Measurement of Water Leaving Reflectance Using a Digital Camera Based on Multiple Reflectance Reference Cards

Gao, Min; Li, Junsheng; Zhang, Fang-Fang; Wang, Shenglei; Xie, Yichun; Yin, Zhipeng; Zhang, Bing

doi:10.3390/s20226580

Cited by 9 publications

(11 citation statements)

References 21 publications

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“…Validation campaigns have consistently found the radiance, R rs in the RGB bands, and hue angle from consumer cameras to be wellcorrelated with reference instruments, but often with a wide dispersion and a significant bias. For R rs , the mean difference between smartphone and reference match-up data is typically ≥ 0.003 sr −1 or ≥ 30%, but varies wildly between studies (Leeuw and Boss, 2018;Yang et al, 2018;Gao et al, 2020Gao et al, , 2022). As an extreme example, Malthus et al (2020) found no correlation at all between HydroColor and reference R rs data, albeit under challenging observing conditions.…”

Section: Introductionmentioning

confidence: 99%

“…Instead, in a process termed gamma correction or gamma compression, the radiance is scaled by a power law. The nonlinearity of JPEG data is a significant contributor to the uncertainty in R rs obtained from consumer cameras and apps such as HydroColor (Burggraaff et al, 2019;Gao et al, 2020;Malthus et al, 2020). Some approaches, including WACODI, attempt to correct for nonlinearity through an inverse gamma correction (Novoa et al, 2015;Gao et al, 2020).…”

Section: Introductionmentioning

confidence: 99%

“…The nonlinearity of JPEG data is a significant contributor to the uncertainty in R rs obtained from consumer cameras and apps such as HydroColor (Burggraaff et al, 2019;Gao et al, 2020;Malthus et al, 2020). Some approaches, including WACODI, attempt to correct for nonlinearity through an inverse gamma correction (Novoa et al, 2015;Gao et al, 2020). This inverse correction cannot be performed consistently because the smartphone JPEG processing differs between smartphone brands, models, and firmware versions (Burggraaff et al, 2019).…”

Section: Introductionmentioning

confidence: 99%

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Accuracy and Reproducibility of Above-Water Radiometry With Calibrated Smartphone Cameras Using RAW Data

Burggraaff

Werther²,

Boss³

et al. 2022

Front. Remote Sens.

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Consumer cameras, especially on smartphones, are popular and effective instruments for above-water radiometry. The remote sensing reflectance Rrs is measured above the water surface and used to estimate inherent optical properties and constituent concentrations. Two smartphone apps, HydroColor and EyeOnWater, are used worldwide by professional and citizen scientists alike. However, consumer camera data have problems with accuracy and reproducibility between cameras, with systematic differences of up to 40% in intercomparisons. These problems stem from the need, until recently, to use JPEG data. Lossless data, in the RAW format, and calibrations of the spectral and radiometric response of consumer cameras can now be used to significantly improve the data quality. Here, we apply these methods to above-water radiometry. The resulting accuracy in Rrs is around 10% in the red, green, and blue (RGB) bands and 2% in the RGB band ratios, similar to professional instruments and up to 9 times better than existing smartphone-based methods. Data from different smartphones are reproducible to within measurement uncertainties, which are on the percent level. The primary sources of uncertainty are environmental factors and sensor noise. We conclude that using RAW data, smartphones and other consumer cameras are complementary to professional instruments in terms of data quality. We offer practical recommendations for using consumer cameras in professional and citizen science.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Accuracy and Reproducibility of Above-Water Radiometry With Calibrated Smartphone Cameras Using RAW Data

Burggraaff

Werther²,

Boss³

et al. 2022

Front. Remote Sens.

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“…Location sensors (GPS) and cameras on board the mobile devices equip the citizens to collect geotagged data and store them. The use of smartphones and digital cameras in citizen science programmes are improving day by day, an example of which is the mobile application HydroColor that derives water leaving reflectance from digital images (Gao et al, 2020). Most of the citizen science programmes in hydrology from 2001 to 2018 seem to have focused on the monitoring of water quality (Njue et al, 2019), probably due to the increased global awareness on the deterioration of water quality plus the availability of low-cost kits to measure basic water quality variables.…”

Section: Introductionmentioning

confidence: 99%

Citizen Scientists Contribute to Real-Time Monitoring of Lake Water Quality Using 3D Printed Mini Secchi Disks

et al. 2021

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Citizen science aims to mobilise the general public, motivated by curiosity, to collect scientific data and contribute to the advancement of scientific knowledge. In this article, we describe a citizen science network that has been developed to assess the water quality in a 100 km long tropical lake-estuarine system (Vembanad Lake), which directly or indirectly influences the livelihood of around 1.6 million people. Deterioration of water quality in the lake has resulted in frequent outbreaks of water-associated diseases, leading to morbidity and occasionally, to mortality. Water colour and clarity are easily measurable and can be used to study water quality. Continuous observations on relevant spatial and temporal scales can be used to generate maps of water colour and clarity for identifying areas that are turbid or eutrophic. A network of citizen scientists was established with the support of students from 16 colleges affiliated with three universities of Kerala (India) and research institutions, and stakeholders such as houseboat owners, non-government organisations (NGOs), regular commuters, inland fishermen, and others residing in the vicinity of Vembanad Lake and keen to contribute. Mini Secchi disks, with Forel-Ule colour scale stickers, were used to measure the colour and clarity of the water. A mobile application, named “TurbAqua,” was developed for easy transmission of data in near-real time. In-situ data from scientists were used to check the quality of a subset of the citizen observations. We highlight the major economic benefits from the citizen network, with stakeholders voluntarily monitoring water quality in the lake at low cost, and the increased potential for sustainable monitoring in the long term. The data can be used to validate satellite products of water quality and can provide scientific information on natural or anthropogenic events impacting the lake. Citizens provided with scientific tools can make their own judgement on the quality of water that they use, helping toward Sustainable Development Goal 6 of clean water. The study highlights potential for world-wide application of similar citizen-science initiatives, using simple tools for generating long-term time series data sets, which may also help monitor climate change.

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“…Pitarch et al [ 9 ] has presented 15 years of the evaluation of hue angle and FUI through

of oceanic waters on a global scale. Gao et al [ 10 ] developed a method to estimate water leaving reflectance via digital imagery.…”

Section: Introductionmentioning

confidence: 99%

A Low-Cost Digital Colorimetry Setup to Investigate the Relationship between Water Color and Its Chemical Composition

Zeng

Mannaerts

Shang

2021

Sensors

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Developments in digital image acquisition technologies and citizen science lead to more water color observations and broader public participation in environmental monitoring. However, the implications of the use of these simple water color indices for water quality assessment have not yet been fully evaluated. In this paper, we build a low-cost digital camera colorimetry setup to investigate quantitative relationships between water color indices and concentrations of optically active constituents (OACs). As proxies for colored dissolved organic matter (CDOM) and phytoplankton, humic acid and algae pigments were used to investigate the relationship between water chromaticity and concentration. We found that the concentration fits an ascending relationship with xy chromaticity values and a descending relationship with hue angle. Our investigations permitted us to increase the information content of simple water color observations, by relating them to chemical constituent concentrations in observed waters.

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Measurement of Water Leaving Reflectance Using a Digital Camera Based on Multiple Reflectance Reference Cards

Cited by 9 publications

References 21 publications

Accuracy and Reproducibility of Above-Water Radiometry With Calibrated Smartphone Cameras Using RAW Data

Accuracy and Reproducibility of Above-Water Radiometry With Calibrated Smartphone Cameras Using RAW Data

Citizen Scientists Contribute to Real-Time Monitoring of Lake Water Quality Using 3D Printed Mini Secchi Disks

A Low-Cost Digital Colorimetry Setup to Investigate the Relationship between Water Color and Its Chemical Composition

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