Colour remote sensing of the impact of artificial light at night (I): The potential of the International Space Station and other DSLR-based platforms

Miguel, Alejandro Sánchez de; Kyba, Christopher C. M.; Aubé, Martin; Zamorano, J.; Cardiel, N.; Tapia, C.; Bennie, Jonathan; Gaston, Kevin J.

doi:10.1016/j.rse.2019.01.035

Cited by 101 publications

(96 citation statements)

References 44 publications

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“…4.8 and shown in Fig. 10 agree well with those found in the literature [1,2,13,19,23,24,46,51,54,57,[59][60][61][62], with the RGB curves centered around 600, 520, and 470 nm, respectively. Notably, the strong secondary peaks seen in [2,51] were not found in our data and may be JPEG artefacts.…”

Section: Resultssupporting

confidence: 88%

“…Furthermore, the significant variations show that the common assumption of sRGB responses [9,22] does not hold, as has been suggested previously [21], and characterization of the spectral response is necessary to convert observed colors to color spaces such as CIE 1931 XYZ or CIELAB [23,25]. However, color measurements still depend on the incident light spectrum [25]; hyperspectral measurements, for example with iSPEX [10], and characterization of common light sources [1,78] may provide valuable additional information. Finally, while no significant response was found at wavelengths <390 or >700 nm on our test cameras, it may be worthwhile in the future and the SPECTACLE database to use a spectral range of 380-780 nm to follow colorimetric standards [25,52,56].…”

Section: Resultsmentioning

confidence: 97%

“…Their low cost makes them ideal for projects involving large scale deployment, autonomous monitoring, or citizen science. Successful scientific applications include environmental monitoring [1][2][3][4][5][6][7][8][9][10][11][12][13], cosmic ray detection [14], vegetation mapping [15][16][17][18][19], color science [9,[20][21][22][23][24][25], and biomedical applications [26][27][28][29][30][31][32][33]. However, the use of consumer cameras is made difficult by limited software controls and camera specifications.…”

Section: Introductionmentioning

confidence: 99%

“…However, for the five digicams included in this work, JPEG data were used, severely limiting the quality and usefulness of these calibrations, as described above.Spectral characterizations are more commonly published since these are vital for quantitative color analysis. Using various methods, the spectral responses of several Canon [1,19,23,24,46,51,54,61], Nikon [1,13,23,24,54,[59][60][61][62], Olympus [23, 24, 51], Panasonic [46], SeaLife [13], Sigma [60], and Sony [1, 23, 46, 51, 61] digital cameras (digicams), as well as a number of smartphones [2, 23], have been measured. Direct comparisons between >2 different camera models are given in [1,2,23,46,51].…”

mentioning

confidence: 99%

“…JPEG (ISO 10918) is based on lossy spatial compression and downsampling to 8-bit values, optimal for small file sizes while maintaining aesthetic qualities. Due to camera-specific processing and compression artefacts, JPEG images lose information and are not recommended for quantitative analysis [1,2,5,10,19,24,32,40,49,50]. While standardizations exist, such as the standard Red Green Blue (sRGB) color space and gamma curve [63], these are not strictly adhered to and cannot be assumed in data processing [68].…”

mentioning

confidence: 99%

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Standardized spectral and radiometric calibration of consumer cameras

Burggraaff¹,

Schmidt²,

Zamorano³

et al. 2019

Opt. Express

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108

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Consumer cameras, particularly onboard smartphones and UAVs, are now commonly used as scientific instruments. However, their data processing pipelines are not optimized for quantitative radiometry and their calibration is more complex than that of scientific cameras. The lack of a standardized calibration methodology limits the interoperability between devices and, in the ever-changing market, ultimately the lifespan of projects using them. We present a standardized methodology and database (SPECTACLE) for spectral and radiometric calibrations of consumer cameras, including linearity, bias variations, read-out noise, dark current, ISO speed and gain, flat-field, and RGB spectral response. This includes golden standard ground-truth methods and do-it-yourself methods suitable for non-experts. Applying this methodology to seven popular cameras, we found high linearity in RAW but not JPEG data, inter-pixel gain variations >400% correlated with large-scale bias and read-out noise patterns, non-trivial ISO speed normalization functions, flat-field correction factors varying by up to 2.79 over the field of view, and both similarities and differences in spectral response. Moreover, these results differed wildly between camera models, highlighting the importance of standardization and a centralized database. accuracy of color measurements and their conversion to standard measures, such as the CIE 1931 XYZ and CIELAB color spaces, is limited by distortions in the observed colors [20] and differences in spectral response functions [21,[23][24][25].Extensive (spectro-)radiometric calibrations of consumer cameras are laborious and require specialized equipment and are thus not commonly performed [23,54,60]. A notable exception is the spectral and absolute radiometric calibration of a Raspberry Pi 3 V2 webcam by Pagnutti et al. [57], including calibrations of linearity, exposure stability, thermal and electronic noise, flat-field, and spectral response. Using this absolute radiometric calibration, digital values can be converted into SI units of radiance. However, the authors noted the need to characterize a large number of these cameras before the results could be applied in general. Moreover, certain calibrations are device-dependent and would need to be done separately on each device. Spectral and radiometric calibrations of seven cameras, including the Raspberry Pi, are given in [51]. These calibrations include dark current, flat-fielding, linearity, and spectral characterization. However, for the five digicams included in this work, JPEG data were used, severely limiting the quality and usefulness of these calibrations, as described above.Spectral characterizations are more commonly published since these are vital for quantitative color analysis. Using various methods, the spectral responses of several Canon [1,19,23,24,46,51,54,61], Nikon [1,13,23,24,54,[59][60][61][62], Olympus [23, 24, 51], Panasonic [46], SeaLife [13], Sigma [60], and Sony [1, 23, 46, 51, 61] digital cameras (digicams), as well as a number of smartpho...

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