بررسی کارآیی روش‌های تصحیح اثر اتمسفر در برآورد تراکم تاج‌پوشش جنگل‌های گیلان با استفاده از شاخص‌های گیاهی حاصل از لندست 8

نوع مقاله : علمی - پژوهشی

نویسندگان

1 دانشجوی دکتری دانشکدة منابع طبیعی دانشگاه گیلان

2 استاد دانشکدة منابع طبیعی دانشگاه گیلان

چکیده

بازتابش پدیده‌های سطح زمین روی داده‌های سنجش از دوری تحت تأثیر عوامل گوناگونی مانند شرایط اتمسفر است. در برخی مطالعات لازم است اثر اتمسفر به شیوه‌های متفاوت و مناسبی حذف شود یا کاهش یابد. در این تحقیق، سه روش تصحیح اتمسفریک تفریق شیء تیره (DOS)، تجزیه و تحلیل سریع خط‌دید اتمسفر ازطریق طیف ابر مکعب (FLAASH)، شبیه‌ساز وکتوری ثانویة سیگنال ماهواره‌ای در طیف خورشیدی (SV6) روی سنجندة OLI ماهوارة لندست 8 جنگل‌های استان گیلان اعمال شده است. از هر تصویر، ده شاخص گیاهی استخراج شد. با استفاده از لایة پوشش جهانی، محدودة جنگل روی شاخص‌های متفاوت استخراج و با استفاده از روش شیءپایه، محدودة جنگل روی تصویر قطعه‌بندی شد. 91 قطعه به‌طور تصادفی انتخاب شد. با استفاده از شبکة نقطه‌چین به ابعاد 20×20 متر، تراکم تاج‌پوشش درختان در هر قطعه روی تصاویر گوگل مشخص شده است. آزمایش پیرسون برای آزمون معناداربودن همبستگی شاخص‌ها با نمونه‌های مرجع، رگرسیون خطی و غیرخطی برای مدل‌سازی تراکم تاج‌پوشش به‌کار رفت. نتایج نشان داد که مدل تصحیح برمبنای کد SV6 در مناطق جنگلی استان گیلان بهتر عمل کرده است. شاخص GARI حاصل از مدل تصحیح اتمسفریک DOS با خطای RMSE برابر 72/17 و شاخص ARVI حاصل از مدل تصحیح اتمسفریک SV6، FLAASH و تصویر اصلی OLI به‌ترتیب معادل 38/15، 87/15 و 78/21 کمترین میزان خطای RMSE را نشان داده است. کاهش آثار اتمسفر در فرایند پیش‌پردازش قبل از مدل‌سازی ضروری و پیشنهادشدنی است. 

کلیدواژه‌ها

عنوان مقاله [English]

Investigation of Atmospheric Correction Methods in Estimation of Forest Canopy Density of Guilan Province Using Vegetation Indices of Landsat 8 Data

نویسندگان [English]

  • S.A.R Nouredini 1
  • A.A Bonyad 2
1 Ph.D. Student, Faculty of Natural Resources, University of Guilan
2 Prof., Faculty of Natural Resources, University of Guilan
چکیده [English]

Reflectance of different of land surface phenomena on remote sensing data was influenced by different conditions including atmospheric conditions. Variety methods of atmospheric correction have been developed for remove and reduction of its effects. In this study three atmospheric correction methods: Dark Object Subtraction (DOS), Fast Line-of-sight Atmospheric Analysis of Spectral Hypercubus (FLLASH) and Second Vector Simulation of Satellite Signal in the Solar Spectrum (6SV) have been applied on OLI sensor of Landsat8 inthe forest regions of Guilan province. Numbers of 10 vegetation indices were extracted from each image. Forest area was extracted on various indices detected by global land cover layer. Forest areas segmented on Landsat8 image by object-based method. In the total 91 segments, randomly were selected. Forest canopy density of any segment plot estimated on Google images using 20×20 m network dotted. Person test was used for correlation between indices and training samples and two linear and nonlinear regression models were used for forest canopy density estimation. The results confirmed that 6SV method dominates than other methods in the forest regions of Guilan province. The lowest root means square error (RMSE) with 17.72 was shown in the green atmospherically resistant vegetation index (GARI) extracted from DOS. The results indicated that the lowest RMSE was in atmospherically resistant vegetation index (ARVI) using 6SV, FLAASH and OLI original image with 18.38, 15.87 and 21.78 respectively. The results of this study were shown that use of atmospheric correction methods in preparing vegetation indices is cause of increasing information accuracy from satellite images. Reduction of atmosphere effects in preprocessing before modeling is necessary and suggestible. 

کلیدواژه‌ها [English]

  • Vegetation index
  • Forest canopy cover
  • remote sensing
  • LANDSAT 8

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