Hyperspectral Satellite Remote Sensing of Water Quality in Lake Atitlán, Guatemala

Flores-Anderson, Africa; Griffin, Robert; Dix, Margaret; Romero-Oliva, Claudia; Ochaeta, Gerson; Skinner-Alvarado, Juan; Moran, Maria Violeta Ramirez; Hernández, B. E.; Cherrington, E. A.; Page, Benjamin P.; Barreno, Flor

doi:10.3389/fenvs.2020.00007

Cited by 45 publications

(29 citation statements)

References 42 publications

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“…Hyperspectral remote sensing techniques for inland and coastal water monitoring have been developed for more than three decades (e.g., [1,2]). Overall, the availability of a continuous spectrum makes algorithms more effective in a wide variety of waters with varying water column depths and bottom reflectance, and lead to a more successful retrieval of a larger number of properties (e.g., [3][4][5][6]).…”

Section: Introductionmentioning

confidence: 99%

First Evaluation of PRISMA Level 1 Data for Water Applications

Giardino

Bresciani

Braga

et al. 2020

Sensors

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This study presents a first assessment of the Top-Of-Atmosphere (TOA) radiances measured in the visible and near-infrared (VNIR) wavelengths from PRISMA (PRecursore IperSpettrale della Missione Applicativa), the new hyperspectral satellite sensor of the Italian Space Agency in orbit since March 2019. In particular, the radiometrically calibrated PRISMA Level 1 TOA radiances were compared to the TOA radiances simulated with a radiative transfer code, starting from in situ measurements of water reflectance. In situ data were obtained from a set of fixed position autonomous radiometers covering a wide range of water types, encompassing coastal and inland waters. A total of nine match-ups between PRISMA and in situ measurements distributed from July 2019 to June 2020 were analysed. Recognising the role of Sentinel-2 for inland and coastal waters applications, the TOA radiances measured from concurrent Sentinel-2 observations were added to the comparison. The results overall demonstrated that PRISMA VNIR sensor is providing TOA radiances with the same magnitude and shape of those in situ simulated (spectral angle difference, SA, between 0.80 and 3.39; root mean square difference, RMSD, between 0.98 and 4.76 [mW m−2 sr−1 nm−1]), with slightly larger differences at shorter wavelengths. The PRISMA TOA radiances were also found very similar to Sentinel-2 data (RMSD < 3.78 [mW m−2 sr−1 nm−1]), and encourage a synergic use of both sensors for aquatic applications. Further analyses with a higher number of match-ups between PRISMA, in situ and Sentinel-2 data are however recommended to fully characterize the on-orbit calibration of PRISMA for its exploitation in aquatic ecosystem mapping.

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Section: Introductionmentioning

confidence: 99%

First Evaluation of PRISMA Level 1 Data for Water Applications

Giardino

Bresciani

Braga

et al. 2020

Sensors

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“…The 6SV is an advanced radiative transfer code capable of accounting for radiation polarization in a mixed molecular-aerosol atmosphere being a vector version of the 6S [33]. The 6S atmospheric correction has already been successfully used in lakes and reservoirs [21,32,[34][35][36][37].…”

Section: Introductionmentioning

confidence: 99%

Temporal and Spatial Variations of Secchi Depth and Diffuse Attenuation Coefficient from Sentinel-2 MSI over a Large Reservoir

et al. 2020

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The Alqueva reservoir (South of Portugal) in the Guadiana river basin constitutes the most important water resource in southern Portugal for domestic and agricultural consumption. We present a methodology developed to characterize spatial and temporal variations of Secchi depth and diffuse attenuation coefficient (both related to dissolved/suspended particles and to water transparency), using high spatial resolution satellite images from Sentinel-2 Multi-Spectral Instrument (MSI). Empirical relations between satellite retrievals of surface reflectances and in situ measurements of water parameters were defined and applied to the entire reservoir for spatial and temporal analysis in the period July 2017-June 2019, useful in the identification of microalgae blooms and rapid variations in water characteristics, which allowed us to differentiate five zones. Water estimates with lower transparency and higher attenuation of radiation were found in the northern area of Alqueva reservoir during the months characterized by higher water temperatures, with Secchi depth monthly averages near 1.0 m and diffuse attenuation coefficient near or above 1.5 m −1 . Satellite retrievals of water with greater transparency in the reservoir were obtained in the southern area in months with low water temperature and atmospheric stability, presenting some monthly Secchi depth averages above 3 m, and diffuse attenuation coefficient below 0.8 m −1 . January 2018 presented great transparency of water with a Secchi depth of 7.5 m for pixels representing the 95th percentile and diffuse attenuation coefficient of 0.36 m for pixels representing the 5th percentile in the Southern region.

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“…Despite the simplicity of this approach, results from this statistical analysis are highly informative about water quality conditions when using Chl-a as indicator of eutrophication or levels of nutrient enrichment and potential nutrient sources. However, one of the criticisms (and limitations) is that these empirical algorithms are calibrated and validated based on a small number of in situ samples (c.a.,~20 samples) [21,81,82]. In this study, we used Level-1 Landsat 8/OLI images (path 22, rows 39 and 40) captured on 21 February 2020 and continuous in situ Chl-a fluorometry data collected approximately 20 h apart (22 February 2020; N = 1441 data observations) to increase the sample size (>1000 sampling points).…”

Section: Remote Sensing-based Algorithms To Estimate Chl-a Concentratmentioning

confidence: 99%

“…Band 1 is centered at 443 nm corresponding to the first Chl-a strong absorption peak; band 4 is centered at 655 nm (low point of the second Chl-a absorption peak) while band 3 is centered at 562 nm within the green range corresponding to the minimum Chl-a absorption ( [87]; Figure 2). Indeed, R t bands 1, 4 and 3 are commonly used for spectral estimates of Chl-a as these bio-physical properties strongly shape its contribution to surface reflectance [81,87].…”

Section: Determining the Best Band Ratio And Algorithm Development Apmentioning

confidence: 99%

Assessing Chlorophyll a Spatiotemporal Patterns Combining In Situ Continuous Fluorometry Measurements and Landsat 8/OLI Data across the Barataria Basin (Louisiana, USA)

Vargas-Lopez

Rivera‐Monroy

Day

et al. 2021

Water

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The acquisition of reliable and accurate data to assess environmental changes over large spatial scales is one of the main limitations to determine the impact of eutrophication, and the effectiveness of management strategies in coastal systems. Here, we used a continuous in situ Chl-a fluorometry sensor and L8/OLI satellite data to develop an algorithm and map Chl-a spatial distribution to assess the impact of freshwater diversions and associated high nutrient loading rates in the Barataria Basin (BB) complex, a coastal system in the northern Gulf of Mexico. We collected water quality samples at 24 sampling stations and high-frequency continuous fluorometry in situ [Chl-a] data along a ~87 km transect from 2019–2020. Field [Chl-a] values were highly correlated (r = 0.86; p < 0.0001) with continuous in situ [Chl-a] fluorometry values. These continuous in situ [Chl-a] values were significantly related to a surface reflectance ratio ([B1 + B4]/B3) estimated using L8/OLI data (exponential model; R2 = 0.46; RMSE = 4.8, p < 0.0001). The statistical model replicated [Chl-a] spatial patterns across the BB complex. This work shows the utility of high-frequency continuous Chl-a fluorometry sampling coupled with L8/OLI image analysis to increase the frequency and number of field data sets to assess water quality conditions at large spatial scales in highly dynamic deltaic regions.

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Hyperspectral Satellite Remote Sensing of Water Quality in Lake Atitlán, Guatemala

Cited by 45 publications

References 42 publications

First Evaluation of PRISMA Level 1 Data for Water Applications

First Evaluation of PRISMA Level 1 Data for Water Applications

Temporal and Spatial Variations of Secchi Depth and Diffuse Attenuation Coefficient from Sentinel-2 MSI over a Large Reservoir

Assessing Chlorophyll a Spatiotemporal Patterns Combining In Situ Continuous Fluorometry Measurements and Landsat 8/OLI Data across the Barataria Basin (Louisiana, USA)

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