Evaluating Land Use Change Detection Methods in Damavand City Using Remote Sensing
Publish Year: 1401
نوع سند: مقاله ژورنالی
زبان: English
View: 165
This Paper With 17 Page And PDF Format Ready To Download
- Certificate
- من نویسنده این مقاله هستم
استخراج به نرم افزارهای پژوهشی:
شناسه ملی سند علمی:
JR_JRORS-5-4_001
تاریخ نمایه سازی: 4 شهریور 1402
Abstract:
Land-use change has significant impacts on environmental and natural resources, including water quality, air and terrestrial resources, ecosystem processes and functions, and climate systems. Therefore, accurate and timely detection of land-use changes is crucial for understanding the interactions between humans and natural phenomena and managing natural resources effectively. This study aimed to monitor land-use changes in Damavand city using remote sensing techniques. Two Landsat ۵ and ۸ satellite images from ۱۹۹۶ and ۲۰۱۸ were used after applying radiometric and atmospheric corrections. Four methods, including band differentiation, band ratio, principal component analysis, and post-classification image detection were employed to detect land-use changes. The results showed that man-made areas increased by ۷۲۸۸ hectares due to construction activities in agricultural fields, leading to a reduction of ۴۰۴۷ hectares of agricultural lands. Additionally, ۱۰۳۲۴ hectares of rich rangeland cover were transformed into poor pastures. The principal component analysis method using band ۳ and the band difference method using band ۵ effectively detected the changes in the region; however, the band ratio method did not perform well. The findings of this study can help policymakers make informed decisions about land use planning in Damavand city.
Keywords:
Authors
Fatah Hasan family
msc student, Department of RS-GIS Faculty of Environment and Energy Science and Research Branch, Islamic Azad University Tehran, IRAN
Zahra Azizi
Science and Research Branch, Daneshgah Blvd, Simon Bulivar Blvd, Tehran
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 :