Hyperspectral and LiDAR Data Fusion: Outcome of the 2013 GRSS Data Fusion Contest

Author

Debes, Christian ; Merentitis, A. ; Heremans, Roel ; Hahn, Juergen ; Frangiadakis, Nikolaos ; van Kasteren, Tim ; Wenzhi Liao ; Bellens, Rik ; Pizurica, Aleksandra ; Gautama, Sidharta ; Philips, Wilfried ; Prasad, Santasriya ; Qian Du ; Pacifici, F.

Author_Institution

AGT Int., Darmstadt, Germany

Volume

7

Issue

6

fYear

2014

fDate

Jun-14

Firstpage

2405

Lastpage

2418

Abstract

The 2013 Data Fusion Contest organized by the Data Fusion Technical Committee (DFTC) of the IEEE Geoscience and Remote Sensing Society aimed at investigating the synergistic use of hyperspectral and Light Detection And Ranging (LiDAR) data. The data sets distributed to the participants during the Contest, a hyperspectral imagery and the corresponding LiDAR-derived digital surface model (DSM), were acquired by the NSF-funded Center for Airborne Laser Mapping over the University of Houston campus and its neighboring area in the summer of 2012. This paper highlights the two awarded research contributions, which investigated different approaches for the fusion of hyperspectral and LiDAR data, including a combined unsupervised and supervised classification scheme, and a graph-based method for the fusion of spectral, spatial, and elevation information.

Keywords

geophysical image processing; graph theory; hyperspectral imaging; image classification; learning (artificial intelligence); remote sensing by radar; 2013 GRSS Data Fusion Contest; LIDAR derived digital surface model; airborne laser mapping; graph-based method; hyperspectral-LIDAR data fusion; unsupervised-supervised classification scheme; Data integration; Feature extraction; Hyperspectral imaging; Laser radar; Vegetation mapping; Data fusion; Light Detection And Ranging (LiDAR); VHR imagery; hyperspectral; multi-modal; urban;

fLanguage

English

Journal_Title

Selected Topics in Applied Earth Observations and Remote Sensing, IEEE Journal of

Publisher

ieee

ISSN

1939-1404

Type

jour

DOI

10.1109/JSTARS.2014.2305441

Filename

6776408