date: 2021-04-16T09:40:38Z pdf:PDFVersion: 1.7 pdf:docinfo:title: The Use of Sentinel-2 for Chlorophyll-a Spatial Dynamics Assessment: A Comparative Study on Different Lakes in Northern Germany xmp:CreatorTool: LaTeX with hyperref Keywords: water quality; algal pigments; atmospheric correction; river?lake system; Sentinel-2 access_permission:modify_annotations: true access_permission:can_print_degraded: true subject: Eutrophication of inland waters is an environmental issue that is becoming more common with climatic variability. Monitoring of this aquatic problem is commonly based on the chlorophyll-a concentration monitored by routine sampling with limited temporal and spatial coverage. Remote sensing data can be used to improve monitoring, especially after the launch of the MultiSpectral Instrument (MSI) on Sentinel-2. In this study, we compared the estimation of chlorophyll-a (chl-a) from different bio-optical algorithms using hyperspectral proximal remote sensing measurements, from simulated MSI responses and from an MSI image. For the satellite image, we also compare different atmospheric corrections routines before the comparison of different bio-optical algorithms. We used in situ data collected in 2019 from 97 sampling points across 19 different lakes. The atmospheric correction assessment showed that the performances of the routines varied for each spectral band. Therefore, we selected C2X, which performed best for bands 4 (root mean square error?RMSE = 0.003), 5 (RMSE = 0.004) and 6 (RMSE = 0.002), which are usually used for the estimation of chl-a. Considering all samples from the 19 lakes, the best performing chl-a algorithm and calibration achieved a RMSE of 16.97 mg/m3. When we consider only one lake chain composed of meso-to-eutrophic lakes, the performance improved (RMSE: 10.97 mg/m3). This shows that for the studied meso-to-eutrophic waters, we can reliably estimate chl-a concentration, whereas for oligotrophic waters, further research is needed. The assessment of chl-a from space allows us to assess spatial dynamics of the environment, which can be important for the management of water resources. However, to have an accurate product, similar optical water types are important for the overall performance of the bio-optical algorithm. dc:creator: Igor Ogashawara, Christine Kiel, Andreas Jechow, Katrin Kohnert, Thomas Ruhtz, Hans-Peter Grossart, Franz Hölker, Jens C. Nejstgaard, Stella A. Berger and Sabine Wollrab dcterms:created: 2021-04-16T09:34:12Z Last-Modified: 2021-04-16T09:40:38Z dcterms:modified: 2021-04-16T09:40:38Z dc:format: application/pdf; version=1.7 title: The Use of Sentinel-2 for Chlorophyll-a Spatial Dynamics Assessment: A Comparative Study on Different Lakes in Northern Germany Last-Save-Date: 2021-04-16T09:40:38Z pdf:docinfo:creator_tool: LaTeX with hyperref access_permission:fill_in_form: true pdf:docinfo:keywords: water quality; algal pigments; atmospheric correction; river?lake system; Sentinel-2 pdf:docinfo:modified: 2021-04-16T09:40:38Z meta:save-date: 2021-04-16T09:40:38Z pdf:encrypted: false dc:title: The Use of Sentinel-2 for Chlorophyll-a Spatial Dynamics Assessment: A Comparative Study on Different Lakes in Northern Germany modified: 2021-04-16T09:40:38Z cp:subject: Eutrophication of inland waters is an environmental issue that is becoming more common with climatic variability. Monitoring of this aquatic problem is commonly based on the chlorophyll-a concentration monitored by routine sampling with limited temporal and spatial coverage. Remote sensing data can be used to improve monitoring, especially after the launch of the MultiSpectral Instrument (MSI) on Sentinel-2. In this study, we compared the estimation of chlorophyll-a (chl-a) from different bio-optical algorithms using hyperspectral proximal remote sensing measurements, from simulated MSI responses and from an MSI image. For the satellite image, we also compare different atmospheric corrections routines before the comparison of different bio-optical algorithms. We used in situ data collected in 2019 from 97 sampling points across 19 different lakes. The atmospheric correction assessment showed that the performances of the routines varied for each spectral band. Therefore, we selected C2X, which performed best for bands 4 (root mean square error?RMSE = 0.003), 5 (RMSE = 0.004) and 6 (RMSE = 0.002), which are usually used for the estimation of chl-a. Considering all samples from the 19 lakes, the best performing chl-a algorithm and calibration achieved a RMSE of 16.97 mg/m3. When we consider only one lake chain composed of meso-to-eutrophic lakes, the performance improved (RMSE: 10.97 mg/m3). This shows that for the studied meso-to-eutrophic waters, we can reliably estimate chl-a concentration, whereas for oligotrophic waters, further research is needed. The assessment of chl-a from space allows us to assess spatial dynamics of the environment, which can be important for the management of water resources. However, to have an accurate product, similar optical water types are important for the overall performance of the bio-optical algorithm. pdf:docinfo:subject: Eutrophication of inland waters is an environmental issue that is becoming more common with climatic variability. Monitoring of this aquatic problem is commonly based on the chlorophyll-a concentration monitored by routine sampling with limited temporal and spatial coverage. Remote sensing data can be used to improve monitoring, especially after the launch of the MultiSpectral Instrument (MSI) on Sentinel-2. In this study, we compared the estimation of chlorophyll-a (chl-a) from different bio-optical algorithms using hyperspectral proximal remote sensing measurements, from simulated MSI responses and from an MSI image. For the satellite image, we also compare different atmospheric corrections routines before the comparison of different bio-optical algorithms. We used in situ data collected in 2019 from 97 sampling points across 19 different lakes. The atmospheric correction assessment showed that the performances of the routines varied for each spectral band. Therefore, we selected C2X, which performed best for bands 4 (root mean square error?RMSE = 0.003), 5 (RMSE = 0.004) and 6 (RMSE = 0.002), which are usually used for the estimation of chl-a. Considering all samples from the 19 lakes, the best performing chl-a algorithm and calibration achieved a RMSE of 16.97 mg/m3. When we consider only one lake chain composed of meso-to-eutrophic lakes, the performance improved (RMSE: 10.97 mg/m3). This shows that for the studied meso-to-eutrophic waters, we can reliably estimate chl-a concentration, whereas for oligotrophic waters, further research is needed. The assessment of chl-a from space allows us to assess spatial dynamics of the environment, which can be important for the management of water resources. However, to have an accurate product, similar optical water types are important for the overall performance of the bio-optical algorithm. Content-Type: application/pdf pdf:docinfo:creator: Igor Ogashawara, Christine Kiel, Andreas Jechow, Katrin Kohnert, Thomas Ruhtz, Hans-Peter Grossart, Franz Hölker, Jens C. Nejstgaard, Stella A. Berger and Sabine Wollrab X-Parsed-By: org.apache.tika.parser.DefaultParser creator: Igor Ogashawara, Christine Kiel, Andreas Jechow, Katrin Kohnert, Thomas Ruhtz, Hans-Peter Grossart, Franz Hölker, Jens C. Nejstgaard, Stella A. Berger and Sabine Wollrab meta:author: Igor Ogashawara, Christine Kiel, Andreas Jechow, Katrin Kohnert, Thomas Ruhtz, Hans-Peter Grossart, Franz Hölker, Jens C. Nejstgaard, Stella A. Berger and Sabine Wollrab dc:subject: water quality; algal pigments; atmospheric correction; river?lake system; Sentinel-2 meta:creation-date: 2021-04-16T09:34:12Z created: Fri Apr 16 11:34:12 CEST 2021 access_permission:extract_for_accessibility: true access_permission:assemble_document: true xmpTPg:NPages: 26 Creation-Date: 2021-04-16T09:34:12Z access_permission:extract_content: true access_permission:can_print: true meta:keyword: water quality; algal pigments; atmospheric correction; river?lake system; Sentinel-2 Author: Igor Ogashawara, Christine Kiel, Andreas Jechow, Katrin Kohnert, Thomas Ruhtz, Hans-Peter Grossart, Franz Hölker, Jens C. Nejstgaard, Stella A. Berger and Sabine Wollrab producer: pdfTeX-1.40.21 access_permission:can_modify: true pdf:docinfo:producer: pdfTeX-1.40.21 pdf:docinfo:created: 2021-04-16T09:34:12Z