Long-Term Spatiotemporal Variability of Whitings in Lake Geneva from Multispectral Remote Sensing and Machine Learning
Details
Serval ID
serval:BIB_37C33EE1A049
Type
Article: article from journal or magazin.
Collection
Publications
Institution
Title
Long-Term Spatiotemporal Variability of Whitings in Lake Geneva from Multispectral Remote Sensing and Machine Learning
Journal
Remote Sensing
ISSN
2072-4292
Publication state
Published
Issued date
06/12/2022
Peer-reviewed
Oui
Volume
14
Number
23
Pages
6175
Language
english
Abstract
Whiting events are massive calcite precipitation events turning hardwater lake waters to a milky turquoise color. Herein, we use a multispectral remote sensing approach to describe the spatial and temporal occurrences of whitings in Lake Geneva from 2013 to 2021. Landsat-8, Sentinel-2, and Sentinel-3 sensors are combined to derive the AreaBGR index and identify whitings using appropriate filters. 95% of the detected whitings are located in the northeastern part of the lake and occur in a highly reproducible environmental setting. An extended time series of whitings in the last 60 years is reconstructed from a random forest algorithm and analyzed through a Bayesian decomposition for annual and seasonal trends. The annual number of whiting days between 1958 and 2021 does not follow any particular monotonic trend. The inter-annual changes of whiting occurrences significantly correlate to the Western Mediterranean Oscillation Index. Spring whitings have increased since 2000 and significantly follow the Atlantic Multidecadal Oscillation index. Future climate change in the Mediterranean Sea and the Atlantic Ocean could induce more variable and earlier whiting events in Lake Geneva.
Keywords
whitings, remote sensing, machine learning, climate index, ground data
Publisher's website
Open Access
Yes
Funding(s)
Swiss National Science Foundation / 200021_175530
Create date
07/12/2022 7:47
Last modification date
09/12/2022 7:09