## Supervised Image Classification

### Composite Bands

- Option 1: Windows > Image Analysis:
	- Select all bands
	- Composite
- Option 2: Open and apply Composite Band tool
- Map RGB with bands on generated layer (landsat 8)
	- 4 3 2 for natural color
	- 5 6 2 for health vegetation
	- 7 6 4 for urban
- Map what color indicates what with a reference (e.g., base map)

### Extract Study Area

- Enable label feature of the map
- Select Dhaka
- Right click on map layer > Data > Export Data

### Classification

- Perform KML conversion using "Layer to KML" tool
- Drag and open the KML file on Google Earth Pro (Places)
- Customize > Toolbars > Image Classification
- Open Training Sample Manager: Select Composite Band layer
- Draw Polygon (or circle)
- Merge multiple training samples into one (e.g., Building)
- Repeat for building, water body, vegetation, etc.
- Create a signature file	[Ocassionally problem arises if not saved on drive C:\]
- Image Classification > Interactive: Automatic
- Image Classification > Maximum Likelyhood:
	- Input "Composite"
	- Input the produced signature file
- Clear training data to remove polygons

### Extract Classification

- Open "Extract by Mask" tool
- Input 1: Interactive Classification output
- Input 2: Dhaka

### Area Calculation

- Raster to Polygon on the Dhaka Interactive Classification layer
- Use field = Class_name
- Dissolve
- Open attribute table of dissolved layer
- If area not calculated, produce area column

## Assignment

- Of assigned district
- Three years (e.g., 2015, 2020, 2025)
- Create layout
- Graph: Show area comparison across the years
- 14th week, tuesday