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:: Volume 7, Issue 3 (12-2019) ::
jgit 2019, 7(3): 1-16 Back to browse issues page
Localization Boyan algorithm to detect forest fires from MODIS sensor images
Omid Azari, Ali Mohammadzadeh *
K.N. Toosi University of Technology
Abstract:   (1062 Views)
Of phenomena which much damage and irreparable import to forests and natural resources is the fire that each year, more than 100 fires occur in Iran and thousands of hectares of trees and plants eliminates. Given that fire risk is high in most parts of the world, full and continuous monitoring on this natural phenomenon, is essential. Use remote sensing is a way to identify and manage fire. Ahead goal in the study, development and improvment, Byun algorithm and compare it with some fire detection algorithms using the MODIS sensor images. Therefore, in addition to the developed algorithm, algorithms Byun in 2007, Lingli Wang in 2008 and Jing Wang in 2011 for the forest area in Golestan Province is localized and implemented. To evaluate the results, the matrix ambiguity and ground data collected from the forests and natural resources in Golestan province has been used that for each algorithm, fire detection rate, false alarm rate and Kappa statistics were calculated and compared which Fire detection rate for Byun algorithms, Ling Wang, Jing Wang and development algorithm by 78.95, 53.84, 46.15 and 72.22 percent respectively and  kappa coefficient, 81.02, 32.37 , 28.37 and 81.11 percent have been achieved which shows the superiority of the algorithm is developed in the study area.
Keywords: Forest fire, Fire detection algorithm, improved algorithm, MODIS sensor.
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Type of Study: Research | Subject: RS
Received: 2016/01/23 | Accepted: 2017/11/1 | Published: 2019/12/21
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Azari O, Mohammadzadeh A. Localization Boyan algorithm to detect forest fires from MODIS sensor images. jgit. 2019; 7 (3) :1-16
URL: http://jgit.kntu.ac.ir/article-1-738-en.html

Volume 7, Issue 3 (12-2019) Back to browse issues page
نشریه علمی-پژوهشی مهندسی فناوری اطلاعات مکانی Engineering Journal of Geospatial Information Technology
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