Detection and Enumeration of Trees using Cartosat2 High Resolution Satellite Imagery

Abstract

Remote sensing plays a key role to monitor the earth resources. Remote sensing uses High Resolution Satellites to capture and observe the various conditions of the earth like Land cover and Land use which provides the information regarding how much of land is covered by forest, wetland, water body and how much of land is used by people for rural development, urbanization and agricultural in digital images. Digital Image Processing is useful in decrypt satellite data which helps to know change detection and land cover classification. In this research, satellite data are used to investigate trees and identifying trees on the earth surface, where it is very difficult task to identify trees from high resolution satellite imagery. Digital Image Processing consists of various techniques like image enhancement, segmentation, feature extraction and classifying the extracted features. In this research, Cartosat2 images are used for detection and enumeration of trees. With utilization of digital image processing, the information can be known that is available in the satellite image. Image processing helps to refines the available data in the satellite images without any loss. Image segmentation is used to analyze the image in a understandable form, where it cleaves the image in the form of pixels. Basically it is used to detect and classify the shapes or object boundaries and other relevant data in the digital images. Contrast Limited Adaptive Histogram Equalization(CLAHE) is one of the effective simple techniques for enhancing image quality. Active Contour Model with masking is best suit for image Segmentation and feature Detection and Tree Enumeration.