بررسی اثر قدرت تفکیک مکانی متغیرهای محیطی بر دقت نقشه‌برداری رقومی ویژگی‌های خاک (مطالعه موردی: دشت سیلاخور، استان لرستان)

مقصودی, زیبا; متین فر, حمید رضا; موسوی, سید روح اله

doi:10.22059/jrwm.2025.386586.1792

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	بررسی اثر قدرت تفکیک مکانی متغیرهای محیطی بر دقت نقشه‌برداری رقومی ویژگی‌های خاک (مطالعه موردی: دشت سیلاخور، استان لرستان)
نشریه علمی - پژوهشی مرتع و آبخیزداری
دوره 78، شماره 3، مهر 1404، صفحه 299-322 اصل مقاله (2.11 M)
نوع مقاله: مقاله پژوهشی
شناسه دیجیتال (DOI): 10.22059/jrwm.2025.386586.1792
نویسندگان
زیبا مقصودی¹؛ حمید رضا متین فر^* ¹؛ سید روح اله موسوی²
¹گروه علوم ومهندسی خاک، دانشکده کشاورزی، دانشگاه لرستان، خرم آباد، ایران
²گروه علوم و مهندسی خاک، دانشکده کشاورزی، دانشگاه تهران کرج، ایران
چکیده
مقیاس متغیرهای محیطی یکی از مهمترین ویژگی‌هایی است که هنگام انتخاب داده برای نقشه برداری رقومی خاک باید در نظر گرفته شود. با توجه یه پیچیدگی های عوامل موثر بر تشکیل خاکها، استفاده از مقیاس مناسب به دلیل نقش مهمی که در انتخاب ویژگی و تعمیم اطلاعات دارد، بسیار حائز اهمیت می‌باشد. هدف از این مطالعه انتخاب مقیاس بهینه برای پیش‌بینی شش ویژگی خاک شامل کربن‌آلی (SOC)، کربنات کلسیم معادل (CCE)، pH، شن، سیلت و رس در دشت سیلاخور استان لرستان است. برای این منظور تعداد 100 نمونه خاک سطحی ( 30-0 سانتی‌متری) بر اساس الگوی نمونه‌برداری تصادفی برداشت گردید. متغیرهای محیطی توپوگرافی و سنجش از دور از مدل رقومی ارتفاع (DEM) و ماهواره لندست 8 استخراج شدند. سپس متغیرهای محیطی بهینه توسط روش حذف ویژگی برگشتی در منطقه انتخاب گردید. مدل‌سازی ویژگی‌های خاک توسط مدل‌های یادگیری ماشین جنگل تصادفی (RF)، رگرسیون بردار پشتیبان (SVR)، کوبیست (CB) و مدل‌سازی ترکیبی اجرا شدند. نتایج مدل‌سازی نشان داد، مدل RF برای پیش‌بینی CCE، pH، Sand و Silt با R2 به ترتیب برابر با 64/0، 65/0، 59/0 و 7/0 بهترین عملکرد را داشت. همچنین مدل SVR با 62/0R2= برای پیش‌بینی SOC و مدل CB با 66/0R2= برای پیش‌بینی Clay بیشترین دقت را نشان دادند. مناسب‌ترین اندازه سلول برای CCE، pH، Sand و Silt 30 30 متر، برای SOC 60 60 متر و برای Clay 90 90 متر شناخته شد. به طور کلی نتایج نشان داد که در مناطقه مطالعاتی استفاده از مقیاس‌های میانی (اندازه سلول 30 30 متر تا 90 *90 متر) منجر به پیش‌بینی ویژگی‌های خاک با دقت بالاتر شد.
کلیدواژه‌ها
خصوصیات خاک؛ مقیاس؛ متغیر محیطی؛ نقشه برداری خاک
عنوان مقاله [English]
Examining the impact of environmental variable scale on the accuracy of digital mapping of soil properties: A case study of Borujerd, Lodestone province
نویسندگان [English]
Ziba Maghsodi¹؛ Hamid Reza Matinfar¹؛ Seyed Roohollah Mousavi²
¹Department of Soil Science, Faculty of Agriculture, Lorestan University, Iran
²Department of Soil Science, Faculty of Agriculture, University of Tehran, Iran
چکیده [English]
The scale of environmental variables is one of the most important features to consider when selecting data. The aim of this study is to improve the accuracy of digital mapping by selecting the optimal scale for predicting six soil properties, For this purpose, 100 surface soil samples (0-30 cm depth) were collected based on a random sampling pattern. Environmental variables related to topography and remote sensing were extracted from the digital elevation model (DEM) and Landsat-8 satellite. The optimal environmental variables were selected using the recursive feature elimination method in the Silakhor Plain region. Soil property modeling was conducted using machine learning models such as random forest (RF), Support Vector Regression (SVR), Cubist (CB), and hybrid modeling. The modeling results showed that the RF model performed best for predicting CCE, pH, sand, and silt with R² values of 0.64, 0.65, 0.59, and 0.70, respectively. Additionally, the SVR model showed the highest accuracy for predicting SOC with an R² of 0.62, while the CB model had the highest accuracy for predicting clay with an R² of 0.66. The most suitable cell sizes for CCE, pH, sand, and silt were identified as 3030 m, for SOC as 6060m, and for clay as 90*90m. The most important environmental variables for SOC, pH, silt, sand, and clay were valley depth, differential vegetation index, and modified vegetation index, respectively. Overall, the results indicated that in the study areas, the use of intermediate scales (cell sizes of 30 to 90 m) led to higher accuracy in predicting soil properties. This is because using larger cell sizes introduces noise that hinders accuracy.
کلیدواژه‌ها [English]
soil properties, scale, environmental variable, soil mapping

مراجع
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بررسی اثر قدرت تفکیک مکانی متغیرهای محیطی بر دقت نقشه‌برداری رقومی ویژگی‌های خاک (مطالعه موردی: دشت سیلاخور، استان لرستان)

Amirian Chekan, A., Taghizadeh-Mehrjardi, R., Sarmadian, F., & Heydari, A. (2017). Three-dimensional mapping of soil texture using spline depth functions and artificial neural networks. Iranian Journal of Soil and Water Research.48(1),113-123. 10.22059/IJSWR.2017.61346. (In Persian).