Open AccessClustering of Trees from Panchromatic Images
Author(s) -
Swathi Thotakura,
Suvarna Vani Koneru,
Praveen Kumar Kollu
Publication year - 2019
Publication title -
international journal of engineering and advanced technology
Language(s) - English
Resource type - Journals
ISSN - 2249-8958
DOI - 10.35940/ijeat.e7466.088619
Subject(s) - panchromatic film , cluster analysis , computer science , tree (set theory) , artificial intelligence , satellite imagery , satellite , image segmentation , decision tree model , image (mathematics) , pattern recognition (psychology) , computer vision , data mining , remote sensing , geography , decision tree , mathematics , engineering , mathematical analysis , aerospace engineering
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.