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Selecting the Best Band Ratio to Estimate Chlorophyll-a Concentration in a Tropical Freshwater Lake Using Sentinel 2A Images from a Case Study of Lake Ba Be (Northern Vietnam)

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TLDR
The results confirmed the potential of S2A to be used as a free tool for lake monitoring and research due to high spatial resolution data (10 m pixel size) and the small error between in situ Chla, and estimated Chla from S 2A acquired concurrently, confirmed the S2C green-red band ratio as the most suitable option for monitoring Chla in Lake Ba Be water.
Abstract
This study aims to develop a method to estimate chlorophyll-a concentration (Chla) in tropical freshwater lake waters using in situ data of Chla, water reflectance, and concurrent Sentinel 2A MSI imagery (S2A) over Lake Ba Be, a Ramsar site and the largest natural freshwater lake in Vietnam. Data from 30 surveyed sampling sites over the lake water in June 2016 and May 2017 demonstrated the appropriateness of S2A green-red band ratio (band 3 versus band 4) for estimating Chla. This was shown through a strong correlation of corresponded field measured reflectance ratio with Chla by an exponential curve (r2 = 0.68; the mean standard error of the estimates corresponding to 5% of the mean value of in situ Chla). The small error between in situ Chla, and estimated Chla from S2A acquired concurrently, confirmed the S2A green-red band ratio as the most suitable option for monitoring Chla in Lake Ba Be water. Resultant Chla distribution maps over time described a partially-seasonal pattern and also displayed the spatial dynamic of Chla in the lake. This allows a better understanding of the lake’s limnological processes to be developed and provides an insight into the factors that affect lake water quality. The results also confirmed the potential of S2A to be used as a free tool for lake monitoring and research due to high spatial resolution data (10 m pixel size).

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Citations
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Journal ArticleDOI

Simultaneous retrieval of selected optical water quality indicators from Landsat-8, Sentinel-2, and Sentinel-3

TL;DR: In this paper , a machine-learning model was developed for retrieval of water quality indicators from multi-source satellite imagery, including chlorophyll-a (Chl a ), Total Suspended Solids (TSS), and absorption by Colored Dissolved Organic Matter at 440 nm ( a cdom (440)), across a wide array of aquatic ecosystems.
Journal ArticleDOI

An UAV and Satellite Multispectral Data Approach to Monitor Water Quality in Small Reservoirs

TL;DR: The results show a moderately good agreement among the three sensors at different spatial resolutions, indicating a high potential for the development of a multi-platform and multi-sensor approach for the eutrophication monitoring of small reservoirs.
Journal ArticleDOI

Monitoring the Water Quality of Small Water Bodies Using High-Resolution Remote Sensing Data

TL;DR: The findings of this study emphasize the use of both high-resolution remote sensing imagery and red-edge portion of the electromagnetic spectrum for monitoring several water quality parameters in small water areas.
Journal ArticleDOI

Improved red-edge chlorophyll-a detection for Sentinel 2

TL;DR: In this paper, an improved version of a semi-analytical chl-a retrieval algorithm using a variable a* model has been presented, which is the result of replacing a fixed chla specific absorption coefficient (a*) with a variable model.
Journal ArticleDOI

Hybrid Chlorophyll-a Algorithm for Assessing Trophic States of a Tropical Brazilian Reservoir Based on MSI/Sentinel-2 Data

TL;DR: OHA proved to be a viable method for estimating chl-a concentration in Ibitinga Reservoir and the extension of this framework allowed a more precise chL-a estimate in eutrophic inland waters.
References
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Journal ArticleDOI

A trophic state index for lakes1

TL;DR: A numerical trophic state index for lakes has been developed that incorporates most lakes in a scale of 0 to 100, which represents a doubling in algal biomass as well as various measures of biomass or production.
Journal ArticleDOI

Ocean Color Chlorophyll Algorithms for SEAWIFS

TL;DR: In this article, a large data set containing coincident in situ chlorophyll and remote sensing reflectance measurements was used to evaluate the accuracy, precision, and suitability of a wide variety of ocean color algorithms for use by SeaWiFS (Sea-viewing Wide Field-of-view Sensor).
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An improved dark-object subtraction technique for atmospheric scattering correction of multispectral data

TL;DR: In this paper, an improved dark-object subtraction technique is demonstrated that allows the user to select a relative atmospheric scattering model to predict the haze values for all the spectral bands from a selected starting band haze value.
Journal ArticleDOI

Estimation of the remote-sensing reflectance from above-surface measurements.

Curtis D. Mobley
- 20 Dec 1999 - 
TL;DR: If rho is not estimated accurately, significant errors can occur in the estimated R(rs) for near-zenith Sun positions and for high wind speeds, both of which can give considerable Sun glitter effects.
Journal ArticleDOI

The use of the empirical line method to calibrate remotely sensed data to reflectance

TL;DR: In this article, it is suggested that the empirical line method allows the calibration of remotely sensed data to reflectance with errors of only a few percent, with theoretical assumptions and practical considerations should be taken into account before applying this approach.
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