MapEdit: solution to continuous raster map creation

Computers & Geosciences 29 (2003) 115–122

MapEdit: solution to continuous raster map creation$

Dejan Ran$ci!c*, Slobodanka Djordjevi-Kajan

Faculty of Electronic Engineering, University of Ni$s, Beogradska 14, 18000 Ni$s, Yugoslavia

Received 5 December 1998; received in revised form 27 August 2002; accepted 30 August 2002

Abstract

The paper describes MapEdit, MS WindowsTM software for georeferencing and rectification of scanned paper maps.

The software produces continuous raster maps which can be used as background in geographical information systems.

Process of continuous raster map creation using MapEdit ‘‘mosaicking’’ function is also described as well as the

georeferencing and rectification algorithms which are used in MapEdit. Our approach for georeferencing and

rectification using four control points and two linear transformations for each scanned map part, together with nearest

neighbor resampling method, represents low cost—high speed solution that produce continuous raster maps with

satisfactory quality for many purposes (71 pixel). Quality assessment of several continuous raster maps at differentscales that have been created using our software and methodology, has been undertaken and results are presented in the

paper. For the quality control of the produced raster maps we referred to three wide adopted standards: US Standard

for Digital Cartographic Data, National Standard for Spatial Data Accuracy and US National Map Accuracy

Standard. The results obtained during the quality assessment process are given in the paper and show that our maps

meat all three standards.

r 2002 Elsevier Science Ltd. All rights reserved.

Keywords: Georeferencing; Rectification; Mosaicking; GIS; Rasters

1. Introduction

Computer applications in cartography and the devel-

opment of geographical information systems (GIS)

provide many possibilities for research. GIS enables

scientists to look at things the way they could never do

before, which should make better natural resources

management possible. However, the appearance of GIS

software technology is not enough in itself. This is

because 80% of every GIS system represents spatial

data, without which, the system is useless. There are

many methods for data capture for GIS, starting from

measurements of the surface of Earth, digitalisation and

vectorization of existing paper maps, aircraft and

satellite imagery and others. Many states are investing

large amounts of money in the creation of digital spatial

databases, but unfortunately, Yugoslavia has not yet

achieved this and this has meant that GIS applications

have not been as frequent as they should have been. One

solution to this data acquisition problem is presented in

this paper, which presents a method of scanning spatial

data from existing paper maps. These are the most

suitable for use and also they are the best tools for

representing large amounts of spatial data georeferenced

onto the same system. Various types of GIS use such

maps. For topographic maps these include air photo-

graphs, data from remote sensors, field notes, coordinate

lists and existing maps (Taylor, 1991). Thematic maps

rely on a wider range of data sources, such as census

reports, meteorological records and historical docu-

ments. In modern cartography the variety of data

sources is increasing, resulting in an exponential growth

in the volume of data. One solution lies in vector

digitising of these maps, but although they consume

storage capacity, raster data can be produced easily and

quickly (Guptil, 1989; Drummond and Bosma, 1989). In

addition, scanned maps have other advantages, because

$Code available on server at http:// www.iamg.org/CGEdi-

tor/inderx.htm

*Corresponding author. Fax: +381-18-46-180.

E-mail address: [email protected] (D. Ran$ci!c).

0098-3004/02/$ - see front matter r 2002 Elsevier Science Ltd. All rights reserved.

PII: S 0 0 9 8 - 3 0 0 4 ( 0 2 ) 0 0 1 1 2 - 7

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the user is already familiar with the original sources and

prefers the standard scales used (Taylor, 1991). Scanned

raster maps are usually used as ‘‘visual context’’ for

users (Mitrovi!c et al., 1994). Users are mostly interested

in just one or a small number of neighbouring objects,

but in order to locate them in space it is necessary to

display geometrical data and textual annotations for a

number of surrounding objects. All these additional data

form a ‘‘visual context’’. Having in mind all this, we

developed a software tool—MapEdit—for fast proces-

sing of scanned paper maps and continuous raster map

production. In this way, we provided a base dataset for

future GIS applications. Of course, there are several

software tools that also do this task. For example,

ERDAS Imagine has an image rectification and mosai-

cing tool (check details on the web1). Blue Marble

Geographics Transformer (check details on the web2)

also has similar functionality. But, because of economic-

al and political conditions in Yugoslavia (especially in

1995. when we developed the first version of our

software) it has been impossible to buy such software

tools. Of course, both above-mentioned software tools

and many others having similar functionality require

powerful computers that can be rarely found in

Yugoslavia in 1995. Thus, our software tool, named

MapEdit, was the only available solution that could run

on computers based on 80486 processors (Mitrovi et al.,

1995).

The paper is organised as follows. Section 2 discusses

the continuous raster map creation process using

MapEdit software (Djordjevi-Kajan et al., 1995) as well

as the algorithms used for georeferencing and rectifica-

tion. Some experimental results in continuous raster

map creation for Serbian Telecom as well as quality

control of produced raster maps are presented in Section

3. Section 4 concludes the paper.

2. Continuous raster map creation process

The starting point for the continuous raster map

creation process (Fig. 1) is preparing the available paper

maps covering the area for which a raster map is to be

created. Paper maps can be scanned all at once or in

parts, depending on the scanner dimensions. The set of

scanned files is the input for the MapEdit—continuous

raster map creation software.

In order to prepare scanned paper maps for use in any

GIS application, we must georeference and rectify all

scanned parts. This means that the relationship between

scanned image and map coordinates must be estab-

lished. In other words, the scanned image must be

reprojected into the georeferenced grid. At the same

time, paper distortions and geometric distortions intro-

duced by the scanning process (paper rotation and

skewing) must be corrected. In order to solve these

problems, MapEdit provides the following functions

(Djordjevi-Kajan et al., 1995):

1. Georeferencing and de-skewing (rectification) of

scanned maps through four control points. This

enables the compensation of paper distortions and

linear distortions introduced by the scanning process,

2. joining of neighboring segments,

3. mosaicing, tiling into pieces that can be stored into

separate files, and

4. quality control.

Fig. 1. Continuous raster map creation process.

1ERDAS IMAGINE. http://www.erdas.com.2Blue Marble Geographics Transformer. http://www.blue-

marblegeo.com.

D. Ran$ci!c, S. Djordjevi-Kajan / Computers & Geosciences 29 (2003) 115–122116

http://www.erdas.com

http://www.bluemarblegeo.com

http://www.bluemarblegeo.com

For the first function, the operator must specify a set

of four control points for each scanned part. The choice

of control points is important. Enough well-defined

control points must be chosen in rectificating an image

to ensure that accurate mapping polynomials are

generated. Usually, control points could be road

intersection, airport runway intersections, bends in

rivers, etc., but in our situation, because we deal with

scanned paper maps that have a coordinate grid already

overprinted, this grid is used for control points. Strictly

speaking, linear transformation which is used in

MapEdit requires only three control points to calculate

six unknowns. In practice, most authorities recommend

a much greater number of control points but, since there

is a cost associated with the collection of the data for

each additional point, there is an argument for making

the number as low as possible consistent with the

accuracy of the transformation needed (Unwin and

Mather, 1998). In order to speed-up the entire process,

MapEdit uses four control points (two sets containing

three control points) and two linear transformations for

georeferencing and rectification.

Based on information obtained from control points

on the scanned parts, MapEdit automatically connects

the scanned parts of paper maps and forms a continuous

raster map. At the same time, georeferencing and de-

skewing of the scanned map parts are also performed.

All GIS databases are ultimately stored and managed in

real-world coordinates. Software should be able to bring

raster and vector data into the same coordinate system

either by fitting the raster data to the vector data, or vice

versa. Georeferencing of data is a requirement for

‘‘heads-up’’ digitising, many editing functions, and any

integrated use of data. Raster data must be georefer-

enced to be stored as a seamless database of adjacent

images. For this purpose we have used a direct

transformation by the grid-on-grid method. This meth-

od is based upon the relation between the rectangular

coordinates of the same points on two projections and

can be applied for the map registration purposes if the

projection of original map has a rectangular coordinate

system (Gauss-Kruger’s, for example). Yugoslav topo-

graphic maps are produced using Gauss-Kruger’s

projection that has rectangular coordinate system. Since

a continuous raster map coordinate system is also

rectangular, we used this solution when we developed

MapEdit. We chose a continuous raster map coordinate

system parallel to the 7th Gaus-Kruger’s zone coordi-

nate system (Gauss-Kruger’s zones are 31 wide), because

it covers the major area of Yugoslavia. The transforma-

tion model is:

ðx0i; y

0iÞ-ðxi; yiÞ; ð1Þ

wherex0i and y0i are continuous raster map coordinates,

and xi and yi are cartographic projection coordinates.

The transformation we used is the general linear

transformation:

xi

yi

" #¼

a b

c d

" #�

x0i

y0i

" #þ

e

f

" #: ð2Þ

This inverse solution, where the coordinates of the

continuous raster map system have been transformed

into the cartographic projection coordinates, guarantees

the filling of each pixel in the continuous raster map with

no missing pixels. In this transformation, the coordi-

nates of the continuous raster map system are trans-

formed into the cartographic projection coordinates

through the use of six coefficients a2f : In order toobtain these coefficients, at least three points known

cartographic projection coordinates (the control points),

are needed. In fact, the algorithm used in MapEdit uses

four control points and two transformations according

to a triangulation method of the rectangular area

determined by the control points (Fig. 2). Note that in

Eq. (2) i ¼ 1; 2; 3 for the first triangle and i ¼ 1; 3; 4 forthe second triangle. The user specifies control points on

the screen, using a special software zoom tool, and for

x2 ,y2

xi ,yi - Cartographic projection coordinates x ',y ' - Continuous raster map coordinates

i = 1, 2, 3, 4

y

x

x ',y '

paper map

transformation

continuous raster map

33

x ',y '22

x ',y '11

x ',y '44

i i

x3 ,y3

x4 ,y4x1 ,y1

Fig. 2. Triangulation method of given rectangular determined by control points.

D. Ran$ci!c, S. Djordjevi-Kajan / Computers & Geosciences 29 (2003) 115–122 117

each one specifies numerical values of the coordinates

(geographical: longitude and latitude, Gaus-Kruger’s or

any other local coordinates—see Fig. 3). Based on this

information, MapEdit computes all the necessary

transformations, determines the correct place for the

scanned part in the continuous raster map, and stores

the data in corresponding map files. Mosaicing is done

in such a way that the information about the correct

place of the map piece in the continuous map is coded

and included into the name of the formed file. For

example, the filename map123058 determines the file

position (123,058) on the (x; y) continuous raster mapgrid (Fig. 4). The map files may have any size but all files

of the same continuous raster map must have the same

dimensions in pixels, which implies that, x and y

dimension must be set before continuous raster map

creation. A class diagram of the continuous raster map

is shown in Fig. 5.

In order to perform georeferencing and rectification,

MapEdit forms a temporary buffer, with the dimension

m � nmap files. The numbers m and n are determined by

the rectangular area on the scanned map formed by four

control points and by the continuous map file size

(Fig. 6). Based on the specified cartographic projection

coordinates, the software automatically determines the

position and names of the needed map files. If the

requested files do not exist, MapEdit automatically

creates them. If the files already exist, the software

transfers data from these files to the temporary buffer.

Next, data from the scanned part are transferred into the

temporary buffer. The algorithm is a modification of the

well-known scan-line algorithm (Foley et al., 1990). For

each pixel belonging to the rectangle determined by the

continuous raster map coordinates of the control points,

the software calculates the corresponding pixel position

in the scanned map file using the described transforma-

tion (see Eq. (2)) and copies the original pixel to the

continuous map. This process is also known as

resampling. For this purpose we used the nearest-

neighbour resampling algorithm (see details on the

Fig. 3. MapEdit software: sample screen display.

000 001002 xxx

x

file yyyxxx

Geographic meridian of longitude

Geographic parallel of latitude

000

001

yyy

y

Fig. 4. Continuous raster map grid.


web3) that chooses the actual pixel that has its centre

nearest to the point located in the image. Depending on

the pixel position in the continuous map (in the first or

in the second triangle), MapEdit uses the appropriate

transformation. When all the pixels have been re-

sampled, the content of the temporary buffer is

transferred into corresponding map files.

The algorithm guarantees a seamless, georeferenced

and rectified continuous raster map that can be used in

any GIS application. For further use, only information

about the real world continuous raster map origin is

needed. This information can be easily exported as a

separate file and joined to the raster map files. The

formulae for calculating cartographic-projection coor-

dinates of the given pixel that belongs to any map file are

straightforward:

CPx ¼ CMOx þ ðxxx � Dx þ xÞ � Sx;

CPy ¼ CMOy þ ðyyy � Dy þ yÞ � Sy;ð3Þ

where CPx and CPy are cartographic projection

coordinates, CMOx and CMOy are continuous raster

map origin coordinates, xxx and yyy are file position

coordinates in the map files grid, Dx and Dy are file

dimensions (in pixels), x and y are pixel coordinates in

map file and Sx and Sy are pixel size in units that have

been used by the given cartographic projection.

3. Experimental results

In order to verify the described methodology, we have

created continuous raster maps at different scales from

1:25,000 to 1:300,000 for the Serbian Telecom GIS

(Stojanovi!c et al., 1997). For the quality control of these

maps we also used MapEdit, which can display the

Fig. 5. Continuous raster map class diagram.

continuous map files

new part

m

n

Fig. 6. Data from existing map files form temporary buffer for

new scanned part.

3GIS Glossary. http://www.gisdevelopment.net/glossary/

n.htm.


http://www.gisdevelopment.net/glossary/n.htm

http://www.gisdevelopment.net/glossary/n.htm

resulting maps to enable visual control of them.

Currently, the display can show one, two or four raster

map files using a map file size of 1260� 945 pixels. Thesedimensions seem to give the best performance in scroll

and search operations. As a result of the disk cache

technologies used in PCs, a small scroll across the raster

map is done without accessing the disk. Manipulation

with raster data in MS WindowsTM environment is thus

fast and easy, and CD ROM or optical disks can store

many of these raster maps. For example, the map of the

former Yugoslavia (255,804 km2) on scale 1:25,000 has

2051 paper sheets, which, when joined, are 80m� 80m.The continuous raster map of the same area created

using MapEdit has about 10,000 map files. With 256

colours and 100 dpi resolution, and using WindowsTM

bitmap format (*.bmp) the storage requirement is about

8GB, which can be compressed for storage down to

about 2GB.

For the quality control of the resulting maps we also

referred to US Standard for Digital Cartographic Data

(DCDSTF, 1988). The testable components specified in

this standard are positional accuracy, attribute accuracy,

logical consistency and completeness. All components

have been tested, but the most important component for

the raster map quality control is the positional accuracy.

For this we referred to the US National Map Accuracy

Standard (Thompson, 1988), which specifies that on

scales smaller than 1:20,000 no more than 10% of tested

points should be more than 1/50 in in horizontal error,

and on maps with scales larger than 1:20,000 the

corresponding error term is 1/30 in. For the positional

accuracy testing and visualisation, we have used the root

mean square error (RMSE). The choice of RMSE has

been prompted by the wide application of this statistic in

GIS software packages (Morad et al., 1996) and by the

fact that RMSE is often used as a practical measure of

accuracy in image digitisation and transformation. For

this purpose, the software enables the user to specify

control points on any regular grid and perform ‘‘heads-

up’’ digitisation from the raster map. It is convenient to

define control points in such a way that they match the

grid already overprinted on the original map (in our

experiment—Gauss–Kruger’s grid) and visible on the

raster map. This enables the user to locate control points

easily. When the ‘‘heads-up’’ digitisation is complete,

users can obtain RMSE results on the screen. RMSE is

calculated using standard formulae (Daosheng, 1995).

For positional accuracy testing, we also referred to

National Standard for Spatial Data Accuracy (FGDC,

1996) that has been developed by the US Federal

Geographic Data Committee (FGDC) and supercedes

the National Map Accuracy Standard. For the hor-

izontal accuracy measurement, NSSDA specifies a

circular error (CE) that represents the probable max-

imum displacement of a feature’s measured horizontal

position from its true position. CE should be stated with

a 95% confidence interval and is based on the sample

standard deviation of the difference between data set

coordinate value and the coordinate value of the control

points. When the sample size is large, as it is in our

situation, the standard deviation and RMSE are nearly

equivalent, and the formula for CE calculation is

(FGDC, 1996):

CEE2:447RMSE: ð4Þ

The MapEdit software provides RMSE visualisation

along x and y axis separately (see Fig. 7) as well as two-

dimensional visualisation related to both x and y

Fig. 7. RMSE visualization for map scale 1:200,000 along y-axis.


coordinates (see Fig. 8). Based on the RMSE visualisa-

tion, users can re-process some of scanned parts in order

to reduce errors.

For the maps of former Yugoslavia, the average

RMSE and CE values at different scales, together with

pixel size (in meters) with 100-dpi resolution scanning,

are given in Table 1. It can be seen that the errors are

within the digitising error (71 pixel). For example, forscale 1:25,000 maps these errors are equivalent to 4–7m

on the ground. MapEdit also controls horizontal errors

related to the US National Map Accuracy Standard

(NMAS). The results are impressive: at scale 1:25,000–

1:300,000, no control points have a horizontal error

greater than 1/30 in and therefore these raster maps meet

NMAS.

4. Conclusions

GIS users are currently challenged to transform

paper-based information efficiently into digital form.

Scanning technology provides a cost-effective way of

meeting this challenge. In Yugoslavia, this was the only

way to speed-up the process of GIS applications

development. In order to support such methodology,

we developed MapEdit, a software tool which prepares

raster maps for use in GIS. Basic MapEdit functionality

and the scanning data-entry method for continuous

raster-map creation have been presented in this paper.

Special attention is paid to the algorithm used for the

map georeferencing and rectification as well as to the

resampling method. In order to verify our approach,

quality assessment of maps formed using MapEdit was

undertaken and the results are presented in the paper.

They show that our approach produces errors that are

within the digitising error range (71 pixel) and meetsthree widely adopted standards: US Standard for

Cartographic Data, National Standard for Spatial Data

Accuracy and US National Standard for Spatial Data

Accuracy. Being PC-based, low cost, relatively easy to

operate, and sufficiently accurate for many purposes,

MapEdit is well suited for PC users.

Fig. 8. Two-dimensional RMSE visualisation for map scale 1:200,000.

Table 1

Obtained RMSE and CE at different scales for former Yugoslavia maps

Scale Number of tested points Pixel size (m) RMSEx (m) RMSEy (m) RMSE (m) CE (m)

1:300,000 272 76.2 53.47 71.75 81.59 199.65

1:200,000 1209 50.8 55.02 67.24 76.78 187.68

1:100,000 420 25.4 29.44 23.33 33.94 83.05

1:50,000 806 12.7 15.36 12.60 18.13 44.36

1:25,000 1548 6.35 6.71 5.27 7.59 18.57


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MapEdit: solution to continuous raster map creation

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