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ENVIRONMENTAL ENGINEERING

The 8thInternational Conference

May 1920, 2011, Vilnius, Lithuania

Selected papers

ISSN 2029-7106print / ISSN 2029-7092 online

ISBN 978-9955-28-829-9 (3 Volume)

ISBN 978-9955-28-827-5 (3 Volumes)

http://enviro.vgtu.lt

Vilnius Gediminas Technical University, 2011

1451

RECTIFICATION OF SATELLITE IMAGERY FROM GOOGLE EARTH:APPLICATION

FOR LARGE SCALE CITY MAPPING

Birute Ruzgiene1, Qian Yi Xiang

2,Silvija Gecyte

3

1, 3Vilnius Gediminas Technical University, Saultekio ave.11, LT-10223 Vilnius, Lithuania.

1Klaipeda state college, Bijn10, LT-91223 Klaipda, Lithuania.

E-mails:1Birute.Ruzgiene@vgtu.lt; 3silvija.gecyte@vgtu.lt2School of computer science and technology, Soochow university, Suzhou, Jiangsu, China.

E-mail: goodcat110@139.com

Abstract. The rectification of high resolution digital aerial images or satellite imagery for large scale city mapping is

modern technology that needs well distributed and accurate defined control points. The digital satellite imagery,

obtained when using widely known software Google Earth, can be applied for accurate city maps construction. The

method named Five control points is suggested for imagery rectification introducing Prof. Ruan Wei (Tong Ji

University, Shanghai) algorithm. Image rectification software created on the base of suggested algorithm can correct

images deformation with required accuracy, is reliable and keeps advantages in flexibility. Experimental research for

testing applied technology has been executed using GeoEye imagery from Google Earth over city Vilnius.

Orthophoto maps at scales of 1:1000 and 1:500 are generated referring to Five control points methodology.

Reference data and rectification results are checked comparing with results from digital aerial images processing

using digital photogrammetry approach. The image rectification process applying investigated method takes short

time (about 45 minutes) when using only five control points and accuracy of created models satisfies requirements

for large scale mapping.

Keywords: digital photogrammetry, satellite imagery, image rectification, city mapping, orthophoto maps.

1. Introduction

The modern digital photogrammetric technology

combining with image processing techniques allows to

determine the position of an objects in a three

dimensional space from aerial photographs or remote

sensing imagery recorded in digital representation. The

digital image processing has possibility to increasemapping efficiency because almost all procedures are

automated (Ruzgiene 2007). Therefore, the

photogrammetric processing of images becomes easer

and provides required precise data for Geodesists,Cartographers, Geographers, Forest Engineers,

Geologists, GIS users, etc.The digital orthophoto maps are one of broadest

used product and successfully can be incorporated as

background information in GIS (Konecny 2003).

Nowadays a very popular virtual globe map from Google

Earth and geographical information obtained fromsatellite imagery is widely used for various survey

applications, Earth surface mapping, monitoring of

environment disasters, etc.

The integration of data from aerial images or

satellite imagery with appropriate resolution in most

digital maps, cartographic and geographic data sets is

very desirable (Ewiak and Kaczynski 2010). Raw digital

images contain internal geometric distortions that results

from the image acquisition process. These distortions canarise from the sensors plane tilt, variations in sensor

altitude, Earth curvature, lens distortion, terrain relief and

others. Therefore original (row) imagery needs for

rectification and transformation (Manual 2004, Wolf and

Dewitt 2000). A correctly processed digital map is free of

significant geometric distortion and transformed to thelocal used projection and coordinate system.

Professor Ruan Wei from Tong Ji University,

Shanghai, China has been introduced the reliable and

practical method (Five Control Points Rectification of

Digitized Image) for creating city map at scales of 1:1000

or 1:500.The one of methods for generation of reliable

rectification model for city maps construction is

announced in Japan patent P2000-298430A (Ruan 2008).

There images rectification processes requires more than

nine control points and the accuracy cant satisfied the

need of the mapping at a scale, e.g. 1:500.

The aim of research is to perform the comparison test

integrating data sets from aerial photography at a scale

1:6000 and satellite imagery from Google Earth

investigating the potential and accuracy of the suggested

Five control points method for getting highest citymodeling efficiency.

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2. Methodology, algorithm and software description

The effects of camera tilt raise the images geometric

deformation. Such effect can be eliminated applying

appropriate digital images rectifying method for precisely

and reliably correction the image planes to object plane.

Using the suggested method "Five Control Points"can be constructed varied scale city map and follows the

digital photogrammetric method for rectification of

digitized images with correction of deformations.

The theoretical basis applied in algorithm is the

interpolation using surface splines. Image rectification

results fits very well for large scale maps, under of only

five rectifying points. The accurate digital rectification,

which gradually corrects the deformation avoiding

deviation that results from surfaces translating or rotating,

can be performed. Results shows that using high

resolution imagery any survey staff can create city map

accurately. Presented method is reliable and could be

used in practices.The image of various deformations, including

coordinate conversion, scale deformation, spin and

translation, is rectified using the one of a formula for

corrections (Ruan 1988). For each point on the digital

image, use the following formula applicable to calculate

the independent points x and y component of weighted

deformations (Ruan 2008):

,ln),(1

22

=

+++=N

i

iii rrFCyBxAyxW (1)

where 222 )()(iii

yyxxr += , .5N

Formula (1) is applied in calculation ofA, B, C, F

(i = 1, N), where total unknowns quantity in rectification

model isN+3. Deformation ofNcontrol points is known.

Therefore Nequation could be constituted. Adding threebalance equations all the unknown variables can be

solved out.

Characteristic of the software. The software, based

on "Five Control Points algorithm and created by author

Qian Yi Xiang, is simply in operating, only a little pick

and data inputting are need for rectification an image, aswell as not very skilled operator is required. The

rectification can be completed within a short time. For

example, only 510 minutes needs for a photo of size4050 cm.

The image processing steps are: scanning image into

computer, input control point coordinates identification(recognition) of rectification points on the photography,

supplying mapping scale, rectification process and

obtaining the corrected images.

Mapping process involves: getting data from

measurements of the rectification points identified inaerial photograph, digitization according to the scale with

the help of Photo Rectification software, construction the

photo map and drawing map using advanced software

Southern CASS 4.0.

The operating process for samples rectification is asfollowing: choosing the needed aerial photograph

(images format *bmp), opening the original map file,

choosing the control points area and precisely

identifying control points (Fig 1, a), inputting the data (x,

y) to fileframe (Fig 1, b), setting mapping data (scale,

coordinates system) and start the image rectification

process (Fig 1, c). The procedure is following up

construction of drawing (measurement of topographicfeatures) having rectification photograph and creation a

map referring to raster images using Southern CASS 4.0

software.

Fig 1. Sample mapping process: a) identifying of control

point, b) framing, c) obtaining of rectification data

3. Experiments and evaluation

The experimental photogrammetric procedures have

been performed using GeoEye satellite imagery from

GoogleEarth over northern part of city Vilnius (Fig 2).

Fig 2. Experimental area fragment of satellite imagery

over city Vilnius from Google Earth

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The next step of the investigation has been based on

analysis of rectification results geometric accuracy.

Reference and rectification data are checked comparing

with results from digital aerial images processing using

digital photogrammetry approach. Digital Photo-

grammetric Workstation LISA has been applied for

checking results from images rectification measuring of

about 120 points. Digital photogrammetric softwareLISA

with extensions of LISA FOTO and raster GIS software

LISA BASIC developed at the Hannover University,

Germany has a lot of possibilities in image processing

(Linder 2009).

The image rectification results for accuracy

evaluation were compared with results from stereoscopic

measurements of the same points. The geometric

accuracy Root Mean Square Error (RMSE) ofinvestigated rectified images at different scales (1:500

and 1:1000) have been received 6 cm and 15 cm

respectively. Such results fulfil the requirements fortopographic mapping at scales of 1:500 1:2000.

4. Conclusions

The digital satellite imagery from Google Earthcanbe applied for accurate city mapping when rectification

of imagery has been processed using technology named

Five control points introducing Prof. RuanWei (Tong

Ji University, Shanghai, China) algorithm.

The image rectification process takes short time

(about 45 minutes) and using only five control points.Satellite or aerial images needs well distributed and

accurate defined control points. There arise difficulties

for finding points well seen on imagery. Control points

with significant height differences are not desirable (e.g.

points on buildings roofs, etc.).

The accuracy of created models satisfies

requirements for large scale mapping.

ReferencesDonnay, J. P.; Kaczynski, R. 2005. Didactic and Digital

Photogrammetric Software. Users Guide. Department of

Geomatics, University of Liege, Belgium; Department of

Photogrammetry, Institute of Geodesy and Cartography,Warszawa, Poland. 71 p.

Ewiak, I.; Kaczynski, R. 2010. Potential for Resurs DK-1

satellite data. Geodezija ir kartografija [Geodesy and

Cartography], 36 (2): 4549.

Konecny, G. 2003. Geoinformation Remote Sensing,

Photogrammetry and Geographic Information Systems.

Tylor & Francis, London. 248 p.

Linder, W. 2009.Digital Photogrammetry.A Practical Course.Springer-Verlag, Berlin Heidelberg. 226 p.

Manual of Photogrammetry(Edited by Chris McGlone). 2004.

Fifth Edition. American Society for Photogrammetry and

Remote Sensing, Maryland, USA. 1151 p.

Ruan, W. 1988. The Method of Weighted Residuals for Solving

Surveying Collocation Problems. Journal of Tong JiUniversity:3342.

Ruan, W. 2008. Introduce a 1:500 map was made by the image

of Google Earth and its software. The International

Archives of the Photogrammetry, Remote Sensing and

Spatial Information Sciences. Vol. XXXVII. Part B3b.Beijing. 503-504.

Ruzgien, B. 2007. Comparison between digital

photogrammetric systems. Geodezija ir kartografija

[Geodesy and Cartography], XXXIII (3): 7579.Wolf, P. R.; Dewitt, B. A. 2000. Elements of photogrammetry

with application in GIS. McGraw-Hill. 608 p.