How to distinguish grassland from woodland by using fast bird remote sensing images

The classification method based on NDVI index, texture information and decision tree can distinguish QuickBird remote sensing images.

1. Classification method based on NDVI index: NDVI index is an index reflecting vegetation coverage and growth state, and the corresponding NDVI value can be obtained by calculating the infrared band and red band of fast bird remote sensing image. The NDVI values of grassland and woodland are usually different, so QuickBird remote sensing images can be classified by setting thresholds.

2. Classification method based on texture information: the texture of grassland and woodland is different, the texture of grassland is more uniform, while the texture of woodland is more complex. Therefore, we can distinguish grassland from woodland by calculating the texture features of QuickBird remote sensing images, such as GLCM.

3. Classification method based on decision tree: Decision tree classification is a common classification method for remote sensing images. Using the multi-band data and characteristics of QuickBird remote sensing image, a classification decision tree model can be constructed to classify grassland and woodland.