12 Soil Erosion
283
or to estimate a variable for input into a soil erosion model. Future uses of remote
sensing data for delineating areas with soil erosion and estimating variables should
increase as new sensors (e.g. EarlyBird, Resources2l, etc.; Corbley 1996) with higher
spatial (1-2 meters) and spectral (100+ wavebands) resolutions are launched. The
higher spatial resolution will permit measurements on smaller areas that are most
important for understanding and quantifying the processes of soil erosion at the field
level. Better spectral resolution may allow us to derive spectral signatures for eroded
areas that are specific for degraded soils and allow better delineation of soil erosion
patterns across the landscape. However, spectral patterns for eroded soils may be site
specific and require a definition of soil properties to be successfully used.
The continued development of scanning laser technology with higher spatial and
vertical accuracies will provide another source of data on topography that will be
useful in measuring centimeter difference due to soil erosion. Krabill et al. (1995)
used a scanning laser altimeter to measure the surface terrain of the Greenland ice
sheet and estimated accuracies of -20 cm for several 1000 kilometers of flight lines.
These measurements were used to study the dynamics of the Greenland ice sheet. Hug
(1996) used a similar scanning laser system to measure urban topography. A scanning
laser altimeter is schedule to be launched on a space platform in 2002. With such
measurements and updating of changes in topography, we can better quantifY soil loss
and have data for understanding the dynamics of water and wind flow across the
landscape.
The fast developing field of Synthetic Aperture Radar (SAR) interferometry (Gens
and van Genderen 1996) with applications to topographic mapping and digital
elevation modeling (DEM) also holds great promise for providing a new source of
data for quantifying soil erosion. SAR data are available from aircraft and satellite
(ERSlIERS2) instruments to begin research. Again the updating of changes in
topography is key for quantifying soil erosion.
Combining these new sources of data with Geographic Information Systems should
provide many new insights into the problems of soil erosion and provide a basis for
quantifying soil loss using remotely sensed data. The future has much to offer in
application of remote sensing data to understanding the role of soil erosion on the
landscape. New sensors and tools will allow the researchers and decision makers to
use improved spectral, spatial, and temporal characteristics of remotely sensed data
and ancillary data with models and GIS for understanding and quantifying patterns
of soil erosion. Management decisions can be based on actual soil erosion rates thus
allowing efforts to reduce soil erosion to be targeted to critical soil erosion areas in
the catchment.
References
Agassi, M. (ed.): Soil erosion, conservation and rehabilitation, New York, Marcel Dekker, Inc (1995)
Biard, F., Baret, F.: Crop residue estimate using multiband reflectance. Remote Sens, Environ. 59,
530-536 (1997)
Bertuzzi, P., Caussignac, J.M., Stengel, P., Morel, G., Lorendeau, J.Y., Pelloux, G.: An automated,
noncontact laser profile meter for measuring soil roughness in situ. Soil Sci. 149, 169-178 (1990)
283
or to estimate a variable for input into a soil erosion model. Future uses of remote
sensing data for delineating areas with soil erosion and estimating variables should
increase as new sensors (e.g. EarlyBird, Resources2l, etc.; Corbley 1996) with higher
spatial (1-2 meters) and spectral (100+ wavebands) resolutions are launched. The
higher spatial resolution will permit measurements on smaller areas that are most
important for understanding and quantifying the processes of soil erosion at the field
level. Better spectral resolution may allow us to derive spectral signatures for eroded
areas that are specific for degraded soils and allow better delineation of soil erosion
patterns across the landscape. However, spectral patterns for eroded soils may be site
specific and require a definition of soil properties to be successfully used.
The continued development of scanning laser technology with higher spatial and
vertical accuracies will provide another source of data on topography that will be
useful in measuring centimeter difference due to soil erosion. Krabill et al. (1995)
used a scanning laser altimeter to measure the surface terrain of the Greenland ice
sheet and estimated accuracies of -20 cm for several 1000 kilometers of flight lines.
These measurements were used to study the dynamics of the Greenland ice sheet. Hug
(1996) used a similar scanning laser system to measure urban topography. A scanning
laser altimeter is schedule to be launched on a space platform in 2002. With such
measurements and updating of changes in topography, we can better quantifY soil loss
and have data for understanding the dynamics of water and wind flow across the
landscape.
The fast developing field of Synthetic Aperture Radar (SAR) interferometry (Gens
and van Genderen 1996) with applications to topographic mapping and digital
elevation modeling (DEM) also holds great promise for providing a new source of
data for quantifying soil erosion. SAR data are available from aircraft and satellite
(ERSlIERS2) instruments to begin research. Again the updating of changes in
topography is key for quantifying soil erosion.
Combining these new sources of data with Geographic Information Systems should
provide many new insights into the problems of soil erosion and provide a basis for
quantifying soil loss using remotely sensed data. The future has much to offer in
application of remote sensing data to understanding the role of soil erosion on the
landscape. New sensors and tools will allow the researchers and decision makers to
use improved spectral, spatial, and temporal characteristics of remotely sensed data
and ancillary data with models and GIS for understanding and quantifying patterns
of soil erosion. Management decisions can be based on actual soil erosion rates thus
allowing efforts to reduce soil erosion to be targeted to critical soil erosion areas in
the catchment.
References
Agassi, M. (ed.): Soil erosion, conservation and rehabilitation, New York, Marcel Dekker, Inc (1995)
Biard, F., Baret, F.: Crop residue estimate using multiband reflectance. Remote Sens, Environ. 59,
530-536 (1997)
Bertuzzi, P., Caussignac, J.M., Stengel, P., Morel, G., Lorendeau, J.Y., Pelloux, G.: An automated,
noncontact laser profile meter for measuring soil roughness in situ. Soil Sci. 149, 169-178 (1990)