Detecting shoreline change employing remote sensing images (Case study: Beris Port - east of Chabahar, Iran)
Publish place: International Journal of Coastal, Offshore and Environmental Engineering، Vol: 5، Issue: 4
Publish Year: 1399
نوع سند: مقاله ژورنالی
زبان: English
View: 97
This Paper With 8 Page And PDF Format Ready To Download
- Certificate
- من نویسنده این مقاله هستم
استخراج به نرم افزارهای پژوهشی:
شناسه ملی سند علمی:
JR_IJCOE-5-4_001
تاریخ نمایه سازی: 29 خرداد 1402
Abstract:
Coastal areas are one of the most crucial and important area in each country. They are also one the most dynamics area, which undergo significant changes in relatively short periods. Protecting coastlines from erosion and/or sedimentation thus, is one of the most important duties in each country. In this study, shoreline change in the Beris Port - east of Chabahar, Iran, was investigated using remote sensing technique and DSAS tools. Beris Port is located ۸۵ km east of Chabahar, on the Makran coast. Landsat ۸ and ۵ satellite images were used to detect shoreline change, due to the port's construction date, satellite imagery of ۱۹۸۸, ۱۹۹۰, ۲۰۱۴ and ۲۰۱۹ was used. Using the NSM, SCE, EPR and LRR statistical indexes of the DSAS tool, erosion and accretion rates were calculated in for the area. According to the LRR index, the lowest shoreline change rate is -۱.۵۱ m/year and is detected to be to the east of port. The highest rate of shoreline change is ۷.۴۴ m/year at the port. According the results, the main reason for this high rate of change is the location of the port, which is in the area perpendicular to its neighborhood coastal area, which causes to trap the current in this area to increase its dynamic activities. Shortly speaking, it was found that the accretion is dominant in port Beris and east of the port is the zone with least amount of accretion.
Keywords:
Authors
Danial Ghaderi
University of Hormozgan
Maryam Rahbani
University of Hormozgan
مراجع و منابع این Paper:
لیست زیر مراجع و منابع استفاده شده در این Paper 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 Paper لینک شده اند :