Study of most element of forest destruction by used the IRS-1C and LANDSAT image in the southern zagros forest (Case study: Kohkeloeye and Boveirahmad province)
سال انتشار: 1397
نوع سند: مقاله ژورنالی
زبان: انگلیسی
مشاهده: 349
فایل این مقاله در 9 صفحه با فرمت PDF قابل دریافت می باشد
- صدور گواهی نمایه سازی
- من نویسنده این مقاله هستم
استخراج به نرم افزارهای پژوهشی:
شناسه ملی سند علمی:
JR_IJABBR-6-3_001
تاریخ نمایه سازی: 3 آذر 1398
چکیده مقاله:
The Zagros forests (west of Iran) have been highly exploited in recent decades by human impacts. Easy access, abundance and variety of valuable forest yields have led to population growth density, creation of new residential areas and deforestation activities. In order to determinate the distribution and rate of deforestation from 1995 to 2006 by using the satellite imagery (IRS-1C and LANDSAT image) and possibility of modeling the changes extent and its relation to physiographic and some human factors by using multiple regression in the Kohkeloeye and Boveirahmad province, Golestan province. Southern Zagros forest, west of Iran. Classification was performed using maximum likelihood classifiers and forest divided two classes (forest and non – forest). Results showed that the maximum likelihood classifiers exhibited the highest results with 96% overall accuracy and 74% kappa coefficient. The results showed that about 462.5 ha from forest areas were deforested in the 12 years. To determination of major element of forest destruction used the multiple regression methods. According to results distance from road and village variables were in contrary of deforestation expanding. Forest destruction was increased with increasing around populated villages and near of this village.
کلیدواژه ها:
نویسندگان
Mozhgan Bazyar
M.Sc. Graduate of forestry, University of Gilan, Some-sara, Iran
Abdolaslam Bonyad
Assistant Prof, Faculty of Natural Resources, University of Gilan, Some-sara, Iran
Sasan Babaie Kafaki
Assistant Prof, Islamic Azad University, Tehran, Iran
مراجع و منابع این مقاله:
لیست زیر مراجع و منابع استفاده شده در این مقاله را نمایش می دهد. این مراجع به صورت کاملا ماشینی و بر اساس هوش مصنوعی استخراج شده اند و لذا ممکن است دارای اشکالاتی باشند که به مرور زمان دقت استخراج این محتوا افزایش می یابد. مراجعی که مقالات مربوط به آنها در سیویلیکا نمایه شده و پیدا شده اند، به خود مقاله لینک شده اند :