Performance of WorldView-3. Nathan Longbotham1, Fabio Pacifici1, Seth Malitz1, William Baugh1, Gustau Camps-Valls2. 1DigitalGlobe, Longmont, CO, USA.
HW3B.2.pdf
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.
Visible Near InfraRed (VNIR) 1.2 meter
Short Wave InfraRed (SWIR) 3.7 meter
CAVIS (Cloud, Aerosol, Water Vapor, Ice & Snow) 30 meter 300
500
700
900
1100
1300 1500 Wavelength (nm)
1700
1900
2100
2300
2500
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).
