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MOVING FROM PIXELS TO PRODUCTS white paper Moving from pixels to products After more than 40 years, the remote sensing community continues to address the two fundamental challenges when using Earth imagery at a global scale: automated information extraction and change detection. Maxar's WorldView-3 satellite was developed by Ball Aerospace in Denver, CO, and was designed to address these challenges by creating consistent datasets as well as providing unique information for agriculture, forestry, mining/geology and other applications. WorldView-3 is the first commercial satellite to have 16 high-resolution spectral bands that capture information in the visible and near-infrared (VNIR) and short-wave infrared (SWIR) regions of the electromagnetic spectrum (EMS). Operating at an altitude of 617 km, the satellite provides 31 cm panchromatic resolution, 1.24 m VNIR resolution, and 3.7/7.5 m SWIR resolution, according to our operating licenses (Department of Commerce). WorldView-3 builds upon WorldView-2's unique VNIR capabilities, providing eight additional spectral bands farther into the SWIR portion of the EMS. This spectral expansion enhances WorldView-3's capability to capture the uniqueness of each ground material's spectral signature. Due to minimal atmospheric influence or noise in this part of the EMS, as well as an enhanced ability to differentiate among ground materials, the SWIR bands open the door for automated information extraction to save time, money and possibly lives. Doubling the spectral bands Remote sensing satellites view Earth from above the atmosphere to provide top-of-atmosphere (TOA) measurements of the Earth's features. Changes in the atmosphere, sun illumination and viewing geometries during image capture result in inconsistent image data, hindering automated information extraction and change detection. Atmospheric conditions typically change during and between different imagery collections due to moisture levels (water vapor) and particulates (aerosols) in the atmosphere. Much research has been done trying to accurately convert the TOA measurements to surface reflectance measurements. Several models have been developed to compensate for these atmospheric conditions and the viewing geometries of various satellites. The remote sensing research community has created normalized indices to counter some atmospheric conditions with limited success. Creating consistent imagery for automated information extraction FIGURE 1. WorldView-3's atmospheric sensor has a slightly wider swath than its imaging swath. imagery sensor atmospheric sensor info@maxar.com maxar.com