276
J.e. Ritchie
with the USLE or RUSLE to determine erosion rates and pattern. Other models could
be substituted for the USLE in this schematic to provide the output needed. Many
remote sensors are potential suppliers of data for the USLE and GIS layers. Photointerpretation and image classification of photographs and spectral images are commonly used to provide input for the crop management factor (C) and soil erosion
control practice factor (P) of the USLE. Photogrammetric techniques provide input
for calculating the slope length factor (L) and steepness factor(S). Airborne lasers and
Synthetic Aperture Radar (SAR) could also provide data for calculating the slope
length factor (L) and steepness factor(S). Photographs and spectral images could
provide data on soil properties and provide the basis for spatially distributing the
erodability factor (K). While for the USLE the rainfall factor (R) is based on typical
rainfall patterns and rates for an area, for other models radar could provide information on rainfall rates and patterns needed for input for calculating erosion on a storm
event basis. Information on all the factors for the USLE is available from non remote
sensing sources. However, by combining remote sensing data with conventional data
a better understanding of the spatial patterns of the factors may be determined. By
using the different GIS data layers determined conventionally or with remote sensing
as input to soil erosion models, soil erosion rates and patterns can be spatially
distributed with GIS techniques. Other techniques can also be used to combine the
GIS data layer to evaluate soil erosion rates and patterns. Examples of the use of GIS
and remote sensing data in natural resource management are given by Ripple (1994).
Remote
Sensing
Data
USLE
Factors
(Ground, Aircraft, Satellite)
SAR
Erosion Model (S)
Photographic
ectra
:
Geographic Informations System (GIS)
:
, -- - - - - - - - - - - - - - - - - - - s-- - - - - - - - - - - - - - - - - - - Z ---------------- '
Output I
Rates and Patterns of Erosion
I
Fig. 12.2. Schematic representation of potential remote sensing data input to USLE. Input for other
erosionihydrology models would be similar
12.4 Case Studies
The application of remote sensing techniques to study and monitor soil erosion can
be divided into the following general approaches: photo interpretation / photo gram-
J.e. Ritchie
with the USLE or RUSLE to determine erosion rates and pattern. Other models could
be substituted for the USLE in this schematic to provide the output needed. Many
remote sensors are potential suppliers of data for the USLE and GIS layers. Photointerpretation and image classification of photographs and spectral images are commonly used to provide input for the crop management factor (C) and soil erosion
control practice factor (P) of the USLE. Photogrammetric techniques provide input
for calculating the slope length factor (L) and steepness factor(S). Airborne lasers and
Synthetic Aperture Radar (SAR) could also provide data for calculating the slope
length factor (L) and steepness factor(S). Photographs and spectral images could
provide data on soil properties and provide the basis for spatially distributing the
erodability factor (K). While for the USLE the rainfall factor (R) is based on typical
rainfall patterns and rates for an area, for other models radar could provide information on rainfall rates and patterns needed for input for calculating erosion on a storm
event basis. Information on all the factors for the USLE is available from non remote
sensing sources. However, by combining remote sensing data with conventional data
a better understanding of the spatial patterns of the factors may be determined. By
using the different GIS data layers determined conventionally or with remote sensing
as input to soil erosion models, soil erosion rates and patterns can be spatially
distributed with GIS techniques. Other techniques can also be used to combine the
GIS data layer to evaluate soil erosion rates and patterns. Examples of the use of GIS
and remote sensing data in natural resource management are given by Ripple (1994).
Remote
Sensing
Data
USLE
Factors
(Ground, Aircraft, Satellite)
SAR
Erosion Model (S)
Photographic
ectra
:
Geographic Informations System (GIS)
:
, -- - - - - - - - - - - - - - - - - - - s-- - - - - - - - - - - - - - - - - - - Z ---------------- '
Output I
Rates and Patterns of Erosion
I
Fig. 12.2. Schematic representation of potential remote sensing data input to USLE. Input for other
erosionihydrology models would be similar
12.4 Case Studies
The application of remote sensing techniques to study and monitor soil erosion can
be divided into the following general approaches: photo interpretation / photo gram-