This document provides an overview of image classification tools in ArcGIS 10: - Image classification allows converting multiband satellite images into single band images with defined or undefined classes. - ArcGIS 10 introduces an image classification toolbar with different classification techniques like unsupervised iso clustered classification. - Training samples developed in other software can be used, and samples can be created or opened in the sample manager for supervised classification.

1. Image Classification in ArcGIS10
By
Ashok Peddi

2. Introduction to image classification
• Image classification tool bar has been introduced in
ArcGIS 10 with different classification techniques .
• Image classification is the process of converting
multiband satellite image into single band image
with different classes, defined or undefined.
• You can develop training sample and you can use the
samples/ trained pixels which you have developed
using other remote sensing software's as well.
• To use this tool bar you need spatial Analyst
extension.

3. Open ArcGIS and right click on the
main menu bar to enable the Image
Classification toolbar(default disabled
from main menu).

4. You need to enable
Spatial Analyst
Extension by going
to customize ->
extension

5. Once you check “image
classification "it automatically
add to the ArcGIS main menu.
Then add the image which you
want to classify to Arc Map.

6. Once you add the image to Arc
Map, it will be added to image
classification tool bar.

9. Use these
button to add
Click on iso delete the
clustered images and
Unsupervised mention the
Classification number of
bands then
click ok ok

10. 1
2 If you have training
sample(Signature
file/shape file)
which you want to
apply the same
rules with this
image, You can.
Click on sample
manager(1) and
then click on open
file(2). You can
even create
training
pixels/samples

11. Now iso clustered unsupervised
classification is ready

12. Observations
• Wide variety of algorithms available including
supervised, unsupervised and hybrid as well.
• Processing may take longer time than remote
sensing software's.
• Not robust algorithams
• Interesting thing is class probability