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Maritime University of Szczecin

Akademia Morska w Szczecinie

2011, 28(100) z. 1 pp. 48–52 2011, 28(100) z. 1 s. 48–52

The accuracy of defining position of sea infrastructure objects

using satellite imagery data

Dokładność określania pozycji obiektów infrastruktury

morskiej z wykorzystaniem satelitarnych danych obrazowych

Andrzej Klewski

1

, Józef Sanecki

1

, Grzegorz Stępień

2

, Weronika Klewska

3

Paweł Pabisiak

4

1 Maritime University of Szczecin, Faculty of Navigation, Chair of Geoinformatics

Akademia Morska w Szczecinie, Wydział Nawigacyjny, Katedra Geoinformatyki 70-500 Szczecin, ul. Wały Chrobrego 1–2, e-mail: a.klewski@am.szczecin.pl

2 Military Geographical Center

Wojskowe Centrum Geograficzne

3 Enterprise of Geophysical Researches Ltd

Przedsiębiorstwo Badań Geofizycznych sp. z o.o.

4 Command of 2nd Mechanized Corps

Dowództwo 2 Korpusu Zmechanizowanego

Key words: : satellite imagery, accuracy of defining position, satellite orthophotomap Abstract

The article presents the analysis of accuracy position defining of sea infrastructure objects using high-resolution satellite imagery. The analysis bases on defining co-ordinates of objects using large-scale maps (field measurements) and their comparison to co-ordinates reading on processed satellite imagery. The article presents the author’s method of location precision enlarging on satellite imagery through additional imagery data support (geodetic and cartographic). Results of conducted analysis define accuracy of object’s location on satellite imagery and are related to the possibility of using these images to large scale cartographical studies.

Słowa kluczowe: obraz satelitarny, dokładność określania pozycji, ortofotomapa satelitarna Abstrakt

Artykuł przedstawia analizę dokładności określania pozycji obiektów infrastruktury morskiej z wykorzysta-niem wysokorozdzielczych obrazów satelitarnych. Analiza opiera się na określeniu współrzędnych obiektów w oparciu o wielkoskalowe mapy (pomiary terenowe) i porównaniu ich do współrzędnych na przetworzonym obrazie satelitarnym. Artykuł prezentuje autorską metodę zwiększania dokładności lokalizacji obiektów na zdjęciach satelitarnych w oparciu o dodatkowe dane obrazowe (geodezyjne i kartograficzne). Wyniki prze-prowadzonej analizy określają dokładność lokalizacji obiektów na obrazach satelitarnych i odnoszą się do możliwości wykorzystania tych obrazów w kartograficznych opracowaniach wielkoskalowych.

Introduction

The building of the Gas-harbour in Świnoujście (Fig. 1) and the West-pomeranian Logistic Center – the Szczecin harbour, where the roads of four branches of transport (sea, river, railway and motor) intersect, opens the way to quick development of economy and infrastructure of the region [1]. Every

type of investment work on each stage (planning, realization, inventory control) is connected with the need of locating an object in space or / and on a map. In investment areas, including harbours and sea terrain, a basic map should be created and constantly updated. The lack of large-scale studies which would project among other things data from land records, territorial development (cables

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running on the bottom of the sea), and in case of territorial sea, e.g. the course of communication routes, navigational marking [2], influences devel-opment of investment. Additionally, at present existing city maps do not give the general view on location of port infrastructure units which usually undergo generalization process, or are overlooked. Existing maps and plans do not reflect logistic pos-sibilities of harbours, their potential, as well as activities in the region.

Fig. 1. Gas-harbour (storage) in Świnoujście – the visualiza-tion [3]

Rys. 1. Gazoport w Świnoujściu – wizualizacja [3]

In the present study, authors introduced possi-bilities of high-resolution satellite imagery used to locate objects of infrastructure in sea harbours area. In the article, the method of location precision enlarging on satellite imagery through additional image correction is proposed. The assessment of improvement of accuracy will be done on the basis of comparison of co-ordinates of measured objects, before and after the stage of additional correction of the image, with received through measurements on the source imagery (the map) co-ordinates.

The methods of position fixing

Currently, fixing co-ordinates of infrastructure is performed on the basis of [4]:

 geodetic measurements: classical method using ground points matrix, satellite – using global po-sitioning systems (e.g. GPS);

 remote sensing imagery data: aerial and satellite orthophotomaps;

 autonomic measuring systems (e.g. using gyro-scopic techniques, gravimetric measurements, astronomical measurements);

 location of objects on a map;

 combined methods (a compilation of above mentioned methods).

Determining a position on satellite imagery is influenced by a variety of factors connected to image registration process, acquaintance of external (spatial) orientation of recording device, photo-points location, as well as methods of geometrical and radiometrical corrections of the image [5]. The acquired data are distorted both by curvature of the Earth and the defects of applied sensors [4]. Fur-thermore, satellite images contain noises connected with atmospheric haze and the unequal lighting of terrain [2, 4]. Therefore, readings from image co-ordinates can differ from those measured in terrain, which leads to errors of several pixels [6].

In the case of using methods based on direct measuring, it can be an additional problem to pre-cisely determine co-ordinates of objects lying far into sea, on platforms or breakwaters where the only solution might be satellite (GPS), or astro-nomical (using sun or stars position) measurements. Their realization is possible in the situation of direct access to terrain. Otherwise, it becomes un-feasible. The present article proposes the method of remote and quick determination of co-ordinates using high-resolution satellite imagery.

The method of enlarging accuracy of object location on satellite imagery

The studied method is based on conducting op-erations according to the schema presented below (Fig. 2).

In the proposed method, what comes as the first step is the choice of input image which is used as reference for further measurements. A source (basic) material can be a large scale map, e.g. in scale 1:10 000, a basic map, or orthophotomap. As source material, an aerial orthophotomap worked out in scale 1:5000 was chosen. As studied material parts of satellite images from two internet portals (Google is one of them) were chosen. The reason this was done is that, it is possible to read co- -ordinates in Google Earth application.

In the first stage of works, these co-ordinates were compared with co-ordinates on source image (aerial orthophotomap). Next, a part of a satellite orthophotomap (Google) was processed (printed) to the image file format and transformed to the aerial orthophotomap co-ordinate system using method “Image to Image”. Geomedia Professional applica-tion was used for this purpose. Next, another part of the orthoptotomap was processed (printed) to the image file format (coming from another internet portal) and adjusted (transformed) using the same method to the aerial orthophotomap co-ordinate system. Thus, a mosaic of three orthophotomaps was created (Fig. 3).

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The next step was a mathematic analysis of ac-curacy of carried out transformations of the images. This was followed by a comparison of co-ordinates on all images using check points. The authors of the study selected points for transformations (GCP – General Control Point) using the principle of pro-ximity – all of them were located close to each other in the radius of a kilometre. An interesting problem, from the point of view of this paper, is that what degree such a choice of points of adjust-ment influences the accuracy of the location of distant points (in a few kilometres radius), which imitates determining points on a sea surface by adjustment of the images to a co-ordinate system to a position of points on the land (Fig. 4).

The next stage was a comparison of co-ordinates of fixed “distant” points with co-ordinates of their counterparts on the source image (aerial orthopho-tomap). Finally, the accuracy of fixing co-ordinates of distance points was calculated.

Fig. 4. Adjusting points (GCP) and distant point, determining Rys. 4. Punkty wpasowania (GCP) i punkty odległe, wyzna-czanie

Fig. 2. The schema of the enlarging accuracy method of object location on satellite imagery Rys. 2. Schemat metody zwiększania dokładności lokalizacji obiektów na obrazach satelitarnych

Fig. 3. Adjustment of images: 1 – aerial orthophotomap (pixel size 0.6 m), 2 – orthophotomap from the Internet (pixel size 1.8 m), 3 – orthophotomap from the Internet (pixel size 1 m)

Rys. 3. Wpasowane obrazy: 1 – ortofotomapa lotnicza (wielkość piksela 0,6 m), 2 – ortofotomapa z serwisu internetowego (wielkość piksela 1,8 m), 3 – ortofotomapa z serwisu internetowego (wielkość piksela 1 m)

Selection of source material and images to study

Co-ordinates measurement in internet application Co-ordinates measurement on aerial orthophotomap Comparison of received co-ordinates

Transformation of satellite image from internet application to the aerial

orthophotomap co-ordinate system

Transformation of additional satellite image (of the same area) to the aerial orthophotomap co-ordinate system

Measurement on imagery Analysis of received results Assessment of received results

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Measuring of co-ordinates

According to the method employed herein, the measurements of co-ordinates (UTM) were exe-cuted first on source image, and then on satellite image (Satellite image 2) using Google Earth appli-cation (Tab. 1).

Measurements were executed in eight points. Four of them later served as points for transforma-tion of satellite image to aerial orthophotomap sys-tem (General Control Point), and another four as check points of image adjustment in the Image to Image method. Next, the third image was trans-formed to the two adjusted images, and then co- -ordinates of the same points were measured on all three images (Tab. 2).

Then, distant points were measured on the im-age marked as satellite imim-age 3 (Fig. 4) and ordinates of these points were compared with co-ordinates on the source image (Tab. 3).

Table 3. UTM co-ordinates of measuring distant points Tabela 3. Współrzędne UTM pomierzonych punktów odleg-łych

Source image

(aerial orthophotomap) Satellite image 3 453003.11 5974984.01 453003.84 5974984.80 453002.43 5975157.55 453003.48 5975157.52

Analysis of accuracy

In accuracy analysis, errors of object locations on satellite imagery for control and distant points, in relation to source image, were calculated and tabulated (Tab. 4).

Table 4. The table of errors of fixed co-ordinates [m]

Tabela 4. Zestawienie błędów wyznaczanych współrzędnych [m]

Source image (aerial orthophotomap)

Satellite

image 2 Satellite image 3

Size of pixel 0.6 1.8 1 RMS error – 0.98 0.29 Mean error m0 marking co-ordinates on control points – 0.78 0.49 Mean error m0 marking co-ordinates on distant points – – 1.06

Additionally, table 4 shows the size of a pixel for every analyzed image, as well as the error of image transformation in the image to image method – RMS error. The introduced analysis of error allows the conclusion that the error of marking co-ordinates on images is approximate in size to the RMS error value (for image 2 a bit lower, for image 3 a bit higher).

Table 1. UTM co-ordinates of measuring points. Marking satellite image as “2” is assumed according to figure 3

Tabela 1. Współrzędne UTM pomierzonych punktów. Oznaczenie obrazu satelitarnego jako „2” przyjęto zgodnie z rysunku 3 Source image (aerial orthophotomap) Satellite image 2 Difference in point setting [m]

451166.18 5973336.86 451160.90 5973343.10 8.17 450910.56 5973326.19 450904.62 5973331.54 7.99 450899.90 5973347.89 450892.66 5973354.07 9.52 450721.15 5973364.81 450714.83 5973371.51 9.21 450552.70 5972834.08 450545.35 5972836.55 7.75 451383.18 5973024.60 451377.08 5973030.50 8.49 451280.56 5972849.16 451275.08 5972855.61 8.46 451238.27 5972823.42 451231.61 5972829.34 8.91

Table 2. UTM co-ordinates of measuring points after transformation in relation to source image. Marking satellite images as “2” and “3” is assumed according to figure 3

Tabela 2. Współrzędne UTM pomierzonych punktów po transformacji względem obrazu źródłowego. Oznaczenia obrazów satelitarnych jako „2” i „3” przyjęto zgodnie z rysunkiem 3

Source image

(aerial orthophotomap) Satellite image 2 Satellite image 3 451166.18 5973336.86 451167.32 5973336.41 451166.39 5973337.10 450910.56 5973326.19 450912.67 5973326.50 450911.06 5973325.58 450899.90 5973347.89 450900.92 5973347.81 450899.07 5973347.93 450721.15 5973364.81 450722.09 5973366.83 450720.24 5973365.45 450552.70 5972834.08 450553.86 5972833.11 450553.63 5972830.80 451383.18 5973024.60 451382.56 5973023.92 451384.17 5973024.84 451280.56 5972849.16 451278.85 5972846.94 451280.01 5972849.24 451238.27 5972823.42 451240.14 5972823.43 451240.37 5972822.97

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It is worth underlying that the precision of adjustment of images was only half a pixel. In such not large transformation error in relation to a pixel size, the error of defining co-ordinates of points for both images is also smaller than a pixel. Further-more, the error of defining of distant points is insignificantly larger than pixel size. This demon-strates the possibility of precise co-ordinates deter-mination in spite of a few kilometre distance between GCP points (Ground Control Points). It is also worth noting that the mean error of defining co-ordinates on the satellite image 2 before addi-tional correction was about 8 m (see Tab. 2), and after performing this correction (a renewed fitting the image) was already only 0.78 m (Tab. 4).

Conclusions

The present article demonstrates the method of increasing the precision of objects location on the basis of additional satellite image correction in relation to higher geometrical accuracy (aerial orthophotomap). Therefore, the following may be concluded:

 satellite imagery can be employed in carto-graphical studies of small areas (several kilome-tres) after additional geometrical correction in relation to materials of higher accuracy of geo-metrical, e.g. aerial orthophotomap, or basic map;

 the stage of additional satellite image correction enhances the precision of objects location on the basis of this image; the degree of enhancement may come up to several or dozen fold in de-pendence on the original accuracy of satellite image (a level of its correction) and the size of processed pixel of image;

 additional image correction can employ photo-points or co-ordinates determined in a geodetic (measuring) way, e.g. corners of buildings for satellite imagery transformation (correction) stage using these points;

 calculating co-ordinates using satellite images with resolution below (better than) one meter (e.g. from QuickBird – 0.6 m resolution) and applying the method described in the article can

result in the precision of determining points in relation to source image of about 1 m;

 the absolute accuracy of fixing position using transformed (geometrically corrected) satellite image and applying the method and the error of point location on the source image of 0.3 mm – in the scale of the study – for scale 1:5000 gives value 1.5 m (0.3 mm x 5 = 1.5 m); the accuracy calculated using the same method for a distant point (about several kilometres) is 1.8 m;

 employing more accurate source materials, e.g. basic map in scale 1:1000, errors of point loca-tion on a satellite image, using the applied method, should be less than 0.6 m, and for dis-tant point should not exceeded 1.1 m;

 the received accuracy figures allow to use satel-lite images in large-scales cartographical stud-ies, also for updating maps;

 the obtained accuracies enhance geometrical precision of satellite images approximately to the level of aerial images.

In authors’ opinion, the results and preliminary conclusions encourage to further research in this area. This, in turn, can lead to opening a new chap-ter in the field of using satellite imagery in produc-tion and updating of large-scale maps, where nowadays aerial photographs are universally ap-plied.

References

1. CHRISTOWA CZ.: Strategia rozwoju funkcji logistycznej polskich portów morskich w warunkach globalizacji go-spodarki. Wyższa Szkoła Morska w Szczecinie, accessible on http://www.portymorskie.pl/2001/06.pdf, 22.06.2009. 2. WOLNY B.: Geodezja i kartografia na obszarze morza

tery-torialnego. Accessible on http://pwiing.szczecin.uw.gov.pl/ page/artykuly/morze.pdf, 22.06.2009.

3. http://www.ums.gov.pl/, accessible on 22.06.2009

4. KLEWSKI A., SANECKI J., MAJ K., STĘPIEŃ G., GMAJ R.: The method of using remote sensing high-resolution imagery data in cartographical study of seaports. Zeszyty Naukowe Akademii Morskiej w Szczecinie, Nr 22(94), 2010, 33–38. 5. Teledetekcja pozyskiwanie danych. Praca zbiorowa pod

red. J. Saneckiego, Wydawnictwo Naukowo-Techniczne, Warszawa 2006.

6. MAJ K., PABISIAK P., STĘPIEŃ G., WYSOTA R.: Detekcja a identyfikacja – od wykrywania do analizy technicznej. Magazyn Geoinformacyjny GEODETA, wrzesień 2007.

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