برآورد مشخصه‌‌های ساختاری جنگل با استفاده از داده‌‌های سنجندة ASTER

نویسندگان

1 دانشجوی کارشناسی ارشد مهندسی منابع طبیعی – جنگلداری، دانشگاه علوم کشاورزی و منابع طبیعی ساری، ایران

2 دانشیار دانشگاه علوم کشاورزی و منابع طبیعی ساری، ایران

3 دانشیار دانشگاه علوم کشاورزی و منابع طبیعی گرگان، ایران

4 استادیار دانشگاه علوم کشاورزی و منابع طبیعی ساری، ایران

چکیده

برآورد مشخصه‌های ساختاری جنگل، از اساسی‌ترین اطلاعات در مدیریت پایدار و برنامه‌ریزی جنگل می‌باشد. در این مطالعه ارتباط بین داده‌های سنجندة ASTER و سه مشخصه مهم ساختار جنگل شامل حجم سرپا، سطح مقطع برابر سینه و تعداد درختان در هکتار، در بخشی از جنگل‌های شمال ایران مورد بررسی قرار گرفت. پیــش‌پردازش و پردازش‌های مناسب بر روی داده‌های طیفی انجام گرفت. پس از برداشت اطلاعات زمینی محاسبات مقادیر حجم، سطع مقطع برابر سینه و تعداد درختان در هکتار در سطح قطعات نمونه صورت گرفت. ارزیابی اعتبار بهترین مدل بدست آمده با تعدادی قطعه نمونه و با معیارهای ارزیابی مناسب مورد بررسی قرار گرفت. نتایج نشان داد که ترکیب خطی شاخص‌های MSAVI2، NDVI و باند سبز نسبت به دیگر شاخص‌ها و ترکیبات باندی به‌کار رفته، توانست مشخصة حجم را بهتر پیش‌‌بینی نماید. برای مشخصه سطح مقطع برابر سینه در هکتار نیز ترکیب خطی شاخص‌‌های MSAVI2، NDVI و نسبت ساده SWIR12 بهترین نتایج را نشان دادند. همچنین ترکیب خطی شاخص MSAVI2 و باندهای SWIR1 و SWIR2 با ضریب تبیین اصلاح شده 85 درصد و ریشه میانگین مربعات خطای 95/50 پایه در هکتار نسبت به سایر ترکیبات بکار رفته توانست مشخصه تعداد درختان در هکتار را بهتر پیش‌‌بینی نماید. نتایج این پژوهش نشان می‌‌دهد که بکارگیری داده‌های سنجندة ASTER و روش رگرسیون خطی می‌‌تواند تا حدودی وضعیت کلی از برخی مشخصه‌های ساختار جنگل مورد مطالعه را ارائه دهند.

کلیدواژه‌ها


عنوان مقاله [English]

Estimation of Forest Structural Attributes Using ASTER Data

نویسندگان [English]

  • s k 1
  • a f 2
  • s s 3
  • j o 4
چکیده [English]

Estimation of forest structural parameters is one of major basic information in sustainable management and planning in forest stands. In this study, relationship between ASTER satellite data and three forest structure factors including stand volume, basal area and number of trees per hectare were investigated in Darabkola forest, northern Iran. A multivariate linear regression approach was used to analyze and evaluate relationship between mentioned characteristics and ASTER satellite data. Relevant preprocessing and methods were conducted on spectral data. After gathering terrestrial information, stand volume, basal area and number per hectare were calculated for sample plots. Using some plots, performance of the best models examined by relevant evaluation criterions. The results showed that a combination of MSAVI2, NDVI and Green bands could predict stand volume characteristics better with R2adj=59.2; and RMSE=116.5 m3/h-1 in comparison with other indices and band combinations. For basal area, the best results were obtained using combination of MSAVI2, NDVI and simple ratio of SWIR12 with R2adj=73.5 and RMSE=5.14 m2/h-1. In addition, combination of MSAVI2, SWIR1 and SWIR2, was a better predictor for number per hectare rather than the other combinations by R2adj equal to 0.85 and RMSE about 50.95 number per hectare. Generally, this research showed that using linear regression approach by the ASTER data presents only general status of forest structure attributes in the study area and having more precise estimation of these attribute needs investigating other approaches such as nonlinear or nonparametric and learning machines approaches.

کلیدواژه‌ها [English]

  • ASTER satellite data
  • Darabkola's forest
  • Forest structure attributes
  • Measurment
  • Multivariate linear regression
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