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Article Dans Une Revue IEEE geoscience and remote sensing magazine Année : 2018

2018 IEEE GRSS Data Fusion Contest: Multimodal Land Use Classification [Technical Committees]

Résumé

The 2018 Data Fusion Contest, organized by the Image Analysis and Data Fusion Technical Committee (IADF TC) of the IEEE Geoscience and Remote Sensing Society (GRSS) and the University of Houston, Texas, seeks to promote progress on fusion and analysis methodologies for multiresolution and multimodal remote-sensing data. New data from complementary and novel sensors are being released, covering large areas with complex content. The following advanced multiresolution and multimodal optical remote-sensing data, acquired by the National Center for Airborne Laser Mapping (NCALM) at the University of Houston,are being provided to the community: * Multispectral light detecting and ranging (LiDAR) data have three simultaneous different optical wavelengths. For the sake of accessibility to various users, the data are available as point cloud data and digital surface models (DSMs) at a 0.5-m ground sampling dist a nce (G SD). * Hyperspectral data at a 1-m GSD cover a 380–1,050-nm spectral range with 48 contiguous bands. * Very-high-resolution red-green-blue imagery presents at a 5-cm GSD.
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hal-01851737 , version 1 (30-07-2018)

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Bertrand Le Saux, Naoto Yokoya, Ronny Hänsch, Saurabh Prasad. 2018 IEEE GRSS Data Fusion Contest: Multimodal Land Use Classification [Technical Committees]. IEEE geoscience and remote sensing magazine, 2018, 6 (1), pp.52-54. ⟨10.1109/MGRS.2018.2798161⟩. ⟨hal-01851737⟩
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