Supervised

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## Regional Remote Sensing Centre-Central, NAGPUR

#### SUPERVISED CLASSIFICATION

#### IMAGE LOADING:

Imagery in the Tif format (PLANARCONFIG_CONTIG & RGB) can be loaded with the menu bar or toolbar option File-Open. Once source file is chosen, imagery details will be displayed. Where band combination has to be given as input . Stretching: Once imagery is loaded, various stretching can be applied as facilitated in toolbar. (Linear, Root, Equalized, Raw)

#### STRETCHING:

Basically there are three types of stretchings which are used extensively have been provided as,

Linear stretches all pixels (all bands) linearly on available range.

Root stretches all pixels (all bands) logarithmically on available range.

Equalized stretches all pixels (all bands) equally on available range.

Beside this CUSTOM mode is also have been provided where user interactive stretching can be done.

#### CUSTOM:

Histogram layout for imagery can be visualized and adjusted for the purpose of stretching.
(applicable to both fullview & zoomview)

Toolbar provides this option.

#### ZOOM VIEW:

Imagery can be viewed at 1:1 extent by enabling zoom mode. Various stretching can be applied for this view also. Further this view can be zoomed in and zoomed out. (Zoom rectangle can be traced by disable the zoom mode and enable it again)

#### ZOOM VIEW TASK COLLECTION:

Zoom view task window provides the facility of stretching, zooming, sample overlaying, Histogram viewing and Band combination for zoom view window.

#### TRAINING SITE COLLECTION:

Classification task window provides the facility of creating class, tracing samples for particular class, editing of it ..etc.

**To edit any sample class parameter, click on particular grid cell and press delete button or double click.

**While creating or editing the training sites, it is better to save in order to have consistency in data. Prior to this sample file can be created using menu option SAMPLE ->CREATE. Extension for this is .sam. e.g. file should be specified as ABC.sam.

Threshold: Threshold parameter can be set for each class for refining the result of classification applicable to parallelepiped and MaxLike criteria.

#### Online classification(Classification preview):

User can check out the result of classification for selected zoom view area with facilitated criteria like Minimum distance, Parallelepiped, Maximum Likelihood with NULL and Without NULL. Cross checking of lassification: Classified output can be cross checked with the use of link classified option in Classification task window. Here you can link output to displayed image and compare feature wise. Masking of area: While classifying the imagery, user may need to mask particular part of imagery. This is facilitated in this module in the form of polygon tracing in master view. This can be achieved using Mask Create option in menu.

#### CLASSIFICATION:

Entire imagery can be classified using above mentioned techniques based on user input i.e. training sites using menu option Classify. Here you can use selectable bands for classification purpose.

Classification facilitates

• Minimum distance,

• Parallelepiped,

• Maximum Likelihood

Minimum distance uses Euclidean distance method to compute distance of particular pixel from mean vectors of given sample classes. And that pixel is classified to nearest distance class.

Parallelopiped method checks whether particular pixel lies in range of Mean - Std Dev to Mean + Std Dev of any given sample classes. Pixel is classified to that class for which it lies in this range otherwise it is classified to Null class. Output of this method is affected by Threshold parameter.

Maximum Likelihood method is based upon covariance factor of sample classes. Particular pixel is classified to class having less covariance with that pixel.

HANDLING TIPS:

1. While drawing the mask in master view ,start with left button click of mouse and continue clicking until last point is reached. At end press right button of mouse which will close the polygon and create the mask.

2. While drawing the sample in zoom view with trace polygon method, start with left button click of mouse and continue clicking until last point is reached. At end press right button of mouse which will close the polygon and create the sample.

3. While drawing the sample in zoom view with trace and close method, start with left button down of mouse and move the mouse over sample area until last point is reached. At end release the button of mouse which will close the polygon and create the sample. Document: Status :

#### Pre-Classification Acuuracy Assesment :

User may need to check correctness of samples in order to ensure the classified output. For this confusion matrix technique is used mostly. For this Confusion matrix option is provided in toolbar. Confusion matrix interface is very simple in nature. Based on input file parameter, just user has to select specific bands and classification criteria for assessment purpose. Output will be displayed in matrix form with Kappa coefficient.