1 Spatial Modelling of the Terrestrial Environment - Georeferencial

Remotely Sensed Topographic Data for River Channel Research 121
is suspected that photogrammetric error is likely to be greater (see below), so that these
global estimates of surface quality are not necessarily reliable. Thus, we have the basic
challenge that the remainder of this chapter seeks to address. We need: (1) to find out which
data points are in error; and (2) to attempt to explain why they are in error to allow either
data re-collection or to justify correction. This should lead to the removal of blunders and
the reduction of systematic error, to produce a surface that is of a higher quality, where that
quality is controlled by random error and defined by equation (2) above.
6.4 Error Identification
Central to the error identification methods that were evaluated and applied is automation in
order to deal with the large number of data points that needed to be checked. First, image
analysis using unsupervised two-way classification of rectified imagery was used to remove
wet and vegetated data points (Figure 6.2(b)). Second, the stereo-matching process also
produced a map identifying which data points had been unsuccessfully matched, and hence
which needed to be interpolated. The result of these two components of post-processing
was the distribution of data points shown in Figure 6.3 for February 2000. The automated
identification of error needed to focus upon the individual point errors and banding shown
in Figures 6.2(b) and 6.3.
6.4.1 The Identification of Localized Error
The photogrammetric data collection process included an element of post-processing to
remove extreme point elevations. This involves a local variance based filter, based upon the
Chauvenet principle (Taylor, 1997) with a point rejected if:
z ij − z => mσ z (6)
where z ij is the point being considered, z is the average elevation defined for all data points
Figure 6.3 The data points left in the surface after removing vegetated and inundated points
shown in Figure 6.2(b)