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The challenge has been the availability of accurate atmospheric measurements at appropriate scale, ensuring imagery can be normalized. WorldView-3 addresses this problem by being the first commercial imaging satellite with an atmospheric sensor as part of its payload. During image capture, the WorldView-3 atmospheric sensor is designed to detect the presence of clouds, aerosols and water vapor at 31 m resolution, thereby measuring the exact atmospheric conditions corresponding to every recorded image. Figure 1 shows how the atmospheric sensor has a slightly wider swath than the imaging swath. Maxar has developed proprietary algorithms that use these atmospheric measurements to normalize WorldView-3 imagery for consistency. This normalization is called atmospheric compensation, which is especially important for information extraction, such as change detection and vegetation analysis because changes due to the atmosphere have been removed. Atmospheric compensation results in surface-reflectance image data. Figure 2 shows an example of a surface-reflectance image aer atmospheric compensation. The Normalized Difference Vegetation Index (NDVI) from data without atmospheric compensation underestimates the amount of vegetation by about 10–13%. Another issue impairing automated information extraction is accurately mapping cloud cover. WorldView-3's sensors have spectral bands that range from the VNIR into the SWIR part of the EMS to accurately distinguish clouds from other bright features such as snow and ice. Figure 3 shows how the longer wavelengths in the SWIR range of the atmospheric sensor are able to penetrate fire smoke and haze. Figure 4 shows an example of a 2010 volcano in Iceland using WorldView-3 simulated data using the Hyperion sensor to differentiate between ash, ice and clouds. WorldView-3 is the first super-spectral satellite to simultaneously map atmospheric conditions during image collection, allowing unprecedented access to normalized imagery across the globe. Such standardization has introduced a new age in automated information extraction and change detection. Creating consistent imagery MOVING FROM PIXELS TO PRODUCTS FIGURE 3. Information from the longest wavelengths on WorldView-3 is able to penetrate much smoke and haze. NATURAL COLOR SWIR8 Smoke Cloud ACTIVE FIRE Cloud A B C FIGURE 2. A WorldView-2 image collected over Longmont, CO, on 10 August, 2011, was used to create (A) a true-color surface-reflectance image after atmospheric compensation, (B) an NDVI using TOA data, and (C) an NDVI using surface-reflectance. The NDVI from TOA data underestimates the relative amount of vegetation by about 10–13 percent. info@maxar.com maxar.com

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