is
ont
che
C BHO (DDH QS
the I-subsets;
. Discrete points, sampled stationary
. Strings of points, sampled dynamically
- The standard error o of modelling by the
I set, which can be differentiated further
according to the successive densification runs.
The standard error o, of modelling by the X set
can be differentiated further according to
accuracy, and comprehensiveness.
ag ;
Ü comprehensiveness (o)
X
c
accuracy (93)
. Comprehensiveness co. of the I-set depends on the
completeness of Z-Set (which features should be
sampled and up to what extent), which depends
on:
. The criterion to detect non linearity in
terrain relief
. Threshold used in the criterion
. Accuracy o. of modelling by the I-set depends
on:
. Image quality and scale
. Precision of instrument
. Operator skill and care
Sampling mode (stationary, dynamically)
The standard error on of modelling by the E-set
depends on:
. Apriory I-set and Op
. Grid interval
. Pointing error
. Interpolation algorithm
Because the skeleton information is sampled prior
to the filling information, it has an influence on
the I-set, thus Z-set affects strongly the further
modelling process.
3.2 Sources of errors
The accuracy of terrain relief modelling is
influenced by two main sources of errors:
. Error of sampling and interpolation 0.»
mentioned earlier
. Measuring error c , depending on; setting error,
the quality of photography, type of terrain,
model scale, precision of the instrument, and
the skill and care of the operator.
Assuming f(x) is the terrain profile, and fi (x)
is the correct height of a point and gi (X) is the
sampled height:
gi (x) = f. (x) + m, (x) (12)
In photogrammetric measurement m, (x) is considered
partly systematic, and partly random, thus the
latter part of m, (x), can be defined as a sequence
of uncorrelated values, which are normally
distributed, with the mean equal to zero and the
variance 62
Assuming that f.(x) and m, (x) are mutually
independent and thüs uncorrelated, the variance of
the error of the modelling is:
2 = 2
Op =0 s e (13)
where c is the error of sampling and
interpolaËion, and o. is caused by the On
81
In (Tempfli, 1986) it has been found that there is
a simple relation;
o2, = 2/3 Ax? oz (14)
In the case of a regular grid and in the absence
of measuring error, the error of sampling and
interpolation can be defined as (Tempfli, 1986);
n/2 -1
e = I { 1 - H(vk) }2 (15)
k=-n/2
Where |F(k)| is the discrete amplitude spectrum of
the input obtained by FFT.
3.3 Estimation of the sampling error oc.
Accuracy of DIM can be estimated by analytical,
semi analytical, or experimental approaches.
3.3.1 Analytical approach Terrain profile
(surface) can be transformed into the frequency
domain (Fourrier Transform). The transfer Function
of sampling and interpolation can be determined
and used for quality assessment (Laan,1973).
Fidelity of the reconstruction (transfer ratio)
can be computed for various sampling interval
(Ax), and plotted against different Ax (Makarovic,
1976).
Transfer Function can be used either for the
planing purpose or for Accuracy estimation of DTM,
reconstructed by sampling and interpolation.
The advantage of this approach is that there is no
need for classification and also its simplicity in
practical application, but the approach is
conceptually involved.
3.3.2 Semi analytical approach Applying the
law of error, propagation, the error of the
reconstruction H - H > min can be computed (Kubik,
K., 1986).
A low polynomial (trend) is substructured from the
input (terrain surface) in order to create the
stationarity condition, and o_, and the covariance
are estimated (stochastic assumptions), 9g; 9 ;
: : mean
and Sax computed, for error estimation.
Shortcoming of the method is some simplified
stochastic assumption on terrain surface
(homogeneous, stationary, and isotropy) vhich can
seldom be realised in case of real terrain relief.
3.3.3 Experimental approach Real terrain
relief. The reconstructed surface of the real
terrain relief is compared to the original surface
and the fidelity of the reconstruction is
estimated.
The flow diagram of the approach is shown in
figure 4.
The advantage of this approach is that it is
conceptually simple.
The shortcoming of the approach is that extensive
experiments and terrain classification are
required.
3.4 Fidelity of DTM obtained by PS
The fidelity of sampling and interpolation (in
case of fixed AX) can be studied by its transfer
function.