Semi-analytical prediction of Secchi depth using remote-sensing reflectance for lakes with a wide range of turbidity

Fukushima, Takehiko; Matsushita, Bunkei; Oyama, Yoichi; Yoshimura, Kazuya; Yang, Wei; Terrel, Meylin Mirtha; Kawamura, Shimako; Takegahara, Akito

doi:10.1007/s10750-015-2584-7

Cited by 11 publications

(5 citation statements)

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“…For clear waters, we still used QAA_v5 because of its good performance in this type of waters (Lee et al, 2002;Fukushima et al, 2016). We adapted the maximum chlorophyll-a index (MCI) originally developed by Gower et al (2005) for switching the QAA_v5 and QAA_T.…”

Section: The Original Lee15 Algorithmmentioning

confidence: 99%

“…The constant requirement of in situ data for model recalibration will make the two empirical relationships the first important equations in these modified QAAs, and thus will limit their applicability in various waters. In contrast, QAA_T proposed by Yang et al (2013) does not include empirical equations for (λ) and (λ) retrievals, and thus it is the most proper algorithm to replace QAA_v6 for retrieving (λ) and (λ) in turbid waters (Yang et al, 2014(Yang et al, , 2015Fukushima et al, 2016).…”

Section: Necessity Of the Qaa_hybridmentioning

confidence: 99%

“…In contrast, the semi-analytical approach retrieves the ZSD based on an underwater visibility theory (Doron et al, 2011;Fukushima et al, 2016Fukushima et al, , 2018Alikas and Kratzer, 2017;Rodrigues et al, 2017). Compared to the empirical approach, the semi-analytical approach has two advantages: (1) a clearer mechanism and thus more reliable results; and (2) this approach often does not need in situ data for recalibrating the retrieval algorithm.…”

Section: Introductionmentioning

confidence: 99%

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An improved algorithm for estimating the Secchi disk depth from remote sensing data based on the new underwater visibility theory

Jiang

Matsushita

Setiawan

et al. 2019

ISPRS Journal of Photogrammetry and Remote Sensing

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The Secchi disk depth (ZSD) is a widely used parameter for evaluating water clarity. Here we propose an improved algorithm, which is based on a new underwater visibility theory, for retrieving more accurate ZSD from remote sensing reflectance (Rrs) in various waters. Two improvements were carried out in the new algorithm. First, we used a hybrid quasi-analytical algorithm (QAA_hybrid) instead of the sixth version of QAA (QAA_v6) for retrieving more accurate total absorption coefficient ( (λ)) and total backscattering coefficient ( (λ)) even in turbid inland waters. Second, we used a dynamic / ratio (i.e., ratio of diffuse attenuation coefficient of upwelling radiance and diffuse attenuation coefficient of downwelling irradiance) instead of using the fixed ratio (i.e., 1.5). The results obtained from in situ Rrs show that the improved ZSD estimation algorithm gave more accurate ZSD estimations, with the root mean square error (RMSE) reduced from 0.2 to 0.1 in log10 unit, mean absolute percentage error (MAPE) reduced from 39 % to 20 % (N=178 with in situ ZSD values between 0.3 -20.8 m). We then applied the improved ZSD estimation algorithm to the 2003-2012 MERIS images for Lake Kasumigaura to further confirm the performance of the improved ZSD estimation algorithm. The 2 results obtained from 19 matchups demonstrate that the estimated ZSD matched well with the in situ ZSD, with the RMSE of 0.11 m and the MAPE of 15%. The improved ZSD estimation algorithm shows a potential to estimate more accurate ZSD values from remote sensing data in various waters.

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Section: The Original Lee15 Algorithmmentioning

confidence: 99%

Section: Necessity Of the Qaa_hybridmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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An improved algorithm for estimating the Secchi disk depth from remote sensing data based on the new underwater visibility theory

Jiang

Matsushita

Setiawan

et al. 2019

ISPRS Journal of Photogrammetry and Remote Sensing

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“…Water transparency relates to the depth to which light will penetrate water and to photosynthesis changes in a specific waterbody over time; thus, it is key to thoroughly evaluating water quality [1][2][3][4][5][6][7][8][9]. Changes in water transparency can also be an indicator of a human threat to an ecosystem [10][11][12][13][14].…”

Section: Introductionmentioning

confidence: 99%

A Semianalytical Algorithm for Estimating Water Transparency in Different Optical Water Types from MERIS Data

2022

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Water transparency (or Secchi disk depth: ZSD) is a key parameter of water quality; thus, it is very important to routinely monitor. In this study, we made four efforts to improve a state-of-the-art ZSD estimation algorithm that was developed in 2019 on the basis of a new underwater visibility theory proposed in 2015. The four efforts were: (1) classifying all water into clear (Type I), moderately turbid (Type II), highly turbid (Type III), or extremely turbid (Type IV) water types; (2) selecting different reference wavelengths and corresponding semianalytical models for each water type; (3) employing an estimation model to represent reasonable shapes for particulate backscattering coefficients based on the water type classification; and (4) constraining likely wavelength range at which the minimum diffuse attenuation coefficient (Kdλ) will occur for each water type. The performance of the proposed ZSD estimation algorithm was compared to that of the original state-of-the-art algorithm using a simulated dataset (N = 91,287, ZSD values 0.01 to 44.68 m) and an in situ measured dataset (N = 305, ZSD values 0.3 to 16.4 m). The results showed a significant improvement with a reduced mean absolute percentage error (MAPE) from 116% to 65% for simulated data and from 32% to 27% for in situ data. Outliers in the previous algorithm were well addressed in the new algorithm. We further evaluated the developed ZSD estimation algorithm using medium resolution imaging spectrometer (MERIS) images acquired from Lake Kasumigaura, Japan. The results obtained from 19 matchups revealed that the estimated ZSD matched well with the in situ measured ZSD, with a MAPE of 15%. The developed ZSD estimation algorithm can probably be applied to different optical water types due to its semianalytical features.

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“…中国科学院国际合作重点项目(131C11KYSB20160061) [Foundation： National Basic Research Program of Ministry of Science and Technology (MOST)， China, No.2012FY111400; Strategic Priority Research Program of CAS, No.XDB03030000; Key Projects of International Cooperation of CAS, No.131C11KYSB20160061]。作者简介：刘翀(1992-)，男，江西南昌人，硕士研究生，研究方向为湖泊环境遥感应用， E-mail: liuchong@itpcas.ac.cn。通讯作者：朱立平(1965-)，男，河北唐山人，研究员，博导，从事青藏高原环境变化研究， E-mail: lpzhu@itpcas.ac.cn。Zhao et al, 2011;Knight et al, 2012;Fukushima et al, 2016; 马建行等, 2016)。借助遥感手段研究湖泊水…”

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基于modis的青藏高原湖泊透明度遥感反演

刘翀¹,

朱丽萍²,

王君波³

et al. 2017

Progress in Geography

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Semi-analytical prediction of Secchi depth using remote-sensing reflectance for lakes with a wide range of turbidity

Cited by 11 publications

References 50 publications

An improved algorithm for estimating the Secchi disk depth from remote sensing data based on the new underwater visibility theory

An improved algorithm for estimating the Secchi disk depth from remote sensing data based on the new underwater visibility theory

A Semianalytical Algorithm for Estimating Water Transparency in Different Optical Water Types from MERIS Data

基于modis的青藏高原湖泊透明度遥感反演

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