Remote Sensing of Suspended Sediment Concentration Along the Middle-Mississippi River

Pereira, Letícia; Andes, Lisa C.; Cox, Amanda L.; Wulamu, Abuduwasiti

doi:10.1130/abs/2016nc-275026

Cited by 4 publications

(7 citation statements)

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“…[5], [7], [10], [14], [17], [18], [22], [23], [25], [26], [28], 55 [39], [46], [52], [59], [60], [64], [66], [69], [79], [80], [86]- [89], [96], [97], [99]- [103], [105], [106], [108], [109], [113], [115], [116]. These technologies enable the monitoring of various water quality parameters with improved spatial resolution and coverage.…”

Section: Introductionmentioning

confidence: 99%

“…These technologies enable the monitoring of various water quality parameters with improved spatial resolution and coverage. Moreover, 60 the availability of open-access remote sensing data, such as those from the Landsat [2]-[4], [7], [10], [23], [24], [28], [29], [39], [51]- [53], [59], [64], [69], [86]- [88], [90], [92], [95], [97], [99], [100], [102], [104], [108], [114], [116] and Sentinel [7], [14], [26], [34],…”

Section: Introductionmentioning

confidence: 99%

“…algal bloom [96], [115], colored dissolved organic matter (CDOM) [24], [26], [66], [79], [80], [113], total organic carbon (TOC) [28], [116], dissolved organic carbon (DOC) [17], [25], [89], secchi disk transparency (SDT) [48], [92], [95], suspended particulate matter (SPM) [119], suspended solids concentration (SSC) [86], [100], secchi disk depth (SDD) [7], [87], [101], pH [7], [46], [87], [88], total dissolved solids (TDS) [2], [4], [10], [28], [53], [64], [81], [99], [117], and electrical conductivity (EC) [4], [39], [46], [119]. in equipment, expertise, and sampling methods.…”

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confidence: 99%

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Citizen Science Applications for Water Quality Monitoring. A Review

Saleem,

Oussalah,

Highighi

2024

Preprint

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In recent years citizen science emerged as apromising technology in environmental science and hy-drology with the potential to overcome the lack of in-situ measurements and create efficient ecosystems. Thispaper provides an up-to-date systematic literature reviewof applications of citizen science technology in water qual-ity monitoring and estimation. A bridge between citizenscience and remote sensing will be established to providea sound framework for comprehensively discussing thevarious approaches and applications. A scrutinizing of var-ious water quality parameters and associated measurement& estimation methods is provided, delving into variousremote sensing systems (microwave and optical systems)and imaging techniques (hyperspectral and hyperspectralmethods). A special interest is focused on reviewing existingrelevant crowd-sourcing mobile apps such as EyeOnWater,HydroColor, EnviObserver, Sechhi App, Hydro Crowd,and SIMILE-Lake monitoring, detailing their workingmechanisms, algorithms, data acquisition processes, usedsensors, and measured water quality parameters. Finally,the paper summarizes key knowledge gaps, challenges andpromising directions in this research field.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

mentioning

confidence: 99%

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Citizen Science Applications for Water Quality Monitoring. A Review

Saleem,

Oussalah,

Highighi

2024

Preprint

View full text Add to dashboard Cite

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“…[39], [46], [52], [59], [60], [64], [66], [69], [79], [80], [86]- [89], [96], [97], [99]- [103], [105], [106], [108], [109], [113], [115], [116]. These technologies enable the monitoring of various water quality parameters with improved spatial resolution and coverage.…”

mentioning

confidence: 99%

mentioning

confidence: 99%

Citizen Science Applications for Water Quality Monitoring. A Review

Saleem,

Torabi Haghighi,

Klöve

et al. 2024

Preprint

View full text Add to dashboard Cite

Abstract. In recent years citizen science emerged as a promising technology in environmental science and hydrology with the potential to overcome the lack of in-situ measurements and create efficient ecosystems. This paper provides an up-to-date systematic literature review of applications of citizen science technology in water quality monitoring and estimation. A bridge between citizen science and remote sensing will be established to provide a sound framework for comprehensively discussing the various approaches and applications. A scrutinizing of various water quality parameters and associated measurement and estimation methods is provided, delving into various remote sensing systems (microwave and optical systems) and imaging techniques (hyperspectral and hyperspectral methods). A special interest is focused on reviewing existing relevant crowd-sourcing mobile apps such as EyeOnWater, HydroColor, EnviObserver, Sechhi App, Hydro Crowd, and SIMILE-Lake monitoring, detailing their working mechanisms, algorithms, data acquisition processes, used sensors, and measured water quality parameters. Finally, the paper summarizes key knowledge gaps, challenges and promising directions in this research field.

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Measuring Suspended‐Sediment Concentration and Turbidity in the Middle Mississippi and Lower Missouri Rivers Using Landsat Data

Pereira

Andes

Cox

et al. 2017

J American Water Resour Assoc

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The Middle Mississippi River (MMR) and lower Missouri River (MOR) provide critical navigation waterways, ecological habitat, and flood conveyance. They are also directly linked to processes affecting geomorphic and ecological conditions in the lower MR and Delta. For this study, a method was developed to measure suspended‐sediment concentration (SSC) and turbidity along the MMR and the lower MOR using Landsat imagery. Data from nine United States Geological Survey water‐quality monitoring stations were used to create a model‐development dataset and a model‐validation dataset. Concurrent gaging data were identified for available Landsat images to generate the datasets. Surface‐reflectance filters were developed to eliminate images with cirrus cloud coverage or vessel traffic. Using the filtered model‐development dataset, unique reflectance‐SSC and reflectance‐turbidity models were developed for three Landsat sensors: Landsat 8 Operational Land Imager, Landsat 7 Enhanced Thematic Mapper Plus, and Landsat 4–5 Thematic Mapper. Coefficient of determination values for the models ranged from 0.72 to 0.88 for the model‐development dataset. The model‐validation dataset was used to evaluate the performance of the models and had coefficient of determination values ranging from 0.62 to 0.79.

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Remote Sensing of Suspended Sediment Concentration Along the Middle-Mississippi River

Cited by 4 publications

References 0 publications

Citizen Science Applications for Water Quality Monitoring. A Review

Citizen Science Applications for Water Quality Monitoring. A Review

Citizen Science Applications for Water Quality Monitoring. A Review

Measuring Suspended‐Sediment Concentration and Turbidity in the Middle Mississippi and Lower Missouri Rivers Using Landsat Data

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