Simulation of In Situ Visible Radiometric Measurements

Bulgarelli, Barbara; D’Alimonte, Davide

doi:10.1016/b978-0-12-417011-7.00013-1

Cited by 1 publication

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“…All these elements are considered in the present study to stress measurement and processing solutions in view of increasing the quality of insitu radiometric data products from hyperspectral in-water free-fall profiles. The study is executed using the MOX Monte Carlo code to simulate radiometric fields for different measurement conditions by applying high-performance computing solutions [14,[19][20][21][22][23][24]. The response of in-water optical sensors is investigated based on a two-dimensional representation of the underwater light distribution.…”

Section: Introductionmentioning

confidence: 99%

Effects of integration time on in-water radiometric profiles

2018

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This work investigates the effects of integration time on in-water downward irradiance E, upward irradiance E and upwelling radiance L profile data acquired with free-fall hyperspectral systems. Analyzed quantities are the subsurface value and the diffuse attenuation coefficient derived by applying linear and non-linear regression schemes. Case studies include oligotrophic waters (Case-1), as well as waters dominated by Colored Dissolved Organic Matter (CDOM) and Non-Algal Particles (NAP). Assuming a 24-bit digitization, measurements resulting from the accumulation of photons over integration times varying between 8 and 2048ms are evaluated at depths corresponding to: 1) the beginning of each integration interval (Fst); 2) the end of each integration interval (Lst); 3) the averages of Fst and Lst values (Avg); and finally 4) the values weighted accounting for the diffuse attenuation coefficient of water (Wgt). Statistical figures show that the effects of integration time can bias results well above 5% as a function of the depth definition. Results indicate the validity of the Wgt depth definition and the fair applicability of the Avg one. Instead, both the Fst and Lst depths should not be adopted since they may introduce pronounced biases in E and L regression products for highly absorbing waters. Finally, the study reconfirms the relevance of combining multiple radiometric casts into a single profile to increase precision of regression products.

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