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J.C. Ritchie
the landscape topography and may have potential applications for evaluating largescale soil erosion patterns and rates.
While remote sensing data can be used alone to access soil erosion rates and patterns, a combination of remote sensing data, soil erosion models, and Geographic
Information Systems (GIS) has much to offer in understanding and measuring the
effects of soil erosion on the landscape. GIS tools allow researchers or decision
makers to combine the spectral, spatial, and temporal characteristics of remotely
sensed data with ancillary data about the landscape and use these many sources as
input to erosion models to quantify rates and patterns of soil erosion. GIS tools
provide the spatial pattern of erosion needed by decision makers for carrying out
management practices to reduce soil erosion on the landscape.
Many early applications of remote sensing for mapping soil erosion and degradation patterns were discussed by Dubucq (1986). He found publications from 1973
using Landsat Multispectral Scanner (MSS) data to map soil erosion prone areas.
Most of the papers cited by Dubucq used photointerpretation techniques to make
maps of potential and actual eroded areas.
12.3 Applications
Photo interpretation remains the most commonly applied remote sensing technique for
studying and mapping soil erosion across the landscape. Photointerpretation has been
defmed as the science of identifying and describing objects imaged on a photograph
and determining their significance (Philipson 1997). Some argue that this is as much
art as science. Photo interpretation is based on the ability of the observer to identify
and delineate objects based on pattern, texture, and color from a photograph. Photointerpreted objects are often noted on the photograph and later transferred to maps.
Such maps are analyzed to determine the eroding area and changes in eroding area (or
other interpreted objects). These changes in eroded area can be determined by
photointerpreting sequential images and plotting changes on a map. More information
about photo interpretation can be obtained from many sources (e.g. Philipson 1997).
Photogrammetry is also widely use for studying and mapping soil erosion. Photogrammetry has been defmed as the science, art, and technology of obtaining reliable
information about physical objects and the environment from photographs (Greve
1996). The principle of the photogrammetric technique is shown in Fig. 12.1.
Photogrammetry has been widely used to measure changes in landscape surfaces for
topographic mapping and to determine gully erosion, rill development, and erosional
losses. Using photogrammetric techniques on sequential photographs allows the
determination of eroding and depositing area on the landscape. More information
about photogrammetric techniques can also be obtained from many sources (e.g.
Greve 1996).
A wide range of digital data with differing spectral and spatial resolution are available from aircraft and satellite platforms. These data can be used to make images for
photo interpretation or can be analyzed spectrally to evaluate soil erosion rates and
patterns. These digital data need to be georeferenced and corrected for atmospheric
interference for best results. Computer software programs are available to correct,
J.C. Ritchie
the landscape topography and may have potential applications for evaluating largescale soil erosion patterns and rates.
While remote sensing data can be used alone to access soil erosion rates and patterns, a combination of remote sensing data, soil erosion models, and Geographic
Information Systems (GIS) has much to offer in understanding and measuring the
effects of soil erosion on the landscape. GIS tools allow researchers or decision
makers to combine the spectral, spatial, and temporal characteristics of remotely
sensed data with ancillary data about the landscape and use these many sources as
input to erosion models to quantify rates and patterns of soil erosion. GIS tools
provide the spatial pattern of erosion needed by decision makers for carrying out
management practices to reduce soil erosion on the landscape.
Many early applications of remote sensing for mapping soil erosion and degradation patterns were discussed by Dubucq (1986). He found publications from 1973
using Landsat Multispectral Scanner (MSS) data to map soil erosion prone areas.
Most of the papers cited by Dubucq used photointerpretation techniques to make
maps of potential and actual eroded areas.
12.3 Applications
Photo interpretation remains the most commonly applied remote sensing technique for
studying and mapping soil erosion across the landscape. Photointerpretation has been
defmed as the science of identifying and describing objects imaged on a photograph
and determining their significance (Philipson 1997). Some argue that this is as much
art as science. Photo interpretation is based on the ability of the observer to identify
and delineate objects based on pattern, texture, and color from a photograph. Photointerpreted objects are often noted on the photograph and later transferred to maps.
Such maps are analyzed to determine the eroding area and changes in eroding area (or
other interpreted objects). These changes in eroded area can be determined by
photointerpreting sequential images and plotting changes on a map. More information
about photo interpretation can be obtained from many sources (e.g. Philipson 1997).
Photogrammetry is also widely use for studying and mapping soil erosion. Photogrammetry has been defmed as the science, art, and technology of obtaining reliable
information about physical objects and the environment from photographs (Greve
1996). The principle of the photogrammetric technique is shown in Fig. 12.1.
Photogrammetry has been widely used to measure changes in landscape surfaces for
topographic mapping and to determine gully erosion, rill development, and erosional
losses. Using photogrammetric techniques on sequential photographs allows the
determination of eroding and depositing area on the landscape. More information
about photogrammetric techniques can also be obtained from many sources (e.g.
Greve 1996).
A wide range of digital data with differing spectral and spatial resolution are available from aircraft and satellite platforms. These data can be used to make images for
photo interpretation or can be analyzed spectrally to evaluate soil erosion rates and
patterns. These digital data need to be georeferenced and corrected for atmospheric
interference for best results. Computer software programs are available to correct,