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Anais da Academia Brasileira de Ciências

Print version ISSN 0001-3765On-line version ISSN 1678-2690

Abstract

HASHEMI, SEYED A.. Evaluation of deciduous broadleaf forests mountain using satellite data using neural network method near Caspian Sea in North of Iran. An. Acad. Bras. Ciênc. [online]. 2016, vol.88, n.4, pp.2357-2362. ISSN 0001-3765.  https://doi.org/10.1590/0001-3765201620150636.

During the recent decades, deciduous forests have been molested by human intervention. Easy access, abundance and diversity of valuable forest products have led to increased population density, creating new residential areas and deforestation activities. Revealing changes is one of the fundamental methods in management and assessment of natural resources. This study is evaluated changes in forests area of 2013 using satellite images. In order to mapping the forest extent condition 2013, images of the mentioned years were digitized and geo-referenced by using the ground control points and the maps of mapping organization. After selecting the best set of band using the Bhattacharya distance index, the image classification was performed by using artificial neural network algorithm. Classification by neural network method 2013 in showed that it has a high overall accuracy equal to 95.96%.

Keywords : satellite data; ETM+; forest area; classification.

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