نوع مقاله : علمی - پژوهشی
نویسندگان
1 گروه مهندسی نقشه برداری، دانشکده مهندسی عمران و حمل و نقل، دانشگاه اصفهان
2 استادیار گروه مهندسی نقشه برداری، دانشکده مهندسی عمران و حمل و نقل، دانشگاه اصفهان
چکیده
ارزیابی دقت نتایج حاصل از طبقه‌بندی تصاویر ماهواره‌ای، بسیار حائز اهمیت است. تاکنون پارامترهای متعددی برای بیان دقت طبقه‌بندی تصاویر، مورد استفاده قرار گرفته‌اند. دو نمونه از متداول‌ترین پارامترها، ضریب کاپا[1] و دقت کلی [2]هستند. بعضی از محققان به این پارامترهای متداول ایراداتی وارد کرده و پارامترهای جدیدی ارائه کرده و معتقدند این پارامترها، معایب پارامترهای متداول را ندارند. در این تحقیق، رابطه دو مورد از این پارامترهای جدید ارزیابی دقت طبقه‌بندی با پارامترهای متداول مورد بررسی قرار گرفته است. این دو پارامتر مغایرت کمی[3] و مغایرت تخصیصی[4] نام گذاری شده‌اند که میزان عدم شباهت را گزارش می‌کنند. به منظور بررسی رفتار این دو پارامتر، روی 57 تصویر شامل سه دسته از تصاویر با قدرت تفکیک متوسط، قدرت تفکیک بالا و قدرت تفکیک خیلی بالا، طبقه‌بندی نظارت شده انجام شد. سپس ضریب کاپا و دقت کلی به عنوان پارامترهای متداول، و مغایرت کمی و مغایرت تخصیصی به عنوان پارامترهای جدید برای هر تصویر طبقه‌بندی‌شده، محاسبه شده و همبستگی مقادیر به دست آمده با یکدیگر بررسی شد. نتایج به دست آمده در این تحقیق نشان می‌دهند که میزان همبستگی بین این دو دسته پارامتر، بالا ولی در جهت منفی است؛ به عبارت دیگر با افزایش مقادیر یک دسته، مقادیر دسته دیگر کاهش می‌یابد. به این ترتیب، پارامترهای مغایرت، اطلاعات جدیدی را درباره نتایج طبقه‌بندی به کاربر ارائه نمی‌کنند، تنها و در صورتی که خطای طبقه‌بندی خواسته شود، می‌توان از پارامترهای مغایرت نیز درکنار آن‌ها استفاده نمود.[1] Kappa Coefficient[2] Overall Accuracy[3] Quantity Disagreement[4] Allocation Disagreement
کلیدواژه‌ها
عنوان مقاله [English]
A Comparative study of the traditional accuracy assessment and disagreement measures of the classification of remote sensing imagery
نویسندگان [English]
- Mehran Dadjoo 1
- Sayyed Bagher Fatemi Nasrabadi 2
1 Department of Geomatics Engineering, Faculty of Civil Engineering and Transportation, University of Isfahan
2 Department of Geomatics Engineering, Faculty of Civil Engineering and Transportation, University of Isfahan
چکیده [English]
Evaluation of the image classification results is very important in the remote sensing projects. So far, many indices have been presented to assess the accuracy of image classification, though Kappa coefficient and Overall accuracy are the most famous ones. Some researchers have criticized these two parameters, and have presented new parameters for evaluation of the classification results. In this paper, the relation between two new accuracy assessment parameters (presented by Pontius & Millones) and traditional accuracy assessment parameters (Overall accuracy and kappa coefficient) is studied. These two new parameters are called “Quantity disagreement” and “Allocation disagreement” which report disagreement between ground truth and classification data. In order to apply the comparative study on the traditional and new disagreement measures, supervised maximum likelihood classification was applied on 57 satellite images with different spatial resolutions. Then, Kappa and Overall accuracy as traditional accuracy parameters and Quantity disagreement and Allocation disagreement as new measures were computed for each classified image and then the correlation coefficients of the both measures were calculated. The results show a high correlation between new parameters and traditional ones in negative direction irrespective the spatial resolution. In this way, the disagreement do not provide new information about the classification results to the user, and only if there is any request for classification error, the new disagreement parameters can be used along with the traditional ones.
کلیدواژه‌ها [English]
- Accuracy Assessment
- Classification
- Disagreement
- Overall accuracy
- Traditional Parameters
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