Research Papers

Evaluating coverage changes in national parks using a hybrid change detection algorithm and remote sensing

[+] Author Affiliations
Zahra Ghofrani

Deakin University, School of Engineering, Faculty of Science, Engineering and Built Environment, Waurn Ponds Campus, Pigdons Road, Geelong, Victoria 3220, Australia

Mehdi Mokhtarzade

K.N. Toosi University of Technology, Geodesy and Geomatics Faculty, No. 1364, Mirdamad Cross, Valiasr St., Tehran 19967-15433 Iran

Mahmod Reza Sahebi

K.N. Toosi University of Technology, Geodesy and Geomatics Faculty, No. 1364, Mirdamad Cross, Valiasr St., Tehran 19967-15433 Iran

Adham Beykikhoshk

Deakin University, School of IT, Faculty of Science, Engineering and Built Environment, Waurn Ponds Campus, Pigdons Road, Geelong, Victoria 3220 Australia

J. Appl. Remote Sens. 8(1), 083646 (Apr 21, 2014). doi:10.1117/1.JRS.8.083646
History: Received November 13, 2013; Revised March 5, 2014; Accepted March 6, 2014
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Abstract.  Remote sensing is a useful tool for detecting change over time. We introduce a hybrid change-detection method for forest and protected-area vegetation and demonstrate its use with two satellite images of Golestan National Park in northern Iran (1998 and 2010). We report on the advantages and disadvantages of the hybrid method relative to the standard change-detection method. In the proposed hybrid algorithm, the change vector analysis technique was used to determine changes in vegetation. Following this, we used postclassification comparison to determine the nature of the changes observed and their accuracy and to evaluate the effects of different parameters on the performance of the proposed method. We determined 85% accuracy for the proposed hybrid change-detection method, thus demonstrating a method for discovering and assessing environmental threats to natural treasures.

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© 2014 Society of Photo-Optical Instrumentation Engineers

Citation

Zahra Ghofrani ; Mehdi Mokhtarzade ; Mahmod Reza Sahebi and Adham Beykikhoshk
"Evaluating coverage changes in national parks using a hybrid change detection algorithm and remote sensing", J. Appl. Remote Sens. 8(1), 083646 (Apr 21, 2014). ; http://dx.doi.org/10.1117/1.JRS.8.083646


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