Chlorophyll Estimation of Lake Water and Coastal Water Using Landsat-8 and Sentinel-2a Satellite

Abstract

Chlorophyll-a is an optically active compound (OAC) commonly used as a proxy for phytoplankton biomass in an aquatic environment. Retrieving the concentration of chlorophyll-a remains a challenge due to the presence of several OAC particularly in water bodies which are in proximity to the land-based activities. In this study, an effort has been made to estimate the chlorophyll-a concentration of both the freshwater Lake Biwa and the coastal water of Wakasa Bay in Japan. A spectral decomposition algorithm was used to determine the chlorophyll-a using the satellite images. The algorithm was applied to the satellite images from two different sensors namely Landsat-8 /OLI and Sentinel-2A/MSI. The satellite-derived chlorophyll-a concentration for the lake and coastal water from two different sensors were compared to assess the performance of both the sensors. The accuracy of the chlorophyll-a results derived from the images was evaluated with the in-situ measurement data of the chlorophyll-a for the Lake Biwa and the coastal water of Wakasa Bay. Both satellite sensors appear to give the best results for the coastal water (R 2 > 0.80) with an RMSE < 0.3 µg/L. However, slight underestimation of chlorophyll-a noted for the Landsat-8 image with an increase in chlorophyll-a concentration. For the lake water, Sentinel-2A results were relatively better (R 2 > 0.70) than Landsat-8, with an RMSE of < 1.0 µg/L. The obtained results will be useful to evaluate the primary productivity of both freshwater and coastal water body.

Estimation of Water Quality in a Reservoir From Sentinel-2 Msi and Landsat-8 Oli Sensors

“…On top of these additional bands, some of the MSI bands have a finer spectral resolution like the green (3), red (4) and near infrared (8a) bands. Finally, the MSI spatial resolutions are of 10 m (4 bands), 20 m (6 bands) and 60 m (3 bands) whereas all the OLI bands have a single spatial resolution of 30 m. Other authors that have compared the performance of statistical models with these two sensors have reached similar conclusions (Yadav et al, 2019, Govedarica, Jakovljević, 2019.…”

“…Recent research in many parts of the world involving water quality have made use of data from Landsat-8 (Liu, Wang, 2019, González-Márquez et al, 2018, Mushtaq, Nee Lala, 2017, Sentinel-2 (Karaoui et al, 2019, Potes et al, 2018 or both (Dutra et al, 2019, Yadav et al, 2019, Watanabe et al, 2018. Table 1 gives a list of some of these authors with the sensor they used and the parameters they analysed.…”

“…The a priori selection of predictor bands was based on articles byYadav et al (2019), Dutra et al (2019) Watanabe et al (2018) and Potes et al (2018) for the chl-a models. The Secchi disk depth was based on papers from Bonansea et al (2015), Rodríguez et al (2014) and Giardino et al (2010) while turbidity used references from Liu and Wang (2019), González-Márquez et al (…”

Monitoring the Water Quality of Small Water Bodies Using High-Resolution Remote Sensing Data

“…Many of these studies consider Landsat imagery (30 m spatial resolution) to be high-resolution [16], which may not be satisfactory for monitoring small water bodies. The comparison between two different remote sensing sensors indicates that higher spatial resolution offers higher accuracy in water quality parameters [34,35]. Taking into consideration that results of water quality are limited due to mixed pixels [36], in this study we evaluate high-resolution (5 m spatial resolution) for monitoring water quality in small water bodies.…”

Improved water quality mapping based on cross‐fusion of Sentinel‐2 and Landsat‐8 imageries

“…European Space Agency (ESA) and U.S. Geological Survey (USGS) make it possible to download different images such as Landsat and Sentinel data free of charge. Owing to having suitable spatial, spectral and radiometric resolutions, these images can be used for studying the surface water quality at short intervals [1–8]. Many studies have been done for water quality assessment using remote‐sensing data.…”