Remote Sensing classifications

Pixel-oriented analysisObject-oriented analysis

Pixel-oriented limitations

Salt and pepper effect

Inappropriate scale of work

Problems when dealing with rich information

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

Important semantic information, necessary to

interpret an image, is not represented in single

PIXELS, but in meaningful OBJECTS ,

and their mutual relationships

Object-oriented approach

Which kind of structure can be seen in here?

color stadistics

shape & size

texture

context

Procces characteristics

Object parameters

Allows scale definition

Segmentation

Classification

Hierarchical system

Different scales

Multi source data fusion

Image

Multi-resolution segmentation

Classification

Analysis workflow

Segmented layer

Classified layer

multispectral image (2.8 m, color)

Example

Pancromatic image (0.7m, b/w)

Tematic information Multi-source data fusion

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

by means of remote sensing .

Segmentation

Example

Example

Hierarchical classification

Example

Hierarchical classification

Example

Hierarchical classification

Example

Hierarchical classification

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