Comparative analysis of supervised methods for the classification of mountain forests based on space imagery from the satellite RapidEye

Abstract

This article is consider the current methods of supervised forest classification using multispectral RapidEye satellite imagery. The comparative analysis of Mahalanobis distance classification and minimum distance classification was made. Found that method of Mahalanobis distances is more efficient for forest classification.

Keywords

• remote sensing
• forest classification
• supervised classification methods
• minimum distance
• Mehalanobis distance
• RapidEye images
• forestry