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International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol XXXV, Part B4. Istanbul 2004 
  
Plate 3: The fields on this hill, which is located in the 
mountainous area just to the south of the Syrian 
border, were the steepest surveyed in the verification 
exercise. The steepest slope angle was 6.1?. These 
fields probably represent the steepest in the entire 
study area, and have only been brought into cultivation 
in the last 3-4 years. 
  
   
Plate 1: Sedimentation in the lower part of a field. The 
buried stones show the impact of sediment 
accumulation. Desiccation cracking is a result of the 
high silt and clay content of these sediments. 
     
The statistical method used to provide verification of 
the application of RUSLE in the study area compares 
predicted soil losses and evidence of rilling. The 
predicted soil losses were derived from the RUSLE 
for the geographical co-ordinates of the fields 
surveyed. A Chi-squared analysis was applied to 
contingency tables of predicted soil losses for 
categories of individual fields and evidence of rilling. 
Chi-square test was run on the above contingency 
table after combining the categories. The value of the 
chi-square is 12.175, this is, just, less than the critical 
value of 13.28 of the chi-square with significance 
level 0.01. The results of the chi-square therefore 
provide weak support for veracity of the application 
of the RUSLE in the study area. However more work 
is required to provide convincing support. 
3.3.2 Quality Assessment: R 
factor. The rainfall station density in the study area (1 
station per 200 km?), though low, meets the WMO 
(World Meteorological Organization) standard of 1 
station per 250 km? (Shaw, 1983). The locational 
errors in this layer will be low given that it is a simple 
linear extrapolation, and the accuracy of resulting 
  
     
   
        
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layer will be determined by the accuracy of the 
computer and software. 
K factor. The soil association maps were published by 
the Ministry of Agriculture of Jordan in 1994 at 
1:250.000. They were produced in digital form by the 
same ministry in cooperation with the Royal 
Jordanian Geographic Center. 
LS factor. The accuracy of the DEM built by 
interpolation from topographic maps with contours 
drawn at 40 m interval, is determined by the x, y and 
z accuracy of the topographic maps. The most 
common measure for the quality of a map feature is 
its relative and absolute positional accuracy. The 
topographic maps available for this study conform to 
the RJGC (Jordan) map accuracy standards. 
C factor. For mapping the land cover in the 1970's, 
Landsat Multi-spectral Scanner (MSS) data (56 x 79 
m?) were available. However, land cover mapping for 
the 1990 year was carried out by the processing of 
finer resolution Landsat Thematic Mapper (TM) data 
(30 x 30 m?) The calibration of the NDVI and 
fractional vegetation cover images from spectral 
unmixing with vegetation cover data relies on ground 
sampling of vegetation that was not collected 
simultaneously with the imagery. Calibration data 
between remotely sensed data and biogeophysical 
variables have relatively low accuracies, and this will 
be the case in this study. It is likely that the greatest 
errors like are in the C factor layers. However, as this 
is a reconnaissance study the C factor layers probably 
show the relative spatial and inter-annual variations in 
vegetation cover that are appropriate to the 
investigation. 
P factor. The only error surrounding the P factor 
would be that some management practices for soil 
conservation had been omitted from the analysis. 
This is extremely unlikely given the prevailing 
farming systems. 
4. CONCLUSION 
A visual analysis of the series of maps of soil losses 
indicates that the most critical factors in the RUSLE 
were: 
e The topographic (LS) factor; and 
e The soil erodibility (K) factor. 
Though in the case of irrigated agriculture the C 
factor is also important. 
Overall there was a 4.2% increase in the predicted 
soil loss from the study area between 1972 and 1992. 
There is not enough support for the contention that 
rates of overall soil loss are accelerating. It is likely 
that these numbers lie within the likely error margin 
of the modeling. 
Verification of the model was attempted by 
comparing predicted soil losses with quantitative and 
qualitative data obtained from 47 fields in the study