Share Email Print

Proceedings Paper

Utilizing hyperspectral remote sensing imagery for afforestation planning of partially covered areas
Author(s): Fatih Omruuzun; Didem Ozisik Baskurt; Hazan Daglayan; Yasemin Yardimci Cetin
Format Member Price Non-Member Price
PDF $14.40 $18.00
cover GOOD NEWS! Your organization subscribes to the SPIE Digital Library. You may be able to download this paper for free. Check Access

Paper Abstract

In this study, a supportive method for afforestation planning process of partially forested areas using hyperspectral remote sensing imagery has been proposed. The algorithm has been tested on a scene covering METU campus area that is acquired by high resolution hyperspectral push-broom sensor operating in visible and NIR range of the electromagnetic spectrum. The main contribution of this study to the literature is segmentation of partially forested regions with a semi-supervised classification of specific tree species based on chlorophyll content quantified in hyperspectral scenes. In addition, the proposed method makes use of various hyperspectral image processing algorithms to improve identification accuracy of image regions to be planted.

Paper Details

Date Published: 15 October 2015
PDF: 8 pages
Proc. SPIE 9643, Image and Signal Processing for Remote Sensing XXI, 96432N (15 October 2015); doi: 10.1117/12.2196532
Show Author Affiliations
Fatih Omruuzun, Middle East Technical Univ. (Turkey)
Didem Ozisik Baskurt, Middle East Technical Univ. (Turkey)
Hazan Daglayan, Atilim Üniv. (Turkey)
Yasemin Yardimci Cetin, Middle East Technical Univ. (Turkey)

Published in SPIE Proceedings Vol. 9643:
Image and Signal Processing for Remote Sensing XXI
Lorenzo Bruzzone, Editor(s)

© SPIE. Terms of Use
Back to Top