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Detectors
Published in C. R. Kitchin, Astrophysical Techniques, 2020
Personal digital video and still cameras automatically obtain their images in colour. To do this, small filters are placed over each CCD element. In the commonly used Bayer arrangement, for each set of four pixels, two have green-transmission filters, one a blue transmission filter and one a red transmission filter (allowing, roughly, for the eye’s intrinsic spectral response). This means that the spatial resolution of the image is degraded – a 10 megapixel colour camera only has the spatial resolution of a 2.5 megapixel monochromatic camera. More importantly for rigorous scientific analysis of the images, the three colours do not come from exactly the same locality within the original object. If the properties of the original object are varying significantly on a size scale equivalent to an individual pixel, then the colour image will give false results. When images at two or more wavelengths are needed for astronomical purposes (including the beautiful colour representations of nebulae and galaxies, etc., ornamenting many astronomy books), it is usual to obtain individual images at each wavelength through appropriate filters and then combine them into a colour (or false-colour) final image. The full spatial resolution of the detector is thus retained and, if wanted, a truer visual representation of the appearance of the object may be obtained by better relative weightings of the different images than that given by the crude Bayer system.26
The Role of Remote Sensing Displays in Earth Climate and Planetary Atmospheric Research
Published in Robert R. Hoffman, Arthur B. Markman, Interpreting Remote Sensing Imagery, 2019
Aside from images, false color is used to display contour maps of remote sensing retrievals of weather and climate parameters. It is often overlooked that remote sensing retrieval techniques are not perfect—photons emitted or reflected by a planet and received by a detector in space are converted by a computer algorithm to the numerical value of some physical parameter. The algorithm used may be simply empirical, based on observations at one location that are not valid globally. It may assume that other physical parameters that also affect the radiation observed are constant, when in reality they are varying. Or the algorithm may be a physical model of the atmosphere that makes simplifying assumptions. But the result, a color contour map with a title indicating the parameter displayed (e.g., precipitation) immediately attains an air of legitimacy and certainty among scientists who know, but sometimes forget that it is not a direct measurement of raindrops collected in a bucket. The intervals chosen for changes in color sometimes have little relationship to the inherent uncertainty in the algorithm that produced the data set, and users often do not ask how large the errors are. This is a different take on the novice vs. expert issue—professional users of data may be naive about how the data displayed were produced, and hence, erroneous scientific conclusions may sometimes be reached.
Environmental Reconstruction of Watershed Vegetation Cover to Reflect the Impact of a Hurricane Event
Published in Ni-Bin Chang, Kaixu Bai, Multisensor Data Fusion and Machine Learning for Environmental Remote Sensing, 2018
However, the true color images may also be low in contrast due to the scattering of blue light by the atmosphere. This is where the false color composite images can help. False color images are comprised of spectral bands other than red, green, and blue, which help in visualizing wavelengths that are not seen by the human eye. The use of bands such as near-infrared facilitates the spectral separation leading to the increase of interpretability of the images. The most commonly used false color combination for Landsat images is the combination of Band 4, Band 3, and Band 2 in the RGB channels. With such a combination, for instance, vegetation will be depicted in red, urban areas in cyan blue, soils in varying colors of dark to light brown, as well as clouds and snow in white or light cyan. The deeper the red, the more likely the vegetation is healthier or denser.
Syncing with the Sky: Daylight-Driven Circadian Lighting Design
Published in LEUKOS, 2021
Nathan Altenberg Vaz, Mehlika Inanici
Note that color legends are different for photopic and melanopic illuminances in the false color images. The photopic illuminances are illustrated with false colors that range from blue to red, where blue tones represent the illuminance values equivalent or less than 300 lux (~30 fc) (recommended target value), and red tones represent the high illuminances (>3000 lux (~300fc), threshold for visual discomfort) in the scene. This is a typical false color scheme used in the UDI (Mardaljevic et al. 2012). The circadian illuminances are illustrated with a different false color scheme that ranges from gray to blue, where gray tones represent the EML values equivalent or less than 240 EML, and the blue tones represent the high values (>960 EML) in the scene.
A Novel In Situ Flamelet Tabulation Methodology for the Representative Interactive Flamelet Model
Published in Combustion Science and Technology, 2020
Prithwish Kundu, Joseph Scroggins, Muhsin M. Ameen
Figure 6 shows the qualitative results for the Spray A condition (900 K) at 1 ms after start of injection (ASOI). The flame reaches a quasi-steady state by this time, and the flame liftoff length is observed to reach a steady value. The flame exhibits a two-stage ignition process. The species formation and heat release observed before the main ignition event are governed by coupled effects of low-temperature chemistry and turbulence. This has a significant impact on the high-temperature ignition and flame stabilization mechanism. Figure 7 shows the temporal evolution of formaldehyde along the plane of the injector. CH2O PLIF images from a single injection event are compared against instantaneous CH2O mass fraction predictions from a single LES realization. As the PLIF images are based on false color, this comparison is qualitative in nature. CH2O formation is observed to begin at 0.19 ms at the periphery of the jet between 10 and 20 mm from the injector. The simulation predicts the onset of the cool flame in similar peripheral regions extending slightly more in the axial direction. The formaldehyde formation regions are then successively transported toward the head of the spray, and similar transitions are captured by the simulations. By the time of the high-temperature ignition, the cool flame region reaches a quasi-steady state extending from approximately 15 to 30 mm from the nozzle. The simulations predict a similar region extending from 15 mm to slightly higher than 30 mm compared to experiments. The RIF-ist formulation qualitatively predicts the correct onset and extent of the cool flame region in tune with the previous tabulated approach (Kundu et al., 2017b).
Evaluation of loss models and effect of LU/LC changes on surface runoff in Subarnarekha river basin
Published in ISH Journal of Hydraulic Engineering, 2021
Asit Kumar Dandapat, Sanat Nalini Sahoo
The Image analysis window’s processing area unties the experience of applying complex handling and investigation strategies to layers of picture and raster information in Arc Map. The system gives a single tick alternative to apply procedures, for example, cutting, standardized distinction vegetation list (NDVI) creation, mosaicking, and trading. False Color Composite (FCC)