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Performance of WorldView-3. Nathan Longbotham1, Fabio Pacifici1, Seth Malitz1, William Baugh1, Gustau Camps-Valls2. 1DigitalGlobe, Longmont, CO, USA.
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FTS/HISE 2015 © OSA 2015

Measuring the Spatial and Spectral Performance of WorldView-3 Nathan Longbotham1, Fabio Pacifici1, Seth Malitz1, William Baugh1, Gustau Camps-Valls2 1

DigitalGlobe, Longmont, CO, USA

2

University of Valencia, Valencia, Spain

Abstract: The new WorldView-3 satellite provides a unique combination of very high spatial resolution and super-spectral capabilities. This presentation explores the practical and theoretical usefulness of this platform as compared against other hyperspectral and multispectral sensors. OCIS codes: 280.0280, 280.4788, 280.4991

The recently launched WorldView-3 satellite is designed to collect unique data by combining very high spatial resolution (VHR) with observation bands in the visible and near-infrared (VNIR) as well as the short wave infrared (SWIR). This new sensing platform is similar to WorldView-2 with two important additions: a dedicated SWIR sensor and the CAVIS (Clouds, Aerosols, water Vapor, Ice and Snow) sensor. This creates a super-spectral platform with veryhigh spatial resolution observations in the SWIR (eight bands at 3.7 m pixel size), multispectral VNIR (eight bands at 1.2 m pixel size), and panchromatic VNIR (one band at 0.3 m pixel size) in addition to the combined VNIR/SWIR CAVIS (12 bands at 30 m pixel size) sensor. The relative positions of the WorldView-3 bands are illustrated in Fig. 1. With a possible revisit time of less than one day and positional accuracy of 3.5 m CE90 (or better) without ground control points, the WorldView-3 platform is well positioned to provide high resolution, timely, and accurate insight to multiple applications, such as mineral exploration, agricultural mapping, and urban monitoring. Previous work using pre-launch simulated WorldView-3 data has shown that the spectral content of the WorldView-3 platform can be competitive to the performance of hyperspectral sensors for common image analysis applications [1]. A separate group of researchers also demonstrated promising uses cases for the new platform by focusing on the capabilities of simulated WorldView-3 data for mineral mapping applications [2]. The current presentation extends this previous work by: (1) Validating previous prelaunch results on real WorldView-3 data and (2) leveraging the spatial content of the WorldView-3 platform, in addition to the spectral information, for a more generalized comparison of information content. The information content available from the WorldView-3 platform is explored in two ways. First, statistical estimates are utilized to measure the data information content and, second, image classification performance is compared against other platforms.

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Fig. 1. The relative band positions, and spatial resolutions, of the WorldView-3 spectral bands. References 1. N. Longbotham, F. Pacifici, B. Baugh, and G. Camps-Valls, “Prelaunch Assessment of WorldView-3 Information Content,” in “6th Work. Hyperspectral Image Signal Process. Evol. Remote Sens. WHISPERS,” (Lausanne, Switzerland, 2014). 2. F. Kruse and S. Perry, “Mineral Mapping Using Simulated Worldview-3 Short-Wave-Infrared Imagery,” Remote Sens. 5, 2688–2703 (2013).