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Pixel-oriented analysis. Object-oriented analysis. Remote Sensing classifications. Pixel-oriented limitations. Problems when dealing with rich information. Inappropriate scale of work. Inaccurate with elements of similar spectral behaviour (ex.: habitats). Salt and pepper effect.

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Presentation Transcript
slide1

Pixel-oriented analysis

Object-oriented analysis

Remote Sensing classifications

slide2

Pixel-oriented limitations

Problems when dealing with

rich information

Inappropriate

scale of work

Inaccurate with elements of similar spectral behaviour (ex.: habitats)

Salt and pepper

effect

slide3

Which kind of structure can

be seen in here?

Object-oriented approach

Important semantic information, necessary to interpret an image, is not represented in single

PIXELS, but in meaningful OBJECTS ,

and their mutual relationships

slide4

Segmentation

Classification

Procces characteristics

Object parameters

color stadistics

texture

shape & size

context

Allows scale definition

Different scales

Hierarchical system

Multi source data fusion

slide5

Image

Segmented layer

Classified layer

Analysis workflow

Multi-resolution segmentation

Classification

slide6

multispectral image (2.8 m, color)

Pancromatic image (0.7m, b/w)

Tematic

information

Example

Objective: To study an urban settlement in Madrid (Spain)

by means of remote sensing .

Multi-source data fusion

slide7

Example

 Segmentation

slide8

Example

 Hierarchical classification

slide9

Example

 Hierarchical classification

slide10

Example

 Hierarchical classification

slide11

Example

 Hierarchical classification

 Correct identification of roads, paths, houses, back-gardens, pools...

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