نوع مقاله : علمی - پژوهشی

نویسندگان

1 استادیار گروه آب‌وهواشناسی، دانشکدة منابع طبیعی، دانشگاه کردستان

2 دانشیار گروه محیط‌زیست، دانشکدة منابع طبیعی، دانشگاه کردستان

3 کارشناس ارشد آب‌و‌هواشناسی کاربردی، دانشگاه کردستان

چکیده

تحقیق حاضر با هدف ارزیابی دقت داده‌های ماهواره‌ای سنجندة مادیس در پایش ریزگردها (ذرات PM10 )، به‌منظور مقایسه با داده‌های ایستگاه زمینی سنجش آلودگی در شهر سنندج انجام گرفته است. بدین‌ترتیب، میزان عملکرد داده‌های ماهواره‌ای در اندازه‌گیری ریزگردها، در ایستگاه زمینی سنندج، مشخص می‌شود. ابتدا داده‌های ماهواره‌ای عمق نوری (ذرات PM10 ) سنجندۀ مادیس، متناظر با داده‌های PM10 زمینی تهیه‌شده از ایستگاه زمینی پایش آلودگی واقع در شهر سنندج، به‌دست آمد؛ آنگاه ضریب همبستگی دو سری داده محاسبه شد. برای پیش‌بینی دقیق داده‌های PM10، دو مدل آریما و شبکة عصبی مصنوعی به‌کار رفت. داده‌های AOD سنجندة مادیس با استفاده از روش حداکثر برآورد احتمال و وزن به‌دست‌آمده از ریشة میانگین مربعات خطا، به‌منظور استفاده در این دو مدل، ترکیب شدند. در نهایت، روش مقایسۀ منفرد برای هریک از مدل‌ها و نیز مقایسۀ مدل‌ها، با هدف شناسایی مدل بهتر در تشخیص و پیش‌بینی داده‌های PM10 حاصل از سنجندۀ مادیس، اعتبارسنجی شد. در مدل شبکۀ عصبی، ضریب همبستگی در مرحلۀ آموزش 52%، در مرحلۀ آزمون 53%، RMSE برابر با 62/1 و MAE برابر 62/2 به‌دست آمد. طبق محاسبات، مدل آریمای 1-0-3 تنها مدل مورد قبول با R برابر با 46/0و 06/0MAE= و 69/0RMSE= است. این بیان می‌کند مدل آریما مدل مناسبی برای پیش‌بینی داده‌هاست اما دقت مدل شبکۀ عصبی، در ارزیابی میزان همبستگی بین داده‌ها، بیشتر تشخیص داده شد. نتایج تحقیق نشان داد که بین داده‌های عمق نوری ریزگرد سنجندۀ‌ مادیس با داده‌های زمینی رابطۀ مستقیمی وجود دارد و این الگوریتم قادر به شناسایی گردوغبار است و می‌تواند جایگزین مناسبی برای محصولات PM10 تولیدشده از سوی ایستگاه زمینی باشد.

کلیدواژه‌ها

عنوان مقاله [English]

Assessment of Correlation between PM10 Data Measured at Ground Station of Sanandaj and AOD Data of MODIS Sensor

نویسندگان [English]

  • Mohammad hossein Gholizadeh 1
  • Jamil Amanollahi 2
  • Fardin Rahimi 3

1 Assistant Prof., Dep. of Climatology, University of Kurdistan

2 Associate Prof., Dep. of Environment, University of Kurdistan

3 M.Sc. of Climatology, University of Kurdistan

چکیده [English]

The aim of this study was to evaluate the accuracy of MODIS satellite data in monitoring aerosol (PM10 particles) to compare with ground pollution station data It was done in Sanandaj. In this case, the performance of satellite data in measuring dust particles at Sanandaj ground station is identified. At first, the aerosol optical depth data provided by MODIS sensor was prepared based on the corresponding of the PM10 measured by pollution monitoring station located in Sanandaj.Then, the correlation coefficient between two series of data was calculated. In order to obtain the accurate prediction of PM10 the ARIMA and artificial neural network were used.The AOD of MODIS sensor was combined using maximum likelihood and root mean square error for input of prediction models. At last, a single comparison method for each model as well as models comparison was evaluated to identify the accurate model in predicting of PM10. In the ANN model R2 was acquired in training phase as 0.52, and testing phase as 0.53 with RMSE=1.62 and MAE=2.62. The analysis showed that the ARIMA model 1-0-3 with R2=0.46, MAE=0.06 and RMSE=0.69 is the only acceptable model.It states that ARIMA model, is a suitable model for prediction of PM10. However, the ANN model was more accurately estimated for the correlation between the data.The results of presented study showed that there is direct relationship between the MODIS sensor AOD data and ground station PM10 data.The results conclude that this algorithm is capable for detecting of dust and can be good alternative to the PM10 provided by the ground stations measurement.

کلیدواژه‌ها [English]

  • MODIS
  • PM10
  • Aerosol optical depth
  • Sanandaj
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