the analysis of chosen generalization methods krzysztof sośnica [email protected]...

The Analysis of Chosen The Analysis of Chosen Generalization MethodsGeneralization Methods

Krzysztof Sośnica

[email protected]

Wrocław, 27th May 2008Wrocław, 27th May 2008SC of GeoinformaticsSC of GeoinformaticsInstitute of Geodesy and GeoinformaticsInstitute of Geodesy and Geoinformatics

Wrocław University of Environmental and Life Wrocław University of Environmental and Life SciencesSciences

Krzysztof SośnicaKrzysztof Sośnica

SC of GeoinformaticsSC of Geoinformatics

Wrocław U of E and LSWrocław U of E and LS

Introduction

Sonoric digitizer

Generalization

methodsSonoric

generalization

Results

Characteristic of method

Bibliography

Summary


Cartographical reefsCartographical reefs

Cartography projection

Terrain elevation

Generalization




Introduction

Sonoric digitizer

Generalization

methodsSonoric

generalization

Results


Bibliography

Summary


GeneralizationGeneralization

Cartographic generalization is the process of selecting and representing information of a map in a way that adapts to the scale of the display medium of the map. In this way, every map has, to some extent, been generalized to match the criteria of display. This includes small-scale maps, which cannot convey every detail of the real world. Cartographers must decide and then adjust the content within their maps to create a suitable and useful map that conveys geospatial information within their representation of the world.

Generalization is not a process that only removes and selects data, but also a process that simplifies it as well. Simplification is a technique where shapes of retained features are altered to enhance visibility and reduce complexity.




Introduction

Sonoric digitizer

Generalization

methodsSonoric

generalization

Results


Bibliography

Summary


SimplificationSimplification




Introduction

Sonoric digitizer

Generalization

methodsSonoric

generalization

Results


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Summary


Sonoric methodSonoric method

The method of sonoric code as well as the device was created and developed by Ewa Krzywicka-Blum and Janusz Kuchmister. This method assumes connecting auditory and kinaesthetic senses. It allows to develop the educational aids by adding drawings, maps, graphs or schemata, which are altered from simplified graphic form into sound.




Introduction

Sonoric digitizer

Generalization

methodsSonoric

generalization

Results


Bibliography

Summary


1 – Operating plate, 5. – Horizontal axis, 18. Indicator, 25 – Vertical axis, 36. Headphones, 38. Discslot, 41. Controling and registering system,




Introduction

Sonoric digitizer

Generalization

methodsSonoric

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Summary


Fig. 1. The operational field of the sonic digitizer

Similarly to the two linear Cartesian co-ordinates locating point belonging to a graphical scene, two characteristics of a signal – the frequency along vertical direction and the volume, in relation to the horizontal move of pointer in the operational area, have been chosen.




Introduction

Sonoric digitizer

Generalization

methodsSonoric

generalization

Results


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Summary


The blind working with the sonic digitizer

Decoding of the elements of the scenes may be performed in three different versions:1) A teacher decodes the scene themselves, moving the detector in the operation area, while a pupil hears out the sounds in the phones,2) A teacher and a pupil decode the scene together (pupil’s and teacher’s hands together move the detector in the operation area) while the pupil hears out the sounds in the phones,3) The pupil decodes the contents of the scene unaided, steering the movement of the detector in the operation area and simultaneously hearing out the sounds in the phones. Source: 9, Krzywicka-Blum, Kuchmister, 1999




Introduction

Sonoric digitizer

Generalization

methodsSonoric

generalization

Results


Bibliography

Summary


Example - rectangleExample - rectangle




Introduction

Sonoric digitizer

Generalization

methodsSonoric

generalization

Results


Bibliography

Summary


Second ExampleSecond Example




Introduction

Sonoric digitizer

Generalization

methodsSonoric

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Summary


Example - PolandExample - Poland




Introduction

Sonoric digitizer

Generalization

methodsSonoric

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Summary





Introduction

Sonoric digitizer

Generalization

methodsSonoric

generalization

Results


Bibliography

Summary


Tobler’s GeneralizationTobler’s Generalization

Eliminating of points without including into consideration the topology.




Introduction

Sonoric digitizer

Generalization

methodsSonoric

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Summary


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Egypt – original contour– 58 pointsEgypt – original contour– 58 points

Result of generalization:Result of generalization:

Egypt – after simplification– 27 pointsEgypt – after simplification– 27 points

- Similar areas;-- Center of gravity is kept;

- Decomposition of points is regular;

Tobler’s GeneralizationTobler’s Generalization




Introduction

Sonoric digitizer

Generalization

methodsSonoric

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Bibliography

Summary


Jenk’s generalization:Jenk’s generalization:

Eliminating points which can be treated as reclinig on the contour line (which distance from the straight line is less than the allowed distance).




Introduction

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Generalization

methodsSonoric

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Summary


Jenk’s generalization:Jenk’s generalization:

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- Areas are kept;- Perimeters are kept;

- Centres of gravity are kept;-Decomposition of points is irregular;


Result of generalization:Result of generalization:





Introduction

Sonoric digitizer

Generalization

methodsSonoric

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Results


Bibliography

Summary


Jenk’s and Tobbler’s generalization:Jenk’s and Tobbler’s generalization:


Result of combined generalization:Result of combined generalization:


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Area change - 0,35%




Introduction

Sonoric digitizer

Generalization

methodsSonoric

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Results


Bibliography

Summary


Lang’s generalization:Lang’s generalization:

This algorithm demands two parameters:- amount of „front points” (n) during examination;- Parameter of tolleration (t)




Introduction

Sonoric digitizer

Generalization

methodsSonoric

generalization

Results


Bibliography

Summary


Lang’s generalization:Lang’s generalization:

Original - Croatia (653) Croatia after simplification(36)

-areas of objects are kept-large reduction of points;

-shape of object is quite good kept




Introduction

Sonoric digitizer

Generalization

methodsSonoric

generalization

Results


Bibliography

Summary


Chrobak’s generalization:Chrobak’s generalization:

In this method hierarchy of points as well as topology are kept. In the first step we choose the constant points, which shall not be removed, then (the second step) we create new points on the contour line.




Introduction

Sonoric digitizer

Generalization

methodsSonoric

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Results


Bibliography

Summary


Chrobak’s generalization:Chrobak’s generalization:

Original – Croatia (653) After simplification (22)

-Particular large amounts of iterations;-Shape of objects are kept;

- Areas are kept




Introduction

Sonoric digitizer

Generalization

methodsSonoric

generalization

Results


Bibliography

Summary


Possible directions:

Sonoric generalization:Sonoric generalization:




Introduction

Sonoric digitizer

Generalization

methodsSonoric

generalization

Results


Bibliography

Summary


Sonoric generalization:Sonoric generalization:

Original - Croatia (653) Croatia after sonoric generalization(53)




Introduction

Sonoric digitizer

Generalization

methodsSonoric

generalization

Results


Bibliography

Summary


Generalization in Orffe’s scale:Generalization in Orffe’s scale:

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Introduction

Sonoric digitizer

Generalization

methodsSonoric

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Summary


Shape ratiosShape ratios

Shape ratios are mathematic equations which describes the geometrical shape of contours. They can be used as an objective indicators for characteristic the shape.

S – area

L – perimeter

Examples:Examples:




Introduction

Sonoric digitizer

Generalization

methodsSonoric

generalization

Results


Bibliography

Summary


Tobler’s generalization(34)Original(745)

Jenk’s generalization (86)

Lang’s generalization (36)




Introduction

Sonoric digitizer

Generalization

methodsSonoric

generalization

Results


Bibliography

Summary


Sonoric generalization(32)

Original (745)

Chrobak’s generalization(34)

Sonoric generalization(22)




Introduction

Sonoric digitizer

Generalization

methodsSonoric

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Results


Bibliography

Summary


Original(745)

in Orffe’s scale (54)




Introduction

Sonoric digitizer

Generalization

methodsSonoric

generalization

Results


Bibliography

Summary


Chrobak’s generalizatio

n(34)Generalization Area W3 W4 W5 W6

Original 1 0,83 0,72 0,91 0,56Tobler 1,12 0,85 0,68 0,83 0,49Jenks 0,82 0,8 0,81 0,78 0,43Lang 0,93 0,85 0,75 0,88 0,52

Chrobak 0,98 0,84 0,72 0,87 0,55Sonoric 1,18 0,88 0,63 0,71 0,48

Lang’s generalization(

36)




Introduction

Sonoric digitizer

Generalization

methodsSonoric

generalization

Results


Bibliography

Summary


Results:Results:

- It is possible to use various simplification It is possible to use various simplification algorithms for generalization the contour lines,algorithms for generalization the contour lines,

- The best results are achieved by the Lang’s The best results are achieved by the Lang’s method (velocity) and by Chrobak’s method method (velocity) and by Chrobak’s method

(accuracy).(accuracy).




Introduction

Sonoric digitizer

Generalization

methodsSonoric

generalization

Results


Bibliography

Summary


BibliographyBibliography1. Klimczak H., 2003: „Modelowanie kartograficzne w badanaiach rozmieszczenia zjawisk 1. Klimczak H., 2003: „Modelowanie kartograficzne w badanaiach rozmieszczenia zjawisk

przestrzennych”, Wydawnictwo AR we Wrocławiu, Wrocław 2003przestrzennych”, Wydawnictwo AR we Wrocławiu, Wrocław 2003

2. Krzywicka-Blum E., 1998; „Sonoryczne uwarunkowania kodowania punktów”, Zesz. Nauk. AR we 2. Krzywicka-Blum E., 1998; „Sonoryczne uwarunkowania kodowania punktów”, Zesz. Nauk. AR we Wrocławiu, S. Geodezja i Kartografia Nr 343, str. 139-134, WrocławWrocławiu, S. Geodezja i Kartografia Nr 343, str. 139-134, Wrocław

3. Kuchmister J., 1998: „Analiza dokładności pozycjonowania punktów w polu operacyjnym 3. Kuchmister J., 1998: „Analiza dokładności pozycjonowania punktów w polu operacyjnym digitizera sonorycznego”, Zesz. Nauk. AR we Wrocławiu, S. Geodezja i Kartografia Nr 343, digitizera sonorycznego”, Zesz. Nauk. AR we Wrocławiu, S. Geodezja i Kartografia Nr 343, str. 181-190, Wrocław, Polskastr. 181-190, Wrocław, Polska

4. Krzywicka-Blum E , Kuchmister J., 1999, monografia, str. 100, Kat. Geod. i Fot. 4. Krzywicka-Blum E , Kuchmister J., 1999, monografia, str. 100, Kat. Geod. i Fot. AR, Wrocław, AR, Wrocław, PolskaPolska

5. Krzywicka–Blum E., Kuchmister J., 2005, „Rola sekwencji sygnałów sonorycznych w tworzeniu 5. Krzywicka–Blum E., Kuchmister J., 2005, „Rola sekwencji sygnałów sonorycznych w tworzeniu wyobrażeń przestrzennych osób niewidomych”, Fizjoterapia t 13, Nr 2 str. 33–39, Wrocławwyobrażeń przestrzennych osób niewidomych”, Fizjoterapia t 13, Nr 2 str. 33–39, Wrocław

6. Ćmielewski K. Krzywicka–Blum E., Kuchmister J, Parol M., 2005, „Urządzenie do odtwarzania 6. Ćmielewski K. Krzywicka–Blum E., Kuchmister J, Parol M., 2005, „Urządzenie do odtwarzania testów sonorycznych”, Patent UPRP Nr 189881, Polskatestów sonorycznych”, Patent UPRP Nr 189881, Polska

7. Bubliński Z. Cetnarowicz K. : „Zastosowanie elementu składowego do przetwarzania obrazów 7. Bubliński Z. Cetnarowicz K. : „Zastosowanie elementu składowego do przetwarzania obrazów optycznych”, Tom 10, zeszyt 1, 1991optycznych”, Tom 10, zeszyt 1, 1991

8. Krzywicka-Blum E.,Kuchmister J. „The sound coding method as an educational aid for the blind”8. Krzywicka-Blum E.,Kuchmister J. „The sound coding method as an educational aid for the blind”9. Krzywicka-Blum E., Kuchmister J. „The sonic modelling in blind people education”9. Krzywicka-Blum E., Kuchmister J. „The sonic modelling in blind people education”

10. Chrobak T. „Automatyzacja procesu generalizacji kartograficznej i jej wyników prezentowanych 10. Chrobak T. „Automatyzacja procesu generalizacji kartograficznej i jej wyników prezentowanych na mapie”, 2006 AGH Krakówna mapie”, 2006 AGH Kraków

Thank you for your attentionThank you for your attention

Krzysztof Sośnica

[email protected]

Wrocław, 27th May 2008Wrocław, 27th May 2008SC of GeoinformaticsSC of GeoinformaticsInstitute of Geodesy and GeoinformaticsInstitute of Geodesy and Geoinformatics

Wrocław University of Environmental and Life Wrocław University of Environmental and Life SciencesSciences

the analysis of chosen generalization methods krzysztof sośnica [email protected]...

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