Spectral Characterization of Aquatic Nutrients and Water Quality Parameters in Marine Environment.

Tripathi, Nitin Kumar; Patil, Abhijit

doi:10.6010/geoinformatics.15.25

Cited by 7 publications

(3 citation statements)

References 11 publications

(7 reference statements)

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“…The Landsat/TM was used much more than other sensors for TP assessment in the reviewed literature. As phosphorus does not directly present optically diagnostic signals in water leaving radiance for the water quality remote sensing spectral domain (400–900 nm), thus empirical modeling is considered the most applicable approach for the remote estimation of TP in water column [ 68 , 69 , 235 ]. The literature review also showed that TP has a similar spatial pattern to chl- a and SD concentration due to a high correlation of TP with these parameters.…”

Section: Water Quality Investigations Through Remote Sensing Technmentioning

confidence: 99%

A Comprehensive Review on Water Quality Parameters Estimation Using Remote Sensing Techniques

Gholizadeh

Melesse

Reddi

2016

Sensors

732

464

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Remotely sensed data can reinforce the abilities of water resources researchers and decision makers to monitor waterbodies more effectively. Remote sensing techniques have been widely used to measure the qualitative parameters of waterbodies (i.e., suspended sediments, colored dissolved organic matter (CDOM), chlorophyll-a, and pollutants). A large number of different sensors on board various satellites and other platforms, such as airplanes, are currently used to measure the amount of radiation at different wavelengths reflected from the water’s surface. In this review paper, various properties (spectral, spatial and temporal, etc.) of the more commonly employed spaceborne and airborne sensors are tabulated to be used as a sensor selection guide. Furthermore, this paper investigates the commonly used approaches and sensors employed in evaluating and quantifying the eleven water quality parameters. The parameters include: chlorophyll-a (chl-a), colored dissolved organic matters (CDOM), Secchi disk depth (SDD), turbidity, total suspended sediments (TSS), water temperature (WT), total phosphorus (TP), sea surface salinity (SSS), dissolved oxygen (DO), biochemical oxygen demand (BOD) and chemical oxygen demand (COD).

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Section: Water Quality Investigations Through Remote Sensing Technmentioning

confidence: 99%

A Comprehensive Review on Water Quality Parameters Estimation Using Remote Sensing Techniques

Gholizadeh

Melesse

Reddi

2016

Sensors

732

464

View full text Add to dashboard Cite

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“…So, in this study, new corrected digital number (DN c ) was used instead of reflectance values (see Section 7.3). Many researchers also applied DN values in their studies [17]. Table 1 shows the sensor characteristics for THEOS scene.…”

Section: Regression Algorithmmentioning

confidence: 99%

TSS monitoring by using THEOS satellite imagery over Penang Island, Malaysia

Lim

MatJafri

Abdullah

2010

Remote Sensing of the Coastal Ocean, Land, and Atmosphere Environment

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Traditional sampling method for marine environment monitoring is time consuming and needs a high cost to carry out the survey. Remote sensing data have been widely used for monitoring marine environment and remote sensing is an efficient method to overcome the problem. This paper assesses the use of multispectral satellite imagery from THEOS for mapping spatial distribution of TSS in a coastal zone. The aim of this study is to evaluate the feasibility of using THEOS satellite image for the water quality studies. Simultaneous in situ measurements of total suspended solids (TSS) concentration and acquisition of satellite imageries were carried out over Penang Island, Malaysia. The locations of in situ sample were determined using a handheld Global Positioning System (GPS). The algorithm used is based on the reflectance model which is a function of the inherent optical properties of water and this in turn can be related to the concentration of its constituents. Multiple regression algorithm was employed using the multi-band data for retrieval of the water constituent. Digital numbers corresponding to the water sample locations were determined for algorithm calibration. Various types of algorithms were tested; R and RMS value were noted. The proposed algorithm is considered superior based on the values of the correlation coefficient and root-mean-square The algorithm was used to generate the TSS map for the Penang Island, Malaysia. Geometric correction was performed to the TSS map and colour-coded for visual interpretation. This study shows the potential application of THEOS satellite images for TSS mapping using the proposed multispectral algorithm.

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“…The SWIR band of a Sentinel 2A/MSI image was proven once again important for Chl-a estimation (R 2 = 0.7) in Chebara Dam (Kenya) [97] and in particular, a second-order polynomial fit was found to be suitable using the reflectance from the difference between the green (B3) and the SWIR-1 (B11) band. Furthermore, [98] studied 11 representative lakes of Greece (included in our dataset) regarding their Chl-a concentrations and managed to establish high correlations between the red and SWIR bands of Landsat 8 images. The authors of [9] also generated a Chl-a three-variable predictive model employing green and SWIR-1 bands and the ratio red/green using EMT+ sensor (R 2 = 0.91) in Río Tercero reservoir (Argentina).…”

Section: Contribution Of Swir Bands In Wq Monitoring Of Case 2 Watersmentioning

confidence: 99%

Modelling of Greek Lakes Water Quality Using Earth Observation in the Framework of the Water Framework Directive (WFD)

et al. 2022

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Given the great importance of lakes in Earth’s environment and human life, continuous water quality (WQ) monitoring within the frame of the Water Framework Directive (WFD) is the most crucial aspect for lake management. In this study, Earth Observation (EO) data from Landsat 7 Enhanced Thematic Mapper Plus (ETM+) and Landsat 8 Operational Land Imager (OLI) sensors have been combined with co-orbital in situ measurements from 50 lakes located in Greece with the main objective of delivering robust WQ assessment models. Correlation analysis among in situ co-orbital WQ data (Chlorophylla, Secchi depths, Total phosphorus-TP-) contributed to distinguishing their inter-relationships and improving the WQ models’ accuracy. Subsequently, stepwise multiple regression analysis (MLR) of the available TP and Secchi depth datasets was implemented to explore the potential to establish optimal quantitative models regardless of lake characteristics. Then, further MLR analysis concerning whether the lakes are natural or artificial was conducted with the basic aim of generating different remote sensing derived models for different types of lakes, while their combination was further utilized to assess their trophic status. Correlation matrix results showed a high and positive relationship between TP and Chlorophyll-a (0.85), whereas high negative relationships were found between Secchi depth with TP (−0.84) and Chlorophyll-a (−0.83). MLRs among Landsat data and Secchi depths resulted in 3 optimal models concerning the assessment of Secchi depth of all lakes (Secchigeneral; R = 0.78; RMSE = 0.24 m), natural (Secchinatural; R = 0.95; RMSE = 0.14 m) and artificial (Secchiartificial; R = 0.62; RMSE = 0.1 m), with reliable accuracy. Study findings showed that TP-related MLR analyses failed to deliver a statistically acceptable model for the reservoirs; nevertheless, they delivered a robust TPgeneral (R = 0.71; RMSE = 1.41 mg/L) and TPnatural model (R = 0.93; RMSE = 1.43 mg/L). Subsequently, trophic status classification was conducted herein, calculating Carlson’s Trophic State Index (TSI) initially throughout all lakes and then oriented toward natural-only and artificial-only lakes. Those three types of TSI (general, natural, artificial) were calculated based on previously published satellite-derived Chlorophyll-a (Chl-a) assessment models and the hereby specially designed WQ models (Secchi depth, TP). The higher deviation of satellite-derived TSI values in relation to in situ ones was detected in reservoirs and shallower lakes (mean depth < 5 m), indicating noticeable divergences among natural and artificial lakes. All in all, the study findings provide important support toward the perpetual WQ monitoring and trophic status prediction of Greek lakes and, by extension, their sustainable management, particularly in cases when ground truth data is limited.

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Spectral Characterization of Aquatic Nutrients and Water Quality Parameters in Marine Environment.

Cited by 7 publications

References 11 publications

A Comprehensive Review on Water Quality Parameters Estimation Using Remote Sensing Techniques

A Comprehensive Review on Water Quality Parameters Estimation Using Remote Sensing Techniques

TSS monitoring by using THEOS satellite imagery over Penang Island, Malaysia

Modelling of Greek Lakes Water Quality Using Earth Observation in the Framework of the Water Framework Directive (WFD)

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