ارتباط عملکرد محصول انگور با شاخص‌های گیاهی سنجش از دور: ترکیبی تصاویر سنتینل راداری و اپتیکی و مدل‌های یادگیری ماشین

ماشین های کشاورزی

مقالات آماده انتشار، پذیرفته شده، انتشار آنلاین از تاریخ 06 مرداد 1404   

نوع مقاله: مقاله پژوهشی

شناسه دیجیتال (DOI): 10.22067/jam.2025.91357.1325

نویسندگان

حمیدرضا ملکی¹؛ مهرانه خدامرادپور^{* 2}؛ حسنی محمدی منور¹

¹گروه مهندسی بیوسیستم، دانشکده کشاورزی، دانشگاه بوعلی سینا، همدان، ایران

²گروه علوم و مهندسی آب، دانشکده کشاورزی، دانشگاه بوعلی سینا، همدان، ایران

چکیده

ﺍﻣﺮﻭﺯﻩ ﺳﻨﺠﺶ ﺍﺯ ﺩﻭﺭ ﺑﻪﻋﻨﻮﺍﻥ ﻳﮏ ﺍﺑﺰﺍﺭ ﻣﺪﻳﺮﻳﺘﻲ در ﮐﺸﺎﻭﺭﺯﻱ ﺩﻗﻴﻖ محسوب می‌شود، که نقش مهمی در شناسایی پوشش‌های گیاهی متفاوت دارد. انگور از ارزشمندترین محصولات باغبانی است که استان همدان حدود 7.3 درصد از وسعت تاکستان‌های کشور را در اختیار دارد. با این حال توزیع جغرافیایی از تاکستان‌ها در این استان وجود ندارد. هدف اصلی این پژوهش، بررسی رابطه عملکرد محصول انگور با شاخص‌های سنجش از دور پوشش گیاهی در تاکستان‌های استان همدان است. به همین منظور، دقت شناسایی تاکستان‌های استان همدان توسط الگوریتم‌های یادگیری ماشین شامل: ماشین بردار پشتیبان (SVM) و حداقل فاصله (MD) و جنگل تصادفی (RF) با شاخص‌های سنجش از دور پوشش گیاهی شامل: شاخص تفاضلی نرمال‌شده گیاهی (NDVI) و شاخص تفاضلی نرمال‌شده آب (NDWI) برآوردشده از تصاویر ترکیبی اپتیکی و رادارای سنتینل (Sentinel-1 و Sentinel-2) انجام شد. سپس براساس دقیق‌ترین نقشه شناسایی تاکستان‌ها، سری زمانی ماکزیمم شاخص‌های NDVI و NDWI سنجنده‌ی مودیس در تاکستان‌ها در سال‌های 2007 تا 2020 برآورد شد و همبستگی آن‌ها با عملکرد واقعی محصول انگور بررسی شد. مقایسه دقت طبقه‌بندی الگوریتم‌های متفاوت بیانگر برتری الگوریتم RF با شاخص NDWI با بالاترین دقت کلی (%95) و ضریب کاپا (0.95) بود. هم‌چنین تحلیل همبستگی بین شاخص‌های NDVI و NDWI سنجنده مودیس مستخرج از نقشه تاکستان‌ها با عملکرد واقعی انگور نشان از رابطه خطی قوی‌تری بین شاخصNDVI  نسبت به NDWI دارد. یافته‌های این پژوهش که بیانگر دقت بالای شاخص‌های سنجش از دور و الگوریتم‌های یادگیری ماشین در تاکستان‌ها است می‌تواند در پیش‌بینی عملکرد محصول انگور قبل از برداشت، بهبود کیفیت انگور و مدیریت بهینه‌ی آبیاری نقش مهمی داشته باشد.

کلیدواژه‌ها

شاخص NDVI؛ شاخص NDWI؛ مدل حداقل فاصله؛ مدل جنگل تصادفی؛ مدل ماشین بردار پشتیبان

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