162
Chapter 18
land cover missions planned in the future which may provide more of this
type of data.
BRDF related activity in CSIRO EOC Research involves:
Data normalization (AVHRR, scanners, videos, air photographs,
calibrations sites, panels)
Atmospheric correction (AVHRR, scanners)
Determining land cover structure (photography, scanners), and
BRDF characterization.
Land cover structure is known to be a major factor in controlling the
BRDF shape, i.e., the magnitude of its reflectance variation with Sun and
look angle. The opportunity to use BRDF to establish and/or monitor land
cover structure is a major research and development task. However, there are
a number of areas where scene brightness R&D is already operational and
this paper is primarily concerned with them.
2.
DATA NORMALISATION & ATMOSPHERIC
CORRECTION
Data normalization and atmospheric correction activities are aimed at
achieving “seamless” mosaicking of video and scanner data as well as
normalization and standardization of satellite data—especially AVHRR and
future environmental satellite data. In the case of satellite applications,
calibration sites must have their BRDF characterized, and it is clear that field
panels used for reflectance measurements must also be carefully
characterized (EOC Discussion Paper, 1996). One pragmatic objective is to
produce base series of data that users now happy to use image processing
(such as filtering and classification) and are familiar with Spot and Landsat
can use with impunity. This has not been true of airborne data nor AVHRR
data in the past.
In current work of this kind around the world, there is an acceptance of
the key role of the ‘Kernel Function’ approach for which many applications
are near operational. In the kernel function approach, the land surface
brightness variation is modeled statistically by a class of simple functions.
Advanced examples of this is the AMBRALS model (which is really a set of
kernels of choice) being applied for the MODIS BRDF product (Strahler et
al., 1995; Wanner et al., 1995) and the RPV model being applied to the
MISR BRDF product (Rahman et al., 1993).
One outcome of the rising understanding of and capacity to model BRDF
in the last 10 to 15 years has been the wider acceptance and recognition of its
crucial role in atmospheric correction. The kernels approach has provided a
tool for BRDF to be introduced into standard atmospheric models, which
Chapter 18
land cover missions planned in the future which may provide more of this
type of data.
BRDF related activity in CSIRO EOC Research involves:
Data normalization (AVHRR, scanners, videos, air photographs,
calibrations sites, panels)
Atmospheric correction (AVHRR, scanners)
Determining land cover structure (photography, scanners), and
BRDF characterization.
Land cover structure is known to be a major factor in controlling the
BRDF shape, i.e., the magnitude of its reflectance variation with Sun and
look angle. The opportunity to use BRDF to establish and/or monitor land
cover structure is a major research and development task. However, there are
a number of areas where scene brightness R&D is already operational and
this paper is primarily concerned with them.
2.
DATA NORMALISATION & ATMOSPHERIC
CORRECTION
Data normalization and atmospheric correction activities are aimed at
achieving “seamless” mosaicking of video and scanner data as well as
normalization and standardization of satellite data—especially AVHRR and
future environmental satellite data. In the case of satellite applications,
calibration sites must have their BRDF characterized, and it is clear that field
panels used for reflectance measurements must also be carefully
characterized (EOC Discussion Paper, 1996). One pragmatic objective is to
produce base series of data that users now happy to use image processing
(such as filtering and classification) and are familiar with Spot and Landsat
can use with impunity. This has not been true of airborne data nor AVHRR
data in the past.
In current work of this kind around the world, there is an acceptance of
the key role of the ‘Kernel Function’ approach for which many applications
are near operational. In the kernel function approach, the land surface
brightness variation is modeled statistically by a class of simple functions.
Advanced examples of this is the AMBRALS model (which is really a set of
kernels of choice) being applied for the MODIS BRDF product (Strahler et
al., 1995; Wanner et al., 1995) and the RPV model being applied to the
MISR BRDF product (Rahman et al., 1993).
One outcome of the rising understanding of and capacity to model BRDF
in the last 10 to 15 years has been the wider acceptance and recognition of its
crucial role in atmospheric correction. The kernels approach has provided a
tool for BRDF to be introduced into standard atmospheric models, which