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Proceedings, XXth congress

H. Sahin* *, H. Topan *, S. Karakis ", A.M. Marangoz*
* ZKU, Engineering Faculty, 67100 Zonguldak, Turkey - (sahin, htopan, karakis, marangoz)@jeodezi.karaelmas.edu.tr
KEY WORDS: High Resolution, Mapping, Analysis, Digitisation, Extraction, Comparison, Orthoimage
The developments in the remote sensing technology have provided the use of high-resolution images for different purposes if
possible. These images can be used for a study such as town planning where high resolution and information content are required. In
this study, high resolution panchromatic KVR-1000 image has been employed for extraction of man-made structures in a
metropolitan city area. The test area is a part of Zonguldak (Turkey) city. First, boundaries of buildings and road’s center lines have
been digitized manually. Additionally, the object oriented classification process has been implemented for the same area. In this
manner, the results from manual digitizing and large-scale maps produced by photogrammetrical techniques have been compared
and the success of manual digitizing has been verified. The large-scale maps have been taken as the base criteria in the comparison.
The second analysis deals with tests using object oriented classification. Both methods include some disadvantages. Operator could
experience some problems during manual digitizing process. The object oriented analysis is an alternative tool which uses grey
values of objects in the process. Both methods have been analyzed for the orderly and disordered zones constituted by the buildings
and the independent houses, respectively.
One of the main objectives of geoinformatics engineering is to
collect data and analyze, represent the products of these data
with diverse means. Today, the reliable production of
information and its rapid serve to the user community is an
important task. The reliability and rapidity aspects of
information provision have accelerated the progress of
technology. As a result of this stormy progress data acquisition
from space has been an operational concern. Data acquired
from space can be used in different disciplines such as
geoinformatics, forestry, agriculture and etc.
Extracting both geometric and semantic information from space
images has been the main concern since the early phase of
remote sensing. Qualitative analysis of images does not help the
user to deduce required information. Abundance of information
in both photographs and space images leads user to digitize
only the interested objects. Digitized objects help user to extract
information on only focused features. Map digitizing started
with the invention of digitizing tablets. The graphical map to be
digitized is laid on the digitizer table and coordinate values of
discrete points are stored in a computer using a cursor. With the
emergence of scanners on the market, graphical maps are
scanned at equal intervals throughout the whole image and
scanned data are stored in raster file format. The next step has
consisted of vectorizing the raster image. Several methods are
developed to vectorize raster images. One of those methods is
called on-screen digitizing as a manual method, and the other
one is called object oriented image analysis as an automatic
method. The basic purpose of developing these methods aims at
reducing operator’s interactivity with the computer and thus
speeding up the digitizing process.

* Corresponding author.
Today, space images can be used for data acquisition purposes.
Many vendor companies provide a wide range of images for
different users. One.of the high resolution space imagery is the
Russian KVR-1000 system. KVR-1000 images are for example
used to isolate illegal buildings in a forest environment in
Greece (Karathanassi et al., 2003). Kostka (2002) uses KVR-
1000 imagery together with other high resolution images in
order to make inferences about climatic studies, transportation
routes, water resources, conservation areas, and relicts of
human land-use. Another study uses KVR-1000 images to
monitor refugee camps in south-east Asia (Bjorgo, 2000).
All above studies deal primarily with semantic relating of
spatial objects. Geometric accuracy potential of KVR-1000
images is not well researched. Therefore a geometric
assessment should be made within the context of this study. For
this goal objects in KVR-1000 images are digitized using
manual and automatic methods. Both obtained results are
compared to 1:1000 photogrammetrically produced digital line
Digitizing is a way of conversion of information from
analogously produced graphical maps to machine readable
vector or raster formats. Many methods are used for the
vectorizing process. Two of these methods are adopted in this
study, These methods are manual on-screen digitizing and
object oriented approach.
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