IEEE Geoscience and Remote Sensing Magazine - June 2013 - 8

Published Items in Each Year
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Hyperspectral

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Radar

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FIGURE 1. Paper counts per year in hyperspectral and radar topics obtained by searching the SCI-Expanded database of the ISI Web-OfScience with the following topics: (a) hyperspectral and remote sensing; (b) radar and remote sensing. Search done on January 2013.

X
Soil

Veg
n2
Water

nb
n1
(a)
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(b)
FIGURE 2. (a) Hyperspectral imaging concept. (b) Hyperspectral
vectors represented in a low-dimensional manifold.

function. To account for this, first a radiometric calibration
of the spectra is generally performed to obtain at-sensor or
top-of-atmosphere (TOA) radiance values. As the reflected
sunlight passes through the atmosphere, it gets partially
absorbed and scattered. Since these effects have a huge
influence on the spectral values, they need to be corrected
to obtain the ground-leaving radiance or reflectance values
8

[9]. Finally, one has to account for the effects of illumination
and viewing angle and the surfaces structural and optical
properties, to lead to the surface reflectance values.
The interactions of the light with the atmosphere are
extremely complex. The radiative transfer theory is often
used to derive models for these interactions [10]. Originally
developed for simulating TOA radiance for the preparation of future satellite missions, inversion of these models
allows for atmospheric correction. The bidirectional reflectance distribution functions (BRDF) describe the reflected
light on a surface as a function of the incoming and outgoing light directions. A first approximation for the BRDF,
termed 'albedo', is the ratio between the reflectance and
the sun's irradiance. BRDF's are usually accompanied by
complex surface structure models such as leaf-to-canopy
models. A schematic overview of the spectral characteristics of hyperspectral data is given in Fig. 3. We remark that,
besides for the conversion to surface reflection, all these
models are relevant as well for quantitative analysis (see
Sections III and VI).
For illustrative purposes, Table 1 displays spatial and
spectral parameters of eight hyperspectral instruments:
two airborne (HYDICE1 and AVIRIS2) and six spaceborne
(HYPERION3, EnMAP4, PRISMA 5, CHRIS6, HyspIRI7 and
IASI8). From this list, EnMAP, PRISMA and HyspIRI are

http://rsd-www.nrl.navy.mil/hydice
http://aviris.jpl.nasa.gov
3
http://eo1.usgs.gov
4
http://www.enmap.org
5
http://www.asi.it/en/flash en/observing/prisma
6
https://earth.esa.int/web/guest/missions/esa-operational-eo-missions/
proba
7
http://hyspiri.jpl.nasa.gov
8
http://smsc.cnes.fr/IASI
2

ieee Geoscience and remote sensinG maGazine

june 2013

http://hyspiri.jpl.nasa.gov

Table of Contents for the Digital Edition of IEEE Geoscience and Remote Sensing Magazine - June 2013