Ocean PHILLS hyperspectral imager: design, characterization, and calibration

Davis, Curtiss O.; Bowles, Jeffrey H.; Leathers, Robert A.; Korwan, Daniel; Downes, T. V.; Snyder, W. A.; Rhea, W. Joe; Chen, Wei; Fisher, John; Bissett, Paul; Reisse, Robert A.

doi:10.1364/oe.10.000210

Cited by 175 publications

(104 citation statements)

References 16 publications

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“…Enhanced products are supported by HICO's spatial resolution (<100 × 100 m), spectral resolution (400 to 900 nm sampled at 5.7 nm) and signal-to-noise ratio (>200:1 for a 5% albedo scene). Based on the Portable Hyperspectral Imager for Low-Light Spectroscopy (PHILLS) airborne imaging spectrometers [3], HICO demonstrates innovative ways to reduce the cost and schedule of a space mission, by adapting proven aircraft imager architecture and using commercial off-the-shelf components. HICO was installed on the International Space Station (ISS) on 23 September 2009 and collected its first images the following day.…”

Section: Introductionmentioning

confidence: 99%

Application of the Hyperspectral Imager for the Coastal Ocean to Phytoplankton Ecology Studies in Monterey Bay, CA, USA

et al. 2014

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As a demonstrator for technologies for the next generation of ocean color sensors, the Hyperspectral Imager for the Coastal Ocean (HICO) provides enhanced spatial and spectral resolution that is required to understand optically complex aquatic environments. In this study we apply HICO, along with satellite remote sensing and in situ observations, to studies of phytoplankton ecology in a dynamic coastal upwelling environment-Monterey Bay, CA, USA. From a spring 2011 study, we examine HICO-detected spatial patterns in phytoplankton optical properties along an environmental gradient defined by upwelling flow patterns and along a temporal gradient of upwelling intensification. From a fall 2011 study, we use HICO's enhanced spatial and spectral resolution to distinguish a small-scale "red tide" bloom, and we examine bloom expansion and its supporting processes using other remote sensing and in situ data. From a spectacular HICO image of the Monterey Bay region acquired during fall of 2012, we present a suite of algorithm results for characterization of phytoplankton, and we examine the strengths, limitations, and distinctions of each algorithm in the context of the enhanced spatial and spectral resolution.

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Section: Introductionmentioning

confidence: 99%

Application of the Hyperspectral Imager for the Coastal Ocean to Phytoplankton Ecology Studies in Monterey Bay, CA, USA

et al. 2014

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“…Ocean Portable Hyperspectral Imager for Low-Light Spectroscopy (Ocean PHILLS)가 개발되었으며, 이는 항공기에 탑재되어 미 연안 관측을 수행하고 있다 [10] . Ocean PHILLS의 후속 센서 로 미 해군연구소(Naval Research Laboratory)에서 개발된 Hypespectral Imager for the Coastal Ocean(HICO)는 350km 궤도의 국제우주정거장(International Space Station, ISS)에 장착되어 관측을 수행 중이다 [11] .…”

Section: 안을 관측하기 위하여 소형화 경량화를 추구한 초분광 센서로unclassified

“…Ocean PHILLS, HICO) 에서는 전단광학계로 상용 굴절광학계를 사용하였다 [10,11] . 이 와 같은 렌즈 형태의 전단광학계는 설계의 편의성, 기존 제 품의 활용도, 제작비용의 효율성의 측면과 더불어 상대적으 로 넓은 관측 영역(HICO의 경우 약 7° FOV)을 갖는다는 장 점이 있다 [11,16] .…”

Section: 비축 삼반사경 형태의 전단광학계 설계unclassified

Design and Performance Analysis of an Off-Axis Three-Mirror Telescope for Remote Sensing of Coastal Water

Oh¹,

Kang²,

Hyun³

et al. 2015

Korean Journal of Optics and Photonics

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We report the design and performance analysis of an off-axis three-mirror telescope as the fore optics for a new hyperspectral sensor aboard a small unmanned aerial vehicle (UAV), for low-altitude coastal remote sensing. The sensor needs to have at least 4 cm of spatial resolution at an operating altitude of 500 m, 4° field of view (FOV), and a signal to noise ratio (SNR) of 100 at 660 nm. For these performance requirements, the sensor's optical design has an entrance pupil diameter of 70 mm and an F-ratio of 5.0. The fore optics is a three-mirror system, including aspheric primary and secondary mirrors. The optical performance is expected to reach 1/15λ in RMS wavefront error and 0.75 in MTF value at 660 nm. Considering the manufacturing and assembling phase, we determined the alignment compensation due to the tertiary mirror from the sensitivity, and derived the tilt-tolerance range to be 0.17 mrad. The off-axis three-mirror telescope, which has better performance than the fore optics of other hyperspectral sensors and is fitted for a small UAV, will contribute to ocean remote-sensing research.

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“…The remote sensing reflectance is the quantity used as the basis for ocean color remote sensing by the Seaviewing Wide Field-of-view Sensor (SeaWiFS) [O'Reilly et al, 1998;Hoge et al, 2001;Hoge and Lyon, 2002] and airborne systems [Davis et al, 2002;Hoge et al, 1999aHoge et al, , 1999b systems. R rs can be obtained from at-sensor radiances after atmospheric correction; for our purposes here it is therefore considered known.…”

Section: Shape Factor Form Of the Radiative Transfer Equationmentioning

confidence: 99%

Radiative transfer equation inversion: Theory and shape factor models for retrieval of oceanic inherent optical properties

Hoge¹

2003

J. Geophys. Res.

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[1] It is shown that the in-water, shape factor formulation of the radiative transfer equation (RTE) (1) yields exact in-air expressions for the remote sensing reflectance R rs and the equivalent remotely sensed reflectance RSR a and (2) can be configured for inherent optical property (IOP) retrievals using standard linear matrix inversion methods. Inversion of the shape factor RTE is exact in the sense that no approximations are made to the RTE. Thus errors in retrieved IOPs are produced only by uncertainties in (1) the models for the shape factors and related quantities and (2) the IOP models required for inversion. Hydrolight radiative transfer calculations are used to derive analytical models for the necessary backscattering shape factor, radiance shape factor, fractional forward scattering coefficient, ratio of air-to-water mean cosines, and diffuse attenuation coefficient for in-water upwelling radiance. These models predict the various shape factors with accuracies ranging typically from 2 to 20%. Using the modeled shape factors the in-air remotely sensed reflectance RSR a can be predicted to within 20% of the correct (Hydrolight-computed) values 96% of the time (or ±0.0005 sr À1 86% of the time) for the synthetic data used to determine the shape factor models. Inversion of this shape factor RTE using field data is a comprehensive study to be published in a later paper.INDEX TERMS: 4552 Oceanography: Physical: Ocean optics; 4847 Oceanography: Biological and Chemical: Optics; 4275 Oceanography: General: Remote sensing and electromagnetic processes (0689); 4842 Oceanography: Biological and Chemical: Modeling; KEYWORDS: remote sensing, optical oceanography, inverse modeling, radiative transfer theory Citation: Hoge, F. E., P. E. Lyon, C. D. Mobley, and L. K. Sundman, Radiative transfer equation inversion: Theory and shape factor models for retrieval of oceanic inherent optical properties,

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Ocean PHILLS hyperspectral imager: design, characterization, and calibration

Cited by 175 publications

References 16 publications

Application of the Hyperspectral Imager for the Coastal Ocean to Phytoplankton Ecology Studies in Monterey Bay, CA, USA

Application of the Hyperspectral Imager for the Coastal Ocean to Phytoplankton Ecology Studies in Monterey Bay, CA, USA

Design and Performance Analysis of an Off-Axis Three-Mirror Telescope for Remote Sensing of Coastal Water

Radiative transfer equation inversion: Theory and shape factor models for retrieval of oceanic inherent optical properties

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