کارایی روش‌های مختلف تهیۀ نقشۀ کاربری/پوشش اراضی در حوضۀ آبخیز معرف کسیلیان

نوع مقاله : پژوهشی

نویسندگان

1 گروه آبخیزداری، دانشکدۀ منابع طبیعی، دانشگاه تربیت مدرس، نور، ایران

2 گروه مرتع و آبخیزداری، دانشکدۀ منابع طبیعی، دانشگاه رازی، کرمانشاه، ایران

10.22059/ije.2023.361471.1743

چکیده

در راستای مطالعۀ کاربری و پوشش زمین، فناوری سنجش از دور به‌ عنوان منشأ تولیدی اطلاعات مکانی و ابزارهای مناسبی که دارد، مورد استقبال بسیاری از پژوهشگران قرار گرفت که دقت و صحت این نقشه‌ها اعتبار و قابلیت کارایی آن‌ها را نشان می‌دهد. هدف از انجام تحقیق حاضر، ارزیابی و مقایسۀ صحت تهیۀ نقشۀ کاربری اراضی به دو روش سنجش از دور و یک روش تفسیر چشمی تصاویر Google Earth در حوضۀ آبخیز معرف کسیلیان است. در تحقیق حاضر پس از برداشت نمونه‌های تعلیمی با استفاده از نرم‌افزار Google Earth و پیاده‌سازی روی تصویر 9 Landsat مربوط به سال 2021، طبقه‌بندی تصاویر در نرم‌افزار ENVI انجام شده و نقشۀ کاربری اراضی بر اساس نمونه‌های آموزشی و روش‌های شبکۀ عصبی و ماشین ‌بردار پشتیبان تهیه شد. در روش تفسیر چشمی تمام کاربری‌ها در تصاویر Google Earth به ‌صورت دستی رقومی شد و نقشۀ کاربری اراضی به ‌دست آمد. سپس صحت‌سنجی نقشه برای هر سه روش صورت گرفت و نتایج نشان داد نقشۀ حاصل از تفسیر چشمی تصاویر Google Earth با صحت کلی و ضریب Kappa 100 درصد نسبت به روش‌های شبکۀ عصبی و ماشین ‌بردار پشتیبان با صحت کلی به‌ترتیب 6/87 و 2/88 درصد و ضریب Kappa به‌ترتیب 76 و 8/77 درصد، به واقعیت زمینی نزدیک‌تر بود. با این‌حال به دلیل زمان‌بر بودن روش تفسیر چشمی به‌ویژه برای آبخیزهای بزرگ و صحت قابل قبول روش‌های شبکۀ عصبی و ماشین ‌بردار پشتیبان، پیشنهاد می‌شود که به‌ویژه در آبخیزهای بزرگ برای تهیۀ نقشۀ کاربری اراضی از روش‌های نوین استفاده شود.

کلیدواژه‌ها

عنوان مقاله [English]

Efficiency of different land use/land cover mapping methods in Kasilian representative watershed

نویسندگان [English]

  • Faezeh Kamari Yekdangi 1
  • Fatemeh Sarouneh 1
  • Abdulvahed Khaledi Darvishan 1
  • Vahid Moosavi 1
  • Soheila Aghabeigi Amin 2
1 Department of Watershed Management, Faculty of Natural Resources, Tarbiat Modares University, Noor, Iran
2 Department of Rangeland and Watershed Management, Faculty of Natural Resources, Razi University, Kermanshah, Iran
چکیده [English]

In line with the study of land use and land cover, remote sensing technology has been welcomed by many researchers as a source of spatial information production and suitable tools, which shows the accuracy and validity of these maps. The purpose of this research is to evaluate and compare the accuracy of preparing land use maps using two methods of remote sensing and one method of visual interpretation of Google Earth images in the Kasilian representative watershed. In this research, after taking educational samples using Google Earth software and implementing them on the Landsat 9 image of 2021, classification of images was done in ENVI software, and the land use map was prepared based on training samples, Neural Network and SVM methods. In the method of visual interpretation, all land uses in Google Earth images were manually digitized and a land use map was obtained. Then, the accuracy of the map was checked for all three methods and the results showed that the map obtained from visual interpretation of Google Earth images with overall accuracy and Kappa coefficient of 100% was in agreement with the ground reality compared to Neural Network and SVM methods with overall accuracies of 87.6% and 88.2% and Kappa coefficients of 76% and 77.8%, respectively. However, due to the time-consuming visual interpretation method, especially for large watersheds, and the acceptable accuracy of Neural Network and SVM methods, it is suggested to use advanced methods to prepare land use maps, especially in large watersheds.

کلیدواژه‌ها [English]

  • Accuracy assessment
  • Landsat sensor
  • Neural Network
  • Support Vector Machine
  • Visual interpretation

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اکوهیدرولوژی
دوره 10، شماره 3
مهر 1402
صفحه 321-334

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سابقه مقاله

  • تاریخ دریافت: 22 اردیبهشت 1402
  • تاریخ بازنگری: 22 خرداد 1402
  • تاریخ پذیرش: 22 تیر 1402

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