scholarly journals Complex network modeling of spectral remotely sensed imagery: A case study of massive green algae blooms detection based on MODIS data

2016 ◽  
Vol 464 ◽  
pp. 138-148 ◽  
Author(s):  
Yi Sui ◽  
Fengjing Shao ◽  
Changying Wang ◽  
Rencheng Sun ◽  
Jun Ji
Keyword(s):  
Complex Network ◽  
Green Algae ◽  
Network Modeling ◽  
Remotely Sensed ◽  
Modis Data ◽  
Remotely Sensed Imagery ◽  
Algae Blooms

scholarly journals Hindcast and Near Real-Time Monitoring of Green Macroalgae Blooms in Shallow Coral Reef Lagoons Using Sentinel-2: A New-Caledonia Case Study

2021 ◽  
Vol 13 (2) ◽  
pp. 211
Author(s):  
Maële Brisset ◽  
Simon Van Wynsberge ◽  
Serge Andréfouët ◽  
Claude Payri ◽  
Benoît Soulard ◽  
...  
Keyword(s):  
Green Algae ◽  
Algal Blooms ◽  
New Caledonia ◽  
Spectral Indices ◽  
Green Macroalgae ◽  
Spectral Bands ◽  
Algae Blooms ◽  
Trade Offs ◽  
Sentinel 2

Despite the necessary trade-offs between spatial and temporal resolution, remote sensing is an effective approach to monitor macroalgae blooms, understand their origins and anticipate their developments. Monitoring of small tropical lagoons is challenging because they require high resolutions. Since 2017, the Sentinel-2 satellites has provided new perspectives, and the feasibility of monitoring green algae blooms was investigated in this study. In the Poé-Gouaro-Déva lagoon, New Caledonia, recent Ulva blooms are the cause of significant nuisances when beaching. Spectral indices using the blue and green spectral bands were confronted with field observations of algal abundances using images concurrent with fieldwork. Depending on seabed compositions and types of correction applied to reflectance data, the spectral indices explained between 1 and 64.9% of variance. The models providing the best statistical fit were used to revisit the algal dynamics using Sentinel-2 data from January 2017 to December 2019, through two image segmentation approaches: unsupervised and supervised. The latter accurately reproduced the two algal blooms that occurred in the area in 2018. This paper demonstrates that Sentinel-2 data can be an effective source to hindcast and monitor the dynamics of green algae in shallow lagoons.

Urban Change Detection Using Multi-temporal Remotely Sensed Imagery (Case Study: Gorgan Area, Northern Iran)

2013 ◽  
Vol 4 (2) ◽  
pp. 339-348
Author(s):  
Somayeh Galdavi ◽  
Marjan Mohammadzadeh ◽  
Abdolrassoul Salmanmahiny ◽  
Ali Najafi Nejad
Keyword(s):  
Change Detection ◽  
Remotely Sensed ◽  
Urban Change ◽  
Northern Iran ◽  
Remotely Sensed Imagery ◽  
Multi Temporal

Monitoring active subglacial volcanoes: a case study using airborne remotely sensed imagery of Grímsvötn, Iceland

2008 ◽  
Vol 29 (22) ◽  
pp. 6501-6514 ◽  
Author(s):  
S. F. Stewart ◽  
H. Pinkerton ◽  
G. A. Blackburn ◽  
M. T. Gudmundsson
Keyword(s):  
Remotely Sensed ◽  
Remotely Sensed Imagery
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