Water wave glint corrections, water depth, light attenuation, and WorldView-3 remote sensing algorithms for Indian River lagoon

2019 ◽  
Author(s):  
Charles R. Bostater ◽  
Samin Aziz
Keyword(s):  
Remote Sensing ◽  
Water Depth ◽  
Water Wave ◽  
Light Attenuation ◽  
Indian River Lagoon ◽  
Indian River

Neural network-based light attenuation model for monitoring seagrass population in the Indian river lagoon

2007 ◽  
Vol 29 (1) ◽  
pp. 63-77 ◽  
Author(s):  
M. T. Musavi ◽  
H. Ressom ◽  
S. Srirangam ◽  
P. Natarajan ◽  
R. W. Virnstein ◽  
...  
Keyword(s):  
Neural Network ◽  
Light Attenuation ◽  
Indian River Lagoon ◽  
Attenuation Model ◽  
Indian River

Environmental Dredging to Remove Fine-Grained, Organic-Rich Sediments and Reduce Inputs of Nitrogen and Phosphorus to a Subtropical Estuary

2018 ◽  
Vol 52 (4) ◽  
pp. 42-57 ◽  
Author(s):  
Austin L. Fox ◽  
John H. Trefry
Keyword(s):  
Water Depth ◽  
Interstitial Water ◽  
Indian River Lagoon ◽  
Benthic Fluxes ◽  
Nitrogen And Phosphorus ◽  
Overlying Water ◽  
Fine Grained ◽  
Total Inventory ◽  
Indian River ◽  
Subtropical Estuary

AbstractEnvironmental dredging of fine-grained, organic-rich sediments, locally referred to as Indian River Lagoon (IRL) muck, have been promoted as an integral part of restoring the IRL, Florida, to a healthy ecosystem. In Turkey Creek, a tributary to the IRL, ~300 metric tons of N and ~70 metric tons of P were removed with 160,000 m3 of wet muck and sand via environmental dredging during 2016 and 2017. Within the established dredged area, muck removal efficiency was ~63%; some areas were not dredged deep enough to remove all the muck. An additional 24,000 m3 of muck located outside the dredged area were not removed due to the presence of docks and seawalls. Prior to dredging, benthic fluxes of dissolved N (as ammonium) and P (as phosphate) from sediments to the overlying water, adjusted to 25°C, averaged 11 mg N/m2/h and 2.5 mg P/m2/h, respectively. Where IRL muck was removed to expose the underlying sand or mixed sand and muck, benthic fluxes of N and P were 20- to 30-fold lower after dredging. Subsequent disturbances, including Hurricane Matthew in October 2016, redistributed residual muck, leaving the dredged area 26% muck-free. Where muck was incompletely dredged or reintroduced by slumping, fluxes returned to predredging values within 6 months as equilibrium was reestablished between sediments and interstitial water. Dredging produced a 50% increase in water depth and basin volume with positive increases in salinity and the total inventory of dissolved oxygen. This deeper basin also serves as a sediment trap that will sequester future inputs of muck and mitigate future benthic fluxes of N and P by reducing the transport of muck into the IRL.

Seagrass management in Indian River Lagoon, Florida: dealing with issues of scale

1999 ◽  
Vol 5 (4) ◽  
pp. 299 ◽  
Author(s):  
Robert W. Virnstein
Keyword(s):  
Water Quality ◽  
Large Scale ◽  
Light Attenuation ◽  
Indian River Lagoon ◽  
Aerial Photographs ◽  
Major Theme ◽  
Fine Scale ◽  
Geographic Scale ◽  
Indian River ◽  
Remote Sensing Mapping

The major theme of this paper is that management of seagrass must deal with issues of geographic scale. Approaches at several scales are needed. Examples are drawn primarily from management programmes for the 250 km long Indian River Lagoon system on the south-east coast of Florida. The Lagoon has several attributes of spatial variation that require approaches at various scales (e.g., from 1:1 000 000 to 1:1). Risks and errors of scaling up and scaling down are described. For large-scale approaches, remote-sensing mapping methods are generally appropriate. In the Indian River Lagoon, true-colour aerial photographs. are typically taken every 2?3 years at 1 :24 000 scale. Such Lagoon-wide maps have fuzzy boundaries and cannot be scaled down to fine scale, but they can be scaled up. At large scale, seagrass restoration/protection targets (to a depth of 1.7 m) are reasonable, but are unreasonable at fine scale. For monitoring change within a bed or meadow at metre to 500 m scale, monitoring of fixed transects is a powerful tool. However, the technique has limited power for comparisons among beds, which requires multiple transects. To build a predictive model, a site-specific study examined the relationships among light, water quality, and seagrasses. The link between seagrass and water quality is made through a light attenuation model incorporating both water column and epiphytes. Extensive sampling is required to test the robustness of the model at all scales. No single scale is appropriate for all approaches, and no approach applies over all scales. If such considerations of scale are not incorporated, errors of measurement, inappropriate techniques for assessment, implementation of wrong solutions, and a lack of understanding of the system under study can result.

Dynamics of microcystins and saxitoxin in the Indian River Lagoon, Florida

Harmful Algae ◽  
2021 ◽  
Vol 103 ◽  
pp. 102012
Author(s):  
Abdiel E. Laureano-Rosario ◽  
Malcolm McFarland ◽  
David J. Bradshaw ◽  
Jackie Metz ◽  
Rachel A. Brewton ◽  
...  
Keyword(s):  
Indian River Lagoon ◽  
Indian River

scholarly journals Bloom dynamics and chemical defenses of benthic cyanobacteria in the Indian River Lagoon, Florida

Harmful Algae ◽  
2017 ◽  
Vol 69 ◽  
pp. 75-82 ◽  
Author(s):  
Jennifer M. Sneed ◽  
Theresa Meickle ◽  
Niclas Engene ◽  
Sherry Reed ◽  
Sarath Gunasekera ◽  
...  
Keyword(s):  
Indian River Lagoon ◽  
Chemical Defenses ◽  
Benthic Cyanobacteria ◽  
Indian River
Sign in / Sign up

Export Citation Format

Share Document