![]() ![]() This will create a single RGB image, which will be dark. ![]() Set band B4 as red, B3 as green, and B2 as blue. Then change the mode from Multichannel to RGB Color in the dialog box that appears. From the Channels Palette (accessed through Photoshop’s Windows menu item) select the Merge Channels command (click on the small downward-pointing triangle in the upper-right corner of the palette). You’ll end up with three grayscale images, which need to be combined to make a color image. To build a natural-color image, open the three separate files in Photoshop: Our eyes and brains are inextricably linked, after all, and what we see (or think we see) is shaped by context.Įnough theory. I try to create imagery that matches what I see in my mind’s eye, as much or more than a literal depiction of the data. (Astronaut Photograph ISS037-E-001180)īecause of this, satellite imagery needs to be processed with care. Seen from above, the Earth’s surface is made brighter and bluer by the atmosphere (compare the hue of the clouds to the hue of the panels on the International Space Station). Colors and color elements in vertical photographs taken from high altitudes vary by a greater or lesser extent from those that we perceive as natural from day to day visual experience at ground level. (A)erial photographs from great heights, even in color, are often quite misleading, the Earth’s surface relief usually appearing too flat and the vegetation mosaic either full of contrasts and everchanging (sic) complexities, or else veiled in a gray-blue haze. Eduard Imhof, a Swiss cartographer active in the mid Twentieth Century, wrote*: In particular, vegetation appears much greener than it actually is, and water is either black or a wholly unnatural electric blue.Įven natural-color satellite imagery can be deceptive due to the unfamiliar perspective. ![]() Although the USGS imagery superficially resembles an RGB picture, it is (in my opinion) inappropriate to call it natural-color. The USGS also distributes imagery they call “natural color,” using shortwave infrared, near infrared, and green light. False-color images, which incorporate wavelengths of light invisible to humans, can reveal fascinating information-but they’re often misleading to people without formal training in remote sensing. I prefer using the red, green, and blue bands because natural-color imagery takes advantage of what we already know about the natural world: trees are green, snow and clouds are white, water is (sorta) blue, etc. (The complete scene data can be downloaded using Earth Explorer.) I’ve highlighted the three bands needed for natural-color (also called true-color, or photo-like) imagery: B4 is red (0.64–0.67 µm), B3 is green (0.53–0.59 µm), B2 is blue (0.45–0.51 µm). Īfter you’ve extracted the files, you’ll have a somewhat cryptically-named directory with the three band files in it (B2, B3, B4): OS X can automatically uncompress the files (with default settings) when the archive is downloaded-double-click to unpack the TAR.) Inexplicably, the TIFFs aren’t compressed. (Windows does not natively support TAR, so you may need to use something like 7-Zip to unpack the files. These arrive in a ZIPped and TARred archive. The data are comprised of 11 separate image files, along with a quality assurance file (BQA) and a text file with metadata (date and time, corner points-that sort of thing). Either use this sample data (184 MB ZIP archive) of the Oregon Cascades, or dip into the Landsat archive with my tutorial for Earth Explorer. The first step, of course, is to download some data. Believe it or not, this doesn’t require any tools more specialized than Photoshop (or any other image editing program that supports 16-bit TIFF images, along with curve and level adjustments). True-color Landsat 8 image collected August 13, 2013.Īlthough it’s possible to process all that data automatically, it’s best to process each scene individually to bring out the detail in a specific region. An area about 40% larger than the united states. Each of these scenes covers an area of about 185 by 185 kilometers (115 by 115 miles)-34,200 square km (13,200 square miles)-for a total of 13,690,000 square km (5,290,000 square miles) per day. Since its launch in February 2013, Landsat 8 has collected about 400 scenes of the Earth’s surface per day. ![]()
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