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بررسی امکان برآورد مقاومت تک محوری خاک جادههای جنگلی با استفاده تکنیک حذف پیوستار | ||
نشریه جنگل و فرآورده های چوب | ||
دوره 75، شماره 3، آذر 1401، صفحه 239-253 اصل مقاله (714.98 K) | ||
نوع مقاله: مقاله پژوهشی | ||
شناسه دیجیتال (DOI): 10.22059/jfwp.2022.336653.1202 | ||
نویسندگان | ||
ستوده بابایی1؛ پرویز فاتحی* 2؛ فاطمه موسوی3 | ||
1دانشجوی کارشناسی ارشد گروه جنگلداری و اقتصاد جنگل، دانشکدة منابع طبیعی، دانشگاه تهران، کرج | ||
2استادیار گروه جنگلداری و اقتصاد جنگل، دانشکدة منابع طبیعی، دانشگاه تهران، کرج | ||
3دانش آموختة دکتری گروه جنگلداری و اقتصاد جنگل، دانشکدة منابع طبیعی، دانشگاه تهران، کرج | ||
چکیده | ||
خت مقاومت خاک برای احداث و نگهداری جادههای جنگلی بسیار ضروری است. تعیین مقاومت خاکهای جنگلی که بیشر از نوع ریزدانه و خمیریاند با استفاده از روش آزمایش مقاومت فشاری تکمحوری انجام میگیرد. طیف سنجی روشی سریع و غیرمخرب است که به شناخت خصوصیات خاک کمک میکند. پژوهش حاضر با هدف بررسی توانایی داده های طیف سنجی برای برآورد مقاومت تک محوری خاک انجام گرفته است. بدین منظور از روش حذف پیوستار، شاخصهای ابرطیفی و ترکیب هر دو روش استفاده شد. در طیف خاک سه محدودۀ جذبی با مرکزیت طولموج های 1400، 1900 و 2200 نانومتر وجود دارد که در برآورد مقاومت تک محوری خاک مؤثرند. پس از جدا کردن محدوده های مورد نظر از طیف کامل خاک، روش حذف پیوستار بر روی این محدودهها اعمال و شاخصهای جذب پیوستار برای 45 نمونه خاک محاسبه شد. مدلسازی برآورد مقاومت تکمحوری خاک با استفاده از رگرسیون گام به گام انجام گرفت. روش ارزیابی متقابل و آمارههای ضریب تعیین (R2)، درصد جذر میانگین مربعات خطا (rRMSE) برای انتخاب بهترین مدل بهکار برده شد. نتایج مدلسازی نشان داد که شاخصهای NINSON و NSMI با 75/0R2 = و 29/11 = rRMSE% و شاخص NBDI حذف پیوستار با 78/0R2 = و 16/10 = rRMSE% نتایج بهتری را ارائه دادند. خطای بهنسبت کم مدل حاصل از روش حذف پیوستار نشان داد که از دادههای طیفسنجی و روش حذف پیوستار میتوان برای برآورد مقاومت خاک استفاده کرد. | ||
کلیدواژهها | ||
شاخصهای ابرطیفی؛ طیف سنجی زمینی؛ حذف پیوستار؛ رگرسیون گامبهگام؛ مقاومت فشاری خاک | ||
عنوان مقاله [English] | ||
Estimating unconfined compressive soil strength of forest roads using continuum removal technique | ||
نویسندگان [English] | ||
Sotoudeh Babai1؛ Parviz Fatehi2؛ Fatemeh Mousavi3 | ||
1M.Sc student, Deportment of Forestry and Forest Economics, Faculty of Natural Resources, University of Tehran, Karaj, Iran | ||
2Assistant Prof. Deportment of Forestry and Forest Economics, Faculty of Natural Resources, University of Tehran, Karaj, Iran. | ||
3PhD. Graduated, Deportment of Forestry and Forest Economics, Faculty of Natural Resources, University of Tehran, Karaj, Iran. | ||
چکیده [English] | ||
Understanding the soil resistance and soil strength are essential for the construction and maintenance of forest roads. Unconfined compressive strength (UCS) test approach is used to determine the strength of fine-grained and cohesive forest soils. Spectroscopy is a fast and non-destructive method that can be used to understand, analysis, and assessment of the soil properties. The present study was aimed to investigate the capability of spectroscopy data to estimate UCS. To do so, a continuum removal technique, narrow band (i.e., hyperspectral) indices, and a combination of both methods were used. Three absorption ranges with wavelengths of 1400, 1900, and 2200 nm are effective in estimating the unconfined strength of the soil. The continuum removal technique was applied on the selected absorption regions and its indices were calculated for 45 soil sample plots. In addition, NINSON and NSMI hyperspectral indices were calculated. The capability of these data to estimate unconfined soil strength was evaluated using multiple stepwise regression analysis. The results of this study showed that NINSON and NSMI indices had an R2 = 0.75 and an rRMSE% of 11.29%. Continuum removal index (i.e. NBDI) gained an R2 = 0.78 and an rRMSE% = 10.16 which shows a better result compared to the individual index. The results of the present study (i.e., a reasonable rRMSE%) showed that the spectroscopy data and continuum removal techniques can be used to estimate soil strength. | ||
کلیدواژهها [English] | ||
continuum removal, field spectroscopy, hyperspectral indices, Stepwise regression, UCS | ||
مراجع | ||
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