Volume XLII-2/W13
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2/W13, 1849-1854, 2019
https://doi.org/10.5194/isprs-archives-XLII-2-W13-1849-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2/W13, 1849-1854, 2019
https://doi.org/10.5194/isprs-archives-XLII-2-W13-1849-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.

  05 Jun 2019

05 Jun 2019

THE SUPERSPECTRAL/HYPERSPATIAL WORLDVIEW-3 AS THE LINK BETWEEN SPACEBORNE HYPERSPECTRAL AND AIRBORNE HYPERSPATIAL SENSORS: THE CASE STUDY OF THE COMPLEX TROPICAL COAST

A. M. Collin1,2, M. Andel3, D. James1, and J. Claudet4 A. M. Collin et al.
  • 1EPHE, PSL Université Paris, 35800 Dinard, France
  • 2LabEx CORAIL, Moorea, French Polynesia
  • 3DigitalGlobe Foundation, 80234 Westminster, Colorado, USA
  • 4National Center for Scientific Research, PSL Université Paris, CRIOBE, 75005 Paris, France

Keywords: WorldView-3, Hyperion, UAV, Superspectral, Coral Reefs, Moorea Island

Abstract. Earth observation of complex scenes, such as coastal fringes, is based on a plethora of optical sensors constrained by trade-offs between spatial, spectral, temporal and radiometric resolution. The spaceborne hyperspectral EO-1 Hyperion sensor (decommissioned in 2017) was able to acquire imagery with 10 nm spectral (220 bands) at 30 m spatial resolutions over 1424.5 km2 scenes. Conversely, the widespread unmanned airborne vehicle (UAV) hyperspatial DJI Mavic Pro camera can collect only natural-coloured imagery of 100 nm spectral (3 bands) but at 0.1 m spatial resolution over ∼10 km2 scenes (with a single battery and calm meteo-marine conditions). The spaceborne WorldView-3 (WV3), featured by 60 nm spectral (16 bands) at 0.3 m spatial resolution (when pansharpened) over 1489.6 km2 scenes, has the capacity to bridge both sensors. This study aims at testing the spectral and spatial performances of the WV3 to discriminate 10 complex coastal classes, ranging from ocean, reefs and terrestrial vegetation in Moorea Island (French Polynesia). Our findings show that geometrically- and radiometrically-corrected 0.3-m 16-band WV3 bands competed with (30-m) 167-band Hyperion performance for classifying 10 coastal classes with 2-neuron artificial neural network modelling, while being able to segment objects seized by 0.1-m (3-band) UAV. Unifying superspectral and hyperspatial specificities, the WV3 also leverages hypertemporal resolution, that is to say 1-day temporal resolution, rivalling UAV’s one.