Best practices in passive remote sensing VNIR hyperspectral system hardware calibrations

Jablonski, Joseph; Durell, Christopher; Slonecker, E. Terrence; Wong, K. K.; Simon, Blair; Eichelberger, Andrew; Osterberg, Jacob

doi:10.1117/12.2224022

Cited by 6 publications

(10 citation statements)

References 12 publications

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“…The calibration process includes several phases: a relative radiometric calibration, which aims for a uniform output across the pixels and time, a spectral calibration, which determines the spectral response of the bands, and an absolute radiometric calibration, which determines the transformation from pixel values to the physical unit radiance. A comprehensive review on calibration procedures for high-resolution radiance measurements can be found in Jablonski et al, [123] and Yoon and Kacker [124]. In the following, we will focus on sensor calibration procedures that are required to generate reflectance maps from spectral UAV data.…”

Section: Sensor-related Calibrationmentioning

confidence: 99%

“…Spectral response gives the system's radiometric response as a function of wavelength for each band and spatial pixel [120,123,136,137]. Monochromators or line emission lamps are usually used for determining the spectral calibration.…”

Section: Spectral Calibrationmentioning

confidence: 99%

“…Either complete measured spectral response or some functional form is used in calculations; typically, a Gaussian with the central wavelength and the full width of half maximum (FWHM) is used as the model spectral response. In addition, the smile effect, which causes a shift of the central wavelength as the function of the position of the pixel in the focal plane, and the keystone, which causes a bending of spatial lines across the spectral axis [123] needs to be corrected. Thus, the spectral response must be measured in the spectral as well as in the spatial detector dimension.…”

Section: Spectral Calibrationmentioning

confidence: 99%

“…Thus, the spectral response must be measured in the spectral as well as in the spatial detector dimension. The smile and keystone characterization are necessary, in particular with hyperspectral sensors [123,137].…”

Section: Spectral Calibrationmentioning

confidence: 99%

“…The next section shows that absolute radiometric calibration can be omitted in cases where only reflectance, is needed and radiance is not. Besides, many factors influence the system radiometric response, such as for example, the shutter, stray light effects, impacts of temperature, and pressure [123,142]. For applications that require very precise data, such as solar induced fluorescence estimation, these parameters also need to be considered.…”

Section: Absolute Radiometric Calibrationmentioning

confidence: 99%

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Quantitative Remote Sensing at Ultra-High Resolution with UAV Spectroscopy: A Review of Sensor Technology, Measurement Procedures, and Data Correction Workflows

et al. 2018

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In the last 10 years, development in robotics, computer vision, and sensor technology has provided new spectral remote sensing tools to capture unprecedented ultra-high spatial and high spectral resolution with unmanned aerial vehicles (UAVs). This development has led to a revolution in geospatial data collection in which not only few specialist data providers collect and deliver remotely sensed data, but a whole diverse community is potentially able to gather geospatial data that fit their needs. However, the diversification of sensing systems and user applications challenges the common application of good practice procedures that ensure the quality of the data. This challenge can only be met by establishing and communicating common procedures that have had demonstrated success in scientific experiments and operational demonstrations. In this review, we evaluate the state-of-the-art methods in UAV spectral remote sensing and discuss sensor technology, measurement procedures, geometric processing, and radiometric calibration based on the literature and more than a decade of experimentation. We follow the 'journey' of the reflected energy from the particle in the environment to its representation as a pixel in a 2D or 2.5D map, or 3D spectral point cloud. Additionally, we reflect on the current revolution in remote sensing, and identify trends, potential opportunities, and limitations.

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Section: Sensor-related Calibrationmentioning

confidence: 99%

Section: Spectral Calibrationmentioning

confidence: 99%

Section: Spectral Calibrationmentioning

confidence: 99%

Section: Spectral Calibrationmentioning

confidence: 99%

Section: Absolute Radiometric Calibrationmentioning

confidence: 99%

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Quantitative Remote Sensing at Ultra-High Resolution with UAV Spectroscopy: A Review of Sensor Technology, Measurement Procedures, and Data Correction Workflows

et al. 2018

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A turn-key calibration roadmap for temperature and radiance from 0.3-14μm

Jablonski¹,

Durell²,

LaVeigne

et al. 2017

SPIE Proceedings

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Calibrating a snapshot mosaic hyperspectral imaging system suitable for static and aerial applications

Zempila¹,

Hamilton²,

Mortimer³

2023

Hyperspectral Imaging and Applications II

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Radiometric calibration of all optical sensors is a key component to achieve high accuracy data, which is traceable to international standards and repeatable through time. This study introduces a hyperspectra l imaging (HSI) system that RAL Space has developed and presents a thorough analysis of the radiometric reflectance calibration chain required for both static and aerial applications, where the HSI system is mounted on a n Unoccupied Aerial System (UAS). RAL Space HSI system comprises two commercially available Ximea snapshot mosaic imagers, one sensitive in the visible (VIS) and the other in the near infrared (NIR) spectral ranges, that are coupled with a dedicated PC and customized LabVIEW code for the capture, process and storage of the raw hyperspectral information (hypercubes). Both imagers are optically characterized for their electrical gain and offset, the vignetting and stray light effects, while the spectral response of each band has also been determined. The corrected digital numbers (DN) are then translated into reflectance values with the use of reflectance standards. For the aerial surveys, an additional step has been developed into the calibration chain that corrects for any changes in ambient illumination during flight with the use of ground based upward-looking measured spectra.Future work will include any correction needed due to temperature dependencies of the calibration chain steps.

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Best practices in passive remote sensing VNIR hyperspectral system hardware calibrations

Cited by 6 publications

References 12 publications

Quantitative Remote Sensing at Ultra-High Resolution with UAV Spectroscopy: A Review of Sensor Technology, Measurement Procedures, and Data Correction Workflows

Quantitative Remote Sensing at Ultra-High Resolution with UAV Spectroscopy: A Review of Sensor Technology, Measurement Procedures, and Data Correction Workflows

A turn-key calibration roadmap for temperature and radiance from 0.3-14μm

Calibrating a snapshot mosaic hyperspectral imaging system suitable for static and aerial applications

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