Climatic Influence on the Carotenoids Concentration in a Mediterranean Coastal Lagoon Through Remote Sensing.
Saved in:
| Title: | Climatic Influence on the Carotenoids Concentration in a Mediterranean Coastal Lagoon Through Remote Sensing. |
|---|---|
| Authors: | Molner, Juan Víctor1 (AUTHOR) molpo@alumni.uv.es, Pérez-González, Rebeca1 (AUTHOR) juan.soria@uv.es, Sòria-Perpinyà, Xavier2 (AUTHOR) soperja@uv.es, Soria, Juan1 (AUTHOR) |
| Source: | Remote Sensing. Nov2024, Vol. 16 Issue 21, p4067. 17p. |
| Subjects: | Agricultural pollution, Environmental monitoring, Remote sensing, Optical properties, Carotenoids, Lagoons |
| Abstract: | The Albufera of Valencia, a Mediterranean coastal lagoon, has experienced a shift to hypertrophic conditions over the past 40 years due to agricultural and urban-industrial pollution. From August 2023 to early 2024, the water of the lagoon turned reddish-brown. This change has been observed in the past, but never with this intensity or duration, which typically occurs during periods of drought. In this study, carotenoid concentrations were analyzed in relation to precipitation and temperature using field and remote sensing data from February 2016 to December 2023. In November 2023, samples showed unusually high concentrations of carotenoids. The study confirmed the effectiveness of a new algorithm for estimating carotenoids using Sentinel-2 imagery to complement chlorophyll-a data. Results showed that temperature and precipitation significantly influenced carotenoid/chlorophyll-a ratio, highlighting a climatic control of phytoplankton community structure. These results highlight the importance of long-term monitoring and conservation efforts to address climate change and human impacts. This research is a first step in using optical properties of lakes as an indicator of phytoplankton dynamics under environmental stress and warns of the potential for increased occurrence or persistence of such phenomena with future climate trends. [ABSTRACT FROM AUTHOR] |
| Copyright of Remote Sensing is the property of MDPI and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Engineering Source |
|
Full text is not displayed to guests.
Login for full access.
|
|
Be the first to leave a comment!
