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Journal articles on the topic 'Bio-optical model'

Author: Grafiati

Published: 4 June 2021

Last updated: 10 February 2022

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1

Shulman, Igor, Sergey Frolov, Stephanie Anderson, Brad Penta, Rick Gould, Peter Sakalaukus, and Sherwin Ladner. "Impact of bio-optical data assimilation on short-term coupled physical, bio-optical model predictions." Journal of Geophysical Research: Oceans 118, no. 4 (April 2013): 2215–30. http://dx.doi.org/10.1002/jgrc.20177.

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2

Arrigo, Kevin R., Cornelius W. Sullivan, and James N. Kremer. "A bio-optical model of Antarctic sea ice." Journal of Geophysical Research 96, no. C6 (1991): 10581. http://dx.doi.org/10.1029/91jc00455.

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3

Kostakis, I., R. Röttgers, A. Orkney, H. A. Bouman, M. Porter, F. Cottier, J. Berge, and D. McKee. "Development of a bio-optical model for the Barents Sea to quantitatively link glider and satellite observations." Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences 378, no. 2181 (August 31, 2020): 20190367. http://dx.doi.org/10.1098/rsta.2019.0367.

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A bio-optical model for the Barents Sea is determined from a set of in situ observations of inherent optical properties (IOPs) and associated biogeochemical analyses. The bio-optical model provides a pathway to convert commonly measured parameters from glider-borne sensors (CTD, optical triplet sensor—chlorophyll and CDOM fluorescence, backscattering coefficients) to bulk spectral IOPs (absorption, attenuation and backscattering). IOPs derived from glider observations are subsequently used to estimate remote sensing reflectance spectra that compare well with coincident satellite observations, providing independent validation of the general applicability of the bio-optical model. Various challenges in the generation of a robust bio-optical model involving dealing with partial and limited quantity datasets and the interpretation of data from the optical triplet sensor are discussed. Establishing this quantitative link between glider-borne and satellite-borne data sources is an important step in integrating these data streams and has wide applicability for current and future integrated autonomous observation systems. This article is part of the theme issue ‘The changing Arctic Ocean: consequences for biological communities, biogeochemical processes and ecosystem functioning’.

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4

Örek, H., R. Doerffer, R. Röttgers, M. Boersma, and K. H. Wiltshire. "A bio-optical model for remote sensing of Lena water." Biogeosciences Discussions 10, no. 3 (March 11, 2013): 4887–925. http://dx.doi.org/10.5194/bgd-10-4887-2013.

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Abstract. Bio-optical measurements and sampling were carried out in the delta of the Lena River (Northern Siberia, Russia) during the high water run-off period between 26 June 2011 and 4 July 2011. The aim of this study was to determine the inherent optical properties of the Lena water, i.e. absorption, attenuation and scattering coefficients, during the period of maximum run-off. In this context CDOM (Colored Dissolved Organic Matter), total particle absorption, total suspended matter and phytoplankton-pigments were measured. CDOM was found to be the most dominant parameter affecting the optical properties of the river, with an absorption coefficient of 4.5–5 m−1 at 442 nm, which was almost four times higher than total particle absorption values at visible wavelength range during the first week of the campaign. This difference decreased over the following days when Total Suspended Matter (TSM) concentration increased. The wavelength dependent absorption spectra of the water constituents were characterized by determining the semi logarithmic spectral slope. Mean CDOM, and Detritus slopes, were 0.0149 nm−1(stdev = 0.0003, n = 18), and 0.0057 nm−1 (stdev = 0.0017, n = 19), respectively, values which are typical for water bodies with high concentrations of dissolved and particulate carbon. Mean total chlorophyll a, and total suspended matter, were also measured to determine the relationship between concentrations and optical properties. Mean chlorophyll a and total suspended matter were 1.821 mg m−3 (stdev = 0.734 n = 18) and 31.89 mg L−1 (stdev = 19.94) respectively. The light penetration depth (Secchi disc depth) was highly correlated with the suspended matter concentration with a maximum of 90 cm. We conclude that the bio-optical properties of the Lena River are rather complex because of the high CDOM and variable particle load which may change within a matter of days. Furthermore, the chlorophyll concentration constitutes a small fraction. Our results will improve the remote sensing protocols of the river and coastal waters in and around the Lena Delta and serve as a basis for characterizing the light climate with respect to primary production.

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Bengil, Fethi, David McKee, Sükrü T. Beşiktepe, Violeta Sanjuan Calzado, and Charles Trees. "A bio-optical model for integration into ecosystem models for the Ligurian Sea." Progress in Oceanography 149 (December 2016): 1–15. http://dx.doi.org/10.1016/j.pocean.2016.10.007.

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6

Jalbuena, R. L., A. C. Blanco, A. Manuel, R. R. Sta. Ana, and J. A. Santos. "BIO OPTICAL MODELLING OF LAGUNA LAKE USING BOMBER TOOL AND WASI-DERIVED INVERTED PARAMETERS." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-4/W16 (October 1, 2019): 277–82. http://dx.doi.org/10.5194/isprs-archives-xlii-4-w16-277-2019.

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Abstract. Laguna Lake is significant to its surrounding cities and municipalities as it serves multiple purposes: flood basin, aquaculture, water source for irrigation and domestic use, among others. Monitoring the lake’s water quality is an integral part ensuring that the lake would continue to serve its purposes. Bio-optical modelling is a type of empirical model that relates the inherent optical properties of water to different biological properties like chlorophyll-a. The BOMBER (Bio-Optical Model Based tool for Estimating water quality and bottom properties from Remote sensing images) tool makes use of the different IOPs apparent optical properties (AOPs) of satellite images to be able to produce water quality maps. To localize the parameters used by the BOMBER tool, the use of WASI (The Water Color Simulator) tool was introduced. Inverting in situ spectral measurements of the lake, WASI tool was able to produce parameters localized for the lake. This research used 2018 Landsat 8 Images to produce images and used a water profiler to validate results. Results show the bio-optical model provided a R-squared value of 0.6912 and an RMSE of 2.43 μg/l which shows good correlation between the in-situ and the bio-optical model results.

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7

Örek, H., R. Doerffer, R. Röttgers, M. Boersma, and K. H. Wiltshire. "Contribution to a bio-optical model for remote sensing of Lena River water." Biogeosciences 10, no. 11 (November 8, 2013): 7081–94. http://dx.doi.org/10.5194/bg-10-7081-2013.

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Abstract. Bio-optical measurements and sampling were carried out in the delta of the Lena River (northern Siberia, Russia) between 26 June and 4 July 2011. The aim of this study was to determine the inherent optical properties of the Lena water, i.e., absorption, attenuation, and scattering coefficients, during the period of maximum runoff. This aimed to contribute to the development of a bio-optical model for use as the basis for optical remote sensing of coastal water of the Arctic. In this context the absorption by CDOM (colored dissolved organic matter) and particles, and the concentrations of total suspended matter, phytoplankton-pigments, and carbon were measured. CDOM was found to be the most dominant parameter affecting the optical properties of the river, with an absorption coefficient of 4.5–5 m−1 at 442 nm, which was almost four times higher than total particle absorption values at visible wavelength range. The wavelenght-dependence of absorption of the different water constituents was chracterized by determining the semi logarithmic spectral slope. Mean CDOM, and detritus slopes were 0.0149 nm−1(standard deviation (stdev) = 0.0003, n = 18), and 0.0057 nm−1 (stdev = 0.0017, n = 19), respectively, values which are typical for water bodies with high concentrations of dissolved and particulate carbon. Mean chlorophyll a and total suspended matter were 1.8 mg m−3 (stdev = 0.734 n = 18) and 31.9 g m−3 (stdev = 19.94, n = 27), respectively. DOC (dissolved organic carbon) was in the range 8–10 g m−3 and the total particulate carbon (PC) in the range 0.25–1.5 g m−3. The light penetration depth (Secchi disc depth) was in the range 30–90 cm and was highly correlated with the suspended matter concentration. The period of maximum river runoff in June was chosen to obtain bio-optical data when maximum water constituents are transported into the Laptev Sea. However, we are aware that more data from other seasons and other years need to be collected to establish a general bio-optical model of the Lena water and conclusively characterize the light climate with respect to primary production.

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8

Gao, Meng, Peng-Wang Zhai, Bryan A. Franz, Yongxiang Hu, Kirk Knobelspiesse, P. Jeremy Werdell, Amir Ibrahim, Brian Cairns, and Alison Chase. "Inversion of multiangular polarimetric measurements over open and coastal ocean waters: a joint retrieval algorithm for aerosol and water-leaving radiance properties." Atmospheric Measurement Techniques 12, no. 7 (July 17, 2019): 3921–41. http://dx.doi.org/10.5194/amt-12-3921-2019.

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Abstract. Ocean color remote sensing is a challenging task over coastal waters due to the complex optical properties of aerosols and hydrosols. In order to conduct accurate atmospheric correction, we previously implemented a joint retrieval algorithm, hereafter referred to as the Multi-Angular Polarimetric Ocean coLor (MAPOL) algorithm, to obtain the aerosol and water-leaving signal simultaneously. The MAPOL algorithm has been validated with synthetic data generated by a vector radiative transfer model, and good retrieval performance has been demonstrated in terms of both aerosol and ocean water optical properties (Gao et al., 2018). In this work we applied the algorithm to airborne polarimetric measurements from the Research Scanning Polarimeter (RSP) over both open and coastal ocean waters acquired in two field campaigns: the Ship-Aircraft Bio-Optical Research (SABOR) in 2014 and the North Atlantic Aerosols and Marine Ecosystems Study (NAAMES) in 2015 and 2016. Two different yet related bio-optical models are designed for ocean water properties. One model aligns with traditional open ocean water bio-optical models that parameterize the ocean optical properties in terms of the concentration of chlorophyll a. The other is a generalized bio-optical model for coastal waters that includes seven free parameters to describe the absorption and scattering by phytoplankton, colored dissolved organic matter, and nonalgal particles. The retrieval errors of both aerosol optical depth and the water-leaving radiance are evaluated. Through the comparisons with ocean color data products from both in situ measurements and the Moderate Resolution Imaging Spectroradiometer (MODIS), and the aerosol product from both the High Spectral Resolution Lidar (HSRL) and the Aerosol Robotic Network (AERONET), the MAPOL algorithm demonstrates both flexibility and accuracy in retrieving aerosol and water-leaving radiance properties under various aerosol and ocean water conditions.

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9

Shengqiang, WANG, CHEN Jin, YANG Wei, LIANG Hanwei, and ZHU Jingjing. "Accuracy assessment of bio-optical model in turbid case Ⅱ waters." Journal of Lake Sciences 23, no. 2 (2011): 217–22. http://dx.doi.org/10.18307/2011.0209.

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10

Zainol, Farrah Dilla, Nopparat Thammawongsa, Somsak Mitatha, Jalil Ali, and Preecha Yupapin. "Nerve communication model by bio-cells and optical dipole coupling effects." Artificial Cells, Nanomedicine, and Biotechnology 41, no. 6 (January 10, 2013): 368–75. http://dx.doi.org/10.3109/21691401.2012.759124.

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11

HUANG, Chang-Chun, Yun-Mei LI, Qiao WANG, Heng LV, and De-Yong SUN. "Suspended particle matter and chlorophyll-a universal bio-optical retrieval model." Journal of Infrared and Millimeter Waves 32, no. 5 (2013): 462. http://dx.doi.org/10.3724/sp.j.1010.2013.00462.

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12

Magnuson, Andrea, Lawrence W. Harding, Michael E. Mallonee, and Jason E. Adolf. "Bio-optical model for Chesapeake Bay and the Middle Atlantic Bight." Estuarine, Coastal and Shelf Science 61, no. 3 (November 2004): 403–24. http://dx.doi.org/10.1016/j.ecss.2004.06.020.

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13

Yap, Yee Ling, Yong Sheng Edgar Tan, Heang Kuan Joel Tan, Zhen Kai Peh, Xue Yi Low, Wai Yee Yeong, Colin Siang Hui Tan, and Augustinus Laude. "3D printed bio-models for medical applications." Rapid Prototyping Journal 23, no. 2 (March 20, 2017): 227–35. http://dx.doi.org/10.1108/rpj-08-2015-0102.

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Purpose The design process of a bio-model involves multiple factors including data acquisition technique, material requirement, resolution of the printing technique, cost-effectiveness of the printing process and end-use requirements. This paper aims to compare and highlight the effects of these design factors on the printing outcome of bio-models. Design/methodology/approach Different data sources including engineering drawing, computed tomography (CT), and optical coherence tomography (OCT) were converted to a printable data format. Three different bio-models, namely, an ophthalmic model, a retina model and a distal tibia model, were printed using two different techniques, namely, PolyJet and fused deposition modelling. The process flow and 3D printed models were analysed. Findings The data acquisition and 3D printing process affect the overall printing resolution. The design process flows using different data sources were established and the bio-models were printed successfully. Research limitations/implications Data acquisition techniques contained inherent noise data and resulted in inaccuracies during data conversion. Originality/value This work showed that the data acquisition and conversion technique had a significant effect on the quality of the bio-model blueprint and subsequently the printing outcome. In addition, important design factors of bio-models were highlighted such as material requirement and the cost-effectiveness of the printing technique. This paper provides a systematic discussion for future development of an engineering design process in three-dimensional (3D) printed bio-models.

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14

Zhang, XiaoXian, XiaoFeng Han, FuGen Wu, Joshua Jasensky, and Zhan Chen. "Nano-bio interfaces probed by advanced optical spectroscopy: From model system studies to optical biosensors." Chinese Science Bulletin 58, no. 21 (March 2, 2013): 2537–56. http://dx.doi.org/10.1007/s11434-013-5700-y.

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15

Terzić, Elena, Paolo Lazzari, Emanuele Organelli, Cosimo Solidoro, Stefano Salon, Fabrizio D'Ortenzio, and Pascal Conan. "Merging bio-optical data from Biogeochemical-Argo floats and models in marine biogeochemistry." Biogeosciences 16, no. 12 (July 1, 2019): 2527–42. http://dx.doi.org/10.5194/bg-16-2527-2019.

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Abstract. New autonomous robotic platforms for observing the ocean, i.e. Biogeochemical-Argo (BGC-Argo) floats, have drastically increased the number of vertical profiles of irradiance, photosynthetically available radiation (PAR), and algal chlorophyll concentrations around the globe independent of the season. Such data may therefore be a fruitful resource to improve performances of numerical models for marine biogeochemistry. Here we present a work that integrates 1314 vertical profiles of PAR acquired by 31 BGC-Argo floats operated in the Mediterranean Sea between 2012 and 2016 into a one-dimensional model to simulate the vertical and temporal variability of algal chlorophyll concentrations. The model was initially forced with PAR measurements to assess its skill when using quality-controlled light profiles, and subsequently with a number of alternative bio-optical models to analyse the model capability when light observations are not available. Model outputs were evaluated against co-located chlorophyll profiles measured by BGC-Argo floats. Results highlight that the data-driven model is able to reproduce the spatial and temporal variability of deep chlorophyll maxima depth observed at a number of Mediterranean sites well. Further, we illustrate the key role of PAR and vertical mixing in shaping the vertical dynamics of primary producers in the Mediterranean Sea. The comparison of alternative bio-optical models identifies the best simple one to be used, and suggests that model simulations benefit from considering the diel cycle.

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Benazzouz, Aïssa, Khalid El Had, Hassan Mabchour, Samira Mellass, and Hervé Demarcq. "Potential Roles Of Eddy Kenetic Energy And Turbulence In Controlling The Bio-optical Ocean Proprieties." E3S Web of Conferences 279 (2021): 04001. http://dx.doi.org/10.1051/e3sconf/202127904001.

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In the Canary Current System (CCS), coherent structures and concurrent movements of surface waters such as meanders, filaments and eddies strongly control the ocean bio-optical proprieties response to the coastal upwelling process. One of the outstanding problems is to understand the mechanisms of the bio-optical proprieties transfer and the connection mechanism between the coastal band and the ocean interior. We use a combination of satellite data and derived mesoscale indicators to provide a comprehensive view of the relationship between the physical and bio-optical proprieties off Moroccan upwelling region (part of the CCS) in terms of wind impulse responsible of sea turbulence, sea surface temperature (SST) response of the wind stress and ocean color proprieties considered as bio-optical ocean proxy response. To optimize the predicted ranges of these parameters, Generalized Additive Model (GAM) was applied. We conclude that the energetic mesoscales structures as seen from the satellite climatology observations can provide insight into dominant transport pathways controlling the bio-optical exchange from the coastal area to the ocean interior structured as an oceanic corridor connecting the Moroccan area to the Canary archipelagos.

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SAKUNO, Yuji, and Takuma MIAKE. "Turbid Ocean Color Reproduction on the Coral Reef using Bio-optical Model." Journal of Japan Society of Civil Engineers, Ser. B2 (Coastal Engineering) 69, no. 2 (2013): I_1131—I_1135. http://dx.doi.org/10.2208/kaigan.69.i_1131.

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18

Gould, Richard W., Sean C. McCarthy, Emanuel Coelho, Igor Shulman, and James G. Richman. "Combining satellite ocean color and hydrodynamic model uncertainties in bio-optical forecasts." Journal of Applied Remote Sensing 8, no. 1 (April 3, 2014): 083652. http://dx.doi.org/10.1117/1.jrs.8.083652.

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19

Churnside, James H. "Bio-optical model to describe remote sensing signals from a stratified ocean." Journal of Applied Remote Sensing 9, no. 1 (November 6, 2015): 095989. http://dx.doi.org/10.1117/1.jrs.9.095989.

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20

Bernardo, Nariane, Alisson do Carmo, Edward Park, and Enner Alcântara. "Retrieval of Suspended Particulate Matter in Inland Waters with Widely Differing Optical Properties Using a Semi-Analytical Scheme." Remote Sensing 11, no. 19 (September 30, 2019): 2283. http://dx.doi.org/10.3390/rs11192283.

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Suspended particulate matter (SPM) directly affects the underwater light field and, as a consequence, changes the water clarity and can reduce the primary production. Remote sensing-based bio-optical modeling can provide efficient monitoring of the spatiotemporal dynamics of SPM in inland waters. In this paper, we present a novel and robust bio-optical model to retrieve SPM concentrations for inland waters with widely differing optical properties (the Tietê River Cascade System (TRCS) in Brazil). In this system, high levels of Chl-a concentration of up to 700 mg/m3, turbidity up to 80 NTU and high CDOM absorption highly complicate the optical characteristics of the surface water, imposing an additional challenge in retrieving SPM concentration. Since Kd is not susceptible to the saturation issue encountered when using remote sensing reflectance (Rrs), we estimate SPM concentrations via Kd. Kd was derived analytically from inherent optical properties (IOPs) retrieved through a re-parameterized quasi-analytical algorithm (QAA) that yields relevant accuracy. Our model improved the estimates of the IOPs by up to 30% when compared to other existing QAAs. Our developed bio-optical model using Kd(655) was capable of describing 74% of SPM variations in the TRCS, with average error consistently lower than 30%.

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21

Wolk, Fabian, Hidekatsu Yamazaki, Hua Li, and Rolf G. Lueck. "Calibrating the Spatial Response of Bio-Optical Sensors." Journal of Atmospheric and Oceanic Technology 23, no. 3 (March 1, 2006): 511–16. http://dx.doi.org/10.1175/jtech1863.1.

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Abstract This article describes an experimental method used to establish the spatial wavenumber response of in situ fluorometers. The method is applied to a fluorometer developed to measure the structure of the fluorescence field at high spatial wavenumbers. This fluorometer detects fluorescence variations on centimeter scales by creating a sampling volume in the undisturbed flow region, outside of the sensor housing. The sampling volume is created by intersecting beams of blue excitation light. To establish the size of the sampling volume and the amount of spatial averaging, the fluorometer and a fast response thermistor are towed repeatedly through a warm, fluorescent plume in a tow tank. The ratio of the measured fluorescence and temperature spectrum determines the wavenumber response of the fluorometer. The measured spectral ratio is well described by the transfer function of a first-order, low-pass filter with a half-power point at 22 cpm. The equivalent spatial resolution is 7 mm. The transfer function model can be used to correct measured fluorescence spectra for the limited wavenumber response of the sensor.

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22

Lv, Dong Yue, Zhi Pei Huang, Li Xin Sun, Neng Hai Yu, and Jian Kang Wu. "Model-Based Golf Swing Reconstruction." Applied Mechanics and Materials 530-531 (February 2014): 919–27. http://dx.doi.org/10.4028/www.scientific.net/amm.530-531.919.

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To increase the efficiency of golf training, 3D swing reconstruction is broadly used among golf researchers. Traditional reconstruction methods apply motion capture system (MOCAP) to gain golfers motion data and drive bio-mechanical model directly. The cost of MOCAP system restricts the application area of golf research and the reconstruction quality of swing relies on the accuracy of the motion data. We introduced the dynamical analysis into swing reconstruction and proposed a Dynamic Bayesian Network (DBN) model with Kinect to capture the swing motion. Our model focused on modeling the bio-mechanical and dynamical relationships between key joints of golfer during swing. The positions of key joints were updated by the model and were used as motion data to reconstruct golf swing. Experimental results show that our results are comparable with the ones acquired by optical MOCAP system in accuracy and can reconstruct the golf swing with much lower cost.

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23

HUANG, Chang-Chun, Yun-Mei LI, Qiao WANG, Heng LV, De-Yong SUN, and Cheng-Feng LE. "Bio-optical retrieval model of suspended particles in Tai Lake using MERIS image." JOURNAL OF INFRARED AND MILLIMETER WAVES 31, no. 4 (September 13, 2012): 367–74. http://dx.doi.org/10.3724/sp.j.1010.2012.00367.

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Maritorena, Stéphane, and David A. Siegel. "Consistent merging of satellite ocean color data sets using a bio-optical model." Remote Sensing of Environment 94, no. 4 (February 2005): 429–40. http://dx.doi.org/10.1016/j.rse.2004.08.014.

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25

Campbell, Janet W. "The lognormal distribution as a model for bio-optical variability in the sea." Journal of Geophysical Research 100, no. C7 (1995): 13237. http://dx.doi.org/10.1029/95jc00458.

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Manuel, A., A. C. Blanco, A. M. Tamondong, R. Jalbuena, O. Cabrera, and P. Gege. "OPTMIZATION OF BIO-OPTICAL MODEL PARAMETERS FOR TURBID LAKE WATER QUALITY ESTIMATION USING LANDSAT 8 AND WASI-2D." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-3/W11 (February 14, 2020): 67–72. http://dx.doi.org/10.5194/isprs-archives-xlii-3-w11-67-2020.

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Abstract. Laguna Lake, the Philippines’ largest freshwater lake, has always been historically, economically, and ecologically significant to the people living near it. However, as it lies at the center of urban development in Metro Manila, it suffers from water quality degradation. Water quality sampling by current field methods is not enough to assess the spatial and temporal variations of water quality in the lake. Regular water quality monitoring is advised, and remote sensing addresses the need for a synchronized and frequent observation and provides an efficient way to obtain bio-optical water quality parameters. Optimization of bio-optical models is done as local parameters change regionally and seasonally, thus requiring calibration. Field spectral measurements and in-situ water quality data taken during simultaneous satellite overpass were used to calibrate the bio-optical modelling tool WASI-2D to get estimates of chlorophyll-a concentration from the corresponding Landsat-8 images. The initial output values for chlorophyll-a concentration, which ranges from 10–40 μg/L, has an RMSE of up to 10 μg/L when compared with in situ data. Further refinements in the initial and constant parameters of the model resulted in an improved chlorophyll-a concentration retrieval from the Landsat-8 images. The outputs provided a chlorophyll-a concentration range from 5–12 μg/L, well within the usual range of measured values in the lake, with an RMSE of 2.28 μg/L compared to in situ data.

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Cherukuru, Nagur, Patrick Martin, Nivedita Sanwlani, Aazani Mujahid, and Moritz Müller. "A Semi-Analytical Optical Remote Sensing Model to Estimate Suspended Sediment and Dissolved Organic Carbon in Tropical Coastal Waters Influenced by Peatland-Draining River Discharges off Sarawak, Borneo." Remote Sensing 13, no. 1 (December 30, 2020): 99. http://dx.doi.org/10.3390/rs13010099.

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Coastal water quality degradation is a global challenge. Marine pollution due to suspended sediments and dissolved matter impacts water colour, biogeochemistry, benthic habitats and eventually human populations that depend on marine resources. In Sarawak (Malaysian Borneo), peatland-draining river discharges containing suspended sediments and dissolved organic carbon influence coastal water quality at multiple locations along the coast. Optical remote sensing is an effective tool to monitor coastal waters over large areas and across remote geographic locations. However, the lack of regional optical measurements and inversion models limits the use of remote sensing observations for water quality monitoring in Sarawak. To overcome this limitation, we have (1) compiled a regional spectral optical library for Sarawak coastal waters, (2) developed a new semi-analytical remote sensing model to estimate suspended sediment and dissolved organic carbon in coastal waters, and (3) demonstrated the application of our remote sensing inversion model on satellite data over Sarawak. Bio-optical data analysis revealed that there is a clear spatial variability in the inherent optical properties of particulate and dissolved matter in Sarawak. Our optical inversion model coupled with the Sarawak spectral optical library performed well in retrieving suspended sediment (bias = 3% and MAE = 5%) and dissolved organic carbon (bias = 3% and MAE = 8%) concentrations. Demonstration products using MODIS Aqua data clearly showed the influence of large rivers such as the Rajang and Lupar in discharging suspended sediments and dissolved organic carbon into coastal waters. The bio-optical parameterisation, optical model, and remote sensing inversion approach detailed here can now help improve monitoring and management of coastal water quality in Sarawak.

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Huang, Changchun, Yunmei Li, Hao Yang, Junsheng Li, Xia Chen, Deyong Sun, Chengfeng Le, Jun Zou, and Liangjiang Xu. "Assessment of water constituents in highly turbid productive water by optimization bio-optical retrieval model after optical classification." Journal of Hydrology 519 (November 2014): 1572–83. http://dx.doi.org/10.1016/j.jhydrol.2014.09.007.

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29

Zhang, Kexin, Wei Li, Hans Eide, and Knut Stamnes. "A bio-optical model suitable for use in forward and inverse coupled atmosphere–ocean radiative transfer models." Journal of Quantitative Spectroscopy and Radiative Transfer 103, no. 2 (January 2007): 411–23. http://dx.doi.org/10.1016/j.jqsrt.2006.08.009.

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Guo Yulong, 郭宇龙, 王永波 Wang Yongbo, 李云梅 Li Yunmei, 王桥 Wang Qiao, 朱利 Zhu Li, and 吕恒 Lü Heng. "Research of Multi-Source Water Remote Image Fusion Algorithm Based on Bio-Optical Model." Acta Optica Sinica 35, no. 4 (2015): 0410001. http://dx.doi.org/10.3788/aos201535.0410001.

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31

Semovski, S. V. "The Baltic Sea and Lake Baikal underwater bio-optical fields simulation using ecodynamical model." Ecological Modelling 116, no. 2-3 (March 1999): 149–63. http://dx.doi.org/10.1016/s0304-3800(98)00171-9.

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32

Holinde, L., and O. Zielinski. "Bio-optical characterization and light availability parameterization in Uummannaq Fjord and Vaigat–Disko Bay (West Greenland)." Ocean Science 12, no. 1 (January 15, 2016): 117–28. http://dx.doi.org/10.5194/os-12-117-2016.

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Abstract. This study investigated the bio-optical conditions of Uummannaq Fjord and Vaigat–Disko Bay, two neighboring, semi-enclosed coastal systems in West Greenland. Though close to each other, the systems differ in their hydrographic structure influencing the bio-optical conditions and, subsequently, the biological activities. Both systems showed high inorganic suspended particulate matter (SPMi) concentrations near river runoff or meltwater influxes (max. of 15.28 mg L−1 at the surface) and low colored dissolved organic matter (aCDOM@350nm, < 1.50 m−1) abundance throughout the systems. High chlorophyll levels (as an indicator of phytoplankton biomass) were measured in the Vaigat (max. of 11.44 µg L−1), which represents the outflow arm of Disko Bay. Light penetration depth as indicated by the 1 % depth of photosynthetically available radiation (PAR) was dominated by chlorophyll and SPMi alike, ranging from 12.2 to 41.2 m. Based on these characteristics, an effective two-component parameterization for the diffuse attenuation coefficient kPAR was developed in order to model light penetration depth as a relevant factor for bio-optical studies in Arctic environments under glacial meltwater influence.

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Qin, G., Y. C. Ding, Ya Xiong Liu, R. K. Du, and X. P. Qi. "Fabrication of Customized Bio-Electrode for Neural Stimulation Using Rapid Prototyping Technique." Materials Science Forum 626-627 (August 2009): 375–80. http://dx.doi.org/10.4028/www.scientific.net/msf.626-627.375.

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In the treatment of disorders, bio-electrodes are used to be implanted into the patients’ deep brain for long-term stimulation. This paper presents a custom design and flexible fabrication process of bio-electrode for treating neural disorders using rapid prototyping (RP) technique. A 3D model of the bio-electrode is designed and the photosensitive resin electrode prototype is fabricated on the laser rapid prototyping machine, and then the bio-electrode is fabricated using this electrode prototype and the silicon rubber mold and winding technique. The spatial distribution of the electric field fabricated of the bio-electrode is analyzed, and the optical photomicrograph reveals that the cylindrical surfaces of the polyurethane of the bio-electrode have smooth surface and no visible microcracks, and the spiral lines are arranged densely and have no defects of loose and falling and partly protruding. The electrochemical experiments show that the electrochemical process of the bio-electrode is reversible and the bio-electrode has good functionality and stability property.

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Roy, Shovonlal, Shubha Sathyendranath, and Trevor Platt. "Retrieval of phytoplankton size from bio-optical measurements: theory and applications." Journal of The Royal Society Interface 8, no. 58 (November 17, 2010): 650–60. http://dx.doi.org/10.1098/rsif.2010.0503.

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The absorption coefficient of a substance distributed as discrete particles in suspension is less than that of the same material dissolved uniformly in a medium—a phenomenon commonly referred to as the flattening effect. The decrease in the absorption coefficient owing to flattening effect depends on the concentration of the absorbing pigment inside the particle, the specific absorption coefficient of the pigment within the particle, and on the diameter of the particle, if the particles are assumed to be spherical. For phytoplankton cells in the ocean, with diameters ranging from less than 1 µm to more than 100 µm, the flattening effect is variable, and sometimes pronounced, as has been well documented in the literature. Here, we demonstrate how the in vivo absorption coefficient of phytoplankton cells per unit concentration of its major pigment, chlorophyll a , can be used to determine the average cell size of the phytoplankton population. Sensitivity analyses are carried out to evaluate the errors in the estimated diameter owing to potential errors in the model assumptions. Cell sizes computed for field samples using the model are compared qualitatively with indirect estimates of size classes derived from high performance liquid chromatography data. Also, the results are compared quantitatively against measurements of cell size in laboratory cultures. The method developed is easy-to-apply as an operational tool for in situ observations, and has the potential for application to remote sensing of ocean colour data.

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Gould, Richard W., Stephanie Anderson, M. David Lewis, W. David Miller, Igor Shulman, Geoffrey B. Smith, Travis A. Smith, David W. Wang, and Hemantha W. Wijesekera. "Assessing the Impact of Tides and Atmospheric Fronts on Submesoscale Physical and Bio-Optical Distributions near a Coastal Convergence Zone." Remote Sensing 12, no. 3 (February 7, 2020): 553. http://dx.doi.org/10.3390/rs12030553.

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Optically-active constituents vary over short time and space scales in coastal waters, and they are impacted by a variety of complex, inter-related forcing processes. As part of the Integrated Coastal Bio-Optical Dynamics (ICoBOD) project, we conducted a field campaign in Mississippi Sound in the northern Gulf of Mexico during spring 2018 to examine the impact of the passage of atmospheric and tidal fronts on fine-scale physical and bio-optical property distributions in a shallow, dynamic, coastal environment. During a 25-day experiment, we deployed eight moorings over a roughly 7 × 7 km box encompassing a frontal zone, to collect a time series of physical and bio-optical measurements. We describe changes in diver visibility related to the passage of a short-duration, high-turbidity surface plume and nepheloid layer development/decay during a tidal cycle. Maximum nepheloid layer development was observed during low tide and lasted about 9–12 h. The strongest turbidity signal extended about 4–5 m above the bottom (approximately half of the water column), although anomalously elevated values were observed all the way to the surface. In addition, high-resolution (50 m) hydrodynamic model simulations provide insight into the frontal dynamics and aid interpretation of the observed patterns. Mooring observations confirmed model-predicted heat flux changes associated with the passage of an atmospheric cold front.

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Mavraeidopoulos, Athanasios K., Emmanouil Oikonomou, Athanasios Palikaris, and Serafeim Poulos. "A Hybrid Bio-Optical Transformation for Satellite Bathymetry Modeling Using Sentinel-2 Imagery." Remote Sensing 11, no. 23 (November 22, 2019): 2746. http://dx.doi.org/10.3390/rs11232746.

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The article presents a new hybrid bio-optical transformation (HBT) method for the rapid modelling of bathymetry in coastal areas. The proposed approach exploits free-of-charge multispectral images and their processing by applying limited manpower and resources. The testbed area is a strait between two Greek Islands in the Aegean Sea with many small islets and complex seabed relief. The HBT methodology implements semi-analytical and empirical steps to model sea-water inherent optical properties (IOPs) and apparent optical properties (AOPs) observed by the Sentinel-2A multispectral satellite. The relationships of the calculated IOPs and AOPs are investigated and utilized to classify the study area into sub-regions with similar water optical characteristics, where no environmental observations have previously been collected. The bathymetry model is configured using very few field data (training depths) chosen from existing official nautical charts. The assessment of the HBT indicates the potential for obtaining satellite derived bathymetry with a satisfactory accuracy for depths down to 30 m.

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Blondeau-Patissier, D., G. H. Tilstone, V. Martinez-Vicente, and G. F. Moore. "Comparison of bio-physical marine products from SeaWiFS, MODIS and a bio-optical model with in situ measurements from Northern European waters." Journal of Optics A: Pure and Applied Optics 6, no. 9 (August 21, 2004): 875–89. http://dx.doi.org/10.1088/1464-4258/6/9/010.

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Maritorena, Stéphane, Odile Hembise Fanton d'Andon, Antoine Mangin, and David A. Siegel. "Merged satellite ocean color data products using a bio-optical model: Characteristics, benefits and issues." Remote Sensing of Environment 114, no. 8 (August 16, 2010): 1791–804. http://dx.doi.org/10.1016/j.rse.2010.04.002.

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Ma, R., J. Tang, and J. Dai. "Bio‐optical model with optimal parameter suitable for Taihu Lake in water colour remote sensing." International Journal of Remote Sensing 27, no. 19 (October 2006): 4305–28. http://dx.doi.org/10.1080/01431160600857428.

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Alvain, S., C. Moulin, Y. Dandonneau, H. Loisel, and F. M. Bréon. "A species-dependent bio-optical model of case I waters for global ocean color processing." Deep Sea Research Part I: Oceanographic Research Papers 53, no. 5 (May 2006): 917–25. http://dx.doi.org/10.1016/j.dsr.2006.01.011.

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Ma, Chunyong, Shu Xu, Hongsong Wang, Fenglin Tian, and Ge Chen. "A real-time photo-realistic rendering algorithm of ocean color based on bio-optical model." Journal of Ocean University of China 15, no. 6 (November 8, 2016): 996–1006. http://dx.doi.org/10.1007/s11802-016-3037-2.

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Holinde, L., and O. Zielinski. "Bio-optical characterization and light availability parametrization in two glacial melt water influenced estuary systems (West-Greenland)." Ocean Science Discussions 12, no. 4 (July 21, 2015): 1537–66. http://dx.doi.org/10.5194/osd-12-1537-2015.

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Abstract. Estuary systems are well-defined semi-enclosed systems which are strongly influenced by their terrestrial and marine boundaries. In this paper we investigate the bio-optical conditions in the water column of two neighboring estuary systems, Uummannaq Fjord and Vaigat–Disko Bay, in West Greenland. Though close to each other, the systems differ by their hydrographic structure influencing the bio-optical conditions and subsequently the biological activities. Both systems show high inorganic suspended particulate matter (SPMi) concentrations near freshwater respective melt water influxes (max. of 15.28 mg L−1 at the surface) and low colored dissolved organic matter (aCDOM@350 nm, < 1.50 m−1) abundance throughout the estuaries. Chlorophyll as an indicator of phytoplankton was solely high in the Vaigat (max. of 11.44 μg L−1) representing the outflow arm of the Disko Bay. Light penetration depth as indicated by the 1 % depth of Photosynthetically Available Radiation (PAR) was dominated by chlorophyll and SPMi alike and reached from 12.2 to 41.2 m. Based on these characteristics an effective two component parameterization for the diffuse attenuation coefficient kPAR was developed enabling to model light penetration depth as a relevant factor for bio-optical studies in Arctic environments under glacial melt water influence.

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Kaufman, Daniel E., Marjorie A. M. Friedrichs, John C. P. Hemmings, and Walker O. Smith Jr. "Assimilating bio-optical glider data during a phytoplankton bloom in the southern Ross Sea." Biogeosciences 15, no. 1 (January 4, 2018): 73–90. http://dx.doi.org/10.5194/bg-15-73-2018.

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Abstract. The Ross Sea is a region characterized by high primary productivity in comparison to other Antarctic coastal regions, and its productivity is marked by considerable variability both spatially (1–50 km) and temporally (days to weeks). This variability presents a challenge for inferring phytoplankton dynamics from observations that are limited in time or space, which is often the case due to logistical limitations of sampling. To better understand the spatiotemporal variability in Ross Sea phytoplankton dynamics and to determine how restricted sampling may skew dynamical interpretations, high-resolution bio-optical glider measurements were assimilated into a one-dimensional biogeochemical model adapted for the Ross Sea. The assimilation of data from the entire glider track using the micro-genetic and local search algorithms in the Marine Model Optimization Testbed improves the model–data fit by ∼ 50 %, generating rates of integrated primary production of 104 g C m−2 yr−1 and export at 200 m of 27 g C m−2 yr−1. Assimilating glider data from three different latitudinal bands and three different longitudinal bands results in minimal changes to the simulations, improves the model–data fit with respect to unassimilated data by ∼ 35 %, and confirms that analyzing these glider observations as a time series via a one-dimensional model is reasonable on these scales. Whereas assimilating the full glider data set produces well-constrained simulations, assimilating subsampled glider data at a frequency consistent with cruise-based sampling results in a wide range of primary production and export estimates. These estimates depend strongly on the timing of the assimilated observations, due to the presence of high mesoscale variability in this region. Assimilating surface glider data subsampled at a frequency consistent with available satellite-derived data results in 40 % lower carbon export, primarily resulting from optimized rates generating more slowly sinking diatoms. This analysis highlights the need for the strategic consideration of the impacts of data frequency, duration, and coverage when combining observations with biogeochemical modeling in regions with strong mesoscale variability.

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Tiwari, S. P., P. Shanmugam, Y. H. Ahn, and J. H. Ryu. "A Reflectance Model for Relatively Clear and Turbid Waters." Engineering, Technology & Applied Science Research 3, no. 1 (February 11, 2013): 325–37. http://dx.doi.org/10.48084/etasr.248.

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Accurate modeling of spectral remote sensing reflectance (Rrs) is of great interest for ocean colour studies in highly turbid and relatively clear waters. In this work a semianalytical model that simulates the spectral curves of remote sensing reflectance of these waters is developed based on the inherent optical properties (IOPs) and f and Q factors. For accommodating differences in the optical properties of the water and accounting for their directional variations, IOPs and f and Q factors are derived as a function of phytoplankton pigments, suspended sediments and solar zenith angle. Results of this model are compared with in-situ bio-optical data collected at 83 stations encompassing highly turbid/relatively cleared waters of the South Sea of Korea. Measured and modeled remote sensing reflectances agree favorably in both magnitude and spectral shape, with considerably low errors (mean relative error MRE -0.0327; root mean square error RMSE 0.205, bias -0.0727 and slope 1.15 and correlation coefficient R2 0.74). These results suggest that the new model has the ability to reproduce measured reflectance values and has potentially profound implications for remote sensing of complex waters in this region.

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Bagniewski, W., K. Fennel, M. J. Perry, and E. A. D'Asaro. "Optimizing models of the North Atlantic spring bloom using physical, chemical and bio-optical observations from a Lagrangian float." Biogeosciences Discussions 7, no. 6 (November 19, 2010): 8477–520. http://dx.doi.org/10.5194/bgd-7-8477-2010.

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Abstract. The North Atlantic spring bloom is one of the main events that lead to carbon export to the deep ocean and drive oceanic uptake of CO2 from the atmosphere. Here we use a suite of physical, bio-optical and chemical measurements made during the 2008 spring bloom to optimize and compare three different models of biological carbon export. The observations are from a Lagrangian float that operated south of Iceland from early April to late June, and were calibrated with ship-based measurements. The simplest model is representative of typical NPZD models used for the North Atlantic, while the most complex model explicitly includes diatoms and the formation of fast sinking diatom aggregates and cysts under silicate limitation. We carried out a variational optimization and error analysis for the biological parameters of all three models, and compared their ability to replicate the observations. The observations were sufficient to constrain most phytoplankton-related model parameters to accuracies of better than 15%. However, the lack of zooplankton observations leads to large uncertainties in model parameters for grazing. The simulated vertical carbon flux at 100 m depth is similar between models and agrees well with available observations, but at 600 m the simulated flux is much larger for the model with diatom aggregation. While none of the models can be formally rejected based on their misfit with the available observations, the model that includes export by diatom aggregation has slightly better fit to the observations and more accurately represents the mechanisms and timing of carbon export based on observations not included in the optimization. Thus models that accurately simulate the upper 100 m do not necessarily accurately simulate export to deeper depths.

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Bagniewski, W., K. Fennel, M. J. Perry, and E. A. D'Asaro. "Optimizing models of the North Atlantic spring bloom using physical, chemical and bio-optical observations from a Lagrangian float." Biogeosciences 8, no. 5 (May 25, 2011): 1291–307. http://dx.doi.org/10.5194/bg-8-1291-2011.

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Abstract. The North Atlantic spring bloom is one of the main events that lead to carbon export to the deep ocean and drive oceanic uptake of CO2 from the atmosphere. Here we use a suite of physical, bio-optical and chemical measurements made during the 2008 spring bloom to optimize and compare three different models of biological carbon export. The observations are from a Lagrangian float that operated south of Iceland from early April to late June, and were calibrated with ship-based measurements. The simplest model is representative of typical NPZD models used for the North Atlantic, while the most complex model explicitly includes diatoms and the formation of fast sinking diatom aggregates and cysts under silicate limitation. We carried out a variational optimization and error analysis for the biological parameters of all three models, and compared their ability to replicate the observations. The observations were sufficient to constrain most phytoplankton-related model parameters to accuracies of better than 15 %. However, the lack of zooplankton observations leads to large uncertainties in model parameters for grazing. The simulated vertical carbon flux at 100 m depth is similar between models and agrees well with available observations, but at 600 m the simulated flux is larger by a factor of 2.5 to 4.5 for the model with diatom aggregation. While none of the models can be formally rejected based on their misfit with the available observations, the model that includes export by diatom aggregation has a statistically significant better fit to the observations and more accurately represents the mechanisms and timing of carbon export based on observations not included in the optimization. Thus models that accurately simulate the upper 100 m do not necessarily accurately simulate export to deeper depths.

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Li, Jun, Tongji Li, Qingjun Song, and Chaofei Ma. "Performance Evaluation of Four Ocean Reflectance Model." Remote Sensing 13, no. 14 (July 13, 2021): 2748. http://dx.doi.org/10.3390/rs13142748.

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Phytoplankton are the main factors influencing light under the sea surface in Case Ι water. The ocean reflectance model (ORM), which takes into account the chlorophyll a concentration data, can calculate the remote sensing reflectance of Case Ι water. In this study, we examined the differences and performance of four ORMs, including Morel and Maritorena (2001, MM01), Morel and Gentili (2007, MG07), Mobley (2014, MO14), and Hydrolight Abcase1 Lookup Tables. The differences between the four ORMs in terms of their absorption and backscattering coefficients were evaluated. Preformation of the four ORMs was compared using the NASA bio-Optical Marine Algorithm Dataset and in situ data from the South China Sea. The results showed that preformation of MM01 was the best.

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Corsini, Giovanni, Raffaele Grasso, and Paolo Cipollini. "Regional bio-optical algorithms for the Alboran Sea from a reflectance model and in situ data." Geophysical Research Letters 29, no. 15 (August 2002): 29–1. http://dx.doi.org/10.1029/2001gl013861.

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Bonamano, Simone, Alice Madonia, Viviana Piermattei, Chiara Stefanì, Luigi Lazzara, Ilaria Nardello, Franco Decembrini, and Marco Marcelli. "Phyto-VFP: a new bio-optical model of pelagic primary production based on variable fluorescence measures." Journal of Marine Systems 204 (April 2020): 103304. http://dx.doi.org/10.1016/j.jmarsys.2019.103304.

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Fujii, M., E. Boss, and F. Chai. "The value of adding optics to ecosystem models: a case study." Biogeosciences 4, no. 5 (October 11, 2007): 817–35. http://dx.doi.org/10.5194/bg-4-817-2007.

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Abstract. Many ecosystem models have been developed to study the ocean's biogeochemical properties, but most of these models use simple formulations to describe light penetration and spectral quality. Here, an optical model is coupled with a previously published ecosystem model that explicitly represents two phytoplankton (picoplankton and diatoms) and two zooplankton functional groups, as well as multiple nutrients and detritus. Surface ocean color fields and subsurface light fields are calculated by coupling the ecosystem model with an optical model that relates biogeochemical standing stocks with inherent optical properties (absorption, scattering); this provides input to a commercially available radiative transfer model (Ecolight). We apply this bio-optical model to the equatorial Pacific upwelling region, and find the model to be capable of reproducing many measured optical properties and key biogeochemical processes in this region. Our model results suggest that non-algal particles largely contribute to the total scattering or attenuation (>50% at 660 nm) but have a much smaller contribution to particulate absorption (<20% at 440 nm), while picoplankton dominate the total phytoplankton absorption (>95% at 440 nm). These results are consistent with the field observations. In order to achieve such good agreement between data and model results, however, key model parameters, for which no field data are available, have to be constrained. Sensitivity analysis of the model results to optical parameters reveals a significant role played by colored dissolved organic matter through its influence on the quantity and quality of the ambient light. Coupling explicit optics to an ecosystem model provides advantages in generating: (1) a more accurate subsurface light-field, which is important for light sensitive biogeochemical processes such as photosynthesis and photo-oxidation, (2) additional constraints on model parameters that help to reduce uncertainties in ecosystem model simulations, and (3) model output which is comparable to basic remotely-sensed properties. In addition, the coupling of biogeochemical models and optics paves the road for future assimilation of ocean color and in-situ measured optical properties into the models.

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