CONVERSION OF RANDOM DIGITAL FILES AND PRINTED
DOCUMENTS INTO A STANDART DIGITAL FILE FORMATS WHICH IS SUITABLE FOR GIS
Ýbrahim BAZ1 and Ýsmail
Rakýp KARAÞ1
1Department of
Geodetic and Photogrammetric Enginnering,
Gebze Institute of
Technology, Gebze , Turkey
Management and organization of spatial
data values form main topics of GIS. In
1. INTRODUCTION
It
is not possible to mention about the existence of an information system which
has no data at all. According to some researches, proportion of cost of the
data gathering work to the total cost of an GIS is
about 60% - 80%. On the other hand, it is also a fact that an effective GIS
needs to be upgraded and renovated continuously. The results of some
investigations indicate that proportion of a GIS’s hardware cost to software
cost and to data production cost is 1:10:100 respectively [Comert,
1996]. To make a GIS more economical and productive, if not necessary, GIS
data, therefore, should not be obtained from the beginning stage, or should not
be obtained from newly started projects. Instead, GIS data should be gathered
from existing data resources as much as possible.
In this case, existing data formats may
conflict with GIS’s data formats. But this can be overcome by converting the
formats of existing data in to a standard format which is suitable for GIS.
In Turkey, nationally well known CADD style
computer programs such as EGHAS, KARTOCAD, NETCAD, etc. have been used to carry
out automated mapping and zone application projects for the last ten years, an
data belong to these projects has been archived either on computer storage
facilities or in printed files. Therefore it may be considered that most of the
data needed for establishment of a GIS exists in some way or another. This
situation increases importance of converting the existing data formats to GIS
data formats.
In this paper, software developments in which a
number of data transformation processes carried out are introduced.
2. TRANSFORMATION OF GRAPHICAL DATA
Effective usage and sharing of data appears to
be an unavoidable fact in any situation where GIS applications are mentioned.
In spatial data management, conventional form of data sharing is the data exchanging,
or transferring data from different sources. In any data exchange process,
there are two sides. The one which provides the data is named as “server”, the
other one which requires the data is named as “applicant”.
In general, data transferring process is known
as transformation of data from one format to another. Transferring process is
being carried out with the use of two methods known as “direct data
transferring” and “indirect data transferring” methods. In the first one,
transferring is applied between two different data formats. Here, as
transferring is carried out from one format to another directly, quality of
data transferring is very high. Data transferring softwares
developed for this purpose are named as “spatial data converters” [Comert, 1999].
In the second one, transferring between two
data formats is being carried out through a interval
format. Here, first of all, format to the server data is being converted to an
interval format, and then the applicant transforms it into its own format [Comert, 1999].
3. TRANSFORMATION OF NON-GRAPHICAL DATA INTO A STANDARD FORMAT
Most important peculiarity of GIS which
distinguishes itself from other information systems is processing and
management of attached graphical and non-graphical data. In the very first
place, information of properties and then quantitative values of geographical
features can be given as examples to the spatial non-graphical data.
Non-graphical data examples can be seen as hand-writing or printed documents
inside the land registrary records,
etc. or can be seen as either printed materials or computer text files of Word,
Excel, Access pragrammes, etc.
Nowadays, it is possible to save or process
hand-writing or printed files and documents as data files in a computer system
through use of Optical Character Recognition (OCR) methods. For this, these
printed files or documents are needed to be transferred into a computer system.
For this purpose, raster images of these materials should be obtained with the
help of a scanner. These raster images are then separated and converted into a
text files with the use of OCR programs.
Serious problems may occur during the separation process. Some conflicts
can be faced while separating characters of the text whether or not they are
letters or words. There are some methods which are used to ease or overcome
this kind of problems. [Oztürk, 1998]
4. SOFTWARE INTRODUCTIONS
As stated above, to be able to make a GIS more
economical and productive, it is necessary to benefit from the existing data at
the very beginning stage of GIS establishment. For this purpose, some computer
programs should be developed to make the existing data usable for GIS
databases. In following texts, two computer programs dealing with graphic and
non-graphic data transfers are introduced.
4.1 Programme CFT For Coordinate and Parcel Data Format Transformation
A
computer
program-CFT which carries out coordinate and parcel data transformation was
developed in Visual Basic programming language. This programme
accepts the coordinate and parcel data files and their formats as server
format, and then transforms them to data files or formats of ACCESS programme.
4.2 Standard Format Formation Programme – SFF
There are two circumstances to mention about
presence of non-graphical data. These data can be in the form of printed pages,
hand or type-writer writings, or can be in the form of text files of EGHAS or
NETCAD programmes.
At the first possible situation, there is a
need for transferring of printed documents to a standard format. For this,
raster images of these data should be obtained via a scanner scanning. Later
on, with the use of OCR methods, the raster image firstly converted to a text
file, and then some editing work is done to rearrange the text.
A computer programme-SFF
which ables printed document or digital data usable
for GIS was
developed in Visual Basic programming language.
4.3 Application Of
CFT
Flow
chart of the execution of main steps of this programme
is given in Figure 1. For the test of the CFT EGHAS’s
coordinate and parcel data files with “.ALN” extension and NETCAD’s
coordinate and parcel files with “.TXT” extension are used. Figures
2 and 3 shows formats of these data files. CFT programme
reads these files and converts them to Access database which show propriety to
GIS databases. Figure 4 shows format of Access database.
4.4 Application of SFF
Flowchart of execution of main steps of this programme is given in Figure 5. For the testing SFF, a text
file produced by EGHAS programme (Fig. 9) and a
document given in Figure 7 were chosen as the text file and printed document.
Both the printed page and the text file consist of land registrary
information about parcels which were produced from a district zone application
project in town Gebze.
RUN
Open File
First Line = LINE
Next Line=LINE
N
N
Mid(LINE,65,3) =? “
Y Y
“This is not a
Evaluate and Question the
suitable
Following Data Block
EGHAS file”
Obtain Coordinates
Obtain Block Corners
Obtain parcel numbers
And Parcel corners
Etc.
Data Y
Exist in the “This Data Exist”
Database
N
Transfer the Data
Y Continue N
To the Database
N Y
Next Line=LINE Last
Line END
Figure 1: Flow Chart of
the program CFT for EGHAS data
Figure 2: Sample of server data (EGHAS’s coordinate and parcel data)
Figure 3: Sample of server data (NETCAD’s
coordinate and parcel data)
Figure 4: Sample of applicant data in Access database
|
First
Line = LINE N
Data Line Next
Line Y
MAP = Mid(8,5,LINE)
BLOCK= …
PARCEL=…
… Evaluate and Question Every Variable Correct the Texts as the First
Letter as Capital Letters the Others as Small Letters Correct the Informal Turkish Characters 1 |
1 Separate
the Name and
Surnames Separate
Rational Values in Shape
of ?/? as ? and ?
Etc.
Y
END Last Line N Next
Line Y N Data
Line |
Figure 5: Flow chart of the program SFF for
EGHAS text files
Figure 6: Sample of standard format in Access
database
Figure 7: Sample of scanned image data
|
36 3541 Arsa 18c1c
3908 1 314 TAM 314.00 0.00
314.00 Ahmet Nas Arif oðlu G22818c1c 103
1 5376.00 36 3542 Arsa 18c1c
3908 2 241 TAM 241.00 0.00
241.00 Osman Ayyýldýz Ahmet oðlu G22B18c1c
103 1 5376.00 36 3543 Arsa 18c1c
3908 3 239 TAM 239.00 0.00
239.00 Osman Ayyýldýz Ahmetoðlu G22818c1c 103
1 5376.00 36 3544 Arsa 18c1c
3908 4 239 TAM 239.00 0.00
239.00 Osman Ayyýldýz Ahmetoðlu G22818c1c 103
1 5376.00 36 3545 Arsa 18c1c
3908 5 278 TAM 278.00 0.00
278.00 Kemal Erdoðan Mehmetoðlu G22818c1c 103
1 5376.00 36 3546 Arsa 18c1c
3908 6 259 118 259 118.00
0.00 118.00 Ali Haydar Diyaroðlu Hüseyin oðlu G22818c1c
103 1 5376.00 36 3546 Arsa 18c1c
3908 6 259 118 259 118.00
0.00 118.00 Kemal Erdoðan Mehmet oðlu G22818c1c 103
1 5376.00 36 3546 Arsa 18c1c
3908 6 259 23 259 23.00 0.00
23.00 Gebze
Belediyesi G22818c1c 103
1 5376.00 36 3547 Arsa 18c1c
3905 7 262 TAM 262.00 0.00
262.00 Haným Usta Mustafa
kýzý G22818c1c 103
1 5376.00 36 3548 Arsa 18c1c
3908 8 264 TAM 264.00 0.00
264.00 Mehmet Usta Mustafa oðlu G22818c1c
102 2 171.00 36 3548 Arsa 18c1c
3908 8 264 TAM 264.00 0.00
264.00 Mehmet Usta Mustafaoðlu G22818c1c
103 1 5376.00 36 3549 Arsa 18c1c
3908 9 267 157 267 157.00
0.00 157.00 Abdurrahman Gündüz G22818c1c 102
1 168.00 36 3549 Arsa 18c1c
3908 9 267 110 267 110.00
0.00 110.00 Gebze
Belediyesi G22818c1c 102
1 168.00 36 3549 Arsa 18c1c
3908 9 267 110 267 110.00
0.00 110.00 Gebze
Belediyesi G22818c1c 101
2 252.00 36 3549 Arsa 18c1c
3908 9 267 110 267 110.00
0.00 10.00 Gebze Belediyesi G22818c1c 103
1 5376.00 36 3550 Arsa 18c1c
3908 10 269 TAM 269.00
0.00 269.00 Kemal Erdoðan Mehmet oðlu G22818c1c 102
3 269.00 36 3551 Arsa 18c1c
3908 11 339 TAM 339.00
0.00 339.00 Kemal
Erdoðan Mehmetoðlu G22818c1c 102
4 339.00 36 3552 Arsa 18c1c
3909 1 346 TAM 346.00 0.00
346.00 Kemal Erdoðan Mehmetoðlu G22818c1c 103
1 5376.00 36 3553 Arsa 18c1c
3909 2 365 TAM 365.00 0.00
365.00 Kemal Erdoðan Mehmetoðlu G22818c1c 103
1 5376.00 36 3554 Arsa 18c1c
3909 3 313 243 313 243.00
0.00 243.00 Recep Türkü G22818c1c 103
1 5376.00 36 3554 Arsa 18c1c
3909 3 313 70 313 70.00 0.00
70.00 Sami Yýlmaz Sabri oðlu G22818c1c 103
1 5376.00 36 3555 Arsa 18c1c
3909 4 272 TAM 272.00 0.00
272.00 Nuran Cömert G22818c1c 103
1 5376.00 36 3556 Arsa 18c1c
3909 5 259 TAM 259.00 0.00
259.00 Kemal Erdoðan Mehmetoðlu G22818c1c 103
1 5376.00 36 3557 Arsa 18c1c
3909 6 253 TAM 253.00 0.00
253.00 Kemal Erdoðan Mehmet oðlu G22818c1c
103 1 5376.00 36 3558 Arsa 18c1c
3909 7 246 22 246 22.00 0.00
22.00 Sami Yýlmaz Sabri oðlu G22818c1c 103
1 5376.00 |
Figure 8: Structure of edited text file of OCR
processing