Fusion of LiDAR and Hyperspectral Data

The dataset is captured over Samford Ecological Research
Facility (SERF), which is located within the Samford valley in south east
Queensland, Australia. The central point of the dataset is located at
coordinates: 27.38572oS, 152.877098oE. The Vegetation Management
Act 1999 protects the vegetation on this property as it provides a refuge
to native flora and fauna that are under increasing pressure caused by urbanization.
The hyperspectral image was acquired by the SPECIM AsiaEAGLE II
sensor on the second of February, 2013. This sensor captures 252 spectral
channels ranging from 400.7nm to 999.2nm. The last five channels,
i.e., channels 248 to 252, are corrupted and can be excluded. The spatial
resolution of the hyperspectral data was set to 1m.
The airborne light detection and ranging (LiDAR) data were captured
by the ALTM Leica ALS50-II sensor in 2009 composing of a total of 3716157
points in the study area: 2133050 for the first return points, 1213712 for the
second return points, 345.736 for the third return points, and 23659 for the
fourth return points.
The average flight height was 1700 meters and the average point
density is two points per square meter. The laser pulse wavelength is 1064nm
with a repetition rate of 126 kHz, an average sample spacing of 0.8m
and a footprint of 0.34m. The data were collected up to four returns per
pulse and the intensity records were supplied on all pulse returns.
The nominal vertical accuracy was ±0.15m at 1 sigma and the
measured vertical accuracy was ±0.05m at 1 sigma. These values have been
determined from check points contrived on an open clear ground. The measured
horizontal accuracy was ± 0.31m at 1 sigma.
The obtained ground LiDAR returns were interpolated and rasterized
into a 1m×1m digital elevation model (DEM) provided by the LiDAR
contractor, which was produced from the LiDAR ground points and interpolated
coastal boundaries.
The first returns of the airborne LiDAR sensor were utilized to
produce the normalized digital surface model (nDSM) at 1m spatial
resolution using Las2dem.
The 1m spatial resolution intensity image was also produced
using Las2dem. This software interpolated the points using triangulated
irregular networks (TIN). Then, the TINs were rasterized into the nDSM and the
intensity image with a pixel size of 1m. The intensity image with 1m
spatial resolution was also produced using Las2dem.
The LiDAR data were classified into ``ground" and
``non-ground" by the data contractor using algorithms tailored especially
for the project area. For the areas covered by dense vegetation, less laser
pulse reaches the ground. Consequently, fewer ground points were available for
DEM and nDSM surfaces interpolation in those areas. Therefore, the DEM and the
nDSM tend to be less accurate in these areas.
In order to use the datasets, please fulfill the following three
requirements:

1) Giving an acknowledgement as follows:

The authors gratefully acknowledge TERN AusCover and Remote
Sensing Centre, Department of Science, Information Technology, Innovation and
the Arts, QLD for providing the hyperspectral and LiDAR data, respectively. Airborne lidar are from http://www.auscover.org.au/xwiki/bin/view/Product+pages/Airborne+Lidar
Airborne hyperspectral are from  http://www.auscover.org.au/xwiki/bin/view/Product+pages/Airborne+Hyperspectral

2) Using the following license for LiDAR and hyperspectral data:

http://creativecommons.org/licenses/by/3.0/
3) This dataset was made public by Dr. Pedram Ghamisi from German Aerospace Center (DLR) and Prof. Stuart Phinn
from the University of Queensland. Please cite: 
In WORD:
Pedram Ghamisi and Stuart Phinn, Fusion of LiDAR and Hyperspectral Data, Figshare, December 2015, https://dx.doi.org/10.6084/m9.figshare.2007723.v3
In LaTex:
@article{Ghamisi2015,
author = "Pedram Ghamisi and Stuart Phinn",
title = "{Fusion of LiDAR and Hyperspectral Data}",
journal={Figshare},
year = {2015},
month = {12},
url = "10.6084/m9.figshare.2007723.v3",

}