ALPMON FINAL REPORT - ARC systems research

Contract ENV4-CT96-0359 ALPMON
2.2.4 Radiometric Correction
Remote sensing data, from space borne or airborne platforms, of land or sea surface in the visible and
near infrared portion of the electromagnetic spectrum is strongly affected by the presence of the
atmosphere on the Sun-target-Sensor path. The data recorded usually do not represent the exact
reflectance from the target surface. This is due to radiometric effects which are partly sensor-related
such as instrument calibration, and those which are scene-related such as atmospheric, topographic,
illumination and view angle effects, and target reflectance characteristics. All of these effects place
limitations on the proper utilisation of the sensed data for targets recognition in the specific application.
In order to optimise information extraction from optically remote sensed data, radiometric correction is
necessary to compensate for the effects of (i) illumination conditions at the time of image acquisition,
(ii) image observation geometry, (iii) atmospheric phenomena and (iv) relief variations on the spectral
signatures of the targets, on the spectral signature of the objects. To correct for these effects,
normally, three prerequisites are to be met, namely (i) a radiometric calibration, (ii) an atmospheric
model, and (iii) a target reflectance model.
The above mentioned pre-processing requirements are applicable to remote sensing data used in all
applications that involve multi-temporal or multi-sensoral imagery. These pre-processing steps are also
necessary to the mere conversion of digital counts to radiance or reflectance units.
From the above mentioned facts, it is clear that radiometric correction is a pre-requisite to any accurate
quantitative interpretation of remote sensing data. It is one of the basic elements in the image analysis
data flow. The major processing categories in it are (i) radiometric calibration, (ii) atmospheric
correction and (iii) topographic correction.
2.2.4.1 Topographic Normalisation (WP6)
Since the project focused on applications within the alpine area, pre-processing of image data required
the correction of topographic effects. Topography does not only affect the geometric properties of an
image but will as well have an impact on the illumination and the reflection of the scanned area. This
effect is caused by the local variations of view and illumination angles due to mountainous terrain.
Therefore, identical land-cover might be represented by totally different intensity values depending on
its orientation and on the position of the sun at the time of data acquisition.
An ideal slope-aspect correction removes all topographically induced illumination variation so that two
objects having the same reflectance properties show the same digital number despite their different
orientation to the sun's position. As a visible consequence the three-dimensional relief impression of a
scene gets lost and the image looks flat.
In order to achieve this result several radiometric correction procedures have been developed. Besides
empirical approaches, such as image ratioing, which do not take into account the physical behavior of
scene elements, early correction methods were based on the Lambertian assumption, i.e. the satellite
images are normalized according to the cosine of the effective illumination angle (Smith et al. 1980).
However, most objects on the earth’s surface show non-Lambertian reflectance characteristics (Meyer
et al., 1993). Therefore the cosine correction had to be extended by introducing parameters, which
simulate the non-Lambertian behavior of the surface (Civco 1989, Colby 1990). The estimation of
these parameters is generally based on a linear regression between the radiometrically distorted bands
and a shaded terrain model. A comparison between four correction methods, including the nonparametric
cosine correction, confirms a significant improvement in classification results, when
applying the parametric models (Meyer et al. 1993).
There is a general agreement within the consortium that topographic normalisation leads to an
improvement of the image data in mountainous terrain. In particular the Minnaert correction produced
useful results. The C-correction seems not to be the appropriate solution, but rather tends to extreme
over-correction of steep slopes. However, all corrections were based on empirical analysis thus being
highly depending on the actual image data.
In spite of the good performance of the models some limitations are to be discussed. A prerequisite to
topographic normalisation is an accurate DEM and precisely geocoded image data. According to
Goodenough et al. (1990) and Itten et al. (1992) the spatial resolution of the DEM should be four times
higher than the spatial resolution of the image data. Using Landsat TM images the required cell size
would be less than 10m, for other image data such as SPOT or IRS-1C it would be even lower. In
general no such DEMs are available for larger regions. The consequence of using lower resolution
DEMs is the lack of topographic details within one grid cell which might disturb the correction locally.
JR, RSDE, ALU, LMU, Seibersdorf, WSL 19