نوع مقاله : مقاله پژوهشی

نویسندگان

1 استاد گروه جغرافیا، پردیس علوم انسانی و اجتماعی، دانشگاه یزد

2 دانشجوی دکتری گروه جغرافیا، پردیس علوم انسانی و اجتماعی، دانشگاه یزد

3 دانشیار گروه جغرافیا، پردیس علوم انسانی و اجتماعی، دانشگاه یزد،

4 استادیار گروه جغرافیا، پردیس علوم انسانی و اجتماعی، دانشگاه یزد

5 استادیار گروه جغرافیای طبیعی، دانشکدة جغرافیا و برنامه‌ریزی محیطی، دانشگاه سیستان و بلوچستان

چکیده

پایش خشکسالی، به‌منظور هشدار سریع برای خطر خشکسالی، بسیار حیاتی و مهم است. در این پژوهش، سعی شده است که شاخص پایش خشکسالی VDI براساس باندهای متفاوت داده‌های ماهواره‌ای مادیس، با تفکیک مکانی متوسط، توسعه یابد. شاخص VDI به تنش آب در گیاهان می‌پردازد. مطالعات طیفی نشان داده است که بازتابندگی باند فروسرخ موج کوتاه (SWIR) با محتوای آب‌برگ ارتباط منفی دارد و به‌دلیل حساس‌بودن SWIR به محتوای آب‌برگ، در ایجاد شاخص‌های گوناگون سنجش از دور، ازجمله VDI و به‌منظور شناسایی محتوای آب گیاهان، کاربرد گسترده‌ای دارد. این پژوهش نقشه‌های خشکسالی شاخص VDI را براساس میزان حساسیت به رطوبت، با استفاده از بازتابش باند‌های 5 و 6 فروسرخ موج کوتاه SWIR (VDI5 و VDI6) مادیس، ارزیابی کرده است. بدین‌منظور از تصاویر ماهواره‌ای مادیس و داده‌های بارش ماهیانة مدل جهانی GLDAS، در محدودة استان سیستان و بلوچستان در دورة زمانی نوزده‌ساله‌ای (2018-2000) استفاده شد. برای ارزیابی دقت نقشه‌های محاسبه‌شده براساس دو باند، ضریب همبستگی پیرسون به‌کار رفت. نتایج همبستگی بالایی را میان شاخص VDI6 و داده‌های بارش نشان داد و مشخص شد که باند 6 موج کوتاه فروسرخ، در استان سیستان و بلوچستان، به شرایط خشک خاک بیشترین واکنش را نشان می‌دهد؛ ازاین‌رو این مطالعه استفاده از شاخص VDI براساس باند 6 را برای شناسایی زودهنگام و نظارت بر خشکسالی کشاورزی در برنامه‌های عملیاتی مدیریت خشکسالی، پیشنهاد می‌کند.

کلیدواژه‌ها

عنوان مقاله [English]

Sensitivity of Vegetation Dryness Index (VDI) to Reflectance of Different Shortwave Infrared Bands in Arid and Semi-Arid Regions (Case Study: Sistan & Baluchestan Province)

نویسندگان [English]

  • Kamal Omidvar 1
  • massumeh nabavi zadeh 2
  • Ahmad Mazidi 3
  • HamidReza Ghaffarian Malmiri 4
  • Peyman Mahmoudi 5

1 Prof. of Geography, Campus of Humanities and Social Sciences, Yazd University

2 Ph.D. Students, Dep. of Geography, Campus of Humanities and Social Sciences, Yazd University

3 Associate Prof., Dep. of Geography, Campus of Humanities and Social Sciences, Yazd University

4 Assistant Prof., Dep. of Geography, Campus of Humanities and Social Sciences, Yazd University

5 Assistant Prof., Dep. of Natural Geography, Faculty of Geography and Environmental Planning, Sistan

چکیده [English]

Drought monitoring is critical for early warning of drought hazard. This study  is  attempted to develop remote sensing drought monitoring index (VDI), based on Accuracy of different bands of Moderate Resolution Imaging Spectroradiometer data MODIS, VDI focuses about the vegetation water stress.
 Spectral studies have demonstrated that due to the large absorption by leaf water, shortwave infrared reflectance (SWIR) is negatively related to leaf water content. Being sensitive to leaf water content, SWIR is widly utilized to construct various remote-sensing indices for example VDI for reflecting vegetation water content, . In this study, Vegetation Drought Index (VDI) was evaluated Based on the sensitivity rate to moisture by shortwave infrared reflectance bands SWIR 5 and 6 (VDI5 and VDI6). The data included the MODIS sensor images from Terra satellite in a period of nineteen years from 2000 to 2018 and Precipitation data are obtained from the Global Land Data Assimilation System (GLDAS), in Sistan & Balouchestan Province, Pearson correlation coefficient was used to evaluate the accuracy of the Drought spatial distribution maps calculated based on the two bands.
Results indicate high significant correlation rate between VDI6 and Precipitation data . Study also showed that shortwave infrared band 6 (SWIR) is more sensitive to agricultural drought than band 5,in Sistan and Baluchestan province . The study recommends  to use VDI index with and 6 for better early detection and monitoring of agricultural drought in operational drought management programmes.

کلیدواژه‌ها [English]

  • Drought
  • VDI Vegetation Drought Index
  • SWIR Shortwave Infrared Bands
  • GLDAS Global Model Precipitation Data
  • Sistan & Baluchestan province
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