Optimizing a remotely sensed proxy for plankton biomass in Lake Kivu

Details

Serval ID
serval:BIB_69429A69DA26
Type
Article: article from journal or magazin.
Collection
Publications
Institution
Title
Optimizing a remotely sensed proxy for plankton biomass in Lake Kivu
Journal
International Journal of Remote Sensing
Author(s)
Knox A., Bertuzzo E., Maria L., Odermatt D., Verrecchia E., Rinaldo A.
Publication state
Published
Issued date
2014
Peer-reviewed
Oui
Volume
35
Pages
5219-5238
Language
english
Abstract
Many regions of the world, including inland lakes, present with suboptimal conditions for the remotely sensed retrieval of optical signals, thus challenging the limits of available satellite data-processing tools, such as atmospheric correction models (ACM) and water constituent-retrieval (WCR) algorithms. Working in such regions, however, can improve our understanding of remote-sensing tools and their applicabil- ity in new contexts, in addition to potentially offering useful information about aquatic ecology. Here, we assess and compare 32 combinations of two ACMs, two WCRs, and three binary categories of data quality standards to optimize a remotely sensed proxy of plankton biomass in Lake Kivu. Each parameter set is compared against the available ground-truth match-ups using Spearman's right-tailed ρ. Focusing on the best sets from each ACM-WCR combination, their performances are discussed with regard to data distribution, sample size, spatial completeness, and seasonality. The results of this study may be of interest both for ecological studies on Lake Kivu and for epidemio- logical studies of disease, such as cholera, the dynamics of which has been associated with plankton biomass in other regions of the world.
Create date
03/08/2014 10:04
Last modification date
20/08/2019 14:24
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