supervised classification using software erdas imagine

5/20/2018 Supervised Classification Using Software Erdas Imagine

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SUPERVISED

CLASSIFICATION USINGSOFTWARE ERDAS IMAGIN

MUHAMAD FAZRUL SHAFIQ BIN ALIASMOHAMAD AKMAL BIN ABDUL RAZAK


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INTRODUCTION

Supervised classification is literally different from unsupervised classificationhuman guided classification instead of unsupervised which is calculated by t

Supervised classification is more accurate for mapping classes, but it depen

on the ability and skills of image specialist. However, the strategy is simple w

specialist must recognize conventional (real and familiar) or meaningful clas

scene related to their knowledge , such as personal experience with what is

the scene or by experience with thematic maps as well as by on-site-visits


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DIFFERENCE BETWEEN SUPERVISEDUNSUPERVISED CLASSIFICATION

SUPERVISED CLASSIFICATION UNSUPERVISED

CLASSIFICATIO

Based on the idea of users can select a region

in an image that are representative of specific

classes.

The user need to bound the region into one

group if the region is similar to other region. These bounds are depends on spectral

characteristic in the area usually its brightness

or strength of reflection.

User need to direct the image processing

software to use a testing sets or input classes

as reference for the classification based on

user knowledge

Software analysis at an image w

user providing sample classes

Software using its own tools or te

determine which the region are r

group them together The user only can specify which

software will use and desired nu

output classes but does not aid i

classification process

User also need to know the area

classified into groups of region w

characteristics that related to the

features on the ground.


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PROCEDURE

1. Open ERDAS IMAGINE and select the File tab. Click the Open folder and select r

from the menu


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2. Next, navigate to the folder on your hard drive that contains your imagery. In the ca

are opening an 8 band multispectral Ortho Ready 2A Geotiff of WorldView-2. Select the

and then click OK in the window.


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3. The image will then open and automatically load the True Color bands into the Red,

Blue guns. Under the Multispectral tab up in the menu under the bands section the us

different WV-2 band combinations. For the example below we selected the false color Iour supervised classification samples.


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AOI Tool

4. Once the wv-2 image is loaded the next step is to start collecting samples for classif

done using the AOI tool. To create an AOI go to the File Tab > New > 2D View > AOI Ltwo tabs will appear which is called Drawing and the other is Format.


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5. Click on the Drawing tab. Under the insert Geometry section click on the Polygo

6. Zoom into your first area to collect a sample using the zoom button and begin coll

first sample with multiple left clicks of the mouse. Double left click to close.

Collect at least three samples for each feature type so that you have a good represen

class type. For this example we are using an image collected over the burn region out

Boulder, Colorado. In this example, collect four different classes with three examples

:-

a) 3 samples from burned vegetation (in black in the false IR image),

b) 3 examples of healthy vegetation,c) 3 examples of man-made features,

d) 3 examples of soil

Each of these polygons will be saved to an AOI FILE.


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Signature Editor

7. Then, add these AOIs to a signature file for use as the training data set for supervis

classification. To open your signature file go to the Raster tab and click on the Superv

under the Classification section.


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8. Next, go into the AOI tab in the main viewer and click on the Select button and sel

AOIs and click on the Create new signature from AOI in the signature editor win

this for all three burn areaAOIs. Once three classes of burn have created, merge t

into one burn class with the aois spectral properties.


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8. Double left click on this new class1 and rename it to something representative of th

Burn Vegetation. You can then delete all the other classes that were input. Then, re

process for the other classes from the aoi.


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9. After the signature file are in their own classes, save the Signature File under the S

Editorwindow click on fileand save as. Navigate to the folder to save the signature f

a name. Then click OK.


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Supervised Classification

10. Under the raster tab click on Supervised and select Supervised Classification.

classification window will open. Then, select the input raster file in the supervised clas

window. Select the saved signature file and open the folder next to the Input Signatuthe .Sig file saved earlier. After that, select the folder to save the output classification f

Classified File and rename the .img file.


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11.Finally, colors of the classes can be change for better representation by click on the

classification.img in the contents window and open the Display Attribute Table. T

on the bottom of the viewer will appear. Find the classes and right click under the c

and select the colors.


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TAMMAT

supervised classification using software erdas imagine

Documents

open erdas

sample classes software

image wuser

image processingsoftware

skills of image specialist

aoi tool4

open folder

mapping classes