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ZENODO
Dataset . 2024
License: CC BY
Data sources: ZENODO
ZENODO
Dataset . 2024
License: CC BY
Data sources: Datacite
ZENODO
Dataset . 2024
License: CC BY
Data sources: Datacite
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Time series of turbidity in Northern Patagonia using the Nechad algorithms (v2009 and v2016) at 665 nm. Time series 2016-2020.

Authors: García, Wirmer; Curra Sánchez, Elizabeth; Lara, Carlos; González Rodríguez, Lisdelys; Urrego, Patricia; Delegido, Jesus; Broitman, Bernardo;

Time series of turbidity in Northern Patagonia using the Nechad algorithms (v2009 and v2016) at 665 nm. Time series 2016-2020.

Abstract

Time series of turbidity in Northern Patagonia using the Nechad algorithms (v2009 and v2016) at 665 nm. Time series 2016-2020. Our study aimed to evaluate the spatio-temporal variability of turbidity from Sentinel-2 (S2) images in the Reloncaví sound and fjord, in Northern Patagonia, Chile, a coastal ecosystem that is intensively used by finfish and shellfish aquaculture. To this end, we downloaded 123 S2 images and assembled a five-year time series (2016-2020) covering five study sites (R1 to R5) located along the axis of the fjord and seaward into the sound. We used Acolite to perform the atmospheric correction and estimate turbidity with two algorithms proposed by Nechad et al. (2009, 2016 Nv09 and Nv16, respectively). Columns (R) represent the spatial distribution of study sites (see Figure 2). For more information see materials and methods. Nv2009 or Nv09 are the results obtained for the Nechad algorithm version 2009. Similar to Nv2016 or Nv16 are the results obtained for the Nechad algorithm version 2016.

Keywords

Temporal Patterns, Reloncaví sound, Ocean Color, Northern Patagonia, Satellite Algorithms, Aquaculture, Water Quality Monitoring, Remote sensing, Chile, Ecological Informatics

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
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