Eutrophication Monitoring for Lake Pamvotis, Greece, Using Sentinel-2 Data
Bibliographic Data
| ID | 22034869 |
|---|---|
| Authors | Maria Peppa (0000-0002-4181-0638, University of the Aegean), M V Peppa (0000-0001-9683-0217, University of the Aegean), Christos Vasilakos (0000-0002-6932-2986, University of the Aegean, corresponding author), Dimitris Kavroudakis (0000-0001-5782-3049, University of the Aegean) |
| Year | 2020 |
| Volume | 9 |
| Issue | 3 |
| Pages | 143 |
| Publication date | 2020-02-29 |
| Peer Reviewed | Yes |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | ISPRS International Journal of Geo-Information (JOURNAL) |
| Journal identifiers | ISSN: 2220-9964 • E-ISSN: 2220-9964 |
| Publisher | MDPI AG (PUBLISHER • IT) |
| DOI | 10.3390/ijgi9030143 |
| OpenAlex | W3010325498 |
| Language | EN |
| References cited | 37 |
The use of remote sensing to monitor inland waters and their current state is of high importance, as fresh waters are the habitat of many species of flora and fauna, and are also important for anthropogenic activities. Water quality can be monitored by many parameters, including dissolved suspended matter, phytoplankton, turbidity, and dissolved organic matter, while the concentration of chlorophyll-a (chl-a) is a representative indicator for detecting phytoplankton and monitoring water quality. The detection of phytoplankton in water layers, through chl-a indicators, is an effective method for displaying eutrophication. Numerous scientific publications and studies have shown that remote sensing data and techniques are capable of monitoring the temporal and spatial distribution and variation of this phenomenon. This study aimed to investigate the eutrophication in Pamvotis Lake, in Ioannina, Greece with the application of chl-a detection algorithms, by using Sentinel-2 satellite imagery data for the time period of 2016–2018. The maximum chlorophyll index (MCI) and maximum peak-height (MPH) algorithms have been applied to top of atmosphere (TOA) reflectance data, to detect chl-a and monitor the trophic range of the water body. Both algorithms were correlated and resulted in Pearson’s r values up to 0.95. Finally, the chl-a concentration was estimated by applying an empirical equation that correlates the MPH and chl-a concentration developed within previous studies. Those results were further analyzed and interpreted with spatial statistical methods, to understand the spatial distribution pattern of the eutrophication in our study area. Our results demonstrated that Pamvotis Lake is a eutrophic lake, and the highest chl-a concentration was located in the east and south-east of the lake during the study period. Sentinel-2 data can be a useful tool for lake managers, in order to estimate the spatial distribution of the chl-a concentration and identify areas prone to eutrophication, as well as the coastal zones that may influence the lake through water canals
Biology · Chlorophyll a · Eutrophication · Geography · Nutrient · Phytoplankton · Remote sensing · Secchi disk · Spatial distribution · Trophic state index · Turbidity · Water quality · Aquatic Ecosystems and Phytoplankton Dynamics · Chemistry · Environmental Science · Marine and coastal ecosystems · Water Quality and Pollution Assessment · Ecology · Geology · Oceanography
| Citation velocity | historical |
|---|---|
| Highly cited | No |