نوع مقاله : مقاله پژوهشی

نویسندگان

1 دانش‌آموخته کارشناسی‌ارشد بیابان‌زدایی، دانشکده منابع طبیعی، دانشگاه صنعتی اصفهان

2 دانشیار گروه مرتع و آبخیزداری، دانشکده منابع طبیعی، دانشگاه صنعتی اصفهان

3 استاد گروه مرتع و آبخیزداری، دانشکده منابع طبیعی، دانشگاه صنعتی اصفهان

4 دانش‌آموخته کارشناسی‌ارشد بیابان‌زدایی دانشکده منابع طبیعی، دانشگاه صنعتی اصفهان

چکیده

مطالعه حاضر با هدف ارزیابی کارایی دو الگوریتم آرتیس و سوبرینا در استخراج دمای سطح زمین از باند مادون قرمز حرارتی تصویر TM سال 2009 در منطقه دامنه استان اصفهان صورت گرفت و صحت نقشه‌های دمایی حاصله از تصویر زمین مرجع شده با داده‌های دمای سطح زمین که در 10 ایستگاه هواشناسی جمع آوری شده بود با استفاده از آنالیز رگرسیون خطی ارزیابی گردید. نتایج نشان داد که هر دو الگوریتم قابلیت پهنه‌بندی توزیع مکانی دمای سطح زمین در منطقه مطالعاتی را دارند و همبستگی بالای میان این دو روش مؤید این امر بود (R>0.97)، ولی الگوریتم آرتیس نسبت به سوبرینا کارایی بهتری را نشان داد. این الگوریتم بیش از 72% از تغییرات دمای سطح زمین که توسط ایستگاه‌های زمین ثبت شده بود را بخوبی نشان داد. مطابق این روش، اراضی بدون پوشش گیاهی و مناطق با پوشش گیاهی بالا در زمین‌های کشاورزی و مراتع بترتیب بالاترین (328 کلوین) و کمترین (291 کلوین) دمای سطح زمین در منطقه را داشتند. نتایج مطالعه بیانگر آن بود که با کاهش پوشش گیاهی مقادیر دمایی افزایش می‌یابد، بنابراین، اطلاعات دمایی بدست آمده از داده‌های سنجش از دور با پوشش وسیع مکانی خود می‌تواند نقش کلیدی در مدیریت اکوسیستم‌ها بازی کند.

کلیدواژه‌ها

عنوان مقاله [English]

Quantitative assessment and validation of the TM land surface temperature using synoptic weather stations

نویسندگان [English]

  • Nahid Moshtagh 1
  • Reza Jafari 2
  • Saied Soltani 3
  • Nafiseh Ramezani 4

1 Department of Natural Resources, Isfahan University of Technology

2 Associate professor, Department of Natural Resources, Isfahan University of Technology

3 Department of Natural Resources, Isfahan University of Technology

4 Department of Natural Resources, Isfahan University of Technology

چکیده [English]

Land surface temperature (LST) is an essential parameter in ecological, hydrologic, climatic, and related studies. The objective of this study was to evaluate the performance of Artis and Sobrino algorithms for retrieving LST from 2009 Landsat TM thermal infrared band in Damaneh region of Isfahan province. The accuracy of LST extracted from geometrically corrected image was then assessed against field-based LST data recorded at 10 meteorological stations using linear regression analysis. The results showed that both algorithms were able to map LST spatial distribution in the region and they were significantly correlated (R>0.97), but the Artis algorithm performed slightly better than Sobrino one. This algorithm explained up to 72% of the variation in the field measurements of LST. According to this algorithm, bare lands and highly vegetated agricultural and rangeland areas had the highest (328k0) and lowest LST (291k0) in the region, respectively. As the results indicated here the decrease in vegetation cover corresponds with increase in temperature values, therefore, remotely-sensed LST information with their extensive coverage can have a key role in ecosystem management.

کلیدواژه‌ها [English]

  • LST
  • Satellite data
  • Climatic data
  • linear regression analysis
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