OLCI data
Remote Sens. 16 (15), art. 2798 10.3390/rs16152798