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ŠUMARSKI LIST 11-12/2010 str. 52     <-- 52 -->        PDF

V. Cetl, B. Barišić, I. Šarušić: PREVOĐENJE KATASTARSKIH PODATAKA U NOVI DRŽAVNI ... Šumarski list br. 11–12, CXXXIV (2010), 593-602
related to graphical method technical limitations. Homogenization is defined
with identical points collected by the usage of Digital OrtoPhoto in scale
1:5000 (DOP5).

Since Croatia is on the beginning of this kind of works, this paper examines
the transformation methods of cadastral data and the optimal selection of identical
point’s density on the sample of cadastral district Brckovljani (Figure 1).

The transformations of cadastral data were performed by the national
GRID model transformation and 7-parameter transformation (Table 1). For
transformations control purposes, coordinates of 4 trigonometric points measured
with CROPOS system (directly in new datum with specified precision of
2 cm) are used. Statistical values for the GRID transformation meet the expectations
(Table 2, left), and some improvements in 7-parameter transformation
(Table 2, right) could be expected if locally estimated parameters will be used.
However, main problems with the local parameters are extra efforts for their
district level estimation and related complications with continuity of transformations
on district borders. The GRID transformation model, after it become
official, seems like appropriate solution.

In the process of homogenization basic principle for the selection of an
identical point is its stability since the time of cadastral survey. Most of the cadastral
plans (approximately 75%) are created by surveys older than 100
years, so this principle is very difficult to meet. Before the selection of identical
points, 200 x 200 meters grid was constructed to support their easier selection
and regular distribution. Selection is performed in 3 different densities overlaying
DOP5 (density I – 0,16 IP/ha, density II – 0,07 IP/ha and density III –
0,02 IP/ha). For the control of identical point’s density impact on the final results
of homogenization, set of 44 control points is used. The situation with
geometry of the cadastral plan before homogenization could be seen in Figure
3 and Table 3. Impact of identical point’s density is evaluated comparing statistics
on control points before homogenization (Table 3, right), and after this
process (Table 4). Only the densest set of identical points (0,16 IP/ha) has statistical
indicators better after than before homogenization. Density has crucial
impact on the costs of the homogenization process but on this example it is easy
to see that savings in this segment could degrade geometry of cadastral plan
which is unacceptable.

Key words: cadastre, transformation, homogenization, HTRS96/TM,
digital cadastral map