Tl T5 T6 
5 1.1 5 1.3 10 2.5 
62.5 10 1.8 31.25} 10 2.2 15.625] 20 4.3 
5 1.6 5 1:7 10 2.8 
125 10 2.0 62.5 10 2.6 31.25 120 4.6 
Ain T os Ax in T %s Ax nin T s 
  
  
  
  
  
  
  
  
  
  
  
  
Table 1: Accuracy of progressive sampling and linear interpolation; all 
values are given in meters 
  
  
  
  
  
  
T1 T5 T6 
5 1.35 5 1.58 10 2.91 
62.5 10 2.26 31.251 10 3.023 15.625| 20 4.57 
5 1.38 5 1.62 10 3.06 
125 10 2.27 62.5 10 2.93 31.25 120 5.24 
Ax in T Og AX in T Og AX in T Og 
  
  
  
  
  
  
  
  
  
  
  
  
Table 2a: R.M.S.E. estimates from composed transfer function, a = 1/8 
  
  
  
  
  
  
Tl T5 T6 
5 1.0 5 1.3 10 2.9 
62.5 10 1.6 31.25] 10 2.4 15.625| 20 4.0 
5 1.4 5 1.4 10 3.1 
125 10 1.6 62.5 10 2.4 31.25 120 4.1 
AX in T Og AX in T Og AX in T Og 
  
  
  
  
  
  
  
  
  
  
  
  
Table 2b: R.M.S.E. estimates from composed transfer function, a = 1/10 
At least for the test sites used, the actual r.m.s.e. of the DEMs are 
smaller, in general, than the estimates computed with o = 1/8, and 
larger than those computed with o - 1/10. The estimates obtained with 
the composed transfer function using oa = 1/10 are closer to the actual 
r.m.s.e. than those with a = 1/8. Comparing table 2b with table 1, we 
find the largest discrepancy for Tl with a minimum grid spacing of 125 m 
and T = 10 m. There the power spectrum of the profile is computed from 
only 96 values (12000/125); thus it is likely to be affected by alias- 
ing, resulting in inferior estimates (see /11/). Whether composed 
transfer function and power spectrum of a profile also yield fair DEM 
accuracy estimates for real terrain must be verified by further 
investigations. If so, a simple procedure would be available for ac- 
curacy assessment, not requiring additional measurements. Computing the 
power spectrum by the Fast Fourier Transform algorithm relies on an 
equispaced sample. A profile extracted from a DEM created by PS, must 
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