Oliver Zielinski

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We present an empirical quality control protocol for above-water radiometric sampling focussing on identifying sunglint situations. Using hyperspectral radiometers, measurements were taken on an automated and unmanned seaborne platform in northwest European shelf seas. In parallel, a camera system was used to capture sea surface and sky images of the(More)
Color of seawater has become an integral tool in understanding surface marine ecosystems and processes. In this paper we seek to assess the correlations and consequently the potential of using shipborne remote sensing products to infer marine environmental parameters. Typical seawater parameters are chlorophyll–a (chl–a), colored dissolved organic material(More)
Societal awareness of changes in the environment and climate has grown rapidly, and there is a need to engage citizens in gathering relevant scientific information to monitor environmental changes due to recognition that citizens are a potential source of critical information. The apparent colour of natural waters is one aspect of our aquatic environment(More)
"Marine Science Reports" publishes monographs and data reports written by scientists of the Leibniz-Institute for Baltic Sea Research Warnemünde and their co-workers. Volumes are published at irregular intervals and numbered consecutively. The content is entirely in the responsibility of the authors. Die elektronische Version ist verfügbar unter / The(More)
The complexity of critical systems such as traffic management has dramatically increased over the last decades, since they involve more and more sensors to derive distributed situational awareness. Most existing systems require an a-priori configuration of sensors or need human intervention to adapt to changes. Furthermore, analysis of data quality or query(More)
Marine processes are observed with sensors from both the ground and space over large spatio-temporal scales. Citizen-based contributions can fill observational gaps and increase environmental stewardship amongst the public. For this purpose, tools and methods for citizen science need to (1) complement existing datasets; and (2) be affordable, while(More)
The imputation of partially missing multivariate time series data is critical for its correct analysis. The biggest problems in time series data are consecutively missing values that would result in serious information loss if simply dropped from the dataset. To address this problem, we adapt the k-Nearest Neighbors algorithm in a novel way for multivariate(More)