Clustering of trees from Panchromatic images

Abstract

Tree Clustering from satellite images assists in ecological environmental protection. It also helps in managing green resources to provide sustainable development guidance. The automatic clustering of trees is a challenging task. Many models tend to give poor results when there is noise in the image. The aim is to propose a model for clustering of tree crown from panchromatic satellite image using image processing algorithms. In the proposed model we use Cartosat-2 satellite data and the image data is pre-processed to enhance the resulted image analyzed using segmentation models. The resulted image is trained using the clustering model which classifies the tree crowns from the panchromatic images. The proposed model can be able to classify tree crowns effectively from satellite imagery. The proposed model also calculates the tree crown height and width from satellite imagery.