Estuarine sediment deposition during wetland restoration: A GIS and remote sensing modeling approach

Newcomer, Michelle; Kuss, Amber Jean; Ketron, Tyler; Remar, Alex; Choksi, Vivek; Skiles, J. W.

doi:10.1080/10106049.2013.798356

Cited by 12 publications

(7 citation statements)

References 27 publications

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“…Turbidity and its effect on associated parameters of sh and sheries, advantages and disadvantages of turbidity, the importance of observing the role of turbidity with respect to sh and sheries increases the importance of observing methods to measure turbidity. A strong correlation between observed turbidity through Remote Sensing studies with the help of changes in re ectance values and in-situ turbidity and has been reported by previous studies (Newcomer et al, 2014).…”

Section: Introductionsupporting

confidence: 82%

Covid-19 pandemic: Impact and assessment of water quality in the lower Ganga riverine system, India

Bhor

Tiwari

Parida

et al. 2022

Preprint

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The COVID-19 pandemic and its associated lockdown imposed all over India from 25th March 2020 to 14th April 2020 have made a significant impact on all sectors of life and livelihood including inland fisheries. However, the intensity and extent of the impact on inland open water resources especially rivers and associated water bodies is still unclear. In this study, an immediate and clear effect was observed in the quality of water flowing through the river Ganga. In consideration of pandemic conditions and difficulty in gathering field data, this study attempts to determine the river water quality in terms of turbidity, based on remote sensing imagery data. These changes have been recorded and analysed using Sentinel-2 multispectral remote sensing data for the lower stretches of river Ganga, for selected five stretches covering an approximate mid-channel length of 537 km. The highest sensitivity for turbidity was found in the red and NIR bands among all the bands which were used to estimate turbidity. Temporal variations were also studied through Normalized Difference Turbidity Index at each of these small stretches. A very steep decline in turbidity in the river water has been observed in each of the stretches. The study improved the understanding that the remote sensing approach is capable of assessing the water quality of river turbidity to a greater extent when there are strong hurdles to collecting research data from field studies.

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Section: Introductionsupporting

confidence: 82%

Covid-19 pandemic: Impact and assessment of water quality in the lower Ganga riverine system, India

Bhor

Tiwari

Parida

et al. 2022

Preprint

View full text Add to dashboard Cite

show abstract

“…Because of the optical reflectance, scattering, and absorption of various substances, different optical properties of the surface reflectance have the significant ability to extract information about the water quality parameters from the surface reflectance measurements. As computer calculating technology progresses, as well as the development of remote sensing technology, particularly spaceborne optical sensors, it is becoming possible to get water quality parameters (WOPs) with a greater spatial range and a better degree of precision [4][5][6].…”

Section: Introductionmentioning

confidence: 99%

Research on Inversion of Suspended Sediment Concentration in Estuary Surface Based on Remote Sensing and GIS

Zeng

Jun

Liu³

2022

Security and Communication Networks

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The concentration of suspended sediments at the estuarine surface (SSC) is a crucial indicator for monitoring water bodies. Given the current situation in which SSC remote sensing inversion is primarily based on low-resolution satellites, this study first discusses remote sensing and GIS technologies before employing the Sentinel-2 satellite, whose resolution can exceed 10 m after resampling. Inversion and comparison of SSC content during wet and dry periods. In addition, based on the neural network’s ability to compensate for the inherent errors of traditional empirical techniques, this study designs and develops an artificial neural network-based neural network corrector to perform secondary correction on the empirical inversion results. In this study, the B2, B3, B4, and B8 inversion models are used to generate the sensitive bands, and the ratio of these bands is used to generate the inversion model. The results indicate that the model has a high level of precision, which can aid in reducing the model’s inherent error and ensuring inversion precision.

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“…Unsuccessful restoration projects often occur by focusing on restoring wetland biota without considering the underlying hydrology and terrain conditions in a region (Kauffman-Axelrod and Steinberg 2010). Similarly, wetland restoration focused on individual wetlands, referred to as at the wetland scale (e.g., Newcomer et al 2013), is likely to fail when it is not integrated into the broader landscape (Van Meter and Basu 2015).…”

Section: Introductionmentioning

confidence: 99%

Quantifying Topographic Characteristics of Wetlandscapes

Branton

Robinson

2019

Wetlands

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Topography underpins natural processes ranging from incident solar radiation to overland flow and water pooling. Despite the influence of topography on natural processes, especially in wetland ecosystems reliant on uplands for water inputs, topography has not been adequately incorporated into reclamation planning. Instead, wetland reclamation projects are typically guided by height-to-length ratios that produce little resemblance to natural wetlands. We present a methodology to quantify the topographic characteristics in landscapes with an abundance of wetlands to guide the reclamation of naturally appearing and self-sustaining wetlandscapes. Topographic characteristics in over 3000 sample landscapes were quantified using terrain roughness and landform element composition and configuration. A large set of metrics was reduced to a statistically independent subset that was applied and compared across three natural regions and a gradient of disturbance. Our results showed that surface roughness and landform element patterns significantly differ among natural regions and that high disturbance landscapes significantly differ from other disturbance levels. To ensure reclaimed wetlandscapes are naturally appearing and self-sustaining, they should replicate the topographic characteristics found within the distribution of surrounding natural landscapes by applying topographic characteristic benchmarks to reclamation design. The presented methodology can be used as a step towards achieving this goal.

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Estuarine sediment deposition during wetland restoration: A GIS and remote sensing modeling approach

Cited by 12 publications

References 27 publications

Covid-19 pandemic: Impact and assessment of water quality in the lower Ganga riverine system, India

Covid-19 pandemic: Impact and assessment of water quality in the lower Ganga riverine system, India

Research on Inversion of Suspended Sediment Concentration in Estuary Surface Based on Remote Sensing and GIS

Quantifying Topographic Characteristics of Wetlandscapes

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